As technology advances, the state of customer service changes along with it. Customers expect companies to adapt to their needs, and technologies like generative AI are playing a major role in meeting those evolving expectations. Here are five customer service trends to keep on your radar as you prepare for the future of customer service, based on new data from the “State of Service” report.1. Service organisations are now revenue generators — not cost centresCompanies are looking for new ways to drive growth and protect their margins, and many see service as a prime opportunity. In fact, 85% of decision makers say service is expected to contribute a larger share of revenue this year.So how can you take action? Our research shows that leading organisations are actively tracking key performance indicators (KPIs) that are linked to tangible business outcomes. In fact, the share of service organisations tracking revenue generation has nearly doubled since 2018, from 51% to an astonishing 91%. The share tracking customer retention rose by 29 percentage points over the same period. If those customer service analytics aren’t already on your radar, it’s time to make some changes — otherwise you risk getting left behind. (back to top)2. Self-service is a clear competitive advantageSelf-service helps customers resolve simple issues, freeing agents to spend more time on high-complexity, high-value interactions.Our latest research shows that high-performing organisations are much more likely than underperformers to provide self-service tools like knowledge-powered help centres, customer self-service portals, and chatbots powered by AI. When customers can interact with a chatbot to answer a question or use a guided journey to start a return, live agents have the time they need to manage more complicated requests. That’s critically important for the 69% of agents who report difficulty balancing speed and quality. (back to top)3. Connected data enables a better customer experienceMany organisations keep data in different silos or applications, so it’s difficult to get a complete view of the customer across all channels.Bringing customer data together is all about creating an end-to-end view of the entire customer journey. This way, you’ll have a continuous feedback loop between sales, service, and marketing, keeping everyone on the same page. Maybe that’s why 82% of high-performing organisations use the same customer relationship management (CRM) platform across all departments — up from 62% just two years ago.The stakes are high: 92% of analytics and IT leaders say the need for trustworthy data is greater than ever. That’s why privacy, security, and trust have already become a major competitive advantage in the evolving AI landscape.As companies try to stay one step ahead of these and other customer service trends, leading organisations are adopting programs that prevent large-language models (LLMs) from retaining sensitive customer data. More organisations are training their own domain-specific models to access a secure AI cloud while storing data on their own infrastructure. These efforts are essential to preserving customers’ loyalty and trust in the years to come.(back to top)4. Conversational AI is taking proactive, personalised service to the next levelWhen it comes to meeting customers’ sky-high expectations, proactive service is more important than ever. “It’s essential to proactively resolve issues before they have any significant business impact,” says Jules O’Donnell, LIKE.TG administration manager at Quickbase. “This means keeping up with technology solutions to scale service and meet customers where they are.”Our latest research backs that up: 95% of decision makers at organisations with AI report cost and time savings, and 92% say generative AI helps them deliver better customer service. It should come as no surprise, then, that 83% of decision makers plan to increase their AI investment over the next year, while only 6% say they have no plans for the technology whatsoever.The introduction of conversational AI assistants is one of the innovations that’s making these benefits possible. From the contact centre to the field, AI assistants surface the right information at the right time to enable proactive service, improve Net Promoter Scores, and increase loyalty.Here’s what that looks like in practice: Responding to customers with personalised, relevant answers grounded in trusted company knowledge across any preferred channel — including email, SMS, live chat, and social mediaResolving customer issues faster using generative answers seamlessly integrated into agents’ and technicians’ flow of workAutonomously completing tasks like auto-summarising intricate support cases and field work orders (back to top)5. AI is improving productivity and safety in the fieldOur research shows that mobile workers say innovative field service technologies make them feel safer and more effective at their jobs, empowering them to be better brand ambassadors. These technologies include intelligent scheduling, route optimisation, AI-generated reports, and augmented reality (which can create detailed 3D rendering of large areas in seconds).One of the emerging benefits of these and other technologies is the ability to generate insights and predict job duration. For example, workers can use AI to easily view asset condition as well as maintenance and repair history, then schedule proactive service to minimise downtime.Customers are benefiting, too. They can book and reschedule their own appointments using intelligent appointment assistance. And many customers have the ability to check when a technician is on the way, reducing no-shows and call volume for a better customer experience all around. (back to top)Staying one step ahead of customer service trendsA great strategy starts with the right questions. How can you pursue innovation while maintaining the integrity of your data? How do you build customers’ loyalty and trust? And what’s the secret to delivering faster, more effective customer service without breaking the bank?The right technologies can help you prepare for the future while keeping up with the latest customer service trends. That’s why your organisation must combine people, technology, and processes to deliver faster, more effective service at scale — with AI assisting you every step of the way.(back to top)

If you’re an email marketer, building a strong subscriber list is one of your top goals. But it’s also crucial to keep those email subscribers over the long term. Sending them great content is a given. But there’s an underrated factor that also determines success: email deliverability. Email platforms Gmail and Yahoo recently announced new measures to help prevent spam from reaching readers’ inboxes, meaning new domain validation requirements for bulk email senders. So if you want to avoid the spam filter, it’s time to take a step back and gain a better understanding of the three phases of email deliverability before you build your next campaign. Email deliverability is a message lifecycle that begins with a customer’s setup (the company sending the email) and extends out to the placement of a targeted message to their email subscribers. Subscriber engagement influences follow-on messaging. What are the phases of email deliverability? Email deliverability has three phases: setup, connect and curate. Your setup is the collection of products that comprise your account – these become personalised experiences and infrastructure for your campaigns. You utilise this infrastructure to then connect to your customers. In your customer outreach, permission is required and relevance is expected. Curate is when you analyse campaign results and take action based on email subscriber sentiment. Delivering an initial 15% off coupon is easy, but boosting engagement in month 15 and beyond is a challenge. Let’s take a deeper look at the elements of these phases and how they translate into long-term email subscribers. 1. Setup phase When we talk about “setup,” we’re referring to specific product offerings that help your mail reach the inbox of your email subscribers. These include: Sender Authentication Package (SAP): This ensures a customer has compliant, authenticated email messages that reflect their brand. Be sure to set up your SAP prior to sending to improve your odds of reaching the inbox. Private Domain: This authenticates a customer’s sending domain for use with email, but it does not come with a dedicated IP or any type of ‘branding’ within the account like a full SAP setup would. Dedicated IP Addresses:All customers who sendmore than 100,000 emails a month either in a single account or across their enterprise need to be utilising a dedicated IP address. This allows them to control the reputation of their sending IP(s). Multiple Dedicated IPs may be needed for high volume senders. Dedicated MTAs (Mail Transfer Agents): Dedicated infrastructure for high volume senders over 500 million annually. Ask your account executive if this solution is right for your company. SSL (Secure Sockets Layer): SSL Certificates are how a URL goes from being HTTP to HTTPS in the browser. SSL allows sensitive information to be uniquely encrypted and transmitted securely. Once your SAP domain is applied to your account, you can secure the domain via the application. You need to have the proper products (and the correct number of them) in place before you start sending email, so you can build out the best sender reputation possible. Your reputation as a properly authenticated sender of compliant mail helps you reach the inbox (and not the spam folder) of your email subscriber on a consistent basis. This helps improve email deliverability, ensuring you get the most for your money. Over time your company’s needs may change, due to organic email subscriber growth (you may need more sending IPs) or restructuring/mergers (changes in domains/SAP setups). It’s important to work with your account executive on a regular basis to review your exact situation. Get articles about marketing selected just for you, in your inbox Sign up now 2. Connect phase If you are in the “connect” phase of email deliverability, you likely already understand that email isn’t as simple as “batch and blast.” Email subscribers and receivers have become more sophisticated over time and expect relevant content sent at a reasonable frequency. Inbound filtering algorithms on the ISP (Internet Service Provider) end are tracking spikes in volume, engagement rates, spam complaints and bounce metrics in real time to determine whether mail should be placed in the inbox, the bulk folder or outright blocked. Here are the components of responsible sending: IP warming: Warming is an exercise all customers using dedicated IPs will need to go through. It’s how a legitimate sender introduces themselves to the ISPs by slowly building volume over time so it doesn’t overwhelm the ISPs like a spammer would and to allow metrics to be gathered for click/open/complaint rates. Permission based marketing: All addresses in a customer’s list must give explicit permission for the customer to send them email via the application. Relevant content/agreed upon frequency: Are you sending your emails more often than you promised? Less often? Is the content different from what you promised? Remember that communications are to be anticipated, personal, and relevant. If your users don’t anticipate your email or your content, reevaluate why you are sending them email in the first place. Easy to opt out: Ensure the unsubscribe process is easy and hassle-free for the end user. It’s better for a user to unsubscribe than mark your email as spam. List hygiene: Do you have addresses that you haven’t mailed to in six months? How about customers who haven’t opened an email or clicked a link in that same time period? These customers cost money to mail, reduce your results, and are more likely to register spam complaints against messages — harming your email deliverability. 3. Curate phase This phase is about monitoring campaign performance to better understand your email subscribers and their preferences. No single metric can tell you how well you’re doing – it takes a comprehensive view over time to really see trends and know where to adjust. Monitor campaign performance for trends: Utilise tracking andData Viewsto keep a close eye on trends around engagement (click rates) and complaints/unsubscribes. Listen to what your subscribers are telling you and adjust accordingly. Take action for high bounce rates: Proactively remove your bounced addresses before your next send. Even though the application automatically holds undeliverable emails after the third bounce, a bounce rate greater than 10% can dramatically harm your deliverability and ISP reputation. A bounce rate this high could suggest problems with the opt-in process for your email subscriber list. Make adjustments: List fatigue is real, as email subscribers tend to disengage over time as interests change or they find new brands. Sending the same 15% off coupon week after week may not be enough to keep an email subscriber engaged. Know that it’s okay to let unengaged subscribers go from your list. Saying goodbye can be hard. After all, you fought to earn that customer’s address. Here we are eight months down the road from their last click, and it seems like maybe they just don’t feel the same way they used to about you. Don’t take it personally – it’s okay to remove email subscribers who are no longer showing interest in your brand from your list. It doesn’t make you a bad marketer. It makes you a savvy one. Understanding where the ROI in your database comes from and nurturing that subscriber base optimises your ability to reach those highly engaged customers in their inbox. This vastly improves the odds of driving further interactions. Continuing to mail an unengaged subscriber base results in lower click/open metrics, more spam complaints and increased likelihood of receivers deciding your mail should be in the junk folder. Best practices to keep email subscribers engaged Our main point is that deliverability isn’t a ‘set forget’ situation. It takes ongoing maintenance of content, lists and products to achieve a consistent high level of success. You may find yourself re-entering the different phases of the email deliverability lifecycle periodically as you are constantly connecting with your email subscribers and curating those results, you may have a business need that requires you to re-enter the setup phase to accommodate increases in email subscriber volume or new lines of business.Setup: Have the proper products and number of products in place to meet your sending goals and ensure compliance.Connect: Send relevant content to opted-in subscribers. Don’t send more than expected and ensure you have a clear call to action to drive engagement.Curate: Review your results and act accordingly. What worked last month may not work today, adjust your audience, content frequency as needed. Mailbox providers Gmail and Yahoo recently announced a set of requirements for bulk mail senders that touches on authentication of the sending domain, use of a clearly defined opt-out method and the importance of keeping spam complaints to a minimum (under 0.3% per Gmail’s guidance). These have been long-standing best practices in email marketing, but enforcement at the major mailbox providers reinforces the need for senders to be aware of the importance of the messaging lifecycle. Ignoring it is the fastest way to find yourself in the spam folder or blocked and unable to reach the inbox of your customers. Start improving your open rates today Want to learn more about the foundation of successful email sending? Discover how on Trailhead, the free online learning platform from LIKE.TG. See how it’s done +400 points Module Email Deliverability Concepts

