LIKE.TG helps over 150,000 customers across a range of businesses, nonprofits, and institutions connect with their customers. People around the world rely on our customer relationship management (CRM) platform to keep their business running. A LIKE.TG Architect is vital to any complex or large-scale LIKE.TG implementation. What is a LIKE.TG Architect? A LIKE.TG Architect helps design and deliver solutions for enterprise-grade customers using LIKE.TG products. The primary responsibility is to recommend the best solution for a given set of requirements and articulate the trade-offs involved in choosing one solution over another. With LIKE.TG, there is never just one way to solve a problem. It’s the LIKE.TG Architect’s responsibility to choose the solution that will hold up over time, that will scale as the number of users increases, and won’t acquire lots of technical debt or require manual changes as time goes on. A LIKE.TG Architect’s job doesn’t stop at solving technical problems. An architect brings technology, people, and processes together using governance and expert communication and listening skills to ensure solutions truly meet the needs of the business. The most successful LIKE.TG implementations involve architects. A study by 10K Advisors found 82% of customers who reported the highest return on investment (ROI) in their LIKE.TG spend said they always work with an architect on their teams. What skills does a LIKE.TG Architect need? A successful architect is a big picture thinker and also an in-depth problem solver. An architect must have broad and deep technical knowledge but they also need to possess listening, communication, and presentation skills. You might be surprised to learn that you don’t need to be a developer to become an architect. However, an architect needs to know how to read code and recommend coding best practices since they are often managing teams that include developers. Most importantly, an architect must know when to code but also when not to code. Having expertise in the declarative (clicks not code) side of the platform can separate a good architect from a great one. Architects often bring knowledge and expertise in integrating LIKE.TG with other technologies and vice versa, as well as experience with governance and development operations. Ultimately, architects blend their technical expertise and business acumen to empower business and IT to work together towards a stronger future. What does a LIKE.TG Architect do? A LIKE.TG Architect is a trusted advisor and leader who partners with business stakeholders and executives to design a vision and architecture for a solution to a business problem. Often in the position of the technical team leader, they help educate the team with technical best practices. They also translate business needs to a technical vision that teams of low-code or pro-code builders can execute on. Architects also build proofs-of-concept (POCs) that teams can further iterate on. An LIKE.TG architect will design the organisation strategy and data model for a LIKE.TG implementation. They will put technical solutions in place for identity and access, implement data and process integrations, and design solutions that account for large data volumes and data privacy needs. They’ll also identify the optimal solution for a business requirement and recommend using clicks, code, or a combination of both depending on the business use case. As highly experienced problem solvers, architects are often the final escalation point for any production issues. An architect can also act as an influencer. They are the trusted technology leader at the table and are often tasked with building buy-in for new solutions. While an architect might not know the answer to every question a business stakeholder might ask, they are experts on LIKE.TG product capabilities and can think quickly and act fast. Their soft skills allow them to understand all stakeholder needs and communicate with them in their language. What are the career prospects for LIKE.TG Architects? The LIKE.TG Architect career path is one of the fastest-growing in the LIKE.TG ecosystem. In the past five years, the demand for LIKE.TG architects has seen a 1,292% annual growth rate. There are a variety of different LIKE.TG architect roles. Depending on your interests or skill level, you might gravitate towards one in particular. Demand for LIKE.TG technical skills continues to grow. Studies show the LIKE.TG ecosystem will produce 4.2 million jobs by 2024, with architect roles demanding an average salary of $123,000 USD. What credentials and certifications are relevant for the job? There are various certification paths for a LIKE.TG Architect that recognise specialised knowledge and skills, as well as growing expertise using the LIKE.TG platform. The LIKE.TG Certified Technical Architect (CTA) solves complex, large-scale customer challenges to produce secure, scalable, and high-performance solutions that maximise the full potential of the LIKE.TG platform. LIKE.TG Certified Solution Architects design domain-specific, multi-cloud solutions on the LIKE.TG platform that power personalised, frictionless customer experiences that maximise business value. Finally, an architect is a visionary. They build systems that will last, that others can maintain and that will scale as the business grows. They are often ambassadors for new technology and always plan for the future, thinking three-to-five years out when recommending a solution. This post was originally published on the U.S.-version of the LIKE.TG blog.

Companies of all sizes are accelerating their digital transformation initiatives, in response to changes in customer behaviours. Many are interested in implementing integrated, access-from-anywhere solutions. These include customer relationship management (CRM) solutions such as those offered by LIKE.TG. Exploring a LIKE.TG CRM solution is one thing. Knowing which products, applications, and configurations best suits your business is another matter. This is why almost all LIKE.TG customers turn to dedicated experts to ease their entry into the world of LIKE.TG. These experts are implementation partners. There is a vast network of LIKE.TG implementation partners that help businesses achieve their CRM goals. Let’s look at some of the most common questions people have about working with a LIKE.TG implementation partner. I’ll also share how you can get the most out of the partner relationship. What is an implementation partner? In simple terms, an implementation partner is an organisation that has been reviewed and approved by LIKE.TG to implement CRM solutions on LIKE.TG’s behalf. Each implementation partner specialises in particular areas, industries, or applications. This means that there’s a partner that caters to every need, challenge, business, product, industry, region, and step along the LIKE.TG journey. Why engage an implementation partner? Our CRM solutions cover the entire spectrum of business operations. These include sales, marketing, service, and sustainability. Each product can be bolstered by add-on applications and platform-to-platform integrations. In other words, the capabilities of the LIKE.TG ecosystem are endless. The challenge is to select the right product with the configurations and integrations that best suit your needs. A larger company may already work with multiple technological solutions. They may need assistance in figuring out how a LIKE.TG product, say, Marketing Cloud, can integrate with their existing systems without causing friction. A smaller company may be scaling quickly and know that continuing to work with spreadsheets will not support this growth. They may realise that they need to automate their processes, or it’s time to develop more personalised customer experiences. Implementing a CRM solution for the first time can feel daunting. It is challenging for internal teams or employees with no experience with LIKE.TG to consider all the variables and implement a new and highly configurable CRM solution. Hiring a full-time employee to take charge of the implementation process can also be expensive. These are some of the situationally specific reasons that 90 percent of LIKE.TG customers rely on partner applications and experts. When is the right time to engage an implementation partner? In a nutshell: as early as possible. As with any significant investment, you need to do your due diligence. First, figure out what needs should be met, gaps should be closed, or issues should be addressed. In the case of LIKE.TG implementation, you formulate a vision of what you want to achieve, which is the ‘what’. Next, determine the ‘how’, which is the most complicated part. As soon as you figure out your goals, it’s time to bring in a partner. The right implementation partner won’t just facilitate the ‘how’, but they’ll also help crystalise the ‘what’. They’ll help you clarify your success metrics, understand what is realistic, and advise on appropriate products. Finally, they’ll lay out a logistically sound timeline for your implementation journey. Bringing in a partner late in the game almost always ends in missed opportunities in terms of scope and understanding. The relationship between a customer and a partner is close and collaborative. The only way to ensure smooth implementation is when the journey begins together. How do I know which partner is right for me? Certifications and credentials come into play, as does the specific expertise of that partner. Some partners have generalised LIKE.TG capabilities. More often than not, they specialise in particular areas or functions of the CRM solution. Some might specialise in Marketing Cloud and customer data platforms (CDP). Others might specialise in harnessing the combined powers of Sales Cloud and Einstein. Another factor, which has come to the forefront in recent years, is value alignment. People want to work with organisations that share their values. For example, they may choose to work with an organisation that champions diversity and equality, or prioritises sustainability. Regardless of whether or not these things are top-of-mind for you, it’s important to shop around. Meet with multiple partners. Get a feel of who they are and the way they work. This is an important relationship, so don’t settle for anything less than the right fit. The best and most comprehensive resource on both partners and products is the LIKE.TG AppExchange. There, 124,000 experts and 4,700 applications are at your fingertips. You can browse certifications, specialisations, and customer reviews. What challenges might I encounter during implementation? I can’t stress enough that bringing in a partner as early as possible reduces the chance of many challenges emerging down the line. What’s also important is to be clear on what you want to solve and how you measure success over time. Most instances of confusion or dissatisfaction come from a lack of understanding on the part of the customer or the partner. If both parties aren’t on the same page, then assumptions can be made, and misunderstandings on timelines and capabilities can arise. This makes objectives and success benchmarks harder to reach. As a customer, you need to be as transparent as you want your partner to be. Never be afraid to ask questions more than once. The implementation process can be highly technical and seeking clarification is natural. Just as you place the customer at the centre of your business, partners place you at the centre of theirs. They measure their success by delivering exactly what you need. Customer success equals partner success. You should always keep that in the back of your mind throughout the process. Any successful relationship in life thrives on open, honest communication from the outset. An implementation partnership is no exception.

LIKE.TG helps more than 150,000 customers in every industry connect with their customers. People worldwide and in APAC rely on our Customer Relationship Management (CRM) platform and Salesforce Customer 360 to keep their businesses running effectively and efficiently. Here, we’re talking about all the developers who work with LIKE.TG technologies to build solutions for our customers and partners. LIKE.TG, of course, employs a lot of developers who build our products. If that sounds more like you, check out our engineering blog. But since LIKE.TG runs LIKE.TG on LIKE.TG, much of what you read here may still apply. How developers work in the world of LIKE.TG With LIKE.TG, you can build solutions using a combination of no-code tools and code. The right tools for the right task. We call this low-code development. Through no-code customisations, developers solve some requirements without coding. This means when they do code, they end up writing less repetitive or boilerplate code. LIKE.TG products are expansive, covering sales, service, marketing, analytics, commerce, and more. Every part of LIKE.TG exposes APIs. Developers use these to create web apps on Heroku, supercharge their integration with MuleSoft, or even customise one of the standard applications. It’s fair to say that any developer can be a LIKE.TG Developer. What does a developer do with LIKE.TG? Most developers who work with LIKE.TG technologies build custom business apps and solutions. They do this either with the LIKE.TG Platform (including Sales Cloud, Service Cloud, and Experience Cloud communities) or with Heroku. While some developers specialise, most fit the description of full-stack developers working with both back-end logic and front-end experiences. Beyond the LIKE.TG Platform, there are many other opportunities for developers in the world of LIKE.TG. Some build custom marketing experiences on Marketing Cloud. Others plumb the depths of data and expose new insights with Tableau. There are developers building engaging commerce experiences with Commerce Cloud’s PWA kit. Others craft their company’s digital HQ with custom Slack apps. LIKE.TG technologies offer opportunities for developers to work with every aspect of business applications. Build Your Developer Career on LIKE.TG New to LIKE.TG development? Here's a quick tour of how you can quickly build apps and integrations with LIKE.TG. Hit the Trails +9,700 points Trailmix Build Your LIKE.TG Developer Career Follow this path to get the skills you need to become a LIKE.TG Platform Developer. Which skills does a developer need to work with LIKE.TG? Code is the stock-in-trade of every developer, so you may wonder which programming languages you might use. A lot depends on which part of the LIKE.TG world you choose to work in. The two most prominent languages in the LIKE.TG world are JavaScript and Apex. JavaScript is, of course, the language used for front-end customisations as surfaced through Lightning Web Components. Apex is the most widely adopted back-end language in the LIKE.TG ecosystem. The LIKE.TG Platform also has two domain-specific query languages. LIKE.TG Object Query Language (SOQL) is a SQL-like query language for accessing data in the LIKE.TG multi-tenant database. LIKE.TG Object Search Language (SOSL) is a text-based search language that can be used to find both data and documents stored on the platform. In addition to the LIKE.TG Platform, certain products support other languages. Both Python and JavaScript are supported languages for the Slack Bolt SDK. For customised marketing experiences, you may use AMPscript for Marketing Cloud. If you build integrations with MuleSoft, your data transformations can be written in DataWeave. If you work with dashboards in LIKE.TG CRM Analytics, you might use the LIKE.TG Analytics Query Language (SAQL) to fine-tune visualisations. And, most recently, Data Cloud gives access to its data using SQL. The technology and language landscape for LIKE.TG is rich and broad. No matter your interests, you can find a niche to master. Since LIKE.TG offers no-code customisations, every developer working in the LIKE.TG ecosystem will end up learning how to use the no-code tools that support their work, too. For instance, certain features that can be complex to implement, like wizards, data security rules, and basic user interface (UI) customisations, can all be can be accomplished without coding at all. Developers with previous experience in enterprise software tend to make the easiest transition to working in the world of LIKE.TG. But this is by no means a requirement. Again, any developer can become a LIKE.TG Developer. Many have joined directly from college or moved over from other software engineering experiences. What are the career prospects for a developer who works with LIKE.TG in APAC? As the ecosystem around LIKE.TG grows, developers continue to be highly sought after. In the past 5 years, the number of new developer positions has increased by 165 percent on average year-over-year. And based on U.S. data, a starting salary for a developer is $105,000 per year. Developers often come to LIKE.TG as a career opportunity. Once here, many get hooked on the friendly support of the LIKE.TG Developer Community. You can also connect, share ideas, and build your skills through local, in-person meetups. Join the conversation virtually with developers daily through the LIKE.TG Developers group in the Trailblazer Community on Trailhead—LIKE.TG’s free online learning platform. Take your learning and networking even further by attending one of the community conferences found worldwide and in APAC. Which credentials and certifications are relevant for the job? As a developer, you want to work with the most relevant technologies, languages, and platforms. No language is more universally relevant today than JavaScript. You can show your JavaScript competence by earning the JavaScript Developer 1 Certification. This certification tests your knowledge of JavaScript in the browser and in NodeJS. While used to validate the skills of many candidates in the LIKE.TG ecosystem, because it’s focused on universal knowledge, any company can use this certification when looking to hire a JavaScript developer. To demonstrate your competence in developing with LIKE.TG Platform-specific features, tools, and technologies, you can pursue several paths. To learn about all the platform features that require no coding, you can take the Platform App Builder Certification. To show knowledge and understanding of different programming features, earn your Platform Developer 1 Certification (PD1). Once you have your PD1, you can go further by pursuing the practical, hands-on Platform Developer 2 Certification. In addition to these core LIKE.TG Platform certifications, you can also pursue specialist certification in products such as: OmniStudio Developer: Develop cloud applications using OmniStudio declarative development tools. Industries CPQ Developer: Develop configure, price, quote (CPQ) applications for the LIKE.TG Communications, Media, and Energy & Utilities clouds. B2C Commerce Developer: Customise LIKE.TG Commerce through configurations, user management, and development with the LIKE.TG B2C Commerce Digital platform. Marketing Cloud Developer: Create personalised, dynamic messages and landing pages using Marketing Cloud scripting languages, data configuration, manipulations, and advanced segmentation, as well as reporting and analytics. Slack Certified Developer: Build interactive apps on the Slack platform. MuleSoft Developer Certifications: Build, test, and deploy APIs and integrations using the MuleSoft platform. Embarking on your developer career journey in APAC. As a developer, you hold some of the most sought-after skills in every industry. Every business needs technical experts to turn their requirements for business applications, integrations, and customer-facing websites into experiences that deliver what their users and customers need. You might have long-standing experience developing on other platforms. You might just be launching your career. You might be somewhere in between. Whatever the case, there are many paths for you to become a developer in the LIKE.TG ecosystem. If this has you excited to learn more, the LIKE.TG Developers website is a great place to start. You can also learn about the latest developer features through our LIKE.TG Developer blog or YouTube channel. And be sure to keep up with all the latest from us on LinkedIn, and connect with us in the LIKE.TG Developers Trailblazer Community Group.

A relational database is a type of database that stores and organises related data points. Data is organised into tables that are linked based on shared data. They are the most common type of database used by businesses today. A database like this enables you to search across one or more tables with a single query. It also helps you understand the connections across your data so you can make better business decisions. Relational databases are ideal for complex data analysis and operations. In a non-relational database, tables can share the same data but they can’t ‘relate’ to each other. With a relational database, they can. One use of a relational database is connecting tables for customer data and transactions. A business will have both data sets but they may be siloed. A relational database brings these together. For example, in the customer table, there may be fields for: Customer ID Customer Address Customer Email, etc. In the transaction table, there may be fields such as: Customer ID Transaction Amount Item Purchased, etc. As both tables contain a Customer ID, the tables can be related. This means a warehouse team can find the Customer Address that corresponds to the Customer ID, without this information being recorded as a separate data point on each transaction. Relating these data sets can also be used to produce reports, such as a customer statement. We explore the features, uses, and benefits of a relational database below. Plus, we outline LIKE.TG’s relational data features. Features of a relational database Relational databases need ACID characteristics. ACID refers to four essential properties: Atomicity, Consistency, Isolation, and Durability. These features are the key difference between a relational database and a non-relational database. Atomicity Atomicity keeps data accurate. It makes sure all data is compliant with the rules, regulations, and policies of the business. It also requires all tasks to succeed, or the transaction will roll back. Atomicity defines all the elements in a complete database transaction. Consistency The state of the database must remain consistent throughout the transaction. Consistency defines the rules for maintaining data points. This ensures they remain in a correct state after a transaction. Relational databases have data consistency because the information is updated across applications and database copies (also known as ‘instances’). This means multiple instances always have the same data. Isolation With a relational database, each transaction is separate and not dependent on others. This is made possible by isolation. Isolation keeps the effect of a transaction invisible until it is committed. This reduces the risk of confusion. Durability Durability means that you can recover data from a failed transaction. It also ensures that data changes are permanent. Uses and benefits of a relational database Relational databases are often the backbone of a customer relationship management (CRM) system — such as LIKE.TG. But tracking customer transactions is just one use case for a relational database. There are many others. We even use some in everyday life. For example, when you withdraw money from an ATM, your bank balance may instantly update on your mobile app if it’s using a relational database. This is because this scenario’s data point (“Account Balance”) is consistently updated across all platforms. There are multiple benefits of using a relational database over a non-relationship database. And many of these affect other systems, including LIKE.TG. Some of the main advantages of a relational database are: Data consistency As mentioned when we outlined ACID, a core part of a relational database is consistency. A relational database model ensures that all users always see the same data. This improves understanding across a business because everyone sees the same information. This ensures that nobody makes business decisions based on out-of-date information. Data working together All the data in a relational database has a ‘relationship’ with other data. Columns are built in a way that makes it easy to establish relationships among data points. Data working together gives a more holistic view of all your data — including your customers. Data flexibility Relational databases allow for flexibility. Users can change what they see. And it’s easy to add additional data at a later time. A relational database also allows for a subset of data to be viewed. This means you can hide certain data if some users only need access to a specific set of columns or rows. Relational data features in LIKE.TG CRM LIKE.TG’s CRM is built on a relational database. LIKE.TG calls its tables “objects”. And these objects can relate to each other. These relationships can be used to share information and create connected views of data. There are two types of relationships in LIKE.TG: Lookup relationships This is the most basic relational connection in LIKE.TG. A lookup relationship links two objects so that you can “look up” one object from the related items on another object. Lookup relationships can be one-to-one or one-to-many. A standard one-to-many relationship is an Account-to-Contact relationship. This allows you to connect several Contacts to a single Account. A one-to-one relationship is when only one set of data needs to be related. For example, if you’re in real estate, you may have a Property object and a Home Seller object. The Property only has one Home Seller, so there is only one set of data that needs to be related. Parent-child relationships Parent-child relationships are harder than lookup relationships. With these, one object is the parent, while the other is the child. The parent object controls some of the behaviours of the child object, such as who can view its data. It also means if you delete a parent object, you delete all the associated child objects. As an example, you may have a parent-child relationship between Property and Offer. All offers are exclusive to one property. Should the property be taken off the market, you can remove the Property object to delete all of the associated offers from your system. Parent-child relationships are used when objects are always related. When objects are sometimes related, this is a lookup relationship. Why choose LIKE.TG LIKE.TG gives you all the benefits of a relational database with the enhanced features of a CRM. Plus, LIKE.TG is taking CRM to the next level, with innovations such as LIKE.TG Einstein which utilises artificial intelligence. LIKE.TG Customer 360 is the world’s #1 CRM system. It brings sales, service, marketing, commerce, IT, and analytics together. And it’s all made possible by a relational database.

Understanding your salary slip is important for managing your finances and staying informed about your compensation. A salary slip, also known as a payslip or wage slip, is a detailed breakdown of your earnings and deductions for a specific pay period. It is an important document for payroll processing and can be useful for tax filing, budgeting, and applying for loans. We’ll take a closer look at salary slips, including what they are, why they are important, and how to keep accurate records. We will also answer some common questions about salary and pay slips, and discuss how a Financial Services CRM like LIKE.TG can help you manage your salary slips more effectively and improve your overall financial operations. What is a Payslip? A payslip, also known as a salary slip or wage slip, is a document issued by an employer to an employee, providing a detailed breakdown of an employee’s earnings and deductions for a given pay period. It is a critical tool for financial management and offers insight into an individual’s compensation. Payslips are a detailed summary of an employee’s compensation, providing proof of income. They typically include the employee’s name, the pay period, gross salary, deductions, and net pay. Payslips are more than just a record of your pay. They are also important for tax purposes. They help you to declare your income accurately to the tax authorities. Payslips are also useful when you apply for a loan or credit. They show how much you are earning and help lenders decide if you can afford to repay what you have borrowed. Understanding and analysing your payslip is important for getting a clear picture of your financial situation. It can help you budget your income, allocate funds to different areas of your life, and plan for future financial goals. It can also help you catch any mistakes or discrepancies in your pay, so you can make sure you’re getting the right amount of money for the work you do. When are payslips distributed or salary slips given out? Salary slips are usually handed out on the same day you receive your salary. However, there are instances when they might be distributed a few days before or after payday. The timing can also depend on your company’s payroll schedule. Some companies distribute salary slips weekly, while others do so biweekly or monthly. Many companies now offer the ability to create payslips using online tools, which can be accessed anytime through a company portal or HR system. You must be aware of your company’s salary slip and bonus distribution schedule to plan your finances effectively. For instance, if you know that your salary slip is issued on the last day of the month, you can ensure that you have sufficient funds to cover your expenses until your next payday. In some instances, you may not receive a hard copy of your salary slip. Instead, your employer might provide access to an online version through a company portal or HR system. This can be a convenient option, allowing you to view your salary slip at any time without the need to keep track of a physical document. Whether in print or digital form, your salary slip is an all-important piece of documentation to retain for your personal records. It serves multiple functions, from tax declarations to financial planning and loan applications. Salary slip format Although the format of a basic salary slip can differ from one company to another, there are certain key elements that are typically included. These are: Using online tools to generate payslips ensures statutory compliance and data security, allowing users to input various details about the company and employees to create and download payslips. Employee Information: This section includes basic details about the employee, such as their name, employee ID, and job designation. Pay Period: The pay period tells you the dates you’re being paid for, for example, 1 January 2023 to 31 January 2023. Gross Salary: This is the total amount of earnings before any deductions are applied. It includes basic salary, allowances, bonuses, and any other earnings during the pay period. Deductions: Here you can see all the items that were subtracted from your gross pay. Common deductions include federal and state income tax, Social Security, Medicare, and health insurance. Each deduction is listed separately, and typically includes the amount taken out of your paycheck. Net Pay: Net pay is the final amount an employee receives after all deductions have been subtracted from gross pay. This is the amount that is typically deposited into the employee’s bank account. Other Details: Some salary slips may also include additional information about employees such as the number of hours worked, overtime pay, leave balances, and any bonuses or incentives earned. Meticulously examine your salary slip, verifying the accuracy of all details and ensuring a clear understanding of the deductions. Should you detect any discrepancies or errors, promptly engage with your employer’s payroll department to seek clarification and resolution. Components of a salary slip A salary slip, also known as a payslip or wage slip, is a document that details an employee’s earnings and deductions for a specific pay period. It serves as an essential financial record and offers valuable insights into an individual’s compensation. Understanding the components of a salary slip is essential for employees to effectively manage their finances and ensure fair remuneration. Personal Information: This section includes your name, employee ID, and contact details such as your address, phone number, and email address. This information is a key player for identification and communication between you and your company or employer. Equally vital is the employer’s name and contact information. This section should feature the employer’s legal name, business address, and contact details, including a phone number and email address. By including this information, you enable all your employees to easily get in touch with you should they have any questions or concerns about their salary slip or their employment in general. The pay period and date are also prominently displayed on a salary slip. The pay period refers to the specific timeframe for which the employee is being compensated. It is typically a fixed duration, such as a month or a fortnight, and is indicated on the payslip. The pay date, on the other hand, refers to the specific date on which the employee receives their salary. Gross salary is the total amount of income you earn before any deductions are made. This includes your base salary and any additional earnings, such as bonuses, commissions, or overtime pay, that you may have received during the pay period. It’s important to understand your gross salary so that you can calculate your total income and plan your finances accordingly. Net salary, on the other hand, is what an employee takes home after all deductions have been made. This includes taxes, social security contributions, health insurance premiums, and any other authorised deductions. The net salary is the actual amount of money that an employee can spend or save, making it a critical component of financial planning and budgeting. In summary, a salary slip is a vital document that provides a clear breakdown of your earnings and deductions for a specific pay period. By familiarising yourself with its components, you can take charge of your finances, ensure the accuracy of your compensation, and make well-informed financial choices. 7 essential elements to include on a payslip A payslip is a vital document that provides information about an employee’s pay and any deductions. To make sure your payslips are clear and contain all the necessary information, they should include: 1. Employee Information: The payslip should prominently display the employee’s full name, employee identification number, and contact information, including their address and phone number. This information helps identify the employee and ensures accurate record-keeping. 2. Pay Period: Clearly indicate the specific pay period covered by the payslip. This information is crucial for employees to understand the timeframe for which they are being compensated. 3. Gross Salary: Your gross salary is the sum you earn before any deductions are made. It includes your base salary, any bonuses, and any other forms of compensation or benefits you receive from your employer. 4. Deductions: This section is where you detail all the different deductions you make from your employee’s gross pay. Common deductions include federal and state taxes, FICA taxes, health insurance premiums, and retirement plan contributions. Each deduction should be clearly labelled and the amount deducted should be specified. 5. Net Pay: Net pay, also known as take-home pay, is the amount that remains after all deductions have been subtracted from the gross salary. This is the actual amount of compensation that you receive. 6. Employer Information: Your payslip should include your employer’s name, address, and contact information, and if applicable, the company logo. This information is important for verifying the payslip’s authenticity and for any inquiries you may have. 7. Additional Details: Depending on your company’s policies and practices, your pay stub might include additional information. This could be the number of hours you worked, any overtime pay, your leave balances, and any bonuses or incentives you’ve earned. These details can give you a more complete picture of your compensation and work status. By including these key components, a payslip becomes a clear and informative document that helps both employers and employees understand their pay, manage their money, and make sure they’re being paid fairly and accurately. The importance of salary slips The salary slip’s importance cannot be overstated. These documents serve as a crucial tool for you to understand your financial standing and manage your finances effectively. One of the primary reasons why salary slips are important is that they provide a detailed breakdown of your compensation and deductions. This information is essential for you to accurately track your income and expenses, and to make informed financial decisions. Salary slips are indispensable for loan applications and visa processing. Lenders often require them as proof of income when you apply for a loan. Similarly, when applying for a visa, they demonstrate your financial stability and income source. Without accurate employment, and up-to-date salary slips, you may face challenges in securing loans or obtaining visas. Salary slips are a key component in tax compliance. They furnish a detailed account of your taxable income and deductions, simplifying the process of filing your taxes accurately and avoiding potential discrepancies. Armed with access to this information, you can fulfil your civic duties and contribute to the smooth operation of the tax system. For many financial transactions are essential. When you apply for a credit card or open a bank account, you may need to provide your salary slip as proof of income. This helps the financial institution understand your financial situation and make a decision about whether to provide you with credit or other financial services. Your salary slip is a document of great importance. It’s not just a piece of paper that shows your earnings; it’s a tool that can help you manage your finances better, apply for loans, process visas, and comply with tax regulations. By understanding the significance of your salary slip and using it to your advantage, you can take control of your finances, make informed decisions, and secure your financial future. Frequently asked questions How frequently should you receive a payslip? The frequency of receiving a payslip can vary depending on your company’s payroll policies and practices. Generally, payslips are distributed on the same day that employees receive their salaries. However, some companies may distribute them a few days before or after payday. It is important for you to be aware of your company’s salary slip distribution schedule so that you can plan accordingly. What to do if you find an error on your payslip If you spot an inaccuracy on your payslip, don’t hesitate to reach out to your employer’s payroll or human resources department. Offer the specifics of the error and any relevant documentation, such as prior payslips or bank statements. The payroll department will investigate and ensure the necessary adjustments are made. How Long to Retain Payslips It is recommended to keep your payslips for at least one year, as they may be required for various purposes such as tax filing, applying for loans, or calculating your average income. Some individuals may choose to keep their payslips for a longer period for their own records and financial management purposes. What details are usually found on a payslip? A payslip typically includes the following information: – Employee information: name, employee ID, contact information – Pay period: start date and end date of the pay period – Gross salary: total earnings before deductions – Deductions: various deductions such as taxes, social security contributions, health insurance premiums, etc. – Net pay: the amount of salary paid to the employee after all deductions have been made – Employer information: name, contact information, employer identification number Can I use my payslip as proof of income? Absolutely. Your payslip is a valuable document that can be used to confirm your income when applying for a loan, renting an apartment, or obtaining a visa. It provides a clear and verifiable record of your earnings and deductions. Financial Services CRM and payslip generator at LIKE.TG Financial Services Cloud is a cloud-based financial services CRM software that delivers a complete, 360-degree view of your customers and their needs. It includes features such as lead management, opportunity management, account management, and customer service. It also offers integrations with other LIKE.TG products and third-party applications. This helps financial services companies to improve customer service, increase sales, and reduce costs. Let’s break down the features: Lead Management: Track, generate and manage leads from various sources, such as online forms, phone calls, and referrals. Opportunity Management: Manage your sales pipeline and track the progress of deals. Account Management: Get a centralised view of customer accounts, including contact information, account history, and open opportunities. Customer Service: Track and resolve customer issues and requests. Beyond these core capabilities, Financial Services Cloud offers a suite of features tailored to the financial services industry. These include: * Compliance management: Assisting financial services companies in meeting regulatory requirements and industry standards. * Wealth management software: Equips you with the tools to manage your investments and monitor your financial progress. * Insurance: Features for managing insurance policies and claims. * Lending: Equips you with the tools to create and manage loan applications and monitor loan performance. Financial Services Cloud is a robust CRM platform designed to elevate your customer service, boost sales, and streamline operations. By offering a comprehensive, unified view of your customers across all channels and business lines, Financial Services Cloud empowers your financial advisors to provide personalised, efficient service to their clients. Discover what a salary slip or payslip entails, including its importance for managing finances, tax filing, budgeting, and applying for loans.

What is a sales funnel?A sales funnel is a marketing term used to capture and describe the journey that potential customers go through, from prospecting to purchase. A sales funnel consists of several steps, the actual number of which varies with each company’s sales model.Well-built sales funnels without gaps allow companies to shepherd potential customers through the buying process towards purchase completion. By contrast, those funnels with gaps will lead to potential customers dropping out of the sales process, like water flowing through a sieve.Why is the sales funnel important?A sales funnel helps marketers understand a customer’s purchasing journey, while also identifying what stage of this journey the customer is at. These insights can be used to decide which marketing channels and activities will best guide the customer towards a purchase. A sales funnel also allows marketers to tailor and optimise their activities and messaging to increase conversions.So, how does a sales funnel work?As the name suggests, a sales funnel takes in a large number of leads and prospects and narrows them down towards the bottom, giving you a smaller number of paying customers. While the specifics of the sales funnel differ from industry to industry—in fact, even from company to company—we can understand how it works with a simple example:Let’s look at the B2C sales funnel for an e-commerce website. A potential customer for the site will start their journey as a visitor: someone who might visit the site by clicking on a Google search result, social media post, or advert. When they visit and browse through the website, they might (and should) be offered a chance to sign up for the e-commerce site’s email list. If they do, they become a lead. Depending on the contact details they share, they can be engaged through various channels such as email, text, and phone. Their interaction with these marketing campaigns is likely to nudge them to return to the e-commerce website to browse relevant products or special offers, turning them into a prospect. From prospect to customer is then a matter of incentivising them enough with product offerings, messaging, or even a simple coupon code.The 6 stages in a sales funnelAgain, it’s important to note that not all companies’ sales funnels will have six levels or stages. Sales funnels vary in size and shape from company to company and industry to industry. However, a basic sales funnel can be described as consisting of six levels. Marketers can take inspiration from this basic structure to design a sales funnel that suits the needs of their organisation.1. Awareness:At the very top of the sales funnel is the awareness stage that is populated by the largest number of people. These people, not quite ready to be prospects yet, have just had their first interactions with your company and its offerings. They don’t know much about your brand at this stage, but are aware that it exists.2. Interest:The first interactions will hook some of these newly-aware people and draw them slightly deeper into the funnel. With their interest piqued, these people will spend some time getting to know more about your company and your offerings. They might browse your website or catalogue, read your blogs, or peruse reviews from past customers.3. Evaluation:Armed with knowledge gathered during the interest stage, your prospects will double down on their efforts to know your company and offerings better. They may reach out to your customer service team with specific questions, or fill out a form to access more information. Remember, by this stage they may have already compared your offerings to those of your competitors. So, it is important to clearly answer their questions and help them understand how your offerings can solve their problems or needs.4. Negotiation and decision:The prospect has now almost decided to purchase your product or service. Depending on the nature of your offerings, they might begin a negotiation over the price, terms of purchase, or both. But it’s fair to assume that they have a purchase intention at this stage.5. Sale:We’ve reached the bottom third of the sales funnel—the prospect and seller have negotiated the terms of the sale to their mutual satisfaction, and the prospect pays the seller to officially become a buyer.6. Renewal or repurchase:The sale stage is not the end of the sales funnel. Soon a time will come when the sales contract is up for renewal. The customer must now decide if they want to continue with the same seller. If so, there might be a fresh round of negotiations over price and purchase terms, followed by a renewal or repurchase.As mentioned earlier, many companies may not experience a sales funnel like the one described above. Many purchase journeys might end at the ‘sale’ stage, while others might be complex enough to warrant even more steps. The above framework, however, is broadly applicable to most business models.Benefits of a sales funnelA well-defined sales funnel can offer several benefits to your company:1. Relevant and timely messaging:A proper sales funnel allows marketers to understand the customer’s purchasing journey, and anticipate the questions and doubts they may have at various stages. These insights can be used to create and deliver relevant and timely marketing messages to the customer.2. Marketing and sales alignment:In case a customer has questions and can’t reach a salesperson because they are too high up in the funnel, they can still receive the information they want through marketing outreach. An effective sales funnel allows marketers to answer the customer’s product/service questions without involving a salesperson that early in the process.3. Time and effort savings:A good sales funnel allows marketers to filter out bad sales leads early on, and focus precious marketing dollars only on leads that exhibit the highest likelihood of converting into paying customers.How to build and nurture a sales funnel—fastBuilding a sales funnel doesn’t have to be a very time-intensive effort. With a little bit of understanding, you can build and maintain a sales funnel that will allow you to identify and harvest quality leads again and again. Building a sales funnel is all about knowing your leads, prospects, and customers, engaging them in a timely and relevant manner, and following up diligently:1. Analyse your existing customersA good sales funnel is built on a deep understanding of your existing customers. The more customer data you can gather and analyse, the more effective your sales funnel will be. You can gather customer data by actively communicating with your customers, and by tracking their interactions with your digital and offline presence. An analysis of your customers should include their pain points, needs, goals, aspirations, and past solutions. Using this data, you can find lookalike audiences, and put out the right messaging at the right time to attract prospects.2. Captivate your target audienceYour audience is likely to be distracted by the multiplicity of demands on their attention. To compel them into your sales funnel, you need to capture their attention across online and offline platforms. Use compelling content that educates and informs prospects, assures them that their needs are known and will be met, and hooks them into asking for more information. The content used to capture your audience’s attention can be organic (non-paid social media posts, blog posts, email newsletters, SEO) as well as paid (social media advertising, targeted keywords, influencer content). Find ways to align this content and related campaigns with the interests and needs of your target audience.3. Create a great landing pageAll your content should lead your prospects somewhere – typically, a landing page. This is where you make your first impression. A great landing page communicates who you are as a company, what your offerings are, and what needs you can solve. Landing pages can also entice visitors with offers and should be used to capture contact data like email addresses. Lastly, but very importantly, landing pages should have a clear call-to-action that takes the prospect further down the sales funnel.4. Create a powerful email campaignHaving captured email information from your leads, keep them engaged with a powerful email campaign. A good email campaign starts by informing and educating leads, helping them understand how your products and services can meet their needs. Only then should it progress to offering your leads offers that compel them to convert into paying customers. Focus on inspiring leads to become customers instead of just bombarding them with crude product pitches.5. Keep following upWhen a customer purchases your products and services, they don’t move out of the sales funnel. Instead, they stay at the very bottom of the funnel, and you want to keep them there. These customers have paid for and used your products and services, and you want them to come back for more. Keep them engaged with recurring communication. Thank them for their purchase and incentivise them to return through promotional (offers) and informational (new product information) campaigns.Your sales funnel is a dynamic tool; feel free to tweak it in response to changes in the market and your company’s offerings. The important thing is to have a sales funnel that captures the widest number of prospects and effectively narrows them down to a smaller pool of loyal customers.Example of a sales funnelImagine a sales funnel for a company that manufactures, markets, and sells stylish furniture online. The company knows that most of its customers are 30-40 year olds who spend a lot of time online, specifically on visual social media platforms like Instagram. So, the company runs a series of Instagram ads using compelling content targeted at potential audiences aged between 30 and 40 years. The Instagram ads route users to the company’s landing page, where a pop up encourages them to sign up for the company’s newsletter to receive tips, updates, and, crucially, offers. The people that sign up have now become leads.Over the next few weeks, these leads are sent content that informs and educates them about the company’s furniture designs and quality. The intent is to inspire them to think about how they can redesign their personal spaces with this company’s furniture.At the end of the email campaign, the company sends these leads a discount coupon. Primed with ideas for their spaces, the discount coupon helps push the leads towards an actual purchase. After the purchase, the company doesn’t forget about these buyers. They become recipients of yet another email campaign with the same goals but different content.And there you have it—a sales funnel. At the top, social media users were made aware of the company and its offerings and drawn into the funnel. Their interest was piqued, they evaluated the offerings, and decided to purchase the product. Hopefully, they will renew their relationship with the company by repurchasing in the future.Measuring a sales funnel’s successA sales funnel is a dynamic tool. It is likely to change in shape and size as your business grows, as you understand your customers’ needs better, as these needs evolve, and as your product and service lines diversify. A good sales funnel is regularly changed in response to evolving business environments.Marketers should also actively tweak their sales funnel based on how well it’s performing. A key metric to track when evaluating sales funnels is the conversion rate—how many visitors are being converted into leads, how many leads into prospects, and how many prospects into paying customers? Understanding these conversion rates will allow you to pinch or expand the funnel in relevant places and eventually arrive at a shape that maximises conversion at that point in time.Optimising the sales funnel The best way to optimise your sales funnel is to try different things and track the resulting changes in conversion rates. The points at which visitors convert into leads, leads into prospects, and prospects into customers are crucial. Marketers need to ensure that the content and activities they use at these points are highly effective.A good way to measure effectiveness is to fervently run A/B testing. Let’s go back to the example of our direct-to-consumer furniture brand. To optimise their sales funnel, the marketing team could run several Instagram ads and check their performance before settling on the most successful one. They should also run A/B testing on their landing page, where visitors are converted to leads, and on their email campaigns, where prospects are converted to customers.Optimising the sales funnel is a constant cycle of testing and incorporating the results.Sales funnel FAQs 1. What is the difference between a sales funnel and a marketing funnel?A marketing funnel precedes a sales funnel. A marketing funnel is meant to draw visitors towards the brand and acquaint them with it. A sales funnel, on the other hand, is supposed to take unaware or partially aware audiences, and guide them towards an actual purchase.2. Is a sales funnel a marketing activity?Yes and no. In the top levels of a sales funnel, the marketing team is heavily involved in converting visitors to leads and leads to prospects. In the middle, the sales team steps in to close the sale. At the bottom, the marketing team steps in again to hopefully renew existing customers’ interest in the company and its offerings.3. Who needs a sales funnel?Every company needs a sales funnel because every company has customers. A sales funnel is a useful tool for all companies, irrespective of their size or industry.4. Do sales funnels really work?If you take away the marketing jargon for a moment, you realise that a sales funnel is nothing more than an exercise in paying attention to your customer and their journey towards making a purchase. Since the customer is king, paying attention to them can only work in your favour. Moreover, by helping you optimise the use of your marketing resources, a sales funnel helps stretch your marketing dollar.5. When do sales funnels not work?A sales funnel may not work if it is poorly built and executed. Without a clear marketing goal, as well as proper targeting and compelling content, a sales funnel is unlikely to draw in enough prospects or keep them in the funnel.6. What is sales funnel leakage?Sales funnel leakage is when prospects and leads slip out of the funnel before they become paying customers. Sales funnel leakage usually happens if marketers can’t keep prospects and leads engaged with their company and offerings through relevant, interesting content and outreach.Conclusion Sales funnels work best when they are built with specific goals for defined target audiences, and are executed using compelling marketing content. Without these three basic tenets, sales funnels tend to be leaky—they let out prospects and leads before converting them into paying customers.If you are trying to build a sales funnel for your organisation, or optimise the one that you have, LIKE.TG solutions can help you. Here’s how:Pardot, our B2B marketing automation tool, enables you to fill your sales funnel with high quality leads, and intelligently nurture them. With it, you can create beautiful landing pages, forms, and email campaigns to personalise customer engagement.With our contact management tool, marketers and salespeople have an ever-present snapshot of customers. Meanwhile our opportunity management capability helps you close deals faster by staying connected to the people and information you need. The LIKE.TG Engage tool allows you to draft and send personalised communications to customers with just one click. It also helps you maintain and view a detailed history of prospect or customer interactions.Powerful reports and dashboards help you ensure that all your sales and marketing decisions, including the building and optimising of your sales funnel, are data-driven and well-informed.