Customer Relationship Management (CRM) databases have become an essential tool for businesses of all sizes. By storing and organising customer data, CRM databases help companies track sales opportunities, manage customer relationships, and deliver better customer service. In this blog post, we will explore the benefits of using a CRM database, discuss how to get started with one, and provide tips for optimising your CRM data. We will also provide a specific example of a CRM database and explore the features and benefits of LIKE.TG, a leading CRM platform. What is a CRM database? A customer relationship management (CRM) database is a software platform that helps businesses manage customer interactions and data. It is a centralised repository for all customer-related information, including contact details, purchase history, support interactions, and more. By leveraging a CRM database, businesses can effectively manage customer relationships, track sales opportunities, and deliver exceptional customer service. A CRM database goes beyond simply storing customer data. It enables businesses to gain valuable insights into customer behaviour, preferences, and buying patterns. This information can be leveraged to personalise marketing campaigns, improve customer service strategies, and drive business growth. Additionally, CRM databases facilitate collaboration among different departments within an organisation, ensuring that all customer interactions are consistent and aligned with the company’s overall goals. In today’s competitive business landscape, having a robust CRM database is essential for businesses that want to succeed. It provides a comprehensive view of the customer journey, allowing businesses to make informed decisions, optimise their sales processes, and deliver a seamless customer experience. With its ability to streamline customer interactions, enhance sales performance, and drive business growth, a CRM database is an indispensable tool for modern businesses. Benefits of utilising a CRM database A CRM database offers a plethora of benefits to businesses of all sizes and industries. Here are some compelling reasons why utilising a CRM database is crucial: Streamlined communication and customer service: A CRM database centralises all customer interactions, making it easier for businesses to track and respond to customer inquiries, complaints, and requests. This streamlined communication enhances customer satisfaction and loyalty, as customers can seamlessly reach out to businesses and receive prompt assistance. Improved customer retention: By leveraging customer data and insights from a CRM database, businesses can develop targeted strategies to retain existing customers. This can be achieved through personalised marketing campaigns, proactive customer service, and loyalty programs. By nurturing customer relationships, businesses can increase customer lifetime value and reduce customer churn. Increased sales and revenue: A CRM database empowers businesses to identify and capitalise on sales opportunities. By analysing customer data, companies can gain insights into customer preferences, buying patterns, and pain points. This knowledge enables businesses to tailor their sales pitches, upselling and cross-selling opportunities, and pricing strategies, leading to increased sales and revenue growth. Enhanced decision-making: A CRM database provides businesses with valuable data and analytics that support informed decision-making. By analysing customer data, companies can gain insights into market trends, customer behaviour, and sales performance. This information empowers businesses to make data-driven decisions about product development, marketing campaigns, and resource allocation, ultimately driving business success. Better targeted marketing: A CRM database enables businesses to segment customers based on various criteria such as demographics, purchase history, and engagement levels. This segmentation allows companies to deliver personalised marketing campaigns that resonate with specific customer groups. Targeted marketing campaigns increase the effectiveness of marketing efforts, resulting in higher conversion rates and improved return on investment (ROI). Data migration: 5 steps to getting started with a CRM database Data migration is a crucial step in implementing a CRM database. Here are five steps to help you get started: 1. Define the Scope and Objectives of Your Data Migration Project: Before embarking on the data migration process, clearly defining your project’s scope and objectives is essential. This includes identifying the specific data that needs to be migrated, the source systems from which the data will be extracted, and the target CRM database where the data will be stored. Additionally, it’s crucial to set measurable objectives for the data migration process, such as ensuring data accuracy, completeness, and consistency. 2. Identify the Source Systems and Data to be Migrated: The next step involves identifying the source systems from which data will be extracted. This could include various systems such as spreadsheets, legacy CRM systems, customer support platforms, e-commerce platforms, and more. Once the source systems are identified, you need to determine the specific data elements that need to be migrated. This may include customer contact information, purchase history, support interactions, product information, and other relevant data. 3. Design the Target CRM Database Schema and Data Model: The target CRM database should accommodate the data migrated from the source systems. This involves creating a database schema that defines the tables, fields, and relationships that will store the data. Additionally, you need to develop a data model that specifies the data types, formats, and constraints for each data element. 4. Extract, Transform, and Load the Data: Once the target CRM database schema is designed, you can proceed with the data migration process. This involves extracting data from the source systems, transforming it to conform to the target CRM database schema, and loading it into the CRM database. Data transformation may include tasks such as data cleansing, data conversion, and data enrichment. 5. Test the Migrated Data and Ensure Data Integrity: The final step is thoroughly testing the migrated data to ensure its accuracy, completeness, and consistency. This involves verifying that the data has been correctly extracted, transformed, and loaded into the CRM database. Additionally, it’s essential to perform data validation checks to identify any errors or discrepancies in the data. Regular data quality checks should be implemented to maintain data integrity over time. CRM database example CRM databases are essential for businesses looking to manage customer interactions effectively and drive growth. Several popular CRM database software options are available, each with unique features and capabilities. Here, we will briefly explore four widely recognised CRM database software: LIKE.TG Sales Cloud CRM, Pipedrive CRM, Zoho CRM, and HubSpot CRM. LIKE.TG Sales Cloud CRM is a comprehensive CRM solution designed for businesses of all sizes. It offers a wide range of features, including sales force automation, customer service management, marketing automation, and analytics. LIKE.TG Sales Cloud CRM is highly customisable and can be integrated with various third-party applications, making it a versatile option for businesses with complex requirements. Pipedrive CRM is a user-friendly CRM software specifically designed for sales teams. It emphasises visual sales pipelines, allowing users to track the progress of their deals easily. Pipedrive CRM also offers features such as lead management, email integration, and mobile access, making it an excellent choice for sales professionals on the go. Zoho CRM is a cloud-based solution offering a wide range of features, including sales force automation, customer service management, marketing automation, and analytics. Zoho CRM is known for its affordability and ease of use, making it an excellent option for small businesses and startups. HubSpot CRM is a free CRM software offering various features, including contact management, lead generation, email marketing, and analytics. HubSpot CRM is an excellent option for businesses looking for a cost-effective CRM solution with powerful marketing capabilities. These four CRM database software options represent a fraction of the available choices in the market. Businesses should carefully evaluate their needs and requirements when selecting a CRM database to ensure they find the best fit for their organisation. Six ways to optimise your CRM data Optimising your CRM data is crucial to ensure its accuracy, consistency, and usability. Here are six effective ways to optimise your CRM data: 1. Identify and Eliminate Duplicate Data: Duplicate data can lead to errors, confusion, and wasted storage space. Regularly audit your CRM database to identify and eliminate duplicate records. This can be done manually or by using data cleansing tools. 2. Enrich Your Data with Additional Sources: Enhance your CRM data by integrating it with other data sources such as social media platforms, loyalty programs, and website analytics. This will provide a more comprehensive view of your customers and their interactions with your business. 3. Standardise Your Data Formats: Ensure consistency in data formats across all fields and records. This includes standardising date formats, currency formats, and measurement units. Data standardisation improves data accuracy and facilitates data analysis. 4. Regularly Cleanse Your Data: Clean your CRM data to remove outdated, incomplete, or inaccurate information. Data cleansing helps maintain data integrity and ensures your CRM system contains only relevant and useful data. 5. Implement Data Governance Policies and Procedures: Establish clear data governance policies and procedures to ensure customer data’s consistent and ethical use. This includes defining data ownership, access rights, and data security measures. 6. Train Your Team on Data Quality: Educate your team about the importance of data quality and provide training on proper data entry and management practices. Empower your employees to maintain accurate and up-to-date customer information. Getting Started with a LIKE.TG CRM Database This section will provide a step-by-step guide on getting started with a LIKE.TG CRM database. We will cover everything from signing up for a LIKE.TG account to importing your data into the database. Step 1: Sign up for a LIKE.TG account The first step is to sign up for a LIKE.TG account. You can do this by visiting the LIKE.TG website and clicking the “Sign Up” button. You must provide your name, email address, and password. You will also need to choose a plan. LIKE.TG offers a variety of plans, so you can choose the one that best fits your needs. Step 2: Import your data Once you have created your LIKE.TG account, you can import your data into the database. You can do this by using the LIKE.TG Data Loader. The Data Loader tool allows you to import data from various sources, including CSV files, Excel files, and other databases. Step 3: Customise your LIKE.TG database After you have imported your data, you can customise your LIKE.TG database to meet your specific needs. You can do this by creating custom fields, objects, and reports. You can also use the LIKE.TG AppExchange to install third-party apps that can extend the functionality of your database. Step 4: Train your team on LIKE.TG Once you have customised your LIKE.TG database, you need to train your team to use it. LIKE.TG offers a variety of training resources, including online courses, webinars, and in-person training. You can also hire a LIKE.TG consultant to help you train your team. Step 5: Go live with LIKE.TG Once your team is trained, you can go live with LIKE.TG. This means that you will start using LIKE.TG to manage your customer relationships. LIKE.TG can help you streamline your sales process, improve customer service, and grow your business.