A Sales-Qualified Lead (SQL) is a potential customer thoroughly assessed by both the marketing and sales teams. Having demonstrated an intention to purchase and meet specific lead qualification criteria, this prospect is considered suitable for advancing to the next phase in the sales process. Once a prospect surpasses the engagement stage, they receive the SQL label, signifying readiness for targeted efforts to convert them into a valued customer. A sales-qualified lead stands at that critical point in the sales process where they have moved beyond the initial interest or basic awareness and are now showing a clear intent to purchase. The way this distinction is made is through a meticulous qualification process, examining factors like your lead’s need for your product or service, their decision-making authority, and their readiness to make a purchase. Identifying a sales-qualified lead means acknowledging a lead’s transition from considering your offerings to actively seeking to solve a problem or fulfilling a need with what you have to offer. In the following piece, we’ll take a closer look into how sales-qualified leads are identified, the criteria that set them apart, and strategies for effectively managing and converting these valuable prospects. After all, understanding the nuances of sales-qualified leads is essential for any sales team aiming to advance their sales process and achieve better outcomes. Why are sales-qualified leads important? Sales-qualified leads (SQLs) are important because they represent the prospects that are most likely to convert into customers. They have already shown interest in a company’s product or service. They may have visited the company’s website, downloaded a whitepaper, or attended a webinar. By focusing on SQLs, sales teams can increase their efficiency and close more deals. In addition to representing new business potential, SQLs can help businesses focus their sales efforts on the most promising leads. By qualifying leads, sales teams can identify the prospects that are most likely to be a good fit for their product or service. This allows them to allocate their resources more effectively and focus on the leads that are most likely to close. The more information a business has about a lead, the better it can qualify them and determine if they are an SQL. Some of the most important information to collect about a lead includes their name, company, job title, email address, phone number, and interests. Businesses can also collect information about a lead’s budget, timeline, and pain points. This information can help sales teams to better understand the lead’s needs and tailor their sales pitch accordingly. By focusing on SQLs, sales teams can increase their efficiency and close more deals. SQLs represent the potential for new business and can help businesses focus their sales efforts on the most promising leads. By qualifying leads, sales teams can identify the prospects that are most likely to be a good fit for their product or service and allocate their resources more effectively. SQL vs. MQL Sales-qualified leads (SQLs) and marketing-qualified leads (MQLs) are two important concepts in the sales process. While both types of leads represent potential customers, they have key differences. MQLs are leads that have been generated by marketing efforts, such as advertising, email campaigns, or social media. These leads have expressed some interest in a company’s product or service, but they have not yet been qualified by the sales team. SQLs, on the other hand, are leads that have been qualified by the sales team as being worth pursuing. These leads have met certain criteria, such as having a budget, a need for the product or service, and the authority to make a purchase decision. The difference between SQLs and MQLs is important because it allows sales teams to focus their efforts on the most promising leads. By qualifying leads, sales teams can avoid wasting time on leads that are not likely to convert into customers. Here’s a closer look at the main differences between sales-qualified leads and marketing-qualified leads: Stage in the Sales Funnel: Marketing-qualified leads are just beginning their journey, their interest has been piqued, and yet they’re not yet ready to buy. Sales-qualified leads are further along and prepared to discuss purchasing. Engagement Level: Marketing-qualified leads interact with your content, showing interest. Sales-qualified leads take significant actions, like asking for a demo, indicating they’re ready to consider a purchase. Qualification Process: Marketing teams identify marketing-qualified leads based on their engagement activities. Sales teams then rigorously evaluate the sales-qualified leads, confirming their readiness and compatibility with what’s on offer. By understanding these distinctions, you can tailor your approach to nurturing and converting leads more effectively. Recognising what makes each type of lead unique allows your marketing and sales teams to align their efforts, moving leads through the sales funnel more efficiently and boosting your chances of making a sale. The shift from marketing to sales-qualified leads isn’t just about sorting leads; it’s about adopting a more strategic mindset that understands each buyer’s journey. It ensures every touchpoint is timely and relevant and propels the prospect closer to saying ‘yes’ to your solution. How Do Organisations Identify SQLs? Different businesses adopt a variety of criteria to identify their sales-qualified leads, a main point in refining the sales process. The success of this strategy depends on consistent collaboration between sales and marketing teams, aimed at ensuring the most promising leads are quickly recognised and nurtured, transitioning smoothly from marketing-qualified to sales-qualified status. Evaluating Engagement and Interest: Finding a viable sales-qualified lead starts with assessing how a lead interacts with your marketing efforts and their demonstrated interest in your offerings. This includes tracking website visits, content downloads, and social media activity and employing a scoring system to prioritise leads based on their level of engagement. This quantitative approach helps single out leads actively seeking solutions, ensuring focus is placed on those most interested. Assessing Budget and Authority: It’s critical to understand a lead’s interest and their ability to make purchasing decisions. By engaging leads with targeted questions, teams can gauge whether a lead has the necessary budget and decision-making authority, focusing efforts on leads capable of moving forward in the sales process. Determining Fit and Need: Assessing whether a lead’s requirements align with your offering involves a detailed look at company size, industry, and specific challenges. Marketing teams are key in this phase, using targeted content and communications to evaluate a lead’s needs and how they match up with your solutions, an essential step in moving a lead towards being sales-qualified. Timeline Consideration: Understanding when a lead plans to make a purchase is also highly important. Sales teams work to align a lead’s buying timeline with the business’s sales cycle, an essential time in deciding if a lead is ready to be considered a sales-qualified lead. The Harmony Between Sales and Marketing: The transition from a marketing-qualified lead to a sales-qualified lead highlights the critical nature of sales and marketing collaboration. Through regular communication and agreed-upon lead scoring criteria, both departments ensure that only the most qualified leads progress through the sales funnel. This partnership is key to refining the lead qualification process, optimising how resources are allocated, and boosting the overall efficiency and effectiveness of the sales strategy. Identifying sales-qualified leads represents a strategic, coordinated effort between sales and marketing, driven by data and an extensive understanding of the customer. This meticulous approach makes the sales funnel more efficient and ensures that sales initiatives are targeted towards leads with the highest conversion potential, fostering sustained business growth. SQL vs. MQL Examples Revisit the comparison between SQLs and MQLs, providing more in-depth insights into the specific characteristics and behaviours that set them apart. Use real-world examples to illustrate scenarios where a lead may transition from being an MQL to an SQL. When refining the sales journey, it’s essential to have a thorough understanding of that defining shift in the funnel from marketing-qualified lead to sales-qualified lead, as it will ensure a more efficient path to purchase for your sales team. Marketing-qualified leads, sparked by marketing engagements such as content downloads, signal that initial interest. This, however will likely evolve into a sales-qualified lead, which marks a deeper intent to buy, demonstrated through actions like premium content engagement. This transition shows us that the lead is now ready for a direct sales interaction. For example, consider a lead’s participation in a detailed product webinar or their consistent interaction with targeted emails. These actions would signify a readiness to begin to explore solutions, positioning them perfectly for a shift to sales-qualified lead status. Recognising and effectively fostering these moments can significantly enhance the effectiveness of the sales funnel, transitioning leads into customers more smoothly and successfully. For sales teams, engaging sales-qualified leads means adopting a nuanced and specialised approach. The interaction history of each lead, be it a closer look into a webinar or a keen interest in pricing information, demands a unique follow-up strategy. This personalisation ensures that sales communications resonate deeply, addressing each potential customer’s specific needs and interests. Leveraging analytics and lead scoring sharpens this focus, pinpointing the subtle but significant signs of a lead’s progression from a marketing-qualified lead to a sales-qualified lead. Such precision makes the most of resource allocation and maximises your conversion opportunities. It’s essential to have a strong feedback loop between sales and marketing teams to enrich this process, fine-tuning lead qualification criteria to ensure a consistently high-quality pool of sales-qualified leads ready for engagement. This collaborative effort extends beyond simple process efficiency, enhancing customer experience and fostering loyalty. By guiding leads through their buying experience with detail-oriented, strategic insights and tailored engagement, businesses can achieve not just higher conversion rates but also build lasting relationships with their customers. Moving a Lead from MQL to SQL Moving a lead from MQL to SQL involves several key steps that help sales teams identify and qualify leads with the highest potential for conversion. Here’s a detailed look at the process: 1. Determine BANT Criteria Fulfillment:Before qualifying an MQL as an SQL, sales representatives assess whether the lead meets the BANT criteria: Budget, Authority, Need, and Timeline. This evaluation determines if the lead has the financial resources, decision-making authority, genuine requirement for the product or service, and a specific timeframe for purchase. Leads that satisfy these criteria are considered strong candidates for further qualification. 2. Lead Scoring:Lead scoring is vital in prioritising MQLs based on their likelihood of converting into customers. Sales teams assign numerical values to various lead attributes, such as industry, company size, job title, engagement level, and website activity. Leads with higher scores are deemed more sales-ready and are nurtured accordingly. 3. Lead Nurturing:Nurturing MQLs involves providing them with relevant information and resources that educate them about the product or service and address their pain points. This can be achieved through personalised email campaigns, webinars, case studies, and content marketing. The goal of lead nurturing is to build trust, credibility, and desire, ultimately moving the lead closer to becoming sales-qualified. 4. Scheduling a Meeting or Call:Once an MQL demonstrates a strong interest in the offering and exhibits readiness to engage in a sales conversation, the next step is to schedule a meeting or call. This allows the sales representative to delve deeper into the lead’s requirements, understand their challenges, and present tailored solutions. 5. Closing the Deal: The final stage of the MQL to SQL journey involves closing the deal and converting the lead into a customer. This entails negotiating terms, addressing objections, and guiding the lead through purchasing. Successful deal closure relies on effective communication, skilful negotiation, and a customer-centric approach. By systematically following these steps, sales teams can effectively identify and qualify MQLs, nurturing them into SQLs and ultimately driving revenue growth. The Difference Between an MQL and SQL In the sales world, understanding the difference between a Marketing Qualified Lead (MQL) and a Sales Qualified Lead (SQL) is crucial for optimising lead generation and conversion processes. While both MQLs and SQLs represent potential customers, they are at different stages of the sales funnel, each requiring distinct strategies for nurturing and qualification. An MQL is a lead that has shown some interest in a company’s product or service, typically through interactions with marketing initiatives such as website visits, content downloads, or email campaigns. MQLs have demonstrated a level of awareness and engagement with the brand but may not yet be ready to make a purchase decision. Nurturing MQLs involves providing them with relevant content, answering their questions, and building trust to move them further down the sales funnel. On the other hand, an SQL is a lead that has been deemed by the sales team to be a good fit for the company’s product or service and is ready to be contacted by a salesperson. SQLs have expressed a stronger interest in the offering and have typically engaged in more substantial interactions with the company, such as requesting a demo, scheduling a consultation, or providing contact information. They are considered sales-ready and more likely to convert into customers than MQLs. The key difference between an MQL and an SQL lies in their level of qualification and readiness to engage with the sales team. MQLs require further nurturing and education to become SQLs, while SQLs are considered hot leads actively considering a purchase and ready for direct contact from a salesperson. Why Differentiating Between MQLs and SQLs is Important Distinguishing between MQLs and SQLs is of paramount importance for several reasons. Firstly, it enables businesses to allocate their resources more efficiently. By focusing their efforts on SQLs, sales teams can prioritise leads that are most likely to convert, maximising their chances of success. This targeted approach allows businesses to optimise their sales processes and achieve greater investment returns. Secondly, differentiating between MQLs and SQLs enhances sales team productivity. Sales representatives can concentrate their time and energy on nurturing and converting SQLs, rather than wasting effort on unqualified leads. This increased focus leads to higher productivity, improved sales performance, and increased revenue generation. Moreover, differentiating between MQLs and SQLs elevates the customer experience. Businesses can provide more relevant and personalised interactions by engaging with leads who are genuinely interested in their offerings. This enhances customer satisfaction and builds stronger relationships, fostering loyalty and increasing the likelihood of repeat business. Lastly, distinguishing between MQLs and SQLs offers valuable insights into the sales funnel. By analysing the conversion rates of MQLs to SQLs, businesses can gain a deeper understanding of their sales process and identify areas for improvement. This data-driven approach allows businesses to refine their lead generation and nurturing strategies, continuously optimising their sales funnel and driving sustainable growth. In conclusion, differentiating between MQLs and SQLs is crucial for efficient lead management and revenue generation. By recognising and nurturing SQLs, businesses can optimise their sales efforts, enhance customer experiences, and gain valuable insights into their sales funnel, ultimately achieving greater success and profitability. SQL vs. MQL: A deeper dive Sales-qualified leads (SQLs) and marketing-qualified leads (MQLs) are pivotal concepts in the sales and marketing realm. SQLs are prospects deemed worthy of pursuit by the sales team, while MQLs are potential customers generated through marketing initiatives but not yet deemed sales-ready. Distinguishing between SQLs and MQLs is crucial for efficient lead management and revenue generation. SQLs are often further along the sales funnel, exhibiting a higher interest in a company’s offerings and a greater likelihood of purchasing. These leads hold higher value for the company as they have a greater potential to close deals and contribute to revenue growth. On the other hand, MQLs require further nurturing before they can be considered sales-ready. These leads have demonstrated some level of interest in a company’s products or services but need additional qualifications to assess their purchase intent and readiness. Marketing teams are vital in generating MQLs by implementing targeted campaigns and capturing relevant data from potential customers. While the distinction between SQLs and MQLs is essential, there’s no rigid formula for categorising leads. Different companies may have varying criteria for defining SQLs and MQLs based on their specific sales processes and target markets. However, understanding these key differences enables sales and marketing teams to collaborate effectively, focusing their efforts on leads with the highest conversion potential. By aligning their strategies and nurturing MQLs into SQLs, sales and marketing teams can optimise their lead generation and conversion processes, ultimately driving revenue growth and achieving organisational success. Saleforce and sales qualified leads LIKE.TG is one of the most popular customer relationship management (CRM) platforms on the market, and it offers a range of features that can help businesses manage and track sales-qualified leads (SQLs). The Sales Cloud Lead Management module provides a centralised location for storing lead information, tracking interactions, and managing the sales process. LIKE.TG also allows businesses to create custom lead-scoring models and qualification criteria, so they can focus their sales efforts on the most promising leads. One of the benefits of using LIKE.TG for SQL management is that it provides a way to track the entire customer journey, from the initial lead capture to the closed deal. This allows businesses to identify which marketing and sales strategies are most effective and to make adjustments as needed. LIKE.TG also provides a range of reporting and dashboard options, so businesses can easily track their progress and measure their success. Here are some specific ways that LIKE.TG can be used to manage and track SQLs: Lead capture: LIKE.TG can be used to capture leads from various sources, including website forms, email marketing campaigns, and social media. Lead scoring: LIKE.TG can be used to score leads based on various criteria, such as their industry, company size, and recent website activity. Lead qualification: LIKE.TG can be used to qualify leads based on specific criteria, such as their budget, timeline, and decision-making process. Opportunity management: LIKE.TG can be used to track the progress of sales opportunities, from the initial contact to the closed deal. Reporting and dashboards: LIKE.TG provides a range of reporting and dashboard options, so businesses can easily track their progress and measure their success. Businesses can use LIKE.TG to manage and track SQLs to improve their sales efficiency, close more deals, and grow their revenue.

Trailblazers are truly the heart and soul of LIKE.TG. Everyone who wants to innovate and deliver success with LIKE.TG can be a Trailblazer. LIKE.TG’s technology helps companies of all sizes deliver customer and employee success from anywhere. The customers, partners, and technology professionals that make up the LIKE.TG ecosystem are seeing endless growth and opportunity. According to a recent IDC report, the LIKE.TG ecosystem will create 9.3 million new jobs and 1.6 trillion in new business revenues worldwide by 2026. This growth is powered by Trailblazers — the learners and innovators who use LIKE.TG to build successful careers, companies, and communities around the world. LIKE.TG’s technology helps companies of all sizes deliver customer and employee success from anywhere. The customers, partners, and technology professionals that make up the LIKE.TG ecosystem are seeing endless growth and opportunity. According to a recent IDC report, the LIKE.TG ecosystem will create 9.3 million new jobs and 1.6 trillion in new business revenues worldwide by 2026. This growth is powered by Trailblazers — the learners and innovators who use LIKE.TG to build successful careers, companies, and communities around the world. So, what is a Trailblazer? Trailblazers are truly the heart and soul of LIKE.TG. And we’ve made it our mission to pave pathways for anyone to unlock career opportunities and provide them with the tools needed to succeed. Trailblazer /treyl-bley-zer/noun A pioneer; an innovator; a lifelong learner; a mover and shaker. A leader who leaves a path for others to follow. Most importantly, a person who builds a better world for others. We believe everyone who wants to innovate and deliver success with LIKE.TG can be a Trailblazer. Whether you’re just starting your career or reskilling for a new one. Whether you’re an experienced leader helping teams to deliver digital transformation or an entrepreneur building business apps. The opportunities are truly endless, and we invite everyone to explore the possibilities. Here, we celebrate some of our amazing Trailblazers and explore how you can start your own Trailblazer journey. Who are Trailblazers? Trailblazers come from all walks of life and deliver success in a variety of roles. Here are a few Trailblazer Stories to show the beautiful diversity of our community, pathways to success, and opportunities to give back: Brian Owens, Business Systems Analyst Brian and his fiance had a pivotal conversation about their future in January 2020. Soon after, Brian decided to pursue a tech career and went all-in on learning with Trailhead, LIKE.TG’s free online learning platform. After many hours of studying, building apps in his Trailhead Playground, and networking with the Trailblazer Community, Brian earned his LIKE.TG Admin Certification. Brian landed his first job as a LIKE.TG Business Analyst in April of 2020. He is eager to help others follow in his footsteps and co-hosts certification study groups and spreads the word about LIKE.TG to Historically Black Colleges and Universities (HBCUs). Erika McEvilly, Junior Developer Erika walked away from a successful business development career when she had her babies. After a few years, she decided to pursue flexible work and discovered LIKE.TG through Supermums, a UK-based Trailblazer Workforce Partner. During her job search, Erika was encouraged to pursue a LIKE.TG Developer career. So she learned to code during the pandemic, with the help of RAD Women Code and Trailblazers around the world. Today, Erika is a Junior Developer for a major financial institution and is paying it forward as co-leader of the London LIKE.TG Developer Community Group. Tracy Lim, Head of CX for Retail Tracy started out as a risk analyst in the banking industry but quickly determined she belonged in marketing. After a stint in B2B sales where she honed her listening skills, Tracy’s leadership offered her an opportunity to break into the field. She excelled at the blend of art and science, which led to opportunities to lead digital transformation and customer experience in the banking industry. When Tracy attended Dreamforce, she discovered the power of peer connections and a passion for helping others. Tracy passes on her love of technology by making Trailhead learning and friendly competitions part of her team’s regular routine. She also leads the LIKE.TG Marketer Group in Manila, Philippines. Max Rudman, CEO Max is the CEO and founder of Prodly, an app that helps businesses automate low-code app development. Before Prodly, Max took a Configure-Price-Quote app from an idea to a thriving company that was acquired by LIKE.TG with 200+ employees. In 2019, Max had new inspiration to solve app development challenges. He decided to build Prodly, which now has 50+ employees and 40+ five-star reviews on AppExchange. Max pays it forward by sharing experience and lessons learned with other entrepreneurs and always enjoys the mutual benefit of shared learning. What’s the story behind the Trailblazer hoodie? The creation of the iconic black hoodie is central to the Trailblazer origin story. In 2015, the Trailblazer spirit was thriving in our community, and we wanted to create a way for them to showcase that identity and spirit. So we created the first black hoodie with “Trailblazer” written across the front in script font. Originally, Trailblazers earned hoodies by learning during LIKE.TG events. Now anyone who wants to wear their Trailblazer pride can get one on the LIKE.TG Store. We also give golden Trailblazer hoodies as a gift of gratitude to Trailblazers who share their stories of doing well and doing good at LIKE.TG events around the world. How do you become a Trailblazer? Anyone can be a Trailblazer with LIKE.TG. Here are a few ways to get started on your journey: Connect with Trailblazers from Anywhere: Join the Trailblazer Community to collaborate with Trailblazers online, and choose from more than 1,300 local and virtual community-led Trailblazer Community Groups in 90+ countries around the world. Skill up on Trailhead: Build your tech and business skills on Trailhead, our free online learning platform. Build your business: Learn how to extend the power of LIKE.TG with apps and Build Apps as an AppExchange Partner. Share your inspiration and expertise: Encourage friends and family to explore career paths in the LIKE.TG ecosystem. Provide answers to product questions, and volunteer to help new Trailblazers skill up and find jobs through Trailblazer Mentorship and Trailblazer Workforce Partners. Trailblazers are the true heart and soul of LIKE.TG, and we love to succeed together. We can’t wait to hear your #TrailblazerStory. Please keep us posted on the Trailblazer Community and social! Don’t forget to spread the word to your family, friends, and communities you love. This post was originally published on the U.S.-version of the LIKE.TG blog.