2023 has been a uniquely challenging year for the insurance sector. Inflation, climate change, and supply chain issues have contributed to 10-year record high losses for some insurance companies. To mitigate these pressures, forward-thinking insurance companies in Southeast Asia are looking for new ways to use artificial intelligence (AI) to create efficiencies across the value chain. And, in doing so, they’re finding new opportunities for growth. In Singapore, for example, 50% of respondents to the LIKE.TG Connected Financial Services Report said they would switch to a new insurer if they offered a better digital experience. However, face-to-face engagement and the human advisory experience is still important in Southeast Asia to build customer trust, especially in high impact and personalised products like Life and Health (LH) insurance. While in the Property Casualty (PC) insurance business, there has been an increasing momentum to go full digital and touchless. There is a generational aspect to this human/digital balance too. For example, the more seasoned generations typically prefer some human touch in the customer journey, while young consumers usually prefer more digital experiences. Meanwhile, advancements in AI – particularly the rapid commercialisation of GenAI products through 2023 – have led insurers to adopt AI in various functions. 1. Adopt a data-first approach to leverage AI Data has always been crucial for managing risk, determining claims, and setting premiums. In addition, it’s also a critical tool actuaries use to set the prices and rules that give insurers confidence that they can cover claims while staying solvent and regulatory compliant. In this way, data is foundational to the insurance sector’s financial health and ability to mitigate risk. The advent of AI has heightened the importance of data in insurance to even higher levels, because AI is only effective when insurers use rich, interconnected, trusted datasets. For example, Thailand-based online car insurer, Roojai, is able to utilise granular data sets to focus on optimising the customer journey from origin to conclusion. This has contributed to a 25% reduction in cost per conversion, and a 16% increase in conversions. To adopt a similar data-first approach, insurers can use LIKE.TG Customer 360 to: Connect and unify customer data to enhance downstream applications with a 360-degree customer view. For example, LIKE.TG Customer 360and MuleSoftconnect your departments and customer data to provide a single, shared view of your customers. Benefit from generative AI without compromising data thanks to best-in-class security guardrails and enterprise security standards. For example, the Einstein Trust Layer uses guardrails like dynamic grounding, zero data retention, and toxicity detection, to protect data privacy and security and improve AI results accuracy. Grows deeper policyholder connections and increases productivity. For example, Data Cloud translates raw data into intelligence that enables insurance agents to visualise all customer engagement and activity, segment audiences, and prioritise cross-sell opportunities. Enhance customer engagement with personalised interactions and insights. For example, a connected CRM gives your teams access to a single source of customer data they can use to personalise content and experiences to meet your customers’ unique needs. Offer AI-driven insights, data analytics, and data visualisation across departments. For example, Tableau Analytics can be used to create intelligent experiences across the company with augmented analytics tools such as one-click storytelling with automated discovery, real-time recommendations, and narrative explanations with natural language generation. 2. Use automation technology to streamline operational processes Swift underwriting is essential to deliver a seamless insurance sales experience to customers. This has been a challenge for insurance companies because underwriting often requires extensive amounts of information processing and decision-making. Imagine managing extensive data on coverage, benefits, and pricing across numerous insurance plans, conducting rule validation, and workflows across various applications. This can significantly lengthen turnaround times. In addition, underwriting is more than just a desktop task. It involves collaboration with various partners and customers. For example, insuring a High Net Worth Individual (HNWI) in Asia might require assessments of health, lifestyle, and financials. This sometimes involves third-party services, which adds further complexity. Similarly, commercial property insurance requires thorough property assessments, sometimes with onsite surveys by risk engineers. These comprehensive processes all contribute to longer turnaround times for the customer. Insurers can streamline insurance processes by leveraging industry solutions. For example, LIKE.TG Financial Services Cloud automates underwriting and pricing, optimises workflows and collaboration, reduces turnaround time, and thus enhances sales conversion and Customer Lifetime Value (CLV) by empowering agents to focus on effective sales engagement and opportunities for cross-selling and up-selling.In addition, Slack, brings conversations, collaboration, and automation together, making collaboration and communication between underwriters, sales agents, product managers, and third party service providers organised and aligned. Past underwriting data and knowledge are made easily accessible through Slack’s AI-powered search. And real-time analytics and visualisation, along with natural language queries, empower employees to make informed decisions quickly. 3. Recruit multi-generational customers with innovative digital engagement As a new, affluent young customer group emerges in the region, insurance engagement is shifting from limited touchpoints to more frequent contact. For example, Singapore-based insurer Singlife understands the importance of connecting with their customers on their preferred channels, and replaced post-delivered policy documents with engaging digital experiences. The aim is to make buying insurance as seamless an experience as shopping on any other online platform. In addition, innovative telematics-based rewards, digital health concierges, health thought leadership, and engaging digital methods like embedded finance and gamified social media campaigns are all helping insurance companies to more effectively engage with customers online. At the same time, social media platforms that attract diverse user groups enable insurers to personalise their marketing efforts. LIKE.TG Marketing Cloud is one tool insurers are using to achieve this. It enables real-time, hyper-personalised engagement with native integration across digital platforms. Marketing Cloud also leverages Einstein AI for automated, customised customer journeys and sophisticated analytics for marketing performance and ROI insights. This approach ensures insurers remain competitive and effective in a rapidly evolving market. Seize today’s opportunities with next-gen solutions The insurance industry stands at a pivotal juncture, marked by both challenges and opportunities. For insurers, the path ahead includes adopting trusted AI and data strategies, automating and augmenting insurance processes, and captivating and retaining multi-generational customers through diverse channels. Leveraging platforms like LIKE.TG’s multi-cloud solutions will be crucial in integrating these initiatives, enabling insurers to not only satisfy current needs but also stay future proof. This strategic approach will drive sustainable growth and resilience in the ever-evolving insurance landscape in Southeast Asia.

Conversion rate is a crucial metric that measures the effectiveness of your website or app in converting visitors into customers. It’s the percentage of visitors who take a desired action, such as making a purchase, signing up for a newsletter, or downloading an app. Understanding conversion rate is essential for businesses looking to optimise their online presence and drive growth. In this blog post, we’ll explore what conversion rate is, how to calculate it, why it’s important, and how to improve it. We’ll also provide conversion rate benchmarks and tips for enhancing your website’s conversion rate with LIKE.TG, the world’s leading customer relationship management (CRM) platform. The definition of conversion rate Conversion rates are a key metric that measures the effectiveness of your website or app in converting visitors into customers. It is calculated as the percentage of visitors who take a desired action, such as making a purchase, signing up for a newsletter, or downloading an app. In simpler terms, it represents the ratio of the number of conversions to the total number of visitors or sessions on your website or app. Conversion rate serves as a valuable indicator of how well your website or app is achieving its intended goals. By monitoring and analysing conversion rates, businesses can gain insights into the effectiveness of their marketing campaigns, website design, user experience, and overall performance. It helps identify areas for improvement and allows businesses to make data-driven decisions to optimise their online presence and drive growth. Furthermore, conversion rate optimisation plays an essential role in tracking the success of specific initiatives, such as marketing campaigns, website redesigns, or the introduction of new features. By comparing conversion rates before and after implementing changes, businesses can quantify the impact of their efforts and make informed decisions about future strategies. Effective conversion rate optimisation strategies 1. Homepage Optimisation Opportunities The homepage serves as the initial point of contact for website visitors, making it crucial for a positive first impression and pivotal in retaining visitor interest to delve deeper into your site. Enhancements can include highlighting links to the product pages for details, promoting a free registration option, or integrating a chatbot to engage with visitors and answer their questions throughout their site exploration. 2. Enhancements for Pricing Pages The pricing page often determines whether visitors proceed to purchase. Utilising CRO techniques here can transform browsers into buyers by tweaking pricing structures (e.g., annual vs. monthly fees), elaborating on product features for different pricing tiers, providing contact options for direct inquiries, or introducing interactive elements like pop-up forms. An example of successful implementation is Hotjar, which added an email opt-in popup on its pricing page, resulting in over 400 new leads within three weeks. 3. Blog Conversion Strategies Blogs represent a significant opportunity for conversions by not only offering valuable industry insights but also by integrating effective CRO strategies to drive conversions and turn readers into leads. Tactics might include embedding multiple calls-to-action throughout posts, or promoting content offers like ebooks or reports in exchange for reader email addresses. 4. Landing Page Enhancements Given their direct call to action, landing pages typically exhibit the highest conversion rates among all types of signup forms—an impressive average of 23%. For example, an event landing page might feature a video from a previous event to boost registration rates for the current year, while a resource offering page could showcase snippets of content to entice downloads. Understanding When to Initiate CRO Knowing the best areas to apply CRO is key to conversion optimisation, and it’s equally important to recognise the right time to begin optimising your site for improved conversion rates. How to calculate conversion rates To calculate your conversion rate, you need to know the number of visitors who took the desired action and the total number of visitors to your website or app during a specific time period. The formula for conversion rate is: Conversion Rate = (Number of conversions / Total number of visitors) * 100 For example, if 100 people visit your website and 10 of them make a purchase, your conversion rate would be 10%. You can track your conversion rates over time using Google Analytics or other analytics tools. This will help you see how your conversion rates are trending and identify any areas where you need to improve. Conversion rates can vary depending on a number of factors, including: The type of website or app you have The target audience you are targeting The traffic source (e.g., organic search, paid advertising, social media) The landing page that visitors are directed to It is important to track and analyse your site’s conversion rate and rates so that you can make data-driven decisions to improve your website or app and drive growth. Conversion rates are a key metric for measuring the success of your business. They measure the success of your marketing and sales efforts, help you identify areas for improvement in your sales funnel, allow you to compare your performance and conversion funnel to industry benchmarks, and can help you to optimise your website and marketing campaigns. By tracking conversion rates, you can gain insights into the effectiveness of various channels and strategies. This enables you to allocate your resources more efficiently, focusing on the methods that yield the highest returns. Moreover, conversion rates help you identify potential bottlenecks in your sales funnel, allowing you to rectify issues and enhance the overall customer experience. Furthermore, conversion rates serve as a benchmark for measuring your performance against competitors. By comparing your conversion rates to industry standards, you can assess your competitiveness and make necessary adjustments to improve your position in the market. Additionally, conversion rates provide valuable data for A/B testing and website optimisation. By experimenting with different elements of your website or app, you can determine what works best for your audience and optimise the user experience accordingly. In essence, conversion rates are crucial for businesses aiming to grow their customer base and revenue. By closely monitoring and analysing conversion rates, businesses can make informed decisions, optimise their marketing strategies, and enhance their overall performance. Conversion rate optimisation (CRO) is the process of increasing the percentage of visitors to your website or app who take a desired action, such as making a purchase or signing up for a service. It involves a data-driven approach to analysing and optimising your website or app to improve its effectiveness in converting visitors into customers. There are five key areas to focus on when optimising your conversion rate: 1. Testing different versions of your website or landing page. A/B testing allows you to compare different versions of your website or landing page to see which one performs better. You can test different elements, such as the headline, call to action, or the web page layout, to determine what resonates most with your target audience. 2. Personalising your website or landing page to your target audience. Personalisation involves tailoring your website or landing page to the specific interests and needs of your target audience. This can be done by using data from your analytics platform to identify the demographics, interests, and behaviours of your visitors. 3. Using clear and concise calls to action. Your call to action (CTA) is what tells visitors what you want them to do next. Make sure your CTA is clear, concise, and easy to find. It should also be relevant to the content on the page and the needs of your target audience. 4. Making it easy for visitors to convert. The checkout process should be as simple and straightforward as possible. Avoid asking potential customers for unnecessary information, and make sure the payment process is secure and easy to understand. 5. Tracking your results and optimising your campaigns accordingly. It’s important to track your conversion rates so that you can see what’s working and what’s not. This will allow you to make data-driven decisions about how to optimise your website or app for better conversions. By following these five steps, you can improve your conversion rate, increase conversions, and drive more growth for your business. Conversion rate benchmarks This section provides conversion rate benchmarks for different industries, services and businesses. It discusses the average conversion rate for all industries, as well as the full conversion rate optimisation process and rates for high-performing websites, B2B websites, and mobile websites. The average conversion rate for all industries is around 2-3%. This means that for every 100 visitors to a website, 2-3 will take the desired action. However, there is a significant variation in conversion rates between different industries. For example, the average conversion rate for e-commerce websites is around 4%, while the average conversion rate for lead generation websites is around 2%. High-performing websites typically have a conversion rate of 5% or higher. These websites are typically well-designed, easy to use, and have a clear call to action. They also tend to have a strong value proposition and a targeted marketing strategy. B2B websites typically have a lower conversion rate than e-commerce websites. This is because B2B sales cycles are typically longer and more complex. B2B websites typically have a conversion rate of around 2-3%. Mobile devices and websites typically have a lower conversion rate than desktop websites. This is because it can be more difficult to design a mobile website that is easy to use and navigate. Mobile websites typically have a conversion rate of around 1-2%. It is important to note that conversion rates can vary significantly depending on a number of factors, such as the type of website or app, the target audience, the traffic source, and the landing page that visitors are directed to. Businesses should track and analyse their conversion rates over time to identify areas for improvement. Improving your conversion rate with LIKE.TG LIKE.TG is a powerful customer relationship management (CRM) tool that can help you improve your conversion rate in a number of ways. Here are a few tips: Track and test your landing web pages, forms, and CTAs: LIKE.TG allows you to track the performance of your landing pages, forms, and calls to action (CTAs). This information can help you identify which elements are working well and which ones need to be improved. You can then use this information to make changes to your website or app and improve your conversion rate. Create targeted and personalised marketing campaigns: LIKE.TG allows you to create targeted and personalised marketing campaigns based on your customer data. This information can help you send the right messages to the right people at the right time, which can increase your chances of converting them into customers. Track and analyse your customer journey: LIKE.TG allows you to track the customer journey from the moment they first visit your website or app to the moment they make a purchase. This information can help you identify any bottlenecks or drop-off points in your sales funnel and make changes to improve your conversion rate. Automate your marketing and sales processes: LIKE.TG can help you automate your marketing and sales processes, which can free up your time to focus on other tasks. This can help you improve your efficiency and productivity, which can lead to more conversions and increased sales and revenue. By following these tips, you can use LIKE.TG to improve your conversion rate and grow your business.