AI-powered marketing automation has emerged as a leading trend, surpassing industry buzz. This transformative technology, particularly when integrated with LIKE.TG, reshapes how brands engage with their audience, providing exceptional experiences while concurrently reducing operational costs. What is AI (Artificial Intelligence) Marketing Artificial Intelligence (AI) marketing represents a paradigm shift in how businesses approach marketing strategies. By harnessing the power of AI, companies can automate and enhance various marketing processes, unlocking a world of possibilities and revolutionising how they engage with their target audience. AI marketing leverages data, analytics, and machine learning to optimise marketing efforts, personalise customer experiences, and elevate overall marketing efficiency and effectiveness. This data-driven approach empowers businesses to make informed decisions and accurately identify trends, patterns, and customer preferences. With these insights, companies can tailor their marketing campaigns to resonate with their audience, increasing engagement, conversions, and customer loyalty. Moreover, AI marketing streamlines marketing operations by automating repetitive and time-consuming tasks, allowing marketing teams to focus on more strategic and creative pursuits. This automation encompasses content generation, social media management, email marketing, and customer service, ensuring a consistent and engaging presence across multiple channels. AI marketing is not just a buzzword; it’s a transformative force reshaping the marketing landscape. By embracing AI, businesses gain access to a wealth of new tools, data science and technologies, empowering them to reach, engage, and convert their target audience with unparalleled precision and effectiveness. In today’s competitive business environment, AI marketing has become an indispensable tool for businesses seeking to thrive and stay ahead of the curve. AI Marketing encompasses various use cases, including: 1. Data Analysis: Automating the collection and analysis of large volumes of marketing data from different campaigns and programs, eliminating the need for manual sorting. 2. Content Generation: AI generates both short and long-form content for marketing purposes, including video captions, email subject lines, web copy, blogs, and more. 3. Media Buying: Predicting a business’s most effective advertisement and media placements, maximising the return on investment (ROI) of marketing strategies while reaching the target audience. 4. Real-time Personalisation: Modifying a customer’s experience with marketing assets, such as web pages, social media posts, or emails, to align with their past preferences and encourage specific actions, such as clicking a link, signing up, or purchasing. 5. Natural Language Processing (NLP): Utilising AI to generate human-like language for content creation, customer service bots, personalised experiences, and more. 6. Automated Decision-Making: Assisting businesses in deciding which marketing or business growth strategies to employ based on historical or external data inputs. By adopting AI marketing strategies, businesses unlock the potential to deliver exceptional customer experiences, build stronger customer relationships, and drive sustainable growth in the ever-evolving digital landscape. AI marketing represents the future of marketing, and businesses that embrace its transformative power will be well-positioned to succeed in the years to come. How does AI Marketing work? AI marketing uses artificial intelligence technologies to automate and enhance marketing processes. These technologies can be applied to a wide range of marketing tasks, with AI marketing platforms including: Marketing Automation: AI automates lead generation, scoring, and customer retention tasks. By leveraging AI, marketers can identify potential customers and engage with them at the optimal time when they are most likely to respond positively to marketing messages. Content creation: AI can generate marketing content, such as blog posts, articles, and social media posts. This can save businesses time and money while still producing high-quality content. Customer service: AI can provide customer service by answering questions and resolving issues. This can free up human customer service representatives to focus on more complex tasks. Predictive analytics: AI can analyse data and predict customer behaviour. This information can be used to personalise marketing campaigns and improve customer engagement. Personalisation: AI technologies create customer profiles based on data gathered from their purchase history and interactions. Marketers can then deliver targeted advertisements, offers, and new products that align with customers’ preferences. Targeted marketing, powered by customer data, enhances engagement, conversion rates, and overall marketing return on investment (ROI). Forecasting: AI serves as a valuable tool for predictive analytics and forecasting. Predictive analytics utilises data from past customer interactions to anticipate their future actions. When applied to larger audience segments and scaled up, AI can also forecast business metrics such as revenue outcomes, providing valuable insights for strategic decision-making. Overall, AI marketing is a powerful tool that can help businesses reach, engage, and convert their target audience. By leveraging AI, companies can gain a competitive edge and thrive in the digital age. How is AI changing digital marketing? Artificial Intelligence (AI) has emerged as a transformative force that is reshaping the digital marketing landscape. Its capabilities are automating mundane tasks and empowering marketers to delve deeper into strategic initiatives. One remarkable application of AI lies in crafting personalised customer experiences. By leveraging AI-driven tools, marketers can analyse customer behaviour, preferences, and past interactions to deliver tailored product or service recommendations. This personalised approach fosters stronger customer relationships and enhances the overall brand experience. Furthermore, AI is pivotal in aiding marketers to comprehend their customers more profoundly. Through meticulous customer data analysis, AI uncovers hidden patterns, trends, and insights. With this knowledge, marketers can devise targeted and effective marketing strategies that resonate with their audience. Beyond enhancing customer experiences, AI also revolutionises how marketers measure their campaigns. Real-time tracking and analysis of campaign performance empower marketers to make informed adjustments, ensuring optimal allocation of resources and budget. This data-driven approach minimises guesswork and maximises return on investment. In content creation, AI proves to be an invaluable asset. AI identifies topics and interests that captivate the target audience by analysing customer data. This enables marketers to craft highly relevant, engaging content that resonates with their customers. Compelling content fosters brand loyalty and drives conversions, propelling businesses toward success. Examples of AI’s practical applications in digital marketing abound. Chatbots, powered by AI, simulate human conversations, providing round-the-clock customer support and assistance. Personalised recommendations, driven by customer data, enhance user experience and boost sales. Dynamic pricing, enabled by AI, optimises pricing strategies based on market dynamics, maximising profits while ensuring competitive offerings. Fueled by AI’s data analysis capabilities, predictive analytics empowers marketers to anticipate customer behaviour and trends. This foresight allows for developing highly targeted and successful digital marketing campaigns. As AI evolves, its impact on digital marketing will only deepen. The future holds boundless opportunities for marketers to harness the power of AI, unlocking new frontiers of innovation and driving unprecedented success. What Are the Types of AI Marketing Tools? In the marketing realm, artificial intelligence (AI) has emerged as a game-changer, offering many solutions that automate and enhance various tasks. 1. Machine Learning: Machine learning, driven by AI, utilises computer algorithms to automatically analyse information and enhance digital marketing campaigns based on experience. By leveraging relevant historical data, machine learning devices can inform marketers about effective strategies and help avoid repeating past mistakes. 2. Big Data and Analytics: The rise of digital media has generated a significant amount of “big data,” presenting opportunities for marketers to gain insights and accurately assess value across different channels. However, the abundance of data can be overwhelming. AI marketing comes to the rescue by rapidly sifting through the data, filtering it to its essentials, and providing analysis. It can also recommend the most valuable elements for future marketing campaigns. 3. AI Marketing Platforms & Tools: Effective AI-powered marketing solutions offer digital marketers centralised platforms for managing the vast amounts of collected consumer data. These AI marketing platforms extract valuable marketing intelligence from the target audience, empowering marketers to make data-driven decisions about effective outreach strategies. For instance, frameworks like Bayesian Learning and Forgetting aid marketers in understanding a customer’s receptiveness to specific digital marketing efforts, leading to improved campaign targeting. 4. Content creation: Generating high-quality articles, blog posts, social media updates, and personalised emails. By analysing vast amounts of data, AI tools identify trends, customer preferences, and relevant topics, allowing businesses to create content that resonates with their target audience. Additionally, AI optimises content by recommending keywords and phrases that enhance search engine rankings and drive organic traffic. 5. Personalisation: Another critical aspect of modern marketing. AI algorithms analyse customer data to gain profound insights into individual preferences, behaviours, and pain points. This information is then leveraged to create personalised marketing campaigns, product recommendations, and customer experiences. By delivering tailored content and offers, businesses enhance engagement, conversions, and overall customer satisfaction. 6. Voice search: With the proliferation of voice-activated devices like smart speakers and smartphones, voice search has become a critical channel for businesses to connect with customers. AI-powered voice search optimisation ensures businesses are easily discoverable to customers using voice commands, maximising their visibility in voice search results. These examples illustrate the diverse spectrum of AI marketing solutions available. As AI technology evolves, we can anticipate even more innovative and advanced solutions to revolutionise how businesses market their products and services. What Are the Benefits of Leveraging AI in your Marketing strategy? Integrating AI into marketing practices has unlocked a treasure trove of benefits that can dramatically transform a business’s approach to reaching and engaging its target audience. One of the most profound advantages of AI marketing is its ability to elevate customer experiences. By deploying AI-powered chatbots and virtual assistants, companies can provide immediate and personalised responses to customer inquiries, ensuring a smooth and enjoyable customer journey. Moreover, AI-driven analytics offer businesses a profound understanding of customer preferences and behaviours, enabling them to tailor their marketing strategies precisely and deliver content that resonates deeply with their audience. Another significant competitive advantage of AI in marketing lies in its remarkable potential to enhance operational efficiency. AI automation seamlessly handles repetitive and time-consuming tasks such as data entry, automated email marketing campaigns, and social media management, liberating marketing teams to devote their attention to more strategic and creative endeavours. This streamlined workflow optimisation increases productivity and significant cost savings, allowing businesses to allocate resources judiciously and effectively. AI’s role in improving decision-making and optimisation within marketing campaigns is genuinely remarkable. By meticulously analysing vast amounts of data and uncovering hidden patterns and trends, AI-powered analytics empower marketers with invaluable insights that guide strategic decisions. This data-driven approach allows businesses to optimise their campaigns with surgical precision, target specific segments more accurately, and maximise their return on investment, propelling their growth trajectory to unprecedented heights. Personalised marketing and customer engagement soar to new heights with the advent of AI marketing. AI algorithms can delve deep into customer data, extracting profound insights that enable the creation of personalised experiences and marketing messages tailored to individual preferences. This profound level of personalisation fosters deep customer engagement, cultivates unwavering brand loyalty, and dramatically elevates the likelihood of conversions. AI-powered recommendations and dynamic pricing strategies amplify personalised customer experiences, driving exponential revenue growth and unparalleled customer satisfaction. Finally, AI injects a refreshing dose of agility and innovation into marketing strategies, propelling businesses to the forefront of industry trends. As AI technology continues its relentless march forward, it unveils many new opportunities for businesses to stay ahead of the curve and outpace competitors. By wholeheartedly embracing AI and fearlessly experimenting with its innovative applications, companies can differentiate themselves from the crowd, drive unprecedented growth, and shape the future of marketing. From AI-generated content creation to predictive modelling, the possibilities are boundless, empowering businesses to unleash their full potential and achieve extraordinary success in the dynamic digital age. Cost Efficiency: AI minimises costs by streamlining expenses across various marketing tactics, from SEO and content marketing to paid ads and influencer outreach. This enables digital marketing teams to redirect resources towards strategic objectives, ensuring a more efficient budget allocation. Personalisation: Addressing the increasing demand for personalised experiences, LIKE.TG AI analyses past customer data platforms to deliver tailored messages at scale. This not only enhances customer engagement but does so without the need for manual intervention. Predictive Analysis: LIKE.TG AI empowers businesses to anticipate industry trends and customer behaviour. Organisations can inform their marketing strategy by analysing customer behaviour and market trends and optimising product launches and campaigns for maximum impact. ROI Optimisation: Leveraging AI-driven insights, LIKE.TG AI contributes to a boost in return on investment. It is a reliable tool for identifying growth opportunities, optimising ad spend, and enhancing the overall customer experience. Time Effectiveness: LIKE.TG AI marketing automation liberates time from repetitive tasks, allowing teams to focus on high-value activities. This includes content creation, nurturing customer relationships, and fostering a more strategic marketing approach. What Are the Pitfalls and Challenges of AI Marketing? Artificial intelligence (AI) is a powerful tool that can be used to improve marketing campaigns. Still, it is essential to be aware of the potential pitfalls and challenges before you invest in AI marketing solutions. This section will discuss some of the key challenges and considerations businesses should consider when using AI for previous marketing campaigns. One of the biggest challenges of AI marketing is the potential for bias. AI algorithms are trained on data, and if the data is biased, then the AI algorithms will also be biased. This can lead to unfair or inaccurate marketing practices, damaging a company’s reputation. For example, an AI algorithm trained on data biased towards white males may be more likely to recommend products and services to white males, even if there are other groups of people who are more likely to be interested in those products and services. Another challenge of AI marketing is the need for more transparency. AI algorithms are often complex and challenging to understand, making it difficult for businesses to know how they make decisions. This can lead to a need for more trust in AI marketing solutions, making it difficult for companies to get the most out of them. Additionally, the cost of AI marketing programs can be a barrier for some businesses. AI marketing solutions can be expensive to develop and implement, making it difficult for small businesses to compete with larger firms with more resources. Finally, there is the potential for AI marketing to be used for malicious purposes. AI algorithms can create fake news stories, spread misinformation, and target people with personalised marketing campaigns designed to exploit their vulnerabilities. This can hurt society and make it difficult for businesses to use AI marketing responsibly. Despite these challenges, AI marketing has the potential to be a powerful marketing tool for businesses. By being aware of the potential pitfalls and challenges, companies can take steps to mitigate these risks and use AI marketing to improve their marketing campaigns. What Are the Examples of AI in Marketing? AI-powered chatbots and virtual assistants are becoming increasingly common on business websites and apps. These AI-driven tools can provide customer service 24/7, answer questions, and help users navigate websites. Chatbots can also collect data and provide insights into customer behaviour. AI-driven personalised email campaigns and content recommendations are another powerful way businesses use AI in digital marketing strategy. By using AI to analyse customer data, companies can create personalised email campaigns that are more likely to be opened and clicked on. AI can also be used to recommend products and content tailored to each customer’s interests. AI-generated product recommendations and upselling opportunities are other ways businesses use AI to boost sales. By using AI to analyse customer data, companies can identify products that customers are most likely to be interested in and then make personalised recommendations. AI can also create upselling opportunities by suggesting complementary products or services that customers might not have considered otherwise. AI-powered social media marketing analytics and optimisation tools are helping businesses to get more out of their social media marketing efforts. Using AI to analyse social media data, companies can identify which posts are most popular, track brand sentiment, and find influencers who can help them reach their target audience. AI can also optimise social media campaigns by automatically posting content at the best times and targeting the right audience. AI-enabled image and video recognition technology is used for content moderation and optimisation. By using AI to analyse images and videos, businesses can automatically identify inappropriate content and remove it from their websites and social media channels. AI can also be used to optimise images and videos for search engines and social media platforms, making them more likely to be seen by potential customers. How to use AI marketing To effectively utilise AI marketing tools and platforms, businesses must first identify their target audience and understand their needs and preferences. This can be done through market research, data analysis, and customer feedback. Once the target audience is identified, businesses can choose the right AI marketing tools and platforms to reach and engage with them. Many different AI marketing tools and platforms are available, each with unique features and capabilities. Businesses should carefully evaluate the options and select the best fit for their needs and budget. Once the AI marketing tools and platforms are in place, businesses can create a data-driven AI marketing strategy. This strategy should outline the goals and objectives of the AI marketing campaign, as well as the specific tactics that will be used to achieve those goals. The fully integrated AI marketing platform and strategy should also include a plan for measuring the campaign’s success and adjusting as needed. One of the most important aspects of AI marketing is personalisation. AI can collect and analyse customer data, which can then be used to create personalised marketing campaigns tailored to each customer’s needs and interests. This can lead to increased engagement, conversions, and customer loyalty. AI can also automate repetitive marketing tasks, such as sending emails, scheduling social media posts, and generating reports. This can free up marketing teams to focus on more strategic tasks, such as developing new marketing campaigns and analysing data. Businesses can gain a competitive edge using AI marketing and deliver more personalised and relevant customer experiences. This can lead to increased engagement, conversions, and customer loyalty. What are Generative AI Marketing Predictions and Trends? The realm of marketing stands on the precipice of a transformative era as generative AI reshapes the landscape, empowering businesses to craft personalised and captivating content, automate mundane tasks, and, with data science talent, unlock profound insights into customer behaviours. As the accessibility and sophistication of AI technology surge, the coming years will undoubtedly witness an exponential embrace of AI-driven marketing strategies. One pivotal trend is the meteoric rise of AI-powered content creation tools, capable of generating high-quality and distinctive content at an unprecedented pace, thereby liberating marketing teams to channel their efforts into more strategic endeavours. Concurrently, AI-driven chatbots are undergoing rapid advancements, offering businesses an avenue to engage with customers round-the-clock, promptly addressing queries with remarkable efficiency. Another trend that warrants close attention is the ascent of AI-powered predictive analytics. This technology empowers marketers to comprehend their target audience better and tailor their marketing endeavours with pinpoint accuracy. By meticulously analysing customer data, AI uncovers hidden patterns and trends, paving the way for personalised marketing campaigns that resonate profoundly with customers, fostering stronger connections and driving business growth. Furthermore, generative AI holds immense promise in elevating customer experiences to unprecedented heights. AI-powered virtual assistants emerge as invaluable assets, providing real-time assistance to customers and swiftly resolving their queries and concerns with remarkable efficiency. Additionally, AI seamlessly personalises the customer journey, presenting tailored recommendations and enticing offers that align precisely with individual preferences, ensuring unparalleled customer satisfaction and loyalty. In essence, the future of AI marketing brims with boundless potential. As AI marketing technology embarks on its inexorable evolution, we can anticipate many groundbreaking innovations that will revolutionise marketing strategies, propelling businesses to unprecedented heights of success. How can you best implement AI? To successfully implement AI in your marketing efforts, there are several key steps to follow: 1. Identify your goals and objectives: Clearly define what you want to achieve with AI marketing. Whether improving customer engagement, increasing lead generation, or optimising campaign performance, having clear goals will guide your AI implementation strategy. 2. Assess your current marketing efforts: Evaluate your existing marketing processes, data sources, and technology infrastructure. Identify areas where AI can complement or enhance your current efforts and prioritise those areas for AI implementation. 3. Choose the right AI tools and platforms: Select AI tools and platforms that align with your goals and objectives. Consider factors such as functionality, scalability, ease of use, and compatibility with your existing systems. 4. Integrate AI into your marketing workflows: Seamlessly integrate AI into your existing marketing workflows to ensure a smooth transition. This may involve training your marketing team members on using AI tools, establishing data-sharing protocols, and updating your marketing processes to accommodate AI-driven insights. 5. Monitor your results and make adjustments as needed: Continuously monitor the performance of your AI marketing initiatives and analyse the results. Use data-driven insights to identify what’s working and what’s not, and make necessary adjustments to optimise your AI marketing investments and implementation. 6. Consider ethical implications: Ensure your AI marketing practices adhere to ethical standards, including data privacy, transparency, and fairness. Implement robust data security measures and obtain consent from customers before using their data for AI-powered marketing. By following these steps, you can effectively implement AI in your marketing efforts and unlock its full potential to drive growth and success. Utilising AI Marketing with LIKE.TG LIKE.TG Einstein is a powerful AI tool that can be used to enhance your marketing efforts. With Einstein, you can create personalised marketing campaigns, automate marketing tasks, and gain insights into your marketing data. Einstein offers a variety of features that can be used for ai enabled marketing campaigns, including: Einstein Lead Scoring: Einstein can help you identify your most qualified leads so you can focus your sales efforts on the most likely to convert. Einstein Segmentation: Einstein can help you segment your customers based on their demographics, interests, and behaviours so you can create more targeted marketing campaigns. Einstein Content Recommendations: Einstein can help you recommend the most relevant content to your customers based on their interests and past behaviour. Einstein Predictive Analytics: Einstein can help you predict customer behaviour and trends so you can make more informed marketing decisions. You can improve your marketing efficiency, effectiveness, and reach by using Einstein. Einstein can help you create more personalised and relevant marketing campaigns, automate marketing tasks, and gain valuable insights into your marketing data. This can lead to increased leads, sales, and revenue. To start with Einstein, you can sign up for a free trial. Once you have signed up for the AI marketing program, you can access Einstein from the LIKE.TG Marketing Cloud. Commonly Asked Questions About AI in Marketing As AI marketing continues to gain traction, it’s natural for businesses to have questions about its implications and applications in marketing program. Here, we’ll address some frequently asked questions about AI in marketing to provide a clearer understanding of this transformative technology. 1. How does AI affect traditional marketing strategies? AI complements traditional marketing strategies by enhancing their effectiveness and efficiency. It automates repetitive tasks, allowing marketers to focus on more strategic and creative aspects. AI also enables personalised customer experiences, data-driven decision-making, and improved campaign performance. 2. What are the limitations of AI in AI marketing tools? While AI offers immense potential, it also has limitations. These include the requirement for high-quality data, the inability to completely replace human creativity and emotional intelligence, and the potential for bias if not adequately managed. 3. How effective is AI for small businesses? AI is highly effective for small businesses as it levels the playing field by providing access to advanced technologies and analytics that were previously only available to larger enterprises. AI can assist small businesses in optimising their marketing efforts, reaching a wider audience, and competing more effectively. 4. Will AI replace human marketers? AI is not meant to replace human marketers but to augment their capabilities. AI handles routine tasks, freeing up marketers to focus on strategic decision-making, creative problem-solving, and building meaningful customer relationships. 5. What are the ethical considerations of using AI in marketing? The use of AI in marketing raises ethical considerations, including data privacy, transparency, and potential bias. Businesses must implement ethical guidelines, obtain customer consent, and ensure responsible AI practices. By addressing these commonly asked questions, businesses can better understand AI marketing and its implications. AI can revolutionise marketing strategies, enabling enterprises to succeed tremendously and deliver personalised customer experiences.

When you think of a copilot, the first thing that comes to mind is probably an airplane. Until now, a copilot has been that person sitting in the second chair in the cockpit, helping the captain on your flight. But sometime last year, the term “copilot” started to trend in a big way in the artificial intelligence (AI) space. Take all of the generative AI technology you’ve come to know and love in apps like ChatGPT, Bard, and Einstein. Now, place that right in the flow of your work — or in that second chair, if you will. At its most basic level, an AI copilot is an AI assistant that can help you accomplish routine tasks faster than before. While the introduction of the modern copilot is linked to the launch of GitHub Copilot in 2021, these AI assistants go back even further. Since the 1990s, AI copilots — which, back then, were basic chatbots like ELIZA and Jabberwacky or virtual assistants like IKEA’s Anna — have been popping up in everything from your email platform to shopping, banking, and medical applications. Here’s the difference between now and then. Imagine you’re booking a business dinner with a client based in a different city. Before the world of AI copilots, you’d first scan the client’s customer relationship management (CRM) record to check for any dietary preferences. Next, you’d open the Resy app and spend far too long looking for a suitable restaurant with availability. Then, on to Expedia to make your travel and lodging reservations, and, finally, your email app to send a charmingly personalised confirmation to your customer. At minimum, you’d be looking at four different apps and at least a half hour of drudgery. Now imagine, instead, that you simply use one app: your trusty AI copilot. Instead of taking four different actions over the course of minutes or hours, you type, “Book dinner with Ted next Thursday.” All the steps above still take place, but the research happens in the background, and mostly without your intervention. Beyond the obvious time savings and the inherent sci-fi novelty, it’s hard to fully articulate the value of this transformation through traditional metrics. These assistants will do the work of dozens of apps to help us build reports faster, craft customer service replies with relevant answers, draft sales emails, send flowers to our bosses, and more. But first, how do they work? How does an AI copilot work? At the heart of AI copilots are powerful building blocks called copilot actions. A copilot action can encompass almost any single task or a collection of tasks for a specific job. These may include: Updating a CRM record. Generating descriptions for new products using your existing CRM data. Composing messages to customers. Handling a range of use cases. Summarising transcripts for a live service agent. Highlighting the most relevant information from meeting notes. These tasks can be “invoked,” or arranged and executed, in any order and are done so autonomously by the AI copilot. This ability to understand requests, reason a plan of action, and execute the needed tasks is what makes these systems and experiences unique. The AI copilot can handle a lot of instructions and learns from that. So, the more actions, the more capable the copilot. Stacked together, actions allow your copilot to perform a dizzying array of business tasks. For example, a copilot can help a service agent quickly resolve an issue in which a customer was overcharged for an order. Or it can help someone in sales trying to close a deal. Want more? Let’s put our copilot into action. Take the example of setting up dinner with your client, Ted. If you use Einstein Copilot, it would know Ted’s initial context, like their name and CRM session history, but it would require a bit more information from you, like the date and time. It could then execute on that and respond with any other questions it may have: It might ask you to clarify which Ted you want to meet with (if you have multiple contacts named Ted) and what type of cuisine Ted prefers. What’s nice about Einstein and other copilots at this level is that it feels like you’re talking with a coworker — but you’re actually chatting with your robust data, which the copilot is serving up in a new conversational way. The AI copilot decides which actions to trigger and then generates runtime dialogues, paraphrasing the actions’ output-data in everyday human language. So, it feels like you’re having a fairly sophisticated conversation with your AI assistant. And then dinner gets set up with little effort on your part. “We’re just telling the system, ‘Hey, do this task,’” said Carlos Lozano, director of product management at LIKE.TG AI. “But behind the scenes, the copilot is orchestrating a complex workflow of business processes and data to deliver a result that would have previously required the user to access multiple actions.” What different types of AI copilots exist? Although the concept of a copilot is fairly new, this technology has existed for a while. Have you ever chatted with a customer service representative only to realise they weren’t a person, but a bot? That’s a type of copilot. It helped you with basic customer service questions, but often couldn’t really get to the important details of your issue. Likely frustrated, you then turned to an actual human for help. Chatbots got more sophisticated with the launch of ChatGPT, Dall-E, Google’s Gemini, and Microsoft’s Bing Chat. Those generative AI platforms — let’s call them Chatbot 2.0 — can help craft emails, write code, generate images, and analyse data. With AI copilots, the interactivity becomes even more conversational, with your own AI assistant working behind the scenes to help improve everything you do. In addition to LIKE.TG, a number of other companies have introduced copilot products to the market, including Microsoft and GitHub, and even Apple is working on one. There are more niche industry-focused AI copilot companies like real-estate digital marketing company LuxuryPresence, healthcare-focused Nabla, and finance-focused ArkiFi. The copilot goes to the next level when it’s connected to data and metadata. What’s metadata? It’s the tagging system that defines your data. For instance, “first name” is the metadata that would define “Ted” in our example. This metadata makes it easier to find, use, and merge your proprietary data. So, this is what separates a workable copilot from a truly exceptional one — one that is super relevant for your everyday work. Here’s the main takeaway: When you are researching adding an AI copilot to your business, determine whether it will simply use external source information, like ChatGPT, or whether you’ll be able to safely connect it to your structured and unstructured data sources. Why you should use an AI Copilot By now, you’re probably familiar with at least one or two large language models (LLMs) like OpenAI’s GPT-4 or Google’s Gemini. These models power chatbots like ChatGPT that are fun to play with and are great for certain tasks. Some, however, only contain data through early 2022, so their responses can be limited. And those models only have access to public information about your business — they don’t have access to your trusted CRM information and data. This means they can’t help you craft relevant customer service answers or supply the juiciest sales opportunities. Nor can they act on your behalf to, say, reply to an email or book a flight. But an AI copilot can do all of the above. Okay, back to your dinner with Ted. You had a successful trip. Now, maybe you want to thank him with a gift basket from his favourite bakery. Because your copilot already has the requisite actions to look up Ted’s CRM contact and account to find his favourite bakery, and to charge goods on your behalf, all you’d need to do is type, “Send Ted his favourite muffins.” Of course, this is only a rudimentary example comprising a couple of copilot actions. Imagine what you could do with an AI copilot capable of orchestrating hundreds, or even thousands, of building blocks in virtually infinite combinations. The gains in efficiency apply to an excitingly wide range of job types. For example, a retail marketer can write product descriptions in numerous languages in just minutes, a healthcare clinician can review X-rays and lab results for multiple patients and help doctors make diagnoses, and a finance worker can use a copilot to analyse reams of data to propose various investment outcomes. The use cases and scenarios go on and on. If it seems like everything related to AI is happening at a breakneck pace — especially when it comes to how you work — and it’s making your head spin, you’re not alone. But you don’t have to be … alone, that is. You’ll have your trusted AI copilot. “With an AI copilot, you can quickly and easily become more efficient and productive, no matter the industry you work in,” Lozano said. “Having a conversational, generative AI-based assistant will truly let you offload those routine tasks while allowing you to interact and engage with data like never before. And that is the beauty of it.” Carlos Lozano, director of product management at LIKE.TG AI, contributed to this article.