How much do your customers like their self-service customer service experience with your business? If they’re not impressed yet, here are three ways you can improve it. Self-service lets your customers find the answers they need on their own time, without the help of an agent. Most importantly, it’s what they prefer: our research found that 61% of customers would rather use self-service for simple issues. Enabling your customers to help themselves also increases efficiency. We found that 67% of organisations are now tracking case deflection, typically done through customer self-service or automated processes.To ensure your self-service customer service channels always make the biggest impact, what can you do quickly — even in just one hour? Turns out, it’s a lot. What you’ll learn: What is self-service customer service? Benefits of self-service How to set up for self-service customer support success What is self-service customer service? At a high level, self-service customer service simply means letting customers help themselves. To give customers this option, you can provide: A help centre, also known as a knowledge base, where customers can search for answers to common questions. A customer portal, a branded website customers log into to access personal information and complete actions related to their account. A customer community, where customers gather to share ideas, answer questions, and solve problems together. Chatbots that provide 1:1 assistance to customers without an agent having to step in. These self-service tools give your customers convenience, speed, and anytime availability. (Back to top) Benefits of self-service Self-service customer support is a win-win for both your customers and your business. Nobody likes to wait in a support queue for assistance. Self-service can also provide fast or even instant answers in some cases. This can lead to a better customer experience and higher customer satisfaction scores (CSAT). Your business benefits by reducing support costs and improving operational efficiency. By deflecting routine questions to self-service channels, you can allocate your resources more effectively. For example, your agents can focus on complex cases that require critical thinking and empathy. (Back to top) How to set up for self-service customer support success Your goal is to make it easy for your customers to find solutions independently. To set your business up to deliver successful self-service, let’s look at three key steps to take. 1. Address frequently asked questions Taking a few minutes to connect with your team will help you understand the most common customer questions to address in your self-service options. Even with advancements in AI, there’s still no substitute for human experience. You can use your team’s insights to make continuous improvements to your self-service customer service channels. Host a daily standup Round up your team and gather commonly asked customer questions and how your agents resolve them. (This can be done virtually or in-person). With advancements in artificial intelligence (AI) technology, soon your AI-powered customer service software may be surfacing commonly asked questions to you. Streamline collaboration with technologyEncourage agents to use collaboration tools like Slack to communicate and work together. Slack helps your team stay aligned and move fast. Use it to bring the right people into the right conversations – like swarming on a difficult case with experts from across your organisation. Make sure your help centre has an accurate knowledge base Knowledge provides the key foundation to building out your self-service experience. Create and consistently update knowledge base articles to make sure your users always have the most relevant information. It’s also the foundation for generative AI in self-service. Remember: the more advanced your knowledge base, the more robust the overall search experience will be to find the right answers faster. 2. Find ways to streamline workflows Simplifying processes by making it easier to find information goes a long way for customers, increases efficiency, and frees up agents from cases that can be handled with self-service. Make it easy to find self-service channelsCustomers don’t want to search for support. Make sure that when they search online for customer support, the results provide a clear path to your help site’s landing page.Your company’s contact information shouldn’t be displayed in the search results. A customer will be less likely to access your help site and use self-service.Once customers get to your site, make it easy to get self-service. With a simple widget or code snippet, you can integrate a fixed channel menu on your help site home page. This can direct customers to chatbots, your knowledge base, or a customer community, like the Serviceblazer community Route cases with chatbotsChatbots can streamline workflows – especially AI-powered ones, which are programmed to have human-like conversations. AI chatbots use natural language processing (NLP), which allows them to better understand human speech – including the intent behind what the customer is saying. These bots can interpret the context of what a customer types or says – and then, with generative AI, respond intelligently based on existing data.Rules-based chatbots also do a lot for self-service. They respond based on buttons a customer clicks or particular keywords the customer uses. If you have a rules-based chatbot, review the chatbot data to find specific keywords for easy answers, and be sure to have an FAQ database the chatbot can use to answer questions. But do consider upgrading – an hour spent learning about the latest in AI chatbot technology could be a step toward greater efficiency. Create guided processesIn your customer self-service portal, you can automate specific processes for customers and free agents from receiving a high-volume of calls. What are the simple issues that take up agents’ valuable time, but could be just as easily done by customers? By integrating a workflow on your end, such as canceling an order or booking a field service appointment, the automation process appears on their screen and walks customers through each step. This not only saves on cost, it increases productivity and efficiency. 3. Continuously improve with data and human review The quick ways we’ve discussed to improve your self-service customer support offering can make a big impact. But there’s even more you can do over time. Tackle the ideas below in one-hour chunks, and soon you’ll be well on your way to building an excellent self-service experience. Prioritise reviewing self-serviceRegularly assess your company’s self-service customer support experience from every angle. For example, how does your help centre home page look? How do your search features perform? Are your article pages consistent? Is your chatbot performing well? Does your site allow visitors to provide feedback – not only about your products, but also the support experience? This handy self-service assessment tool can help you identify any gaps where you’re currently not meeting best practices. It gives you helpful guidance on where to focus your improvement effort. Review your dataWhat are your objectives for self-service customer service? Perhaps you want to increase case deflection, so you can give customers the kind of assistance they prefer and reserve your agents’ energy for more complex matters. Or maybe you want to increase CSATs. Decide on the key performance indicators (KPIs) that matter to your team. Then use service analytics to track and monitor this data with easy-to-understand charts and graphs. Ready to get started? With a few simple updates, you can ensure your self-service customer support channels are working hard to help your customers quickly find the answers they need. In time, your customers will be getting an efficient and easy self-service customer service experience they’ll love. Then watch your CSATs soar. (Back to top)

Demand forecasting is an essential business practice in which companies are able to anticipate future market demands for their products or services. By accurately predicting these demands, businesses can optimise their operations, minimise costs, and effectively meet customer needs. Throughout this blog, we’ll take a closer look into the concept of demand forecasting, explaining its significance and exploring the various factors that influence it, whilst also discussing the benefits and providing practical methods and models to help businesses forecast demand more effectively. We’ll also continue to take a look at the latest trends in demand forecasting and how LIKE.TG can be leveraged to enhance and improve demand forecasting accuracy. What is demand forecasting? Demand forecasting is a key business process that enables companies to predict future market demands for their products or services. It involves analysing historical data, current market conditions, and other relevant factors to make informed predictions about future demand patterns. By accurately anticipating demand, businesses can optimise their operations, minimise costs, and effectively meet customer needs. Demand forecasting is essential for businesses of all sizes and across all industries. It plays a pivotal part in the decision-making processes related to production, inventory management, sales and marketing teams, and overall resource allocation. Effective demand forecasting helps businesses avoid overproduction, which leads to excess inventory and increased costs, as well as underproduction, which results in lost sales and dissatisfied customers. Demand forecasting techniques range from simple to complex, depending on the availability of data and the level of accuracy required. Some common techniques include historical data analysis, passive demand forecasting, trend analysis, market research, and econometric modelling. Businesses can also leverage advanced analytics and machine learning algorithms to enhance the accuracy of their passive demand forecasts. Accurate demand forecasting provides businesses with a competitive edge by enabling them to respond swiftly to changing market dynamics and customer preferences. It helps businesses optimise their supply chains, reduce inventory holding costs, and allocate resources efficiently. Effective demand forecasting supports data-driven decision-making, leading to improved overall business performance and profitability. Demand Forecasting Explained Within business, the ability to anticipate future demand for products or services is essential. Demand forecasting serves as a compass, guiding businesses through the ever-changing currents of the market. By predicting demand accurately, companies can optimise production schedules, maintain and manage inventory levels to their optimal amount, and craft effective marketing strategies. The significance of demand forecasting lies in its power to illuminate the path ahead. Armed with insights into future demand, businesses can make choices that propel them towards success. They can anticipate market trends, identify shifts in consumer behaviour, and navigate economic fluctuations with agility. Effective demand forecasting lays a solid foundation for strategic decision-making, enabling businesses to expand production capacity, increase operational efficiencies, introduce new products, and venture into new markets with confidence. The process of demand forecasting involves a meticulous examination of historical data, market trends, and a multitude of other relevant factors. Businesses employ a range of methodologies, from time-tested statistical models to cutting-edge machine learning algorithms, to make informed predictions about future demand. The choice of method hinges on the complexity of the product or service, the availability of data, and the desired level of accuracy. However, the path of demand forecasting is not without its challenges. Uncertainty looms as demand can be swayed by a myriad of factors – economic shifts, evolving consumer preferences, technological disruptions, and the actions of competitors. To navigate these uncertainties, businesses incorporate flexibility into their quantitative demand forecasting models, ensuring they can adapt swiftly to unforeseen market changes. Despite the challenges, demand forecasting remains an invaluable tool for businesses seeking to gain a competitive edge in the marketplace. By harnessing historical data, conducting thorough market research, and employing sophisticated analytical techniques, businesses can enhance the precision of their demand forecasts. This empowers them to make better decisions, optimise operations, and stay ahead of the curve in the ever-evolving business landscape. Why Is Demand Forecasting Important for Businesses? In a business setting, demand forecasting is an essential. Equipped with insights into future demand, companies can anticipate market trends, identify shifts in consumer behaviour, and navigate economic fluctuations with agility. This foresight allows them to optimise operations, reduce costs, and meet customer demand effectively. One of the key benefits of demand forecasting is its ability to improve efficiency and reduce costs. By accurately predicting future demand, businesses can optimise their production schedules, inventory levels, and workforce planning. This reduces the risk of overproduction, which can lead to waste and increased costs, as well as the risk of stockouts, which can result in lost sales and customer dissatisfaction. Another important benefit of demand forecasting is increased responsiveness to market changes. As business environments are ever-changing, companies that can quickly adapt to changing market conditions have a significant competitive advantage. Demand forecasting helps businesses identify emerging economic trends, and shifts in consumer preferences, enabling them to adjust their strategies and product offerings accordingly. This agility allows companies to stay ahead of the competition and capitalise on new opportunities. Enhanced customer satisfaction is another key outcome of effective demand forecasting. By accurately predicting demand, businesses can ensure that they have the right products and services available to meet customer needs. This reduces the likelihood of stockouts and backorders, which can lead to customer frustration and dissatisfaction. Demand forecasting helps companies optimise their customer service operations, ensuring that they have the resources in place to handle customer inquiries and complaints efficiently. Effective demand forecasting also supports better financial planning and budgeting. By having a clear understanding of future demand, businesses can more accurately forecast their revenue and expenses. This enables them to make sound financial decisions, allocate resources efficiently, and manage cash flow effectively. Accurate demand forecasting reduces the risk of financial surprises and helps businesses maintain financial stability. Finally, demand forecasting is a key player in improving supply chain management. By sharing demand forecasts with suppliers, businesses can ensure that they have the necessary raw materials and components to meet production requirements. This collaboration helps optimise the entire supply chain, reducing lead times, minimising inventory levels, and improving overall efficiency. Effective demand forecasting enables businesses to build strong relationships with suppliers and gain a competitive advantage in the market. What Factors Impact Demand Forecasting? Various factors influence the precision of demand forecasting, a crucial component of effective business planning. These factors can be broadly categorised into external and internal elements. External factors encompass the overarching economic landscape. Economic indicators like GDP growth, inflation rates, interest rates, and consumer confidence greatly impact consumer purchasing behaviours. When economic conditions are favourable, consumer demand for products and services flourishes, while economic downturns can lead to decreased demand. Market and consumer trends are another significant external influence. Changing consumer preferences, innovative product introductions, and technological advancements can reshape market dynamics and alter product demand. Businesses must continuously monitor market trends to stay ahead of demand shifts. Seasonal patterns can also affect demand and weather conditions contribute to demand forecasting. For instance, seasonal products like winter clothing or summer beverages experience predictable fluctuations in demand. Businesses must account for these seasonal variations to optimise their own inventory planning and production strategies. Competitor activity is another external factor that can impact the demand for a product. The introduction of competing products or services, changes in pricing strategies, or shifts in marketing campaigns can influence consumer choices. Businesses need to closely monitor their competitors’ actions to mitigate any negative impact on their demand for a product. Internal factors also contribute to demand forecasting accuracy. Production capacity, inventory levels, and marketing efforts all contribute to demand forecasters. Ensuring sufficient production capacity to meet demand, maintaining optimal inventory levels to avoid stockouts, and effectively promoting products through marketing channels are essential for managing demand successfully. By comprehending and analysing these external and internal factors, businesses can enhance the accuracy of their demand forecasts. This enables them to make well-informed decisions regarding production planning, inventory management, marketing strategies, and overall resource allocation, ultimately driving business growth and profitability. Benefits of Demand Forecasting Effective demand forecasting serves as a guiding compass, empowering businesses to navigate the ever-changing currents of the marketplace with precision and agility. One of its benefits lies within resource allocation. Through accurate demand projections, businesses can meticulously plan their production schedules, ensuring that they possess the essential resources – raw materials, skilled labour, and state-of-the-art equipment – to satisfy future customer demand, without the perils of overstocking or shortages. This strategic approach translates into reduced costs and enhanced operational efficiency, laying the foundation for sustainable growth. Another highlight of demand forecasting is its ability to cultivate customer delight. By maintaining optimal inventory levels, businesses ensure that their customers can effortlessly obtain the products or services they desire, when they desire them. This proactive approach minimises the frustrations of stockouts, backorders, and interminable wait times, fostering customer loyalty and satisfaction. Meeting customer demand with precision not only strengthens the business’s reputation but also arms it with a formidable competitive advantage. Demand forecasting also serves as a catalyst for enhanced profitability. By using sales forecasting and aligning production and inventory levels with anticipated demand, businesses can effectively combat waste and maximise revenue streams. This strategic alignment allows them to produce the right products, in the ideal quantities, and at the opportune time, thereby diminishing the risks of overproduction or underproduction. Armed with accurate demand forecasts, businesses can engage in strategic negotiations with suppliers, securing favourable pricing and terms that further bolster their financial position. Beyond its immediate impact on resource allocation, customer satisfaction, and profitability, demand forecasting also elevates decision-making across all echelons of an organisation. Armed with reliable demand projections, businesses can chart their course with confidence, making plans regarding product development, marketing strategies, and expansion plans. This enables them to cease market opportunities, introduce products or services that resonate with customer needs, and venture into new markets with a calculated approach. By aligning their decisions with the compass of demand forecasting, businesses can mitigate risks and amplify their chances of success, propelling them towards sustained growth and industry leadership. How to Forecast Customer Demand To derive accurate demand forecasts, businesses must embark on a series of meticulous steps. The initial phase of demand forecasting often involves comprehending the product lifecycle and industry trends that affect demand now. It’s to recognise the stage of the product’s lifecycle (introduction, growth, maturity, or decline) and understand how industry trends may influence the demand forecast. The next step entails identifying and analysing historical demand data. This involves gathering data on past sales, customer demand, and market trends. Analysing this historical sales data can reveal patterns and trends that can inform future sales and demand forecasts. Selecting the appropriate and accurate forecasting method is also critical. There are various forecasting methods available, each with its own strengths and weaknesses. Some common methods include moving averages, exponential smoothing, and regression analysis. The choice of method depends on the nature of the product, the availability of data, and the level of accuracy required. Collecting and analysing relevant data is another key step in forecasting sales further. This may involve gathering data on various economic trends and indicators, consumer behaviour, competitor activity, and other factors that can influence demand. Analysing this data can provide valuable insights into future demand trends. Finally, it is essential to make adjustments through active demand forecasting based on market conditions. Demand forecasts are not static; they need to be continuously monitored and adjusted based on changing market conditions and customer expectations. This may involve incorporating real-time data, such as sales figures and customer feedback, into the forecasting process. By following these steps and employing robust demand forecasting techniques, businesses can enhance the accuracy of their predictions that drive success. 10 Demand Forecasting Methods This section provides an overview of 10 demand forecasting methods, encompassing time series analysis, causal methods, judgmental methods, simulation, quantitative methods, and machine learning methods. 1. Time Series Analysis Time series analysis involves analysing historical demand data to identify patterns and trends. Common techniques include moving averages, exponential smoothing, and seasonal decomposition. 2. Causal Methods Causal methods establish a relationship between demand and various influencing factors, such as economic indicators, consumer behaviour, and competitor activity. Regression analysis and econometric models are commonly used causal methods. 3. Judgmental Methods Judgmental methods involve incorporating expert opinions and market insights into the forecasting process. These qualitative methods may include the Delphi method, executive opinion, and customer surveys. 4. Simulation Methods Simulation methods use computer models to simulate real-world conditions and generate demand scenarios. Monte Carlo simulation and system dynamics are examples of simulation methods. 5. Machine Learning Methods Machine learning algorithms can analyse large datasets and identify complex patterns. Artificial neural networks, decision trees, and random forests are commonly used machine learning methods for demand forecasting. 6. Moving Averages Moving averages calculate the average demand over a specified period, smoothing out short-term fluctuations. Simple moving averages (SMAs) and exponential moving averages (EMAs) are commonly used. 7. Exponential Smoothing Exponential smoothing assigns exponentially decreasing weights to past demand data, giving more importance to recent data. Single exponential smoothing (SES), double exponential smoothing (DES), and triple exponential smoothing (TES) are different types of exponential smoothing techniques. 8. Seasonal Decomposition Seasonal decomposition separates demand into seasonal, trend, and residual components. Seasonal indices are used to adjust demand forecasts for seasonal variations. 9. Regression Analysis Regression analysis establishes a statistical relationship between demand and one or more independent variables (e.g., price, advertising, economic indicators). Linear regression, multiple regression, and logistic regression are common regression techniques. 