When it comes to business transactions, an invoice serves as an essential commercial document. This detailed and itemised record of a transaction between a buyer and a seller captures necessary information about the goods or services provided, their quantities, pricing, and the total amount due, they’re also commonly referred to as bills, statements, or tabs. Beyond their role as a mere record of purchase, invoices play a multifaceted role in business operations. They act as critical pieces of evidence, serving as legal documentation that substantiates the occurrence of a transaction. This documentation becomes particularly significant in cases of disputes or discrepancies, providing a clear and verifiable account of the exchange between parties. A pro forma invoice is an initial estimate of costs provided to a client before services are rendered. It acts as a commitment to provide a service to completion, with the value indicated being subject to market changes. Invoices are also all-important when it comes to managing cash flow, enabling businesses to keep track of their income and expenses. By issuing invoices promptly and accurately, businesses can ensure that payments are received in a timely manner, maintaining a healthy financial flow and avoiding cash flow disruptions. The issuance of an invoice typically follows the delivery of goods or the rendering of services by the seller. It serves as a formal request for payment, outlining the terms and conditions of the transaction, including the payment due date and any applicable discounts or penalties. The buyer is then expected to fulfil their payment obligations in accordance with the specified terms of the commercial invoice, ensuring a smooth and efficient financial exchange between parties. A brief history of invoices Invoices have been used in some form since the days of ancient Mesopotamia, when clay tablets were used to record transactions. The word “invoice” itself comes from the Latin word “invocare,” meaning “to call upon.” The first invoices were used primarily by merchants to record sales and track payments. Over time, invoices became more standardised and were used by businesses of all types. Invoices have evolved significantly over the years, reflecting changes in technology and business practices. Early invoices were handwritten or typewritten and often contained minimal information. However, as businesses grew and became more complex, they became more detailed and standardised. Today, invoices typically include information such as the seller’s name and contact information, the buyer’s name and contact information, the date of the invoice, a description of the goods or services provided, the quantity of each item, the price per item, and the total amount due. In addition to their traditional role as a record of transactions, invoices now serve a variety of other purposes. For example, invoices can be used to: Track sales and manage cash flow Report financial information Comply with tax regulations Facilitate payment processing As businesses continue to evolve, invoices will likely continue to change and adapt to meet new needs. However, the overarching purpose of an invoice – to record a transaction and request payment – will likely remain the same. Functions of invoices Invoices serve several vital functions in the business space. They act as a record of transactions, providing a detailed account of the goods or services provided, the quantities involved, and the agreed-upon prices. They also function as legal documents that enforce payment, outlining the terms and conditions of the sale of goods and services tax specifying the due date for payment. In exceptional cases, such as selling farming products like sugar cane, the buyer determines its value and issues a recipient-created tax invoice based on this determination. Furthering that, invoices serve as a source document for accounting purposes. They provide the necessary information for recording sales, tracking expenses, and calculating taxes. Invoices also play a role in tracking the status of payments, allowing businesses to monitor which invoices have been paid and which are still outstanding. By fulfilling these functions, invoices are key tools for managing cash flow, maintaining accurate financial records, and ensuring timely payments. Effective invoicing practices are needed to ensure the smooth operation of any business. By providing clear and accurate information, invoices facilitate efficient payment processing and help maintain positive relationships with customers. They also contribute to overall financial management by enabling businesses to monitor their financial performance and make informed decisions. Utilising modern invoicing software like LIKE.TG Billing can further streamline the invoicing process, saving time, reducing errors, and enhancing overall efficiency. Different types of invoices, including pro forma invoice There are five main types of invoices that businesses use: sales invoices, credit invoices, debit invoices, progress invoices, and self-billed invoices. Each type of business invoice used has a specific purpose and is used in different situations. Sales invoices are the most common type of invoice and are used to record sales of goods or services. They typically include information such as the seller’s name and contact information, the buyer’s name and contact information, the invoice number, the date of the invoice, a description of the goods or services provided, the quantity of each item, the price per item, and the total amount due. Credit invoices are used to correct errors on sales invoices or to provide discounts or refunds to customers. They typically include information such as the seller’s name and contact information, the buyer’s name and contact information, the invoice number, the date of the invoice, a description of the reason for the credit, the amount of the credit, and the total amount due after the credit has been applied. Debit invoices are used to charge customers for additional goods or services that were not included in the original sales invoice. They typically include information such as the seller’s name and contact information, the buyer’s name and contact information, the invoice number, the date of the invoice, a description of the additional goods or services provided, the quantity of each item, the price per item, and the total amount due. Progress invoices are used to bill customers for work that is in progress. They typically include information such as the seller’s name and contact information, the buyer’s name and contact information, the invoice number, the date of the invoice, a description of the work that has been completed, the percentage of the work that has been completed, the total amount due for the work that has been completed, and the total amount due for the entire project. An interim invoice is issued every month to reflect the work done during that period. This is especially useful for long-term projects with a large scope or prolonged engagement period to ensure payment while working to fulfil the terms of the agreement. Interim invoices refer to a series of invoices issued at different stages of a project, based on an agreed-upon payment schedule. Self-billed invoices are used when a buyer agrees to pay a seller for goods or services without receiving a traditional invoice. They typically include information such as the seller’s name and contact information, the buyer’s name and contact information, the invoice number, the date of the invoice, a description of the goods or services provided, the quantity of each item, the price per item, and the total amount due. What to include on an invoice, such as the invoice number When creating an invoice, it’s crucial to include specific information to ensure its validity and clarity. Here are some essential elements that should be included on an invoice: Business Information: Display the name, address, contact information (phone number and email), and logo (if applicable) of your business or organisation prominently at the top of the invoice. This information helps the customer easily identify the sender and contact you if necessary. Customer Information: Include the name, address, and contact information (phone number and email) of the customer or client receiving the invoice. This information ensures the invoice reaches the intended recipient and facilitates communication regarding payment or any queries. Invoice Number: Assign a unique invoice number to each invoice issued. This number helps in tracking and referencing invoices efficiently. Make sure the invoice numbering system is sequential and non-repeating to avoid confusion. Invoice Date: Specify the date the invoice was issued. This date serves as a reference point for payment terms and helps in managing cash flow effectively. Payment Due Date: Clearly state the date by which the payment for the invoice is due. This information is crucial for both the customer and your business, as it ensures timely payments and prevents late payment issues. Description of Goods or Services: Provide a detailed description of the goods or services provided, including quantity, unit price, and any applicable discounts. Be as specific as possible to avoid any confusion or disputes regarding the charges. Total Amount Due: Calculate and display the total amount due per tax invoice, including any applicable taxes, shipping charges, or additional fees. Make sure the calculations are accurate and clearly presented to ensure prompt payment. Payment Terms: Specify the payment terms, such as accepted payment methods (e.g., bank transfer, credit card, check), any early payment discounts, or any applicable late payment fees. Clearly communicate these terms to avoid misunderstandings and encourage timely payments. Contact Information for Inquiries: Provide contact information (phone number, email, or both) for customers to reach out with any questions, concerns, or inquiries regarding the invoice. This fosters open communication and ensures customer satisfaction. By including these essential elements on your electronic invoices, you ensure that all necessary information is conveyed to your customers, facilitating smooth transactions, accurate record-keeping, and efficient cash flow management for your business. Tips for invoicing, including managing recurring invoices Here are some tips for invoicing that can help you get tax invoices paid faster and improve your cash flow: Send invoices to collect payment promptly. The sooner you send an invoice, the sooner you can get paid. Try to send invoices within 24 hours of completing a job or providing a service. Offer early payment discounts. Encourage customers to pay their invoices early by offering a small discount. For a services tax, for example, you could offer a 2% discount for payments made within 10 days. Provide tax invoices with multiple payment options. Make it easy for customers to pay their invoices by offering multiple payment options. This could include accepting credit cards, debit cards, checks, and online payments. Follow up on late payments. If a customer is late on a payment, don’t be afraid to follow up with them. Send a reminder email or make a phone call to let them know that their payment is past due. Keep accurate records of all invoices. It’s important to keep accurate records of all invoices, including the date the final invoice was sent, the date the payment was received, and the amount of the payment. This will help you track your cash flow and ensure that you’re getting paid for all of your work. By following these tips, you can improve your invoicing process and get paid faster. Modern invoicing software with LIKE.TG Billing Modern invoicing software can help you automate your invoicing process, saving you time and money. LIKE.TG Billing is a modern invoicing software that integrates with your other LIKE.TG products. It is easy to use, scalable, and reliable. LIKE.TG Billing offers a variety of features that can help you improve your invoicing process, including: Automatic recurring invoice generation: LIKE.TG Billing can automatically generate invoices for you based on your sales orders and contracts. This saves you the time and hassle of having to create invoices manually. Customisable templates: LIKE.TG Billing allows you to create customisable invoice templates that match your company’s branding. This helps you create professional-looking invoices that impress your customers. Easy invoice payment and processing: LIKE.TG Billing makes it easy for your customers to pay their invoices. They can pay online using a credit card or PayPal, or they can mail in a check. Automatic payment reminders: LIKE.TG Billing can automatically send payment reminders to your customers who have overdue invoices. This helps you get paid faster. Detailed reporting: LIKE.TG Billing provides you with detailed reporting on your invoices. This information can help you track your sales and cash flow, and make informed decisions about your business. If you’re looking for modern invoicing software that can help you automate your invoicing process and save time and money, LIKE.TG Billing is a great option. What you can do with invoice software With invoice software, businesses can automate and streamline the invoicing process, saving them time and money. By automating tasks such as invoice generation, payment tracking, and sending reminders, invoice software can significantly reduce the administrative burden associated with invoicing. Additionally, invoice software can help businesses create professional-looking invoices that enhance their brand image and make a positive impression on customers. Invoice software often includes customisable templates that allow businesses to design invoices that match their unique branding and preferences. These templates can include the business logo, contact information, and other relevant details, ensuring that invoices are consistent and visually appealing. Furthermore, invoice software can generate invoices in various formats, such as PDF, HTML, and Excel, making it convenient for customers to view and save invoices in their preferred format. Invoice software also simplifies the process of tracking and managing payments. With features such as online payment processing and automatic payment reminders, businesses can easily track the status of invoices and receive payments faster. This can significantly improve cash flow and reduce the risk of late payments. Additionally, invoice software can generate detailed reports on invoicing data, providing businesses with valuable insights into their invoicing trends and customer payment behaviour. These reports can help businesses make informed decisions about their invoicing strategies and improve their overall financial management. By leveraging the capabilities of invoice software, businesses can streamline their invoicing processes, enhance their professional image, and improve their cash flow management. With features such as automation, customisable templates, easy payment processing, and detailed reporting, invoice software provides businesses with the tools they need to optimise their invoicing practices and achieve greater success. Advantages of using invoice software Invoice software is a powerful tool that offers a multitude of advantages to businesses, streamlining their invoicing processes and boosting efficiency. Here are some key benefits of incorporating invoice software: 1. Time-Saving Automation: Invoice software automates tedious and repetitive invoicing tasks, saving businesses valuable time. From generating invoices to tracking payments, everything can be done with just a few clicks, freeing up employees to focus on more strategic tasks that drive growth. 2. Error-Free Precision: Invoice software eliminates human errors often associated with manual invoicing. No more worries about incorrect calculations or data entry mistakes. This precision not only enhances the business’s credibility but also prevents disputes and maintains customer satisfaction. 3. Professional Image Enhancement: With the invoice template software, businesses can design and send professional-looking invoices that reflect their brand identity. Customised templates and logos make invoices visually appealing, leaving a positive impression on customers and fostering trust. 4. Simplified Payment Management: Invoice software streamlines the payment process by providing a centralised platform for tracking invoices and payments. Businesses can easily monitor the status of unpaid invoices, send payment reminders, and accept online payments, ensuring a smooth and efficient cash flow. 5. Data-Driven Decision Making: Invoice software generates detailed reports and analytics, providing businesses with valuable insights into their invoicing trends and customer payment behaviour. This data empowers businesses to make informed decisions, identify areas for improvement, and optimise their invoicing strategies for maximum profitability. 6. Enhanced Customer Experience: Invoice software enables businesses to provide a superior customer experience. Customers can easily access and download invoices, view payment history, and contact the business with any queries. This convenience fosters customer satisfaction and loyalty. 7. Scalability and Flexibility: Invoice software is scalable, adapting to the growing needs of businesses. Whether handling a small volume of recurring invoices, or a large number of transactions, invoice software can seamlessly accommodate business growth without compromising efficiency. By embracing invoice software, businesses unlock a world of benefits, transforming their invoicing processes and gaining a competitive edge. From time-saving automation to data-driven decision-making, invoice software empowers businesses to thrive in today’s market.

Starting a small and medium-sized business (SMB) involves planning, making key financial decisions, and understanding what it takes to succeed. The good news is, that you have the potential to make a big impact if you can learn what it takes to be successful as an SMB.These tips will help you realise that small businesses make big bucks. But first, let’s be sure to define SMBs and why they are so important to our economy.What are small and medium-sized businesses?A business with 1-20 employees is defined as small, while businesses with 21-100 employees are considered medium-sized. That’s the standard definition for SMB, of course. The term SMB, which stands for “small and medium-sized business,” is a useful one for analysts and researchers tasked with defining the difference between the IT needs of large enterprises and the challenges faced by smaller companies. The second attribute used to define an SMB is annual revenue: small business is usually defined as organisations with less than $50 million in annual revenue; midsize enterprise is defined as organisations that make more than $50 million, but less than $1 billion in annual revenue.SMBs collectively have the power to shift entire industries, define new requirements for enterprise software, and essentially change the way all of us work.Why are SMBs so important? MBAs and economists will tell you that their power comes from the fact that the economy can only support a limited number of large enterprises, creating a long-tail market for SMBs. That market consists of many small and medium-sized businesses that (in aggregate) carry almost as much market power as the bigger players.Large enterprises have room for fluff — they swell and slow down if they aren’t careful. SMBs don’t have that luxury, and as a result, they are built for speed. The only way to thrive as a fast-paced organisation is to fill your team with people with heart, and then feed their passion for what you do. Which makes the customer their number one priority.In fact, 65% of customers expect companies to adapt to their changing needs and preferences. But 61% of customers say most companies treat them as a number. As a small or medium-sized business, you have the ability to treat every customer as an individual.What are the benefits of an SMB?The global economy relies on small and medium-sized businesses for job creation, economic growth, and innovation. Governments are now recognising the importance of small and mid-size businesses and are allocating resources and programs to support them. Small and medium enterprises play a large role in driving competition in both local and global markets. They benefit local economies by creating employment opportunities, generating tax revenue, and contributing to the success of other businesses. Additionally, these businesses make significant contributions to global exports and distribution.What are the challenges for smaller organizations? Small and medium businesses do have challenges that can hinder growth and success. One major challenge is keeping up with the increasing preference for digital interactions among customers. Failure to have the right tools for the job can leave these businesses lagging.Cybersecurity poses a growing threat to small and medium businesses as well. SMBs are particularly vulnerable to ransomware attacks due to inadequate antivirus software. Upgrading to a robust security solution designed for enterprises can safeguard their data, applications, and devices.Expanding into new markets is another hurdle for SMBs. Limited resources often prevent them from performing thorough market research, making it difficult to make informed decisions. Additionally, disruptions in supply chains can disproportionately impact mid-size businesses, as larger companies have more leverage in negotiations.SMB = Speed-Maximising BusinessesB2B brands hoping to sell into the bustling SMB market can shift their understanding of the term to a new acronym that fits their unique profile better. SMBs are not just small and medium-sized businesses — they are speed-maximising businesses.Under this new acronym, anyone hoping to land the business of an SMB needs to understand three core tenets of the way they work.1. SMBs have a need for speed. They need to move quickly, and can’t stomach your request for a six-month deployment. They want you to move fast or get out of the way. If you don’t, they’ll drop you — fast.2. Motivations vary for SMBs. If they wanted to be pencil-pushers or cogs in a wheel, SMB personnel would have joined large enterprises. Consider what motivates your prospects before you make introductions. When you do, you’ll spark more interesting and highly motivated conversations.3. Different SMBs are different. Shocking, right? But you’d be surprised by how many sales representatives try to run the same play against vastly different companies. Each SMB is unique, so take the time to learn about your prospect’s business before making sale-stalling assumptions.How do you help your SMB grow?To foster growth, SMBs should focus on investing in capabilities that support growth including improving business automation and administrative tasks. By leveraging technology and collaboration tools, they can drive growth by streamlining operations, reducing costs, and increasing efficiency.Cloud-based solutions that integrate people, finance, and payroll functions enable SMBs to access real-time data and analysis, which all help informed decision-making.As small businesses transition into mid-size companies, employee engagement platforms can play a crucial role in enhancing employee satisfaction and retention, contributing to overall growth.SMBs may be small, but they have big heart and can make a huge impact. With the right tools, people, and strategy, they can help our economy as a whole.

Today’s world faces unprecedented disruption and change. The digitisation of every aspect of our life, economy, and society continues rising. To thrive in this dynamic ecosystem, an organisation needs true business agility and innovation at scale. This calls for a new operating paradigm to drive digital evolution in the new world. This is where API-led connectivity comes in. The future of business is composable, connected, and automated. Any successful future organisation must adopt composability as it’s the means to resilience, adaptability, and growth in the face of change and disruption. What is API-led connectivity? API-led connectivity is a methodical way to connect data to applications through reusable and purposeful APIs within an organisation’s ecosystem. These APIs are developed to play a specific role: unlocking data from systems, composing data into processes, or delivering an experience. Building blocks are the most fundamental unit of the composable enterprise. They have a clearly articulated purpose of driving a business or technology outcome. They can be automated and orchestrated with other capabilities, making them interoperable. They are discoverable, accessible, and manageable. They represent the “nouns and verbs,” or the “vocabulary” of your business. It’s the API that converts a piece of software into a building block by enabling governance, manageability, visibility, security, monetisation, intelligence, and discovery. API-led connectivity goes beyond the REST APIs to enable universal connectivity. Why is API-led connectivity important? API-led connectivity is fundamental in driving business agility for an organisation. It allows an organisation to tap into the innovation done by other players in their ecosystem. As the picture above suggests, a retail business leverages capabilities (shipping, payments, marketing, infrastructure, social media, sentiment analysis, geo-location, etc.) from other organisations in addition to its own capabilities to drive success now. The flexibility in connecting both the internal and external building blocks to meet the business needs is the key to driving business agility. So when a new initiative comes along, rather than building the solution components, API-led connectivity enables the rewiring, reconnecting, and orchestrating of the building blocks. The winner in the digital race is not the one who creates the fastest, but who integrates the fastest. This makes API-led connectivity a critical integration strategy for an organisation. The number of moving parts and the complexity of the technology and business landscape will continue to increase. So the traditional ad-hoc point-to-point connections often implemented as an afterthought will not scale. They have led to brittle systems that are prone to failure and prohibitive to maintain. API-led connectivity, on the other hand, is future-proof and enables scalable universal connectivity. It changes the role of integration from a necessary evil to a business differentiator. It enables a flexible model for value exchange between building blocks, thereby allowing organisations to have agility in implementing innovative business models. What are the 3 APIs that enable API-led connectivity? API-led connectivity provides an approach for connecting and exposing building blocks in an ecosystem. Their scope can vary: within a specific domain, within a line of business (LoB), across an organisation spanning multiple LoBs or geographies, and into the external ecosystem. There is a natural tiering as well that moves from the system of records to the system of engagements. The APIs used in an API-led approach to connectivity fall into three categories: System APIs Process APIs Experience APIs System APIs System APIs usually access the core systems of record and provide a means of insulating the user from the complexity or any changes to the underlying systems. They create the nouns of your business vocabulary into reusable building blocks. Once built, many users can access data without any need to learn the underlying systems and can reuse these APIs in multiple projects. Process APIs Process APIs interact with and shape data within a single system or across systems (breaking down data silos). They often represent the verbs of your business vocabulary. They help implement an organisation’s processes without having to worry about the source systems where data originates or the target channels through which that data is delivered. They lend themselves very well to automation capabilities and Bots. Experience APIs Experience APIs are catered toward delivering a delightful end-consumer experience. They get their power by maniacally focusing on the consumer and reusing the building blocks already created (typically in the form of System or Process APIs). Often built by a different persona, they can speed up delivery by working from the API specs built as a part of the design-first approach. This drives a coherent omnichannel experience without having to go back to the system of records in an unmanageable point-to-point fashion. Get IT articles selected just for you, in your inbox Sign up now How does API-led connectivity work? API-led connectivity is a critical element in closing the IT delivery gap and enabling the composable enterprise. Let’s use a simple scenario to explain this point: Suppose you need to develop a web app to provide real-time order status and order history for sales teams to engage with customers. Let’s assume you have customer data in SAP and LIKE.TG, inventory data in SAP, and order data in an e-commerce system. In a traditional point-to-point integration approach, your IT team might aggregate customer data by wiring together customer data from both systems with code. Then, the aggregated customer data is further combined with order data in the e-commerce system to produce both the order status and order history data with more code. Now, these two data sources are hooked into a web app API which the web app can leverage. This project might be considered a success because it was launched on time, on budget, and has the correct functionality – but does it solve for business agility? If the IT team must build a mobile app, they aren’t able to use any of the work from previous projects. They have to start from scratch. Incremental changes become expensive, and soon the familiar and undesirable spaghetti code pattern begins to take shape. But with an API-led connectivity approach, when teams must build a new mobile app, they now have reusable building blocks to start from (created from System and Process APIs), eliminating most of the work needed to build them. Creating the mobile app, therefore, is a matter of rewiring instead of recreating. This makes it easier to innovate and add new services, e.g. adding shipment status information in the same way they accessed order status and history. This is the key to driving agility and adopting a product mindset as opposed to a project mindset. API-led connectivity is not limited to just RESTful APIs; it also relies on flexible universal connectivity patterns. How does API-led connectivity reduce IT’s workload? As change and demands for digitisation grow, IT finds itself in a tough spot. The number of new projects necessary to implement today’s technology and business needs measured against IT’s capacity to deliver them is spiraling upward. IT has to deliver on these ever-increasing projects and maintain legacy systems even as its resources stay constant. Eventually, what results is an IT digital transformation delivery gap: Most IT decision-makers expect their budgets to stay the same or increase very slightly, so unlimited resources are not an option. This is where the digital paradigm of building a composable, connected, and automated enterprise is the way out. Rather than delivering on individual projects, IT delivers the reusable building blocks of the enterprise, and with the right tooling and automation, enables LoB folks to innovate as well. API-led connectivity is the cornerstone of building this connected ecosystem. Every new project permits the creation of new building blocks. So when a new initiative comes along, rather than starting from scratch, API-led connectivity enables their reuse. This re-assembly can reduce the IT digital transformation delivery gap. Emergent benefits of API-led connectivity When an organisation uses API-led connectivity to build a composable enterprise, they can eliminate the IT digital transformation gap. Business agility API-led connectivity allows an organisation to tap into the innovation done by other players in their ecosystem. This enables businesses to be nimble and agile, not only in connecting to the right building blocks but also providing flexibility in the business value exchange models. As the picture shows, it’s not just the technical flexibility, but this connectivity also enables the right kind of value exchange between building blocks. For example, if you adopt a freemium monetisation strategy, you can have a different level of SLA for a trial customer and a different Platinum SLA for your Tier 1 customers. Build vs. buy: Driving the business differentiator API-led connectivity in the composable ecosystem helps business and IT leaders make the right build vs. buy decision. The choices made here, what to build versus buy or partner, have far-reaching consequences on the success of a project and its time-to-value. Businesses build their business differentiator, which captures their intellectual property, which they can monetise. You can integrate the supporting domains into the composable enterprise. So the all-important build vs. buy decision becomes create vs. integrate decision enabled by API-led connectivity. Drive the intelligent enterprise Through API-led connectivity, businesses can have end-to-end real-time visibility into their data flows, thereby creating an organisation’s central nervous system. This ‘business context aware’ visibility into the data and the related meta data enables them to see the forest for the trees and to drive network intelligence, analytics, and data science/machine learning models that were previously unattainable. It also lets the organisation collect real-time business KPIs, which eventually help them measure and fine-tune their business operations and strategy. Break data silos and create a customer 360 This universal connectivity also helps break data silos. It lets you build a true customer 360 with data attributes and sources that span across the entire ecosystem (internal, LoB, or external). APIs are the purest form of data: Context-aware, real-time, domain-specific, secure, and curated for consumption. API-led connectivity also delivers a coherent way to engage with your customers across any channel seamlessly. Experience APIs drive a specific channel of user engagement. By connecting to the Process APIs as opposed to the systems of record directly, they drive a consistent user experience and make it easy to spin up a new channel. API-led connectivity in the composable enterprise can drive any System of Engagement. The engagement layer could be a LIKE.TG Cloud, Slack, or any other technology component. This is critical in driving a consistent and coherent omnichannel experience for your customers. How does MuleSoft enable API-led connectivity? MuleSoft has pioneered the API-led connectivity architectural paradigm, which has now found universal acceptance. The key part of the offering starts from the vision of driving business agility at scale by enabling the composable, connected, and automated enterprise, as mentioned earlier. The next part is the methodology: the architectural paradigm of connecting your organisation’s building blocks using API-led connectivity as a key pillar to delivering on this vision. It’s the actual product capabilities and continuous innovation to make the vision a reality delivered through the Anypoint platform and related product capabilities. It provides the most flexible ways of connecting the building blocks: REST Connect, Orchestration, RPA, BOTs, GraphQL, EDI, and more. It supports various integration patterns: APIs, PubSub, EDA, ETL, ELT, microservices, ESB, B2B, SFTP, and others. A rich marketplace with pre-built OotB box connectors, templates, and accelerators for key industries and SaaS providers makes it easy to start enabling universal connectivity in your ecosystem. The tightly integrated iPaaS, full API lifecycle, and automation capabilities help accelerate your digital transformation journey. On average, MuleSoft’s customers found that the agility and speed provided by API-led connectivity led to delivering projects three to five times faster and increased team productivity by 300% compared to legacy or homegrown integration solutions. Examples of API-led connectivity in action Let’s look at real-world scenarios to understand the impact of API-led connectivity. Financial industry: Multiple LoBs and omnichannel Consider a scenario where an organisation provides multiple offerings to its customers through four different LoBs operating under different brands: checking and account management, loans and credit cards, savings and investments, and auto loans. The four LoBs operated in their silos resulting in a broken customer experience and a missed opportunity to cross-sell and upsell the customer. This is the illustrative three-layered ALC architecture for them: They started their journey by creating a Process level “Identity and Authentication Customer” API, providing a consistent way to authenticate their customers across all offerings. A significant step forward in driving CX and a necessary step in its digital transformation journey. The “Get Accounts, and Transactions” API in the Process layer was instrumental in driving a consistent omnichannel experience. It tapped into the four system APIs below: Core Bank Accounts API, Loans API, Credit Card API, and Auto Lease API – each representing the four different LoBs. This enables a holistic view of the customer’s financial health. Not only that, but the same “Get Accounts and Transactions API” can now power multiple experiences: the financial advisor in the financial services cloud, marketing cloud, online banking platform, and mobile banking app. Developers don’t have to duplicate the work of going from the top to the bottom of the stack repeatedly. This simplifies the architecture, reducing the long-term operational cost, and it’s future-proof. It gives the organisation the ability to switch the core banking provider without having any significant upstream/downstream impact, thereby enabling a true plug-and-play architecture. It also allows multiple providers to co-exist during the transition period without disrupting the business. This is a great example of how API-led connectivity drives a true customer 360. Transportation industry: Partner and supply chain Consider a scenario of a company that provides freight and transportation services to mid-market clients. Their business strategy required them to onboard new partners quickly, so they built an EDI transformation layer using MuleSoft’s Partner Manager to cater to their partner’s different data formats and transport protocols. They ended up reducing the time to onboard a new partner from six to nine months down to 60 days. This is the illustrative three-layered ALC architecture for them. But the story doesn’t end there. It’s not just about getting the right information from your partner, supplier, or manufacturer in the door, but how you act on it with other entities inside your organisation to drive efficiency, visibility, and actionable insights. That’s where API-led connectivity complements the traditional B2B/EDI patterns. The System layer at the bottom unlocks the system of records, or the “nouns” of your organisation. For example, you could use the OotB connector for SAP to unlock the invoice or the location data. The process layer orchestrates the System APIs to model your business processes. The Experience layer on the top is customised to deliver a delightful end-customer experience. The beauty of this architecture is that each layer abstracts the complexity from the layer below and creates reusable building blocks. So the shipment 360 API that draws from order, transportation, location, and inventory can not only service the partner ecosystem, but the same shipment API can also drive up the customer experience by powering the service portals and mobile apps as well. API-led connectivity-based architecture is built for agility and reuse. How can I learn more about API-led connectivity? To discover more about customers in every industry who have benefited from API-led connectivity, find out how API-led connectivity enables digital transformation.