10. Econometric Models Econometric models are advanced statistical models that account for the interdependencies and dynamics of various economic factors influencing demand. These models often require extensive data and specialised expertise. Demand Forecasting Models Demand forecasting models are vital tools for predicting future demand and aiding businesses in making better choices. Several models can be employed for various types of demand forecasting, each with its own advantages and applications. Here are some commonly used demand forecasting models: Moving Average Model: The moving average model is a simple yet effective technique that calculates the average of past project sales and future demand, over a specified period. It assumes that future demand will follow a similar pattern to past demand. This model is suitable for stable demand patterns with minimal fluctuations. Exponential Smoothing Model: The exponential smoothing model is an extension of the moving average model that assigns exponentially decreasing weights to past demand data. This model gives more importance to recent demand data, making it more responsive to changing demand patterns. It is suitable for forecasting demand patterns that exhibit gradual trends or seasonal variations. Seasonal Autoregressive Integrated Moving Average (SARIMA) Model: The SARIMA model is a sophisticated time series analysis technique that combines autoregressive, integrated, and moving average components. It is beneficial for forecasting seasonal demand patterns. The SARIMA model identifies and accounts for seasonality, making it suitable for businesses with pronounced seasonal fluctuations in demand. Machine Learning Model: Machine learning algorithms, such as regression, decision trees, and neural networks, can be employed for demand forecasting. These models leverage historical demand data, along with other relevant factors, to make predictions. Machine learning models are particularly effective in capturing complex relationships and non-linear patterns in demand data. The choice of demand forecasting model depends on various factors, including the nature and types of demand forecasting the product or service, the availability of historical data, and the level of accuracy required. Businesses may use a combination of different models to enhance the accuracy of their demand forecasts. Demand Forecasting Examples Demand forecasting is used in various industries to predict future demand for products or services. Here are a few examples short term demand forecasting: Retail: Retailers use demand forecasting to optimise inventory levels and avoid stockouts or overstocking. By accurately predicting demand, retailers can ensure that they have the right products in the right quantities to meet customer demand. This helps reduce costs associated with holding excess inventory and improves customer satisfaction by ensuring that products are available when customers want them. Manufacturing: Manufacturers use demand forecasting to plan production schedules and manage supply chains. By accurately predicting demand, manufacturers can avoid production disruptions and through an efficient supply chain, they can ensure they have the necessary resources to meet customer demand. This helps reduce costs associated with production overruns or shortages and improves customer satisfaction by ensuring that products are available when customers need them. Transportation: Transportation companies use demand forecasting to plan routes and schedules and allocate resources. By accurately predicting demand, transportation companies can optimise their operations and ensure that they have the necessary capacity to meet customer demand. This helps reduce costs associated with empty vehicles or overloaded routes and improves customer satisfaction by ensuring that goods are delivered on time. Healthcare: Healthcare providers use demand forecasting to plan staffing levels, manage patient flow, and allocate resources. By accurately predicting demand, healthcare providers can ensure that they have the necessary staff and resources to meet patient needs. This helps reduce costs associated with understaffing or overstaffing and improves patient satisfaction by ensuring that patients receive timely and efficient care. Financial services: Financial institutions use demand forecasting to manage risk, plan investments, and allocate resources. By accurately predicting demand, financial institutions can look into how to allocate their capital and manage their risk exposure. This helps reduce costs associated with bad investments or excessive risk-taking and improves customer satisfaction by ensuring that customers have access to the financial services they need. Demand Forecasting Trends This section discusses the latest trends in demand forecasting, including the use of artificial intelligence and machine learning, real-time data and analytics, collaborative forecasting, and sustainability and ethical considerations. Artificial intelligence (AI) and machine learning (ML) are transforming demand forecasting by enabling businesses to analyse vast amounts of data and identify patterns and trends that would be difficult or impossible for humans to detect. By leveraging AI and ML algorithms, businesses can create more accurate and reliable demand forecasts, leading to better decision-making and improved business outcomes. Real-time data and analytics are a major component in modern demand forecasting. With the advent of the Internet of Things (IoT) and other data-generating technologies, businesses can now collect real-time data on various factors that influence demand, such as customer behaviour, market trends, and supply chain disruptions. By analysing this real-time data, businesses can make more informed and agile decisions, quickly adapting to changing market conditions. Collaborative demand forecasting method involves bringing together different stakeholders within an organisation to contribute their expertise and insights to the demand forecasting process. This approach combines the knowledge of sales, marketing, production, and other departments, resulting in more comprehensive and accurate forecasts. Collaborative internal demand forecasting also fosters a culture of shared responsibility and improves communication and alignment across the organisation. Sustainability and ethical considerations are increasingly becoming important factors in demand forecasting. Businesses are recognising the need to minimise the environmental impact of their operations and ensure ethical practices throughout the supply chain. Demand forecasting plays a large part in optimising resource allocation, reducing waste, and promoting sustainable practices. By considering sustainability and ethical factors in demand forecasting, businesses can align their operations with their values and meet the expectations of environmentally conscious consumers. These trends are revolutionising the field of demand forecasting, enabling businesses to make more accurate predictions, like the ability to predict demand, optimise their operations, and gain a competitive advantage in a data-driven business environment. Demand Forecasting with LIKE.TG Demand forecasting is an essential business process for optimising operations, reducing costs, and meeting customer demand effectively. LIKE.TG, a leading customer relationship management (CRM) platform, provides a variety of tools and capabilities to help businesses create accurate demand forecasts. One of the key features of LIKE.TG for demand forecasting is Einstein Discovery, a powerful artificial intelligence (AI)-powered tool that helps businesses analyse historical data and identify trends and patterns that can be used to predict future demand. Einstein Discovery uses machine learning algorithms to automatically detect relationships between different variables and generate accurate forecasts. LIKE.TG also allows businesses to leverage historical sales data to create demand forecasts. By analysing past sales data, businesses can gain insights into seasonal trends, sales trends, market fluctuations, and customer behaviour patterns. This historical data can be used to build statistical models and time series analysis to predict future demand. In addition to historical data, LIKE.TG enables businesses to incorporate predictive analytics into their demand forecasting process. Predictive analytics uses advanced statistical techniques and machine learning algorithms to analyse a variety of data sources, including customer demographics, market trends, economic indicators, and social media sentiment, to further generate revenue forecasts. LIKE.TG also allows businesses to integrate external data sources into their demand forecasting process. This can include data from market research firms, industry reports, and social media platforms. By combining internal data with external data points, businesses can gain a more comprehensive view of the market and make more accurate demand forecasts. LIKE.TG provides a user-friendly interface that makes it easy to create and manage demand plans and forecasts collaboratively with team members. Different users can access and update forecasts, share insights, and discuss assumptions, ensuring a collaborative and transparent demand planning process. Finally, LIKE.TG provides tools to monitor sales forecasts, make sales projections and track the performance of demand forecasts against actual results. This allows businesses to continuously evaluate the accuracy of their forecasts and make adjustments as needed. By analysing forecast errors and identifying the factors that influence demand, businesses can continuously improve their forecasting accuracy and optimise their operations.

It’s no secret that the business world runs on leads, opportunities and sales. But sales managers, sales reps and support staff now have AI-powered CRM tools to do a lot of the heavy lifting. With so much rich information at our fingertips, businesses can confidently look to the future more accurately than ever before, confidently projecting future financial activity. One of the most powerful tools in a company’s arsenal is sales projection. In a nutshell, sales projection is simply using your CRM’s real data to develop realistic financial or performance-based predictions. Why is Sales Projection important? One of the key reasons to employ sales projection as a planning tool in your business is to empower your management team. Sales projections place your decision makers in the driving seat, ensuring they’re well equipped to effectively plan for day-to-day operations such as KPIs (key performance indicators), budgets and staffing. When prepared correctly (and we’ll get to that soon), the most significant role your sales projection plays is to describe your potential sales performance and how it aligns with your revenue projections. Sales projections also give your business a glimpse into the future (crystal ball, anyone?) to see and monitor your business health, productivity and growth metrics. You can see how your business is tracking against target performance, which is reassuring in the best-case scenario. If performance isn’t meeting objectives, real-time sales data can be the powerful nudge you need to investigate what’s not working and make necessary tweaks and adjustments. This can be due to any number of factors such as pricing, inventory problems or underperforming team members. The difference between Sales Projections and Sales Forecasts Sales projections are a little different to sales forecasts. Both are important to use but it is good to know what sets them apart. Sales projections use current ‘real’ data to gain an understanding of future sales activity. Using the data in your CRM, you can test multiple hypothetical scenarios to examine sales potential, leading to strategic decision-making. By contrast, sales forecasts use historical data to predict future results or, in other words, they tell us what we expect to see based on past performance. Advantages of Sales Projections Sales projections impact all areas of operational business, and really help to gauge the difference between where companies are now, and where they want to be. Bringing sales projections into your strategic planning can provide advantages such as: Data-driven decision making. Once your company has examined multiple possible scenarios, you will have a clear idea of what your organisational priorities will be. For example, if you’re looking to expand into a new market and the sales projection figures support this move, you can confidently plan the next tranche of actions to activate this goal. Goal setting. Setting the right goals equates to setting your team up for success. Being able to chart potential sales performance outcomes means you can set realistic and achievable goals. Taking your team on the journey to understand the data behind these targets will hopefully inspire them to hit the ground running! Staffing predictions. Time really is money, and that statement is never truer than when you’re talking about onboarding the right team. If your sales projections have shown a need to increase or change your staff footprint, the sooner you have this intel, the more chance you have to create the right team and attract the right talent. Financial planning. This is probably the holy grail of what accurate sales projections can do for your business. Once your sales projections have supplied the numbers, you can allocate your budgets accordingly to support your organisational objectives. Managing product stock. We’ve already discussed how sales forecasting can pinpoint budget and personnel requirements, and this includes managing product inventory. When you can clearly estimate product sales over the coming financial period, you can ensure you have sufficient (but not too much) stock on hand. Inventory control streamlines expenditure against planned sales. Optimising customer service quality. Harnessing the power of your sales team is a key benefit and really leverages the value of sales projections data. Arming your sales team with sales projections gives them the opportunity to prepare for all interactions with their customers and to convert those sales. Sales team performance. Sales projections provide rich benchmarking and reporting capabilities. Once your sales period has closed, you will be able to measure results against projections. In a perfect world, your results will resemble the projections and meet or slightly exceed them. If actual results fall short, this could mean the sales projections data wasn’t quite accurate or it could reveal barriers to success such as a sales pipeline issue or a staffing dilemma. Sales Projection optimisation Now that we know how helpful sales projections are, let’s move onto sales projection optimisation. Broadly speaking, optimisation is simply monitoring and refining through regularly reviewing your sales data, proactively managing your sales pipeline and constantly evolving your sales forecasting. As your day-to-day business progresses, you will amass solid quantities of sales data. This is going to become one of your best friends in preparing sales projections. Keeping your data as clean and accurate as possible through your collection and organisation process processes will set you up with a solid foundation to start predicting future sales. Good pipeline management refers to proactively reviewing each stage of the pipeline from leads to opportunities and then to quotes, conversions and sales. Regularly reviewing your pipeline gives you the opportunity to check in on customer progress, to measure results to date and to ensure the data is up to date. Lastly, you should be constantly examining your sales forecasting model and making amendments and refinements as you go. Your sales predicting process should evolve and grow with your business. Types of sales projections There are multiple sales prediction techniques you can apply to get the tailored insights you need, but generally sales projection types generally fall into these categories: Historical sales projections. Looking in the rear-view mirror allows you to make predictions based on past sales performance. If you’re tracking year-on-year trend lines and observing an average growth of 12% each year, it is reasonable to apply this business growth estimate for coming years. Multivariable sales projections. You can access more nuanced and tailored insights based on a customised view. You can toggle in different factors such as average sales value per customer, current leads and opportunities data, and other sales data can be plugged in to customise the projections. Length of sales cycle sales projections. Using length of sales cycle sales projection as technique focuses on who your customers are, what their buyer journey looks like and how they buy your product. You can use your understanding of how long your opportunities generally take to convert and apply this data to your planning. Point-in-time sales projections. You can use this sophisticated approach to analyse how your open opportunities are tracking towards conversion. Using a point-in-time approach, you can review factors such as the length of time the opportunity has been open, the number of interactions and cost per opportunity data to predict when opportunities will close (or not). Pipeline sales projections. This is where your CRM will really come into its own by providing you with clear insights into expected sales revenue at any given moment. Using the data at your fingertips, pipelines sales projections home in on where your opportunities are at in their customer stage and how likely they are to commit. Calculating annual Projected Sales Your company’s financial sales targets are high on any commercial entity’s hit list, so it is crucial to get this right. This is usually the lynchpin upon which everything else hinges so ensuring accurate projections are in place will set your business and your team up to succeed. Once you have your annual sales forecasting lined up, this baseline data will provide you with the decision-making power you will need to make strategic plans for the year ahead. It will also give you a strong base to lean on through the financial year as unexpected highs and lows unfold. For example, say one of your suppliers is suddenly unable to fulfil an order you need for production. Your CRM can tell you immediately which of your opportunities may be affected. This knowledge will put your team on the front foot to be able to proactively manage this challenge. Sales Projection formula To calculate sales at a high-level, you’re looking at the quantity of goods, products and services sold and multiplying this by its selling price. Annual sales = quantity sold x price per unit It is also good to consider your revenue. Revenue is any stream of income into your business, including sales. Sales is just one metric of revenue. Annual revenue = sales + other income streams Once your annual sales and annual revenue figures have been determined, you can then continue to consider other financial planning calculations that take operational factors into account such as gross profit, net profit and operating margin. How to create a sales projection Creating a sales projection is as simple as following a few simple steps: Understand your prospective sales opportunities. When you’re undertaking revenue planning, a key consideration is who your customers are. Knowing what they buy, how often and how they pay for your product (one-off or subscription model) becomes the cornerstone of your sales strategy. Review past performance. Looking back at the past few years of sales and revenue performance against targets will set the scene on what is realistic and achievable. Remember, SMART goals! Specifically speaking, delve into metrics to understand your pipeline results. That is, how many leads did you get? How many became opportunities and how many became sales? What about opportunities lost – how many were there and why were they lost? Environmental scanning. Your business doesn’t operate in a vacuum! Understanding your environmental factors, market trends and external pressures will provide a layer of depth to your sales projections (and to your financial planning). Being aware of your macro environment in your strategic sales planning will contribute to achievable goals. Talk to your people. Your sales team is also a wealth of knowledge you can tap into to get a sense of what it’s like in the trenches. Working collaboratively with your staff can assist in setting realistic sales targets and timeframes, as well as comprehending their capacity to deliver on KPIs. Set sales targets. You should now be able to set sales targets based off the research you have conducted. These goals can include anything from number of opportunities, number of sales, year-on-year growth and total sales. Common sales projection mistakes to avoid While sales projects are unquestionably useful, there are some pitfalls to avoid. Here are the mistakes we see most often: Sales projection data error. Not getting your data right the first time can let you down when reporting against your sales projections. The key takeaway here is to ensure your KPIs align to organisational objectives – you want to ensure your hardworking team knows exactly what they need to achieve. On the bright side, your sales projections can be living data. If you spot something is incorrect early on, there is time to reset and move on. Low quality data management. Quality data and data management is almost as important as getting your CRM software! Keep in mind that your CRM is only as powerful as your data management so this is vital to get right. Train your people to ensure data management quality control practices are embedded and upheld. Sales projection and LIKE.TG Sales Cloud If you’re champing at the bit to start work on your sales projections, consider investing in a sales CRM such as LIKE.TG Sales Cloud – this is where the rubber really hits the road. LIKE.TG allows you to combine AI, your customer, and lead data with CRM capabilities in a single location. Your customer’s privacy is safely protected, but you get the insights you need.LIKE.TG Sales Cloud has a rich app-based network of tools ready for you to access and leverage including LIKE.TG Einstein AI Solutions scoring to triage your leads, generative AI to get ahead of communication and it can even connect into Slack, increasing connectivity between people and pipeline! Frequently asked questions What is a sales projection plan? A sales projection plan is a comprehensive and strategic approach to setting revenue planning goals for your business. You should consider your customer, your product, your sales history, the sales market and external factors and your staff to assist you in setting achievable sales projections. Why are sales projections important? Sales projections are important for financial planning, business growth estimates, resource and staff planning purposes. Once your business has a clear sales projection set for the year, sales managers and decision makers can confidently support these goals. How do you make accurate sales projections? The best way to deliver an accurate sales projection is with CRM software such as LIKE.TG Sales Cloud. This CRM is the number #1 on the market and with good reason – powered by AI, LIKE.TG Sales Cloud can slice your lead, opportunity and sales conversion data within seconds to provide you with customised projection data for your business.

Accenture established its LIKE.TG practice in the Philippines in 2012 with a small team of CRM specialists. Today, the practice comprises 1,900 employees who work across Advanced Technology Centres in Cebu and Manila. It has also been awarded the highest number of accredited practitioners within the country. I met with the team to discuss the development of the practice and how they are driving customer and employee success. Here are the key takeaways, including best practices for building and maintaining LIKE.TG talent. Practice achieves 44% increase in LIKE.TG certifications In 2023, Accenture’s team in the Philippines increased its number of LIKE.TG certifications by 44%. The number of certified individuals in the practice has also increased by an average of 24% year on year over the last four years. LIKE.TG and Accenture have worked closely together to upskill the team and build new capabilities. Our joint LIKE.TG Days are just one example. The most recent event saw more than 200 people come together for learning and inspiration. We discussed our roadmap, priorities for growth, and new opportunities for collaboration. We also presented a deep dive on our AI-driven solutions and shared product demos. Accenture also held onsite certification exams during the event with 115 consultants taking part and a high number passing their exams. In addition to LIKE.TG Days, we’ve partnered with Accenture to run several industry-specific enablement sessions. These sessions have been aligned to Accenture’s key practice areas, including education, financial services, public sector, and utilities. On top of all this, Accenture launched the first LIKE.TG Developer Group in the Philippines back in 2016 and it has continued to host learning sessions, meetups, and campus programs for those interested in sharpening their LIKE.TG skills. Get articles selected just for you, in your inbox Sign up now Growing a diverse pipeline of talent Bringing net new LIKE.TG talent into its business is just as important as upskilling existing talent. That’s why Accenture works with universities to teach students LIKE.TG and other job-ready skills. The business has established the Accenture Technology Academy which is open to students at several universities in the Philippines. The academy not only enables students to learn new skills, but fast-tracks their applications to join Accenture after graduation. More than 800 students from across different universities have participated to date, with around 25% going on to secure placement within Accenture. Another program designed to nurture new talent is Accenture’s Near Hire Training (NHT) program which helps marginalised and unemployed individuals become entry-level voice and data encoding agents. A free training program, NHT is designed to give everyone an equal opportunity to build new skills and gain employment in a call centre or business process role. Accenture is also a proud supporter of the For the Women Foundation which helps upskill and secure job placement for working mums and other women. Through all these initiatives, Accenture has been able to grow its pipeline of talent and create a diverse and inclusive workplace. Capturing new opportunities onshore and offshore Accenture’s practice in the Philippines has largely existed to support customers in other regions. However, local demand for LIKE.TG skills is growing and presents an exciting opportunity for consultants to work with customers face to face. To capture these opportunities and grow onshore and offshore, Accenture is continuing to expand its capabilities. Building generative AI skills is a particular focus as it will help Accenture deliver more value for customers in areas like customer service and business process outsourcing. Marvin Bonifacio, Cebu Tech Lead and LIKE.TG Technical Architect at Accenture in the Philippines, has also become the first in the country to be certified as a Sales Champion for LIKE.TG. This represents the team’s ongoing commitment to its partnership with LIKE.TG and helping more businesses harness the benefits of the platform.

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.