Today we are constantly generating and consuming vast amounts of data. From social media posts and online transactions to sensor data and scientific research, the volume, variety, and velocity of data are growing exponentially. This phenomenon is known as big data. In this article, we will explore the concept of big data, its origins, and its significance in the modern world. We’ll also look closely into how big data works, provide real-world examples of its applications, and discuss its impact on various industries and sectors. Finally, we will look ahead to the future of big data and its potential to transform our lives and businesses even further. What is big data? There’s an overwhelming influx of data that characterises our daily interactions. This phenomenon, commonly referred to as big data, encompasses a vast and ever-growing collection of information. It extends beyond the traditional structured data found in relational databases to include unstructured data such as social media posts, sensor data, and weblogs. The sheer volume, variety, and velocity of this data present both challenges and opportunities for businesses and organisations. The term “big data” was coined in the early 21st century to describe the exponential growth and complexity of data. Its defining characteristics are often summarised by the three Vs: Volume, Velocity, and Variety. Volume refers to the immense quantity of data generated daily. Velocity pertains to the rapid speed at which this data is produced and processed. Variety encompasses a diverse range of data formats, including structured, unstructured, and semi-structured data. The sources of big data are as varied as the data itself. Social media platforms, e-commerce transactions, sensor networks, and scientific research contribute to this ever-expanding pool of information. The proliferation of smartphones, IoT (Internet of Things) devices, and cloud computing has further accelerated the growth of big data. History of big data The history of big data is relatively short, but it has already had a profound impact on the way we live and work. In the early days of computing, data was scarce and expensive to store. In the early days, raw data was often collected and stored without much processing, making it challenging to derive meaningful insights. As a result, businesses and organisations were forced to be very selective about the data they collected and stored. However, with the advent of cheaper storage and more powerful computers, it became possible to collect and store vast amounts of data. This led to the rise of big data. The term “big data” was first coined in 2005 by Roger Mougalas. Mougalas used the term to describe the massive amounts of data that were being generated by the Internet and other digital sources. He argued that this data could be used to gain valuable insights into human behaviour and to improve decision-making. In the years since Mougalas coined the term, big data has become a major force in business, government, and society. Big data is used to improve customer service, develop new products and services, and make better decisions. It is also used to study human behaviour, track disease outbreaks, and fight crime. The potential of big data is enormous. However, there are also challenges associated with big data. One challenge is the sheer volume of data that is available. This data can be difficult to store, process, and analyse. Another challenge is the privacy of big data. Big data can be used to track people’s movements, habits, and preferences. This information can be used for good, but it can also be used for malicious purposes. Despite the challenges, the potential of big data is too great to ignore. Big data is changing the world, and it is important to understand how it works and how it can be used. Data-driven innovation Data-driven innovation is the process of using big data analytics to analyse data and derive insights for informed decision-making. This can help organisations improve efficiency and productivity, develop new products and services, and improve customer service. Data scientists and analysts play a crucial role in analysing data to uncover trends and patterns that can drive business decisions. One example of data-driven innovation is the use of big data analytics to improve customer service. By analysing customer data, businesses can identify trends and patterns in customer behaviour. This information can then be used to develop targeted marketing campaigns, improve customer service strategies, and develop new products and services that meet the needs of customers. Another example of data-driven innovation is the use of big data analytics to improve healthcare. By analysing patient data, healthcare providers can identify trends and patterns in patient health. This information can then be used to develop personalised treatment plans, improve patient outcomes, and reduce healthcare costs. The potential of data-driven innovation is enormous. By harnessing the power of big data, businesses and organisations can improve their operations, develop new products and services, and make better decisions. However, there are also challenges associated with data-driven innovation. One challenge is the sheer volume of data that is available. Another challenge is the privacy of big data. Businesses and organisations need to be careful about how they collect, store, and use big data. They need to make sure that they are protecting the privacy of their customers and employees. Despite the challenges, data-driven innovation is a powerful tool that can help businesses and organisations improve their operations and make better decisions. By harnessing the power of big data, businesses and organisations can gain a competitive advantage and achieve success. How Big Data Works with Structured and Unstructured Data In order to understand big data, it’s important to know how it works. A data lake is often used to store unstructured big data, allowing for flexible data management and quick access. The big data process can be broken down into five key steps: data collection, data storage, data processing, data analysis, and data visualisation. The first step in the big data process is data collection. This involves gathering data from a variety of sources, such as sensors, social media, and customer transactions. Once the data has been collected, it needs to be stored in a way that makes it easy to access and analyse. This is where data storage comes in. The next step is data processing. This involves cleaning and preparing the data to ensure data quality, which may include removing duplicate data and correcting errors. This may involve removing duplicate data, correcting errors, and converting the data into a format that is compatible with the analysis tools that will be used. Once the data has been processed, it can be analysed to identify patterns and trends. This involves using statistical and machine-learning techniques to identify patterns and trends in the data. This information can then be used to make informed decisions about everything from product development to marketing strategies. The final step in the big data process is data visualisation. This involves presenting the results of the data analysis in a way that is easy to understand. This may involve creating charts, graphs, and other visual representations of the data. Big data examples Big data is being used by businesses across a wide range of industries to improve their operations and deliver better customer experiences. Here are a few examples: Retail: Big data is used by retailers to track customer purchases, analyse customer behaviour, and develop targeted marketing campaigns. Retailers use big data analysis to uncover customer preferences and optimise inventory management. This information can be used to improve the shopping experience, increase sales, and reduce costs. Healthcare: Big data is used by healthcare providers to improve patient care, reduce costs, and develop new treatments. Healthcare providers, as business users, leverage big data to enhance patient care and operational efficiency. This information can be used to identify patients at risk for certain diseases, develop personalised treatment plans, and track the effectiveness of treatments. Finance: Big data is used by financial institutions to detect fraud, assess risk, and develop new financial products. This information can be used to protect customers from financial crime, improve the efficiency of financial transactions, and develop new investment opportunities. Transportation: Big data is used by transportation companies to improve logistics, reduce costs, and improve safety. Big data helps transportation companies in resource management by optimising routes and reducing fuel consumption. This information can be used to optimise shipping routes, track the location of vehicles, and predict traffic patterns. Manufacturing: Big data is used by manufacturers to improve quality control, reduce costs, and develop new products. This information can be used to identify defects in products, optimise production processes, and develop new products that meet the needs of customers. These are just a few examples of how big data is being used by businesses to improve their operations and deliver better customer experiences. As the volume, velocity, and variety of data continue to grow, we can expect to see even more innovative and groundbreaking uses of big data in the years to come. Big Data Technologies in Today’s World Big data has become an integral part of our daily lives and has revolutionised the way we interact with technology, businesses, and information. In today’s world, the amount of data created every day is simply mind-boggling. According to recent estimates, the global data creation is a staggering 2.5 quintillion bytes of data every single day, and this number is only expected to grow exponentially in the years to come. The impact of big data can be seen across various industries and sectors. For instance, in the healthcare sector, big data is used to improve patient care, reduce costs, and develop new treatments. By analysing vast amounts of patient data, healthcare providers can identify trends and patterns, leading to more personalised treatment plans and better patient outcomes. Similarly, in the financial industry, big data plays a crucial role in detecting fraud, assessing risk, and developing innovative financial products. The retail industry also leverages big data to enhance customer experiences and drive sales. By tracking customer purchases, analysing customer behaviour, and developing targeted marketing campaigns, retailers can gain valuable insights into consumer preferences and provide more personalised services. Big data also plays a significant role in the manufacturing industry, where it is used to improve quality control, reduce costs, and develop new products. Furthermore, the entertainment industry has embraced big data to create more engaging and personalised experiences for consumers. By analysing user data, content providers can tailor recommendations, improve streaming quality, and develop new content that resonates with their audience. The growth of the Internet of Things (IoT) has further amplified the significance of big data. With billions of devices connected to the internet, from smartphones and smartwatches to industrial sensors and home appliances, the volume of data generated is immense. This data holds valuable insights into consumer behaviour, operational efficiency, and asset tracking, enabling businesses to make informed decisions and optimise their operations. The world of big data continues to evolve rapidly, presenting both opportunities and challenges for businesses and organisations. Harnessing the power of big data effectively requires robust data management strategies, advanced analytics capabilities, and a commitment to data privacy and security. By embracing big data and leveraging its potential, businesses can gain a competitive edge, drive innovation, and transform their operations. Future of Big Data and Machine Learning The future of big data is bright. As the amount of data in the world continues to grow, so too will the need for tools and technologies to process and analyse it. This growth will create new opportunities for businesses and organisations of all sizes to use big data to improve their operations, develop new products and services, and make better decisions. One of the most important developments in the future of big data will be the continued growth of artificial intelligence (AI) and machine learning (ML). These technologies are already being used to automate many of the tasks associated with big data processing and analysis, and they will become even more powerful in the years to come. As AI and ML become more sophisticated, they will be able to identify patterns and trends in data that are invisible to the human eye. This will allow businesses and organisations to make even better decisions and to develop new products and services that are tailored to the needs of their customers. Another important development in the future of big data will be the increasing use of data visualisation tools. These tools make it possible to present big data in a way that is easy to understand and interpret. This will allow businesses and organisations to communicate the results of their big data analyses to their stakeholders in a way that is clear and concise. Finally, the future of big data will also see an increasing focus on data privacy and security. As more and more data is collected and stored, it is important to ensure that it is protected from unauthorised access and use. Businesses and organisations will need to invest in data security measures to protect their data from cyberattacks and other threats. The future of big data is full of potential. As the amount of data in the world continues to grow, so too will the opportunities for businesses and organisations to use it to improve their operations, develop new products and services, and make better decisions.

Isn’t business to business (B2B) sales just like any other type of sales? In the simplest sense, maybe this statement is true. But in the real world, B2B sales is very different from business to consumer (B2C) sales. In the battleground of B2B sales, salespeople face multiple decision-makers, lengthy closing times, and complex sales cycles.Helping other businesses realise what they need to be successful, and fulfilling these needs with your offerings and solutions is B2B sales.With the digital age, the traditional model of B2B sales has been disrupted by changes in the way people purchase goods and services. Internet penetration and the consequent explosion in easily accessible knowledge and networking have affected B2B sales as much as anything else. But in every change, there is opportunity.What is B2B sales?B2B sales involve one business selling goods and/or services to another business, as opposed to selling them directly to end consumers. B2B salespeople need to be more convincing and good at negotiating, as business buyers are highly evolved and deal sizes can be huge. They must thoroughly understand their prospect’s organisation, needs, challenges, and industry. The role of B2B salespeople has evolved from simple selling to something more consultative, making them advisors to their customers.What does a B2B sales process look like, and how does it work?The B2B sales process is a series of steps that is meant to take a business buyer from the initial stage of discovery to a closed sale. It requires a well-thought-out strategy and the use of sales techniques suitable for each target persona.Every organisation will need a slightly different B2B sales process involving anywhere from five to eight steps. A typical eight-step sales process consists of:Developing in-depth understanding of offerings: The best sales reps have great command over their offerings and where these fit into specific markets. They can easily justify their value proposition to the right customers. This requires them to do the background work and continuously hone their mastery of the products and services they sell.Prospecting: Prospecting involves finding new prospects that have a need or use for your offerings. Salespeople can use both online (LinkedIn, Quora, digital marketing campaigns, etc.) and offline (conferences, expos, referrals, cold calls, etc.) channels to find new prospects.Qualifying: Once new quality leads are identified, salespeople connect with them to know if they are potential buyers. Taking prospects through the sales process, especially for B2B sales, can be expensive and time-consuming, which is why it is important to qualify leads early in the process.Research: A salesperson should know about the prospect’s organisation, their needs, challenges, and industry trends. Research is vital in B2B sales due to its complex nature and the professional expertise buyers are likely to have. Also, with a single view of past interactions, sales reps can access all the relevant information about each prospect in one place for more contextualised conversations. Good research enables salespeople to tailor their pitch to each stakeholder’s needs.Pitching: Pitching can be in the form of a presentation, product demonstration, or a combination of multiple methods. Pitching is one of the most crucial steps in converting a B2B prospect into a customer.Handling objections: Savvy business buyers make decisions based on the value your company can add to theirs. Salespeople should use the qualification and research stages to anticipate questions prospects might ask. The better a salesperson can respond to questions and objections, the more confidence they can inspire in prospects.Closing: Depending on the situation, closing a deal can take the form of a quotation, price negotiation, or contract signing.Nurturing: B2B sales are rarely one-off transactions. Most B2B sales are focused on getting repeat business. B2B salespeople need to maintain and nurture relationships with their clients even after deals are closed. This could involve following up with them on delivery of their purchased products and services, providing after-sales support, or simply checking in periodically for cross- and upsell opportunities.The B2B sales process serves as a roadmap for B2B salespeople to maximise their efficiency by stringently following the steps crucial for closing deals and ensuring repeat business.What is a B2B sales funnel?A B2B sales funnel is the sales process from the customer’s perspective. Like the sales process, the sales funnel too can have multiple stages. But today, this customer journey is not linear. Customers spend a significant amount of time researching and discussing their options with friends and colleagues. By the time a salesperson is involved in this journey, customers may even be close to a decision.A typical B2B sales funnel involves these stages:Awareness: The buyer finds out about your offerings either by themselves, a targeted ad, or from a cold-calling salesperson.Interest: A conversation with a salesperson piques the buyer’s interest in the product; they get an early idea of whether the product or service will serve their needs or not.Objection: After receiving a pitch from the salesperson, the buyer considers it and raises objections, if any. Objections allow the buyer to get more information about the product or service.Decision: After responding to their objections, the buyer decides if they want to buy the product or service being offered.Purchase: This is when the deal is closed after the prospective buyer’s organisation arrives at a decision.Evaluation: After purchasing the product or service, the buyer uses it and evaluates whether it fulfils their needs and solves their problems.Repurchase decision: After evaluating it, the buyer may or may not decide to repurchase the product or service. If the evaluation is positive, the buyer might consider repurchasing. If it’s negative, they might look for other suppliers. Outreach from salespeople can often greatly help swing the repurchase decision in favour of the seller.The B2B sales funnel helps a B2B salesperson better understand the buyer’s journey and align the sales process accordingly, thereby increasing the chances of closing the sale.B2B versus B2C sales: What’s the difference?The most obvious difference between B2B and B2C sales is the nature of the customers. Selling clothes to a customer is a completely different process from selling industrial textile looms to a manufacturer.For B2B sales, professional buyers or executives from various industries are customers. Anyone can be a customer for business to consumer sales.The differences in the customers’ nature also create differences in their decision-making and purchasing processes. Business buyers make purchases based on rational, strategic bases to generate further value. In contrast, consumer buyers can make decisions based on reasoning, emotions, desires, or personal values.The difference in purchase decisions calls for B2B and B2C salespeople to adopt very different sales tactics and marketing strategies.Here are some key characteristics of B2B sales:Larger average transaction values: B2B sales typically involve larger order quantities and pricier products, both of which contribute to higher average transaction values. Businesses are usually willing to pay a good price for the goods or services they need, if they perceive value in them.Multiple stakeholders: B2B sales often involve several stakeholders on the buyer side and are rarely dependent on one person’s approval. Some stakeholders might merely influence the sale, while others will have the authority to sign off on the final contract. More people involved means more of the salesperson’s time and effort needed to convince each stakeholder.Professional buyers: Businesses buy products and services that are likely to have a marked impact on their operations, justifying the due diligence needed to arrive at any decision. Some businesses even hire professionals to guide their purchasing decisions. B2B salespeople also need discipline and a high level of expertise to address purchasers’ objections and arguments satisfactorily.Fewer customers: Due to the specificity of most B2B products and services, the addressable market for a B2B salesperson is often quite narrow, especially when compared to B2C products and services. B2B customers return a higher lifetime value, compensating for their fewer numbers and high acquisition costs.Long sales cycles: The B2B sales cycle is usually lengthy owing to the involvement of multiple stakeholders and decision-makers, higher average transaction values, complex purchasing processes, and the material impact of the purchase and offerings on the buyer’s business. A typical B2B sales cycle can last several months, involving multiple meetings, emails, and phone calls.In B2B sales, relationship building through constant nurturing is needed to ensure repeat business. Getting new customers costs 5-10 times more than keeping existing ones. Since B2B sales typically involve bigger deal sizes and complex processes, repeat business becomes crucial for your business’s predictable growth.Not that repeat sales don’t matter in B2C sales. However, relationship building in B2C sales is done at a personal, emotional level, and involves smaller purchase values than B2B sales.How do you make B2B sales?Making B2B sales requires you to follow the same loose framework for making any sale. Build a sales strategy that is well-suited to target your ideal customer, break it down into repeatable steps that your sales team can follow, measure performance, and make improvements as and when needed.The difference is in the way you approach your prospects and customers and how you align your selling model with their purchasing process.Try to make your sales process as convenient, fast, and transparent as possible. Salespeople also need to have a good understanding of what they sell. B2B customers do not appreciate their time wasted, and showing a lack of knowledge and experience will not inspire confidence.Research well and get to know what they sell, to whom, which markets, etc. Understand the role of each stakeholder and their individual challenges and needs. This can help you hyperpersonalise your pitch to show how your offerings can address multiple pain points and goals. In addition, automating parts of your sales cycle is an effective way of making it faster.What are some B2B sales techniques?Within a basic sales process, sales teams can employ one or more of the following sales techniques to increase their chances of succeeding:Solution selling: This involves gaining a deep understanding of the buyer’s business, needs, and problems, and offering a tailored, holistic solution in response, rather than pushing one-size-fits-all products. Solution sellers almost never offer products off-the-shelf. Solution selling might incur higher sales costs, but the solution’s suitability usually results in a higher rate of closing.Account-based sales: This method focuses on premium customers, offering them end-to-end, highly tailored experiences. Each account, with all its shareholders, is treated as a complete market. A host of resources that would otherwise be put into full market segments is allocated to each account. This helps grow revenues from each key account through more targeted cross- and upselling.Challenger sale: In this method, salespeople educate and inform the customer about their needs in response to market trends, risks, and opportunities. The salesperson takes on a more active role here, helping customers realise a need in the first place.Sandler selling system: The system places greater emphasis on the buyer-seller relationship. Salespeople need to establish themselves as trusted advisors to clients, inspiring mutual confidence to work towards shared success. This system leverages human psychology and the buyer-seller dynamic to accelerate the sales cycle.Value selling: Value selling instructs salespeople to emphasise and establish the value addition their products or services can make to the buyer’s business. The value additions presented need to be concrete and measurable, such as cost savings, revenue increments, or productivity improvements.What are some key B2B sales tips?No matter the sales techniques used, all B2B salespeople can benefit from the following tips:Tailor customer communication on a case-to-case basis. This helps convey the value your offerings can add to the customer’s business faster.Continuously train your sales team. Professional B2B buyers appreciate salespeople who demonstrate expertise.Focus on solving problems rather than pushing your products, as B2B buyers are constantly looking for ways to improve efficiencies and reduce costs. Show active listening, empathy, and critical thinking by asking the right questions and providing relevant information.Adopt omnichannel outreach to stay in touch with B2B customers. With greater digitisation, B2B buyers too are warming up to newer channels to engage and buy on.Use social selling techniques to get B2B customers’ attention and approval. They care about their peers’ opinions, making referrals a great way to establish contact.Collect and display positive customer feedback, using these case studies for your sales playbook.Ensure all other customer-facing teams, such as marketing and customer service, are aligned to the sales goal.Beyond CRM solutions, employ sales engagement tools that use data and Artificial Intelligence (AI) to enable faster, smarter decision-making and action.Consider building a dedicated B2B sales team to increase revenue shares from your most valuable customers. This makes more sense if your organisation has different business units or departments that handle both B2B and B2C customers.Inside versus outside B2B salesInside B2B sales is made remotely by reps sitting in an office (or any location), whereas outside B2B sales is those made by reps in the field.Outside sales tend to be more successful because of the personal touch salespeople can add by interacting with customers directly. Outside salespeople might close more sales and drive order values up. However, outside sales is more expensive and time-consuming.With a wide variety of communication tools now available to salespeople, selling from anywhere is increasing in popularity, more so since the pandemic struck. Inside sales cost less and give managers more control and better oversight of the sales process.How is B2B sales changing?B2B sales has undergone a dramatic change in recent years. Business buyers now have access to a lot of information about products, services, and suppliers. They also have a wide range of options to choose from. This makes the B2B sales space more competitive and requires B2B salespeople to engage customers more meaningfully.Business buyers now expect a highly personalised purchase experience. To deliver this, salespeople must possess an intimate understanding of the needs and desires of buyers. Salespeople can also leverage technology to conduct better research about a prospect and their organisation or industry.Sellers also have access to a range of B2B sales tools that they can deploy, including data analysis tools, sales reporting and tracking, B2B marketing automation and targeting programs, and sales management and forecasting software. These tools improve the efficacy of sales teams, helping reps move clients along the sales funnel faster and more successfully.The way forward for B2B salesB2B sales has changed, but for the better. With more tools at the disposal of both buyers and sellers, salespeople can proactively reach out to prospective buyers at the right time. With business buyers expecting highly personalised purchase experiences, salespeople need to leverage data-driven tools and their social skills. Addressing the needs of business buyers and forging lasting relationships with them is the key to success in B2B sales.Now more than ever, it’s important to build deeper connections with customers, manage your business in real time, and adapt fast as the world continues to evolve. Learn how Sales Cloud can help you grow your business and bring out the best in every rep.This post was originally published on the LIKE.TG I.N. blog.

Cross-selling involves selling related, supplementary products or services based on the customer’s interest in, or purchase of, one of your company’s products. Its a great way of increasing customer loyalty and deeping customer relationships which in turn can improve customer lifetime value and retention. This makes cross-selling an excellent growth strategy. What we will cover: Cross-Selling vs. UpsellingExamples of Cross-SellingBenefits of Cross-SellingPotential Drawbacks of Cross-SellingSteps for Cross-Selling to CustomersCross-Selling techniquesCross-Selling: Key facts and FAQs Cross-Selling vs. Upselling Cross-selling and upselling are two distinct practices that involve approaching existing customers and convincing them to purchase additional products or services. In the case of upselling, your goal is to sell a more expensive, more advanced product to the customer than they had planned by conveying its added benefits. One example of upselling would be a cable television provider selling a premium plan with a more extensive selection of channels to a current subscriber of a basic package. Upselling may also entail approaching the customer at the point of sale for one product, offering a more advanced alternative. In both upselling and cross-selling, companies must effectively utilise their existing and potential customer base to increase sales by offering appropriate additional products to the right customers. However, cross-selling never involves encouraging customers to replace their current choices with more expensive ones. LEARN MORE ABOUT UPSELLING Examples of Cross-Selling Some examples of cross-selling include an electronics retailer offering a deal on a computer case, mouse, and screen cleaning wipes to a customer who purchases a new laptop, or an insurance provider offering renters’ insurance to its car policyholders. Benefits of cross-selling The main benefits of cross-selling include increased sales revenue, improve customer satisfaction and in B2B businesses, increased Customer Lifetime Value (CLV) through deeper integration in a customer’s business. When it works, cross-selling is great for both you and for your customers. The ideal situation is one where your existing customer is not aware of a product or service that would improve their customer experience. You find them on their customer journey at the ideal point, via their preferred contact method, and they react positively and go on to purchase the recommended product. Your sales increase, and their customer satisfaction increases because the product better fits their needs. Potential Drawbacks of Cross-Selling When it doesn’t work, cross-selling can be annoying for customers and ineffective at generating sales. This is almost always down to a lack of planning or appropriate data. If you recommend a product that makes no sense – for instance, promoting winter clothing to a customer who just bought a bathing suit – you may drive that customer away. If you approach a customer by phone who would typically place orders via email, you may not be able to make contact. And strangely enough, cross-selling is not always a great idea, even when it works. According to a Harvard Business Review study published in 2012, certain types of problem customers can actually make cross-selling a profit-losing strategy. According to Denish Shah and V. Kumar, some customer types can put stress on your customer service staff, whether by returning or cancelling a large number of goods and services or withholding spending in other areas to spend on your cross-selling promotions. It’s crucial to analyse customer data and metrics related to your cross-selling marketing campaigns to evaluate which efforts produce cross-sales without reducing overall profitability, and which customers should be left out of cross-selling or approached with different methods, such as upselling. In general, cross-selling too many options to too many customers can be a losing endeavour if you don’t have a well thought out strategy in place. Steps for Cross-Selling to Customers Identify related products and services suitable for cross-selling Identify suitable customers ready for a cross-selling Develop a cross-selling campaign and customer journey Before you can convince your customers to respond to cross-selling efforts, you need to identify which products and services go together: What do customers typically buy as add-ons to their purchases? What products are usually purchased together? Or even, what products have been successful in previous cross-selling campaigns? Solid data makes all the difference. Say your company is a fitness centre: Do some of the members often buy drinks at your front desk? They might be interested in a supplementary beverage program for a flat monthly fee. Or maybe your online electronics shop has wireless headphones that could be marketed to recent smartphone buyers – these customers may even have browsed for headphones, but left them in their shopping carts without purchasing. Identify related products and services suitable for cross-selling The next step in creating effective cross-sellingcampaigns is targeting the right audience. Identifying cross-sellcustomers starts with the data you gather from your customers at every stage of their customer journey. You can use information about in-person and digital communication your company has had with customers, their purchasing and browsing histories, whether they’ve repeatedly returned merchandise or cancelled services. All of this information can help you identify the best candidates for a cross-selling campaign. You can also target “look-a-likes” who demonstrate similar behaviours or characteristics to these customers. Identify suitable customers ready for a cross-selling Organising the information you receive through customer purchase histories and interactions is infinitely more effective when you use sales and marketing software with effective tools for CRM, and even better when coupled with AI-assisted sales analytics. Artificial Intelligence tools can automatically contact customers who display interest in certain products without the need for your staff to set up a new campaign each time. This frees up your marketing and sales staff for the more personal interactions that machines can’t perform. Develop a cross-selling campaign and customer journey Once you’ve identified customers who are ideal candidates for cross-selling, you’ve got to convert them. You then need to develop a strategy for presenting the potential cross-sales. If you have an online store, cross-selling through ads that appear during the checkout process can be effective, as can email campaigns targeting those who recently purchased a product. For higher cross-selling conversion rates, test out different approaches to making contact with customers, and adjust your approach based on analytics-based results. Cross-selling techniques Now that you’ve identified the customers you’d like to approach and the products you’d like to cross-sell, here’s some advice about techniques and some cross-selling tips to keep in mind: Offer the customer additional products and services that will genuinely provide them with added value: Think about cross-sales from your a customer’s point of view, not just in terms of how much revenue you think you can generate. If you’re utilising a CRM, fewer well-placed offers are far more valuable than a greater range of offers that don’t benefit your customer relationships. Find your customers at effective touch points on their customer journey: If they’ve used your website to place orders, email or targeted ads might be the best method for cross-selling. If they’re more likely to visit a store in person, a salesperson is more likely to cross-sell additional products and services to them in person or on the phone. Use your existing inbound marketing campaigns to promote supplementary products and services: If you have content targeting an audience that buys luxury cars, for instance, you can include ads for car accessories on your blog posts and product descriptions to encourage cross-sales. Make effective use of the data your customers provide: The new generation of consumers expects personalised service, even when it comes to upselling and cross-selling, and the tools for providing that through solid data are out there. Encourage cross-sales by creating spaces for interaction between customers: An online community for skateboard buyers may be as effective at encouraging sales of additional wheels and other parts as your direct marketing efforts. Make use of social selling techniques: For example, social media influencers are a valuable tool for reaching the widest possible audience in the current, predominantly digital sales environment. Offer incentives for influencers who already promote your products to mention supplementary products on their social media channels. When handled with care, Cross-selling can be an effective way to increase sales revenue for your company. While you should take advantage of potential cross-sales, you need tools for gathering and analysing data to use cross-selling in a way that benefits your business and your customers.Managing your marketing and sales data intelligently gives you a competitive edge on your cross-selling efforts, thanks to sales AI. Find out more about LIKE.TG’s cloud software and Einstein Analytics with a deep dive into AI. That’s a lot of info! Here’s what you should take away from this article: What is cross-selling? Cross-selling is the process of offering a customer products that are compatible with the ones they’re purchasing. What’s the difference between cross-selling and upselling? Upselling is the practice of selling a more expensive product to a customer, while cross-selling is offering supplementary products. What’s an example of cross-selling? An example of cross-selling would be offering a deal on a computer case to a customer who purchases a laptop. What are the benefits of cross-selling? Benefits of cross-selling include increased sales revenue, improved customer satisfaction and increased Customer Lifetime Value (CLV). Are there drawbacks to cross-selling? When it doesn’t work, cross-selling can be annoying and ineffective. This is usually down to offering incompatible or inappropriate products. What are some steps for cross-selling to customers? The most important part of any cross-selling strategy is identifying products or services that are compatible with one another. After that, it’s identifying which customers are most likely to benefit. What are some cross-selling techniques? When cross-selling, it’s important to always try to add value to the customer experience. You’ll also want to make sure that you’re offering the appropriate products at the appropriate touchpoints. Cross-selling isn’t limited to burgers and software. It can be valuable in any industry, with any product. Case in point: As a sales consultant, my clients sometimes need more than a basic training course or hour-long coaching session. Cross-selling books, additional training, or sales resources is almost always an option — and to make sure the door is open for those cross-sells, I continuously deliver valuable articles or insights to build trust. Then, when an opportunity presents itself, I go for the cross-sell. This happened recently, shortly after the launch of my third book on sales. I had a few clients at the time who showed some interest in additional training for their sales teams, but I didn’t know exactly what they were looking for. So, I asked open-ended questions like, “What industry-specific insights or examples would be helpful?” and “What’s the best learning modality for your team?” Eventually, I uncovered a good fit: a few clients with smaller sales teams that wanted resources sellers could use on their own time. I confidently proposed a cross-sell in our regular check-in conversations, offering bulk copies of my book at a discounted rate. Happily, they accepted, and many have noted since that the book has made their training more impactful. Frequently asked questions What is cross selling and why is it important? Cross-selling involves selling customers related items when they are making a purchase. It’s important not only because it boosts revenue, but also because it increases customer satisfaction, builds engagement, and helps to create solid and lasting customer relationships Does cross selling work? Yes. Cross-selling provides value for both businesses and customers, leading to increased revenue, increased customer satisfaction and better long-term relationships. This is assuming that cross-selling is done correctly – as the products or services being cross-sold must be appropriate and fit the needs of the customer. What is an example of cross selling? Cross-selling involves offering additional products that complement a purchase. For example, if a customer is buying a new bike, the retailer might offer them a discount on a tyre pump or a bike light. An electronics retailer might offer a case, an external hard drive and a mouse with the purchase of a new laptop.

Demand forecasting, a major aspect of business strategy, is pivotal in anticipating future demand for products and services. By leveraging demand forecasting techniques, businesses gain the ability to make informed decisions regarding production, inventory management, and marketing strategies. This blog looks into the intricacies of demand forecasting, exploring its significance, challenges, and various methodologies employed to predict market trends accurately. We’ll also provide practical examples and industry insights to illustrate how businesses can harness the power of demand forecasting to gain a competitive edge within the evolving marketplace. Demand forecasting overview In the ever-changing business landscape, accurately predicting future demand for products and services is paramount to success. This is where demand forecasting comes into play. Demand forecasting is the art and science of predicting the future demand for a particular product or service. By leveraging historical data, market trends, and various analytical techniques, businesses can gain valuable insights into consumer behaviour and market dynamics, enabling them to make better choices regarding production, inventory management, and marketing strategies. The significance of demand forecasting cannot be overstated. It empowers businesses to enhance their operations, minimise production costs, and ensure customer satisfaction by meeting demand effectively. Accurate demand forecasting also assists businesses in identifying potential market opportunities, plan for seasonal fluctuations, and respond swiftly to consumer preferences changes. Numerous demand forecasting methods and techniques are available, each with strengths and limitations. Some of the commonly used short-term demand forecasting methods include: – Quantitative methods: These methods rely on historical data and statistical analysis to predict future demand. Examples include time series analysis, regression analysis, and econometric models. – Qualitative methods: These methods incorporate subjective judgments and market research to estimate future demand. Techniques such as surveys, expert opinions, and focus groups fall under this category. – Causal methods: These methods establish a cause-and-effect relationship between demand and various factors such as economic indicators, consumer behaviour, and market trends. The choice of demand forecasting method depends on several factors, including the nature of the product or service, the availability of historical data, and the level of accuracy required. It is often beneficial to employ a combination of methods to enhance the reliability of forecasts. Demand forecasting is a continuous process that requires regular monitoring and updating. As new data becomes available, forecasts should be revised to reflect changing market conditions. By staying attuned to market dynamics and leveraging robust demand forecasting techniques, businesses can gain a competitive edge and navigate the uncertainties of the marketplace with greater confidence. Demand Forecasting explained Demand forecasting is an imperative component within the business strategy domain, enabling organisations to peer into the future and anticipate the ebb and flow of market demand. This intricate process of predicting consumer behaviour holds the key to optimising production, managing inventory precisely, and crafting marketing strategies that hit the bullseye. At the heart of demand forecasting lies the meticulous analysis of historical data, discerning patterns and trends illuminating the demand trajectory. Techniques such as moving averages and exponential smoothing transform this data into invaluable insights, guiding businesses toward the correct conclusions. Another avenue for demand forecasting involves venturing into the field of market research, where surveys, focus groups, and customer conversations unveil consumers’ hidden desires and preferences. This qualitative approach paints a vivid picture of market dynamics, allowing businesses to tailor their strategies accordingly. When historical data falls short or market shifts disrupt the landscape, businesses turn to the expertise of industry veterans – sales representatives, market analysts, and specialists with a wealth of knowledge. Their informed judgement acts as a compass, navigating the uncertainties and charting a course toward accurate demand forecasts. Econometric models, wielding the power of statistics and mathematical finesse, establish intricate connections between demand and economic factors like GDP, inflation, and consumer spending. These sophisticated tools, however, demand specialised knowledge and careful thought regarding complex economic relationships. Machine learning algorithms and artificial intelligence emerge as game-changers at the cutting edge of demand forecasting. Their ability to process vast data volumes and discern intricate patterns unlocks a new level of precision. These methods capture the nuances of non-linear relationships and integrate a diverse array of variables, yielding forecasts that resonate with market realities. The choice of demand forecasting method hinges on a delicate balance of factors: the nature of the product or service, the availability of historical data, the degree of market uncertainty, and the resources at hand. Often, a prudent approach involves blending multiple methods, and harnessing their collective strengths to enhance forecast accuracy. Regular updates to demand forecasts are paramount in a world of constant flux. Market conditions, economic trends, and consumer whims can shift lightning, demanding businesses to stay nimble and responsive. By continuously monitoring actual demand and incorporating fresh data, organisations can refine their forecasts, ensuring their decisions remain grounded in reality. Demand forecasting, an art as much as a science, lies at the heart of business success. It empowers organisations to hone their operations, minimise costs, and adapt seamlessly to the ever-changing market landscape. Embracing this practice enables businesses to navigate the complexities of consumer demand, securing their competitive edge and propelling them toward sustained growth. Benefits of demand forecasting Businesses that accurately forecast demand gain a competitive edge by optimising inventory levels, improving customer satisfaction, planning for future production and staffing needs, identifying and mitigating risks in the supply chain, and supporting data-driven decision-making and strategic planning. Optimising inventory levels: Accurate demand forecasting and inventory planning help businesses maintain optimal inventory levels, avoiding stockouts that can lead to lost sales and customer dissatisfaction, as well as excess inventory that ties up capital and incurs storage costs. By aligning inventory levels with anticipated demand, businesses can minimise costs and maximise profitability. Improving customer satisfaction: To attain customer satisfaction, you must first meet customer demand. When businesses accurately forecast demand, they can ensure adequate inventory to promptly fulfil customer orders. This reduces the likelihood of stockouts, backorders, and delayed deliveries, all of which can lead to customer frustration and churn. By consistently meeting customer demand, businesses build customer trust and loyalty. Planning for future production and staffing needs: Demand forecasting enables businesses to plan for future production and staffing needs. By anticipating demand trends, businesses can adjust their production schedules and workforce levels accordingly. This helps them avoid production bottlenecks, capacity constraints, and labour shortages, ensuring smooth operations and efficient resource allocation. Identifying and mitigating risks in the supply chain: Demand forecasting helps businesses identify potential risks in the supply chain, such as disruptions due to natural disasters, geopolitical events, or supplier issues. By anticipating these risks, businesses can develop contingency plans and mitigation strategies to minimise their impact on operations and customer service. Supporting data-driven decision-making and strategic planning: Accurate demand forecasting provides valuable insights that inform the organisation’s data-driven decision-making and strategic planning. It helps businesses allocate resources effectively, set realistic sales targets, optimise marketing campaigns, and make informed product development and expansion investments. By leveraging demand forecasting, businesses can make proactive decisions that align with market dynamics and customer needs, driving long-term growth and success. Challenges of demand forecasting Businesses face numerous challenges when forecasting demand, which can impact the accuracy and effectiveness of their predictions. One significant challenge lies in data accuracy and availability. Businesses rely on various data sources, such as historical sales data, market research, and economic indicators, to forecast demand. However, the accuracy and reliability of these data sources can vary, leading to potential errors in the forecasting process. Some businesses may also need more historical data, especially for new products or services, making it difficult to establish reliable demand patterns. Another challenge in demand forecasting is the influence of external factors beyond a business’s control. Economic conditions, changes in consumer preferences, technological advancements, and global events can significantly impact internal demand forecasting. For instance, a sudden economic downturn can lead to decreased demand for non-essential products, while a new technological innovation may disrupt existing markets and create unexpected demand. Businesses must continuously monitor and analyse these external factors to adjust their demand forecasts accordingly. Long lead times, particularly in industries with complex supply chains, pose another challenge in demand forecasting. Certain products may require extended production or shipping times, making it difficult to predict demand over longer horizons accurately. This challenge is compounded by the risk of stockouts or overstocking, which can negatively affect customer satisfaction and profitability. Product seasonality also presents forecasting difficulties. Demand for specific products or services may fluctuate significantly based on seasonal factors, such as weather, holidays, or fashion trends. Accurately predicting these seasonal variations is vital to avoid stockouts during peak demand periods and excess inventory during off-seasons. Lastly, rapidly changing consumer preferences can disrupt even the most carefully crafted demand forecasts. Factors such as evolving tastes, social media, consumer trends, and consumer behaviour shifts can quickly alter market dynamics. Businesses must stay agile and responsive to these changes by continuously gathering and analysing consumer insights to adapt their demand forecasts. Addressing these challenges requires businesses to adopt robust demand forecasting methodologies, leverage advanced analytics tools, and maintain a data-driven approach. By overcoming these obstacles, businesses can improve the accuracy of their demand forecasts, increase their operations, and gain a competitive advantage in the market. Why Is Demand Forecasting Important for Businesses? Demand forecasting is a crucial business process that enables companies to anticipate future demand for their products or services. By accurately predicting demand, businesses can maximise their operations and make informed decisions that drive growth and profitability. Demand forecasting is a necessity when it comes to several key areas: Supply Chain Management: Accurate demand forecasting allows businesses to maintain optimal inventory levels, reducing the risk of stockouts and overstocking. This optimisation of inventory levels directly impacts cash flow, customer satisfaction, and overall supply chain efficiency. Production Planning: With precise demand forecasts, businesses can effectively plan their production schedules to meet anticipated demand. This ensures that they have the right resources, materials, and workforce in place to fulfil customer orders efficiently. Proper planning minimises production disruptions, reduces costs, and enhances operational efficiency. Marketing and Sales Strategies: Demand forecasting provides valuable insights into market trends and customer preferences. This information empowers businesses to develop targeted marketing and sales strategies that resonate with their customers. By aligning marketing efforts with forecasted demand, businesses can make the most of their marketing budgets and maximise their return on investment. Financial Planning and Budgeting: Accurate demand forecasting enables businesses to make informed financial decisions. By anticipating future demand and revenue, businesses can create realistic budgets, allocate resources effectively, and plan for future investments. This financial planning ensures the long-term sustainability and growth of the business. Risk Management: Demand forecasting helps businesses identify potential risks and challenges in the market. By anticipating fluctuations in demand, businesses can develop contingency plans to mitigate these risks and minimise their impact on operations. This proactive approach enhances business resilience and allows companies to respond swiftly to changing market conditions. Overall, demand forecasting is an essential tool that empowers businesses to make data-driven decisions, increase their operations, and gain a competitive edge in the market. By accurately predicting future demand, businesses can achieve improved customer satisfaction, increased profitability, and sustainable growth. What Factors Impact Demand Forecasting? This section discusses the various factors that can impact demand forecasting. These factors include economic conditions, seasonality, weather, competitors’ actions, and changes in consumer preferences. Economic conditions play a significant role in demand forecasting. A strong economy typically increases demand for goods and services, while a weak economy can lead to decreased demand. Factors such as GDP growth, inflation, interest rates, and consumer confidence affect economic conditions and demand forecasting. Seasonality is another essential factor to consider in demand forecasting. Many products and services experience predictable fluctuations in demand throughout the year. For example, demand for ice cream is typically higher in the summer months, while demand for winter coats is higher in the winter months. Businesses need to take seasonality into account when forecasting demand to ensure that they have adequate inventory to meet customer needs. Weather can also impact demand forecasting. For example, a cold and snowy winter can increase demand for heating oil and snow removal services, while a hot and dry summer can increase demand for air conditioners and swimming pools. Businesses located in areas with volatile weather patterns need to adjust their demand forecasts quickly in response to changing weather conditions. Competitors’ actions can also affect demand forecasting. For example, if a competitor launches a new product or service similar to yours, it can decrease demand for your product or service. Businesses need to keep a close eye on their competitors’ activities and be prepared to adjust their demand forecasts accordingly. Finally, changes in consumer preferences can also impact demand forecasting. For example, becoming more health-conscious can lead to decreased passive demand forecasting for sugary snacks and increased demand for healthy foods. Businesses need to be aware of changing consumer preferences and be able to adjust their demand forecasts accordingly. By considering all of these factors, businesses can improve the accuracy of their demand forecasts and make better-informed decisions about production, inventory, and marketing. 7 Demand Forecasting Types When it comes to demand forecasting, there exists a diverse array of methodologies, each tailored to specific business scenarios and product characteristics. Let’s take a deeper look into seven prominent demand forecasting types, exploring their distinctive features, strengths, and limitations: 1. Historical Data Analysis: This method leverages historical sales data to project future demand. It’s straightforward to implement, making it a popular choice for businesses with ample historical information. However, its accuracy is limited by the assumption that past trends will continue into the future, which may only sometimes hold true. 2. Expert Opinion: This method involves soliciting insights from industry experts, sales personnel, or customers to estimate future demand for a product. It’s beneficial when historical data is scarce, or the product is new to the market. However, the accuracy of this method hinges on the expertise and objectivity of the individuals providing the estimates. 3. Market Research: Conducting market research surveys, focus groups, or analysing consumer behaviour can provide valuable insights into future demand. This method is well-suited for new product launches or understanding evolving customer preferences. However, it can be time-consuming and may not accurately capture purchasing behaviour accurately. 4. Econometric Models: These models incorporate economic indicators, such as GDP growth, inflation, and consumer spending, to forecast demand. They are advantageous when there’s a strong correlation between economic factors and product demand. However, econometric models require robust data and expertise in economic analysis, which may only be readily available to some businesses. 5. Time Series Analysis: This method analyses historical demand data to identify patterns and trends. It’s effective for products with relatively stable demand patterns. However, it needs help to capture sudden shifts in demand caused by unforeseen events or market disruptions. 6. Causal Models: Establish cause-and-effect relationships between various factors and demand. They are helpful when there’s a clear understanding of demand drivers, such as advertising, promotions, or pricing. However, building causal models can be complex and requires substantial data and expertise. 7. Machine Learning Algorithms: These algorithms leverage historical data and advanced statistical techniques to predict demand. They excel in handling large datasets and identifying intricate patterns. However, machine learning models require specialised expertise and can be challenging to interpret, making it difficult to understand the underlying reasons behind the forecasts. Each of these demand forecasting methods has its merits and drawbacks. The choice of method depends on factors such as data availability, product characteristics, market dynamics, and the level of accuracy required. Businesses should carefully evaluate these factors and select the most appropriate method to ensure reliable and actionable demand forecasts. How to Forecast Demand To forecast demand, businesses can leverage historical sales data and market research to gain insights into past demand patterns and market trends. This data can be analysed using statistical techniques and econometric models to identify factors influencing demand, such as seasonality, economic conditions, and consumer preferences. Businesses can also employ machine learning and artificial intelligence algorithms to analyse large volumes of data and identify complex relationships between variables that may impact demand. Qualitative factors such as consumer behaviour, economic conditions, and competitive activity should be considered when forecasting demand. Consumer surveys, focus groups, and market research can provide valuable insights into consumer preferences and buying patterns. Economic indicators such as GDP growth, inflation, and unemployment rates can also impact demand, while understanding the strategies and actions of competitors can help businesses anticipate changes in market share. Regularly updating and refining forecasts is crucial due to the evolving nature of markets. New information and changing market conditions can quickly render forecasts obsolete. Businesses should establish a process for continuously monitoring demand-related data and incorporate new information into their forecasts as soon as it becomes available. This agility allows businesses to adapt their strategies and make informed decisions in response to evolving market conditions. Businesses can develop robust demand forecasts that support effective decision-making by combining historical data analysis, market research, qualitative insights, and machine learning techniques. Accurate demand forecasting enables businesses to advance production schedules, manage inventory levels, plan marketing campaigns, and allocate resources efficiently, ultimately driving growth and profitability. Demand Forecasting Methods Demand forecasting is critical to business planning, enabling companies to make informed decisions about production, inventory, marketing, and financial strategies. Businesses can utilise various demand forecasting methods to predict future demand for their products or services. Here are some commonly used demand forecasting methods: Time Series Analysis: This method analyses historical demand data to identify patterns and trends. It assumes that future demand will follow similar patterns as observed. Time series analysis includes techniques such as moving averages, exponential smoothing, and seasonal decomposition of time series. Causal Analysis: This method identifies and analyses the causal factors influencing demand. It involves studying the relationship between demand and factors such as economic conditions, market trends, consumer behaviour, and competitive activity. Causal analysis helps businesses understand the underlying drivers of demand and make more accurate forecasts. Judgmental Forecasting: This method involves using the knowledge and expertise of experienced professionals to make demand forecasts. It is often used when historical data is limited or when qualitative factors play a significant role in demand. Judgmental qualitative demand forecasting techniques include expert opinion, the Delphi method, and market research. Machine Learning: Machine learning algorithms can be used to analyse large volumes of data and identify complex patterns that may not be evident through traditional quantitative demand forecasting and methods. Machine learning techniques such as regression analysis, decision trees, and neural networks can be applied to demand forecasting. Econometric Models: These models use statistical and economic theories to forecast demand. They incorporate economic variables such as income, prices, interest rates, and consumer sentiment to predict future demand. Econometric models are often used for short-term demand and long-term demand forecasting. The choice of demand forecasting method depends on several factors, including the availability of historical data, the nature of the product or service, the forecast horizon, and the level of accuracy required. By selecting the appropriate demand forecasting method and regularly updating forecasts based on new data, businesses can improve their decision-making and achieve better operational efficiency and profitability. Demand Forecasting Examples Demand forecasting is a valuable tool for businesses of all sizes and industries. Here are a few examples of how demand forecasting can be used in practice: Retail: A clothing retailer might use demand forecasting to predict how many units of a new product to produce for the upcoming season. By considering factors such as historical sales data, current fashion trends, and economic conditions, the retailer can decide how much inventory to carry to meet customer demand. Manufacturing: A industrial equipment manufacturer might use demand forecasting to predict how many units of a particular product to produce each month. By considering factors such as customer orders, production capacity, and lead times, the manufacturer can ensure that it has enough inventory to meet customer demand without overproducing. Transportation: A logistics company might use demand and forecasting models to predict how much freight it will need to transport each week. By considering factors such as shipping volumes, economic conditions, and weather patterns, the logistics company can ensure that it has enough resources to meet customer demand. Healthcare: A hospital might use demand forecasting to predict how many patients it will need to accommodate daily. By considering factors such as historical patient data, current patient trends, and the availability of medical staff, the hospital can ensure that it has enough resources to meet patient demand. Technology: A software company might use demand forecasting to predict how many licences of a new software product to sell each month. By considering factors such as market research, competitor analysis, and pricing strategy, the software company can ensure that it has enough licenses to meet customer demand without overproducing. Demand Forecasting Trends Demand forecasting has significantly transformed in recent years, driven by technological advancements and changing business dynamics. The emergence of real-time data and machine learning has revolutionised the field, enabling businesses to make more accurate and timely predictions. Real-time data provides businesses with up-to-the-minute information on market conditions, consumer behaviour, and supply chain dynamics, allowing them to respond quickly to changes in demand. Machine learning algorithms analyse vast amounts of data to identify patterns and trends, enabling businesses to make more accurate forecasts and optimise their operations. Collaborative planning is another critical trend in demand forecasting. This approach involves bringing together stakeholders across the organisation, including sales, marketing, production, and finance, to develop demand forecasts collectively. Collaborative demand planning also fosters a shared understanding of market dynamics and ensures forecasts align with the business strategy. By combining the knowledge and expertise of various teams, businesses can improve the accuracy and reliability of their demand forecasts. The rise of artificial intelligence (AI) and advanced analytics further enhances demand forecasting capabilities. AI-powered tools can analyse vast amounts of data, identify complex patterns, and make predictions with a high degree of accuracy. Advanced analytics techniques, such as predictive modelling and simulation, enable businesses to test different scenarios and make informed decisions about their production and inventory levels. By leveraging AI and advanced analytics, businesses can gain a competitive edge by optimising their supply chains and meeting customer demand more effectively. In summary, the evolution of demand forecasting is characterised by integrating real-time data, machine learning, collaborative planning, and AI-powered analytics. These trends are revolutionising how businesses predict demand, enabling them to make more accurate and data-driven decisions. By embracing these trends, businesses can gain a competitive advantage, progress their operations, and meet the ever-changing needs of their customers. How to Choose Demand Forecasting Software Choosing the right demand forecasting software is essential for businesses developing their operations and making informed decisions. With a wide range of demand forecasting software options available, it’s essential to consider several key factors to select the best tool for your organisation. 1. Assess Your Business Needs: Before selecting software, thoroughly assess your business’s unique needs and requirements. Consider the size and complexity of your organisation, the industry you operate in, and the specific forecasting challenges you face. Determine the level of accuracy and granularity required for your forecasts and the types of data you need to analyse. 2. Evaluate Software Features and Functionality: Evaluate the features and functionality offered by different demand forecasting software options. Look for software that provides the necessary capabilities, such as historical data analysis, trend identification, seasonal adjustment, and scenario modelling. Consider the user interface, ease of use, and the level of customisation available to meet your specific requirements. 3. Scalability and Integration: Choose software that can scale to meet your growing business needs. Consider whether the software can handle increasing data volumes and complexity as your business expands. Assess the software’s ability to integrate with your existing systems, including enterprise resource planning (ERP) and customer relationship management (CRM) systems, to ensure seamless data flow and analysis. 4. Cost and Return on Investment: Compare the costs associated with different software options, including licensing fees, implementation costs, and ongoing maintenance and support. Evaluate the potential return on investment (ROI) by considering the benefits the software can bring in terms of improved forecast accuracy, reduced inventory costs, optimised production planning, and enhanced customer service. 5. Customer Support and Training: Consider the level of customer support and training provided by the software vendors. Ensure that the vendor offers responsive and reliable support to address any issues or queries you may have. Assess the availability of training resources, such as user manuals, tutorials, and workshops, to help your team effectively use the software. 6. Data Security and Compliance: Evaluate the software’s security measures to protect your sensitive business data. Ensure that the software complies with relevant industry regulations and standards. Consider the data encryption methods, access controls, and disaster recovery plans offered by the software vendor. By carefully considering these factors, you can select the demand forecasting software that best aligns with your business goals and requirements, enabling you to make data-driven decisions and gain a competitive edge in your industry. Make Demand Forecasting Easier with LIKE.TG Demand forecasting is an essential business process, but getting accurate results can take time and effort. LIKE.TG makes demand forecasting easier with AI-powered tools that help you get accurate results in minutes, collaborate with your team on forecasts, and adjust your forecasts as new data comes in. You’ll also get real-time insights into your demand forecast so you can make informed decisions. LIKE.TG’s demand forecasting tools use a variety of data sources to create accurate forecasts, including historical sales data, current market conditions, and even future sales trends. This data is then analysed using machine learning algorithms to identify patterns and relationships that can be used to predict future demand. LIKE.TG’s demand forecasting tools are easy to use and can be customised to meet the specific needs of your business. You can create forecasts for individual products or services or entire product lines. You can also create forecasts for different periods, such as days, weeks, or months. Once you’ve created a forecast, you can share it with your team and collaborate on it. You can also track the accuracy of your forecasts over time and make adjustments as needed. LIKE.TG’s demand forecasting tools are valuable for businesses of all sizes. They can help you improve your planning and decision-making, ultimately increasing your profitability. Here are some of the benefits of using LIKE.TG’s demand forecasting tools: Get accurate results in minutes: LIKE.TG’s demand forecasting tools use AI-powered algorithms to analyse data and create accurate forecasts quickly and easily. Collaborate with your team: You can share your forecasts with your team and collaborate on them. This makes getting everyone on the same page and making better choices easy. Adjust your forecasts as new data comes in: LIKE.TG’s demand forecasting tools allow you to adjust your forecasts as new data becomes available. This ensures that your forecasts are always up-to-date and accurate. Get real-time insights into your demand forecast: LIKE.TG’s demand forecasting tools provide real-time insights into your demand forecast. This information can help you make better choices regarding your business.

Since the onset of the pandemic, businesses all over the world have pivoted to digital with unprecedented speed. While this transition was hastened out of necessity, the convenience and flexibility that came with it has created a new set of customer expectations. As we head into 2022, successful businesses now know that the only way to meet these expectations is by adopting a customer-centric mindset. The best way to place customers at the centre of everything is through digital transformation. The latest research confirms this. Eighty-eight percent of customers expect companies to accelerate digital initiatives due to the pandemic. Digital experiences are of particular interest to younger generations, with 76% prioritising convenience over brand. So, what exactly is digital transformation and how can businesses start the process? Defining digital transformation To put it simply, digital transformation is a reimagining of business for the digital age. It involves adopting digital technologies to create or modify processes across all areas of your business, whether internal or customer-facing. Digital transformation crosses silos and departments. It isn’t limited by the size or scope of your organisation. From larger, established brands to small businesses starting out, digital transformation can be the most effective way to future-proof your organisation. While it’s a fluid, evolving process, you can start transforming right now. To further understand digital transformation, it’s helpful to differentiate it from similar terms. Digitisation is the conversion of data from analog to digital. Think of a physical handwritten spreadsheet becoming an Excel file. Digitalisation, however, is harnessing digital information in ways that simplify and streamline established ways of working. It’s not changing the way you do business as a whole, but it increases your operational efficiency. For example, point-of-sale software in the retail space, which greatly speeds up the established transaction process. Digital transformation not only overhauls the way business is conducted, but in some cases it creates brand new classes of business. For example, the way Netflix went from a DVD delivery service to a revolutionary digital content channel. This sparked a legion of imitators and disrupted both the video rental and film and television industries. The many benefits of digital transformation Digital transformation can positively impact your business on almost every level. On the consumer side of the equation, it gets you closer to the individual customer and their unique needs, which leads to increased satisfaction and repeat business. By the same token, it often allows customers to take a more active and autonomous role in the buying experience (such as through self-service options). On the employee side, digital transformation enables efficient processes; allows access to powerful systems, data and analytics; and fosters new levels of collaboration and connection. All of which are highly empowering to the working individual. Digital transformation provides a foundation for innovation, and allows for further development as your business evolves. For example, setting up an online store, then as time goes on, adding an augmented reality showroom. As digital transformation is a fluid, ongoing process that can expand and morph alongside market demands, your business benefits from future-proofing. These are just a number of the many benefits that digital transformation will bring to your organisation. Is it time to start your digital transformation journey? A number of factors can determine whether you’re ready to implement a digital transformation strategy. You may have sensed a recent drop-off in referrals, especially since the pandemic. Repeat business numbers may have also dipped. Perhaps your previous tried-and-true methods of promoting your business are no longer generating new leads. Internally, you might be facing an increase in complaints from employees and teams over communication and collaboration issues. Perhaps these are problems that can’t be easily resolved due to physical separation or clashing hybrid-work schedules. Perhaps most glaringly – your systems, whether technological or otherwise, may feel dated. Your employees may be requesting features or processes that you can’t provide … yet. If one or more of these factors ring true for you, it’s time to start a conversation about digital transformation. I’m ready for the conversation. What now? The best way to start your digital transformation journey is to get your team together and brainstorm. This brainstorm should involve a forensic audit of your processes, operations, employee and customer experiences, and existing technologies. Look for weak spots such as gaps, inefficiencies, disconnections, and difficulties. Once you have considered every angle, you can start creating your strategy. How? The answer’s coming up in the next article in this digital transformation series. For a deeper dive into how to get started on digital transformation, read our digital transformation guide.

So what is Dreamforce? The short answer is that it’s the largest software conference in the world. But that doesn’t come close to doing it justice — Dreamforce isn’t like any other conference. For our Trailblazers — our community of customers, partners, and employees — it’s a much-anticipated highlight of the year. For those who are new to LIKE.TG and what we do, it’s an unmissable opportunity to connect, learn, have fun, and give back. And this year our focus on artificial intelligence (AI), data and CRM will be paramount. For businesses grappling with the incredible challenges and opportunities presented by AI, Dreamforce is a goldmine of expertise and insight along with new AI-powered product launches you won’t want to miss. And if you can’t attend the in-person event in San Francisco? Don’t worry. Tune in to ​​Dreamforce: The Asia Pacific Edition to get access to a special Asia Pacific Edition of the Dreamforce Main Keynote. When you register, you’ll also gain access to the entire Dreamforce schedule, broadcast live on LIKE.TG+. Dreamforce: not just another tech conference Anyone who has attended Dreamforce will tell you it’s a truly unique experience. It’s a vivid combination of innovation and inspiration, featuring: unmissable advice from industry rockstars on how to unite your teams around your customer unforgettable shows from, well, actual rockstars (hello, Foo Fighters!) deep dives into the AI-powered technologies that are transforming business and empowering staff exciting new product announcements fireside chats with a diverse range of leaders and thinkers plenty of opportunities to give back, along with practical advice about how to use your business as a platform for change Your Dreamforce FAQs answered When and where is Dreamforce? Dreamforce 2023 takes place September 12–14 in San Francisco, and on LIKE.TG+ — our free streaming service available to audiences all over the world. You can watch a special version of the main keynote by tuning in to Dreamforce: The Asia Pacific Edition. And that’s not all — you can catch the highlights of Dreamforce wherever you are with hand-picked on-demand sessions on LIKE.TG+. Who goes to Dreamforce? Every attendee will find something to take away from Dreamforce — no other tech event provides so many hands-on learning opportunities to help build the future of business, together. Our community includes professionals from every level and every industry. You’ll connect with the most innovative brands in the world, visionaries and changemakers, executive leaders from companies of five to the Fortune 500, LIKE.TG employees and experts, and Trailblazers who are MVPs at what they do, and those who are just starting their journey. We host many other events throughout the year, including TrailblazerDX, which slants toward LIKE.TG administrators, developers, and architects, and Connections, which attracts marketing, customer service, and commerce professionals. Dreamforce sounds big. How is LIKE.TG addressing its core value of sustainability? At Dreamforce we’re committed to creating a sustainable, low-carbon future and accelerating the world’s journey to net zero. Each year, we make every effort to have a more sustainable Dreamforce. This year, we are proud to limit non-sustainable swag; provide carbon-friendly menus, eco-friendly packaging and refillable water stations; and offer onsite attendees the opportunity to offset their travel-related emissions. We will also feature luminary speakers and hands-on demo stations that will educate and enable you to take climate action. What can I expect from Dreamforce? So much! Here’s a handy breakdown of what your Dreamforce experience might look like. Learning at Dreamforce At its core, Dreamforce is a learning experience. Whether you’re front row or watching later on LIKE.TG+, you’ll learn about the latest innovations from our partners, our visionary speakers and from each other. And you’ll be able to apply those lessons to your own experiences, take those learnings home and transform your business. Being inspired at Dreamforce Looking for inspiration? You can count on Dreamforce to deliver. Our guest lineups are legendary and in the past have included industry pioneers and thought leaders like Dr Jane Goodall talking about a sustainable global future, Thankyou’s Justine And Daniel Flynn on pairing profit and purpose, Tristan Harris from the Center for Humane Technology advising on ethics in artificial intelligence, and Yaroslav Ivakhno from the Ukrainian Red Cross Society sharing strategies for doing good fast in a crisis. And the inspiration doesn’t just come from big name headliners. Often the most memorable moments are from other attendees — Trailblazers upping their skills and seeing their impact play out. Giving back at Dreamforce LIKE.TG is built on Trust, Customer Success, Innovation, Sustainability and Equality. We believe amazing things happen when we work together to help others. Each year at Dreamforce we partner with nonprofits to bring attendees opportunities and activities that make an impact in our community and help the people who need it most. And if you’re looking for ways your business can be a platform for change, Dreamforce is a goldmine not just of inspiration but of actionable advice and insights. Having stacks of fun at Dreamforce When it comes to fun, making new friends and building your community, Dreamforce sets a high standard. When Trailblazers get together it’s like an epic family reunion. Expect an inclusive, collaborative, and welcoming environment where dancing is encouraged — so feel free to bring your whole, authentic self. Which events should I look out for? With so much on offer, it’s hard to go wrong — but we’ve got a few tips to get you started. Want to hear from local industry legends and thought leaders? There are 27 LIKE.TG customer speakers from across the Asia Pacific region, across 29 sessions. If you’re looking for speakers from Australia, get ready for unmissable insights from customers including the Department of Health and Aged Care, Norths Collective, NAB, Endeavour Energy, Fisher & Paykel, Origin Energy, PaySauce, Rapid Response, ResMed, Sutton Tools, and P&N Bank. Check out our eight amazing speakers from the ASEAN region with customers including Jollibee, MTI Singapore, Cebu Pacific Air, Cloud Jedi, Petronas, and Tanaga Nasional Berhad. And from India, look for speakers from customers like Air India, Sony Pictures Network India, Titan Company Limited and Asian Paints. Need a break? We hear you! There’s a lot to take in. Kick back in the APAC Lounge or do a spot of networking. When you’re ready to dive back into the action, we’ve got exclusive executive workshops and networking events on offer. Where do I sign up for LIKE.TG+? Register for free right here so you don’t miss out on Dreamforce: The Asia Pacific Edition, exclusive interviews, new product announcements and deep dives into AI, data-driven decision making, and CRM.