Sales promotion is a marketing strategy that businesses use to boost sales, create brand awareness, and drive customer loyalty. It involves various techniques and tactics to incentivise customers to make a purchase or take a specific action. In this article, we will delve into the world of sales promotions, exploring its definition, uncovering its benefits and drawbacks, and examining different types of sales promotions. We’ll also provide insights on how to effectively plan, execute, and measure your sales promotions, and how LIKE.TG can assist you in optimising your sales promotion efforts. What is sales promotion? Sales promotion is a marketing strategy designed to increase the sales of a product or service. It involves various techniques and tactics to incentivise customers to make a purchase or take a specific action. Unlike advertising, which focuses on creating awareness and building brand recognition, sales promotion is more action-oriented and aims to drive immediate results. Sales promotions can be used for a variety of purposes, including: Introducing a new product or service: Sales promotions can help create excitement and generate buzz around a new offering, encouraging potential customers to try it out. Increasing brand awareness: Sales promotions can help increase visibility and recognition of a brand, especially when they involve unique or creative offers. Generating leads: Sales promotions can be used to capture contact information from potential customers, providing businesses with valuable leads for future marketing and sales efforts. Benefits of sales promotions Sales promotions can be used to achieve a number of benefits, including increasing brand awareness, generating leads, boosting sales and revenue, building customer loyalty and repeat business, and clearing out old stock or inventory. Increasing Brand Awareness Sales promotions can help to increase brand awareness by introducing new products or services to potential customers. They can also remind existing customers of your brand and encourage them to make repeat purchases. By offering discounts, free samples, or other incentives, sales promotions can attract new customers and get them to try your products or services. This can lead to increased brand recognition and loyalty. Generating Leads Sales promotions can also be used to generate leads for your business. By offering a free consultation, a white paper, or other valuable content, you can capture the contact information of potential customers who are interested in your products or services. This information can then be used to follow up with these customers and nurture them into becoming paying customers. Boosting Sales and Revenue Sales promotions can also be used to boost sales and revenue. By offering discounts, rebates, or other incentives, you can encourage customers to make purchases that they might not have otherwise made. This can lead to increased sales and revenue for your business. Building Customer Loyalty and Repeat Business Sales promotions can also be used to build customer loyalty and repeat business. By rewarding customers for their purchases, you can show them that you appreciate their business and encourage them to continue to buy from you. This can lead to increased customer loyalty and repeat business, which can help you to grow your business over the long term. Clearing Out Old Stock or Inventory Finally, sales promotions can also be used to clear out old stock or inventory. By offering discounts or other incentives, you can encourage customers to purchase products that are not selling well. This can help you to free up space in your warehouse and make room for new products. Drawbacks of sales promotions Sales promotions, while effective, are not without their drawbacks. One potential downside is the risk of cannibalising sales from other channels. For instance, if a product is heavily discounted during a sales promotion, customers may be more inclined to purchase it during the promotion rather than at its regular price. This can lead to a decrease in sales at full price, offsetting the gains from the sales promotion. Another challenge lies in accurately measuring the effectiveness of sales promotions. While some promotions may result in an immediate boost in sales, it can be difficult to determine the long-term impact on customer behaviour and brand loyalty. Additionally, tracking the ROI of sales promotions can be complex, as it involves considering various factors such as the cost of the promotion, changes in sales volume, and customer acquisition and retention rates. Furthermore, sales promotions can potentially trigger price wars among competitors. When one business offers a significant discount or promotion, other businesses in the same industry may feel compelled to follow suit to maintain their market share. This can lead to a race to the bottom, with businesses continually slashing prices to outdo each other, ultimately eroding profit margins for all involved. Finally, if not executed properly, sales promotions can damage a brand’s image. Offering excessive discounts or promotions too frequently can cheapen the brand’s perception in the eyes of consumers. This can make it challenging to restore the brand’s value proposition and premium pricing once the promotion ends. To mitigate these drawbacks, businesses should carefully consider the objectives, target audience, and potential impact of sales promotions before implementation. Balancing the benefits and risks, setting clear goals, and continuously monitoring and evaluating the results are crucial to ensuring the success of sales promotions while minimising any negative consequences. 10 types of sales promotions There are many different types of sales promotions that businesses can use to increase sales. Some of the most common include: Price discounts: Price discounts are one of the most common types of sales promotions. They involve offering a product or service at a reduced price for a limited time. Price discounts can be effective in generating leads, increasing brand awareness, and clearing out old stock. Loyalty programs: Loyalty programs are another popular type of sales promotion. They involve rewarding customers for their repeat business. Loyalty programs can help to build customer loyalty and repeat business, and they can also be used to collect valuable customer data. Free samples: Free samples are a great way to introduce new products or services to potential customers. They can also be used to generate leads and build brand awareness. Buy-one-get-one (BOGO) offers: BOGO offers are a type of sales promotion that involves offering two products or services for the price of one. They can be effective in generating leads, increasing brand awareness, and clearing out old stock. Rebates: Rebates are a type of sales promotion that involves offering a refund to customers who purchase a product or service. Rebates can be effective in generating leads, increasing brand awareness, and clearing out old stock. Contests: Contests are a fun and engaging way to generate leads, increase brand awareness, and build customer loyalty. Contests can be held online, in-store, or through social media. Referral programs: Referral programs are a type of sales promotion that involves rewarding customers for referring new customers to a business. Referral programs can be effective in generating leads and building customer loyalty. Flash sales: Flash sales are a type of sales promotion that involves offering a product or service at a deep discount for a very limited time. Flash sales can be effective in generating leads, increasing brand awareness, and clearing out old stock. Social media promotions: Social media promotions are a type of sales promotion that involves using social media platforms to promote a product or service. Social media promotions can be effective in generating leads, increasing brand awareness, and building customer loyalty. Email marketing promotions: Email marketing promotions are a type of sales promotion that involves using email to promote a product or service. Email marketing promotions can be effective in generating leads, increasing brand awareness, and building customer loyalty. How to prepare your sales force for a sales promotion To ensure the success of a sales promotion, it is crucial to adequately prepare the sales force. This involves setting clear and achievable objectives for the promotion. These objectives should be specific, measurable, achievable, relevant, and time-bound. For instance, a sales promotion objective could be to increase sales of a particular product by 15% within a two-week period. Providing comprehensive training is also essential to equip the sales team with the knowledge and skills necessary to execute the sales promotion effectively. This training should cover product knowledge, sales techniques, and communication skills. Role-playing exercises and simulations can be incorporated into the training to enhance the sales team’s preparedness. Furthermore, it is important to ensure that the sales team has the necessary resources to support the sales promotion. This may include marketing materials, such as brochures, flyers, and social media graphics. Additionally, the sales team should have access to customer relationship management (CRM) systems and other relevant technology to facilitate their tasks. Motivating the sales team is crucial to driving their performance during a sales promotion. This can be achieved through various incentives and rewards, such as commissions, bonuses, and non-monetary recognition. Setting up friendly competitions among the sales team can also foster a sense of healthy competition and motivation. By following these steps and ensuring that the sales force is well-prepared, businesses can increase the likelihood of a successful sales promotion. A well-prepared sales team is more likely to effectively communicate the value of the promotion to customers, drive sales, and achieve the desired objectives. Where to hold your sales promotion When choosing a location for your sales promotion, there are several key factors to consider to ensure its success. The first is the location of your target market. Your sales promotion should be held in a place that is easily accessible to your target audience. If your target market is local, consider holding the promotion in a central location within your community. If your target market is broader, you may want to consider holding the promotion in a larger city or region. The size of your sales promotion is also an important factor to consider when choosing a location. If you are expecting a large number of attendees, you will need to find a location that can accommodate the crowd. This could include a convention centre, a large retail store, or an outdoor space. If you are expecting a smaller number of attendees, you may be able to get by with a smaller location, such as a conference room or a restaurant. The cost of the location is another important factor to consider. Some locations may be more expensive than others, so it is important to set a budget before you start your search. Be sure to factor in the cost of renting the space, as well as any additional costs, such as parking, catering, and security. The accessibility of the location is also important. Make sure that the location is easy to get to, both by car and public transportation. If possible, choose a location that is close to major highways or public transportation hubs. Finally, consider the atmosphere of the location. The atmosphere should be conducive to the type of sales promotion you are holding. For example, if you are holding a product launch, you may want to choose a location that is modern and stylish. If you are holding a customer appreciation event, you may want to choose a location that is more relaxed and informal. How to make sales promotion effective To make sales promotion effective, it is crucial to follow a strategic approach. Here are some key steps to ensure the success of your sales promotion: 1. Define Your Target Audience: Clearly identify your target audience and tailor the sales promotion specifically to their needs, preferences, and buying behaviour. Understand their pain points, interests, and motivations to create a promotion that resonates with them. By targeting the right audience, you increase the chances of your sales promotion being successful. 2. Set Clear and Achievable Goals: Define specific, measurable, achievable, relevant, and time-bound (SMART) goals for your sales promotion. Determine what you aim to achieve, whether it’s increasing brand awareness, generating leads, boosting sales, or building customer loyalty. Having clear goals helps you measure the success of your promotion and make necessary adjustments. 3. Choose the Right Sales Promotion Type: Select the most appropriate sales promotion type based on your product or service, target audience, and business objectives. There are various options available, such as discounts, loyalty programs, free samples, BOGO offers, rebates, and contests. Choose the promotion type that aligns best with your goals and resonates with your target market. 4. Promote Your Sales Promotion Effectively: Once you’ve chosen the right sales promotion type, effectively communicate it to your target audience. Utilise multiple channels to promote your sales promotion, including social media, email marketing, website, in-store signage, and paid advertising. Create a sense of urgency and excitement to encourage customers to take advantage of the promotion. 5. Track and Measure Results: Continuously monitor and measure the results of your sales promotion to assess its effectiveness. Use key performance indicators (KPIs) such as sales volume, website traffic, lead generation, customer engagement, and conversion rates to evaluate the success of the promotion. Analyse the data to identify what worked well and what needs improvement for future promotions. How LIKE.TG can help with sales promotion LIKE.TG is a powerful customer relationship management (CRM) platform that can help businesses with sales promotion in various ways. It offers a range of tools and features designed to streamline and enhance sales promotion campaigns. LIKE.TG enables businesses to track and manage sales promotion campaigns effectively. With its robust reporting and analytics capabilities, businesses can gain valuable insights into the performance of their sales promotions, including metrics such as campaign reach, engagement rates, conversion rates, and revenue generated. This data-driven approach allows businesses to make informed decisions and optimise their sales promotion strategies for better results. LIKE.TG also facilitates the creation of personalised sales promotions for customers. By leveraging customer data and preferences stored in the CRM, businesses can tailor their sales promotions to meet the specific needs and interests of individual customers. This personalised approach enhances customer engagement and increases the likelihood of conversions. LIKE.TG streamlines sales promotion processes through automation. The platform allows businesses to automate tasks such as sending promotional emails, generating coupons, and tracking customer interactions. This automation saves time and resources for sales teams, enabling them to focus on building relationships and closing deals. LIKE.TG enables businesses to measure the success of their sales promotions accurately. With its advanced analytics tools, businesses can track key performance indicators (KPIs) such as sales volume, revenue, customer acquisition, and customer retention. This data helps businesses evaluate the effectiveness of their sales promotions and make necessary adjustments to improve future campaigns. Additionally, LIKE.TG integrates seamlessly with other marketing and sales channels, providing a unified platform for managing sales promotions. Businesses can connect LIKE.TG with their website, social media platforms, email marketing tools, and point-of-sale systems to create a cohesive sales promotion experience for customers. This integration ensures consistency in messaging and enhances the overall customer experience. In summary, LIKE.TG offers a comprehensive suite of tools and features that empower businesses to execute successful sales promotion campaigns. By leveraging LIKE.TG, businesses can track and manage campaigns effectively, create personalised promotions, automate processes, measure success, and integrate sales promotions with other marketing and sales channels.

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.

The potential role of artificial intelligence (AI) in banking is massive. Predictive AI already supports many standard banking practices, such as chatbots managing routine inquiries or call centre agents’ dashboards. As generative AI continues to evolve, we expect lots of time-saving opportunities around rote tasks that improve the customer experience due to AI’s ability to produce natural language content, images, and coding. McKinsey estimates that banks could add $1 trillion in value annually through strategic use of AI. To take full advantage of AI’s now-and-future potential, banks must take steps to clean up their data, analyse their existing systems, and identify process challenges that could benefit from the technology. Here are four ways we expect forward-thinking banks will use AI to improve both the employee and customer experience. Data: Safeguard privacy, security, and trust with financial AI Nearly nine in 10 analytics and IT leaders are making data management a high priority in their AI strategy. Banks are laser-focused on keeping their data secure: It’s fundamental to building trust with customers. Yet nearly half of executives say they believe AI introduces security risks, while 59% of consumers say they don’t believe AI is secure. Banking regulators are concerned as well, especially when it comes to generative AI, which relies on large language models (LLM) to generate responses. “Getting your data in order is fundamental,” says Amir Madjlessi, Managing Director and Banking Industry Advisor at LIKE.TG. “You need to evaluate the quality and quantity of your data and, if necessary, upgrade data collection and management processes. Without those steps, your AI won’t be able to extract relevant and accurate insights from your systems.” Once you’ve prepped your data, deploying AI in banking requires further unique data management, with varying access rights for different functions. For example, to follow fair lending practices, banks must hide demographic information like religion or country of origin from lending officers. But that same information must be available to regulators as evidence of fair lending. Data management is even more complex when it comes to generative AI, which relies on LLMs to learn how to properly respond to prompts. Leveraging solutions that have built-in data integrity like ethical guardrails can help banks address data challenges and meet compliance rules. LIKE.TG, for example, has a zero data retention policy for LLMs — we don’t share client data with external LLMs. Sales: Discover opportunities faster AI can act like a personal assistant, helping relationship managers improve their lead and opportunity scoring across all kinds of services and products — from checking bundles to secured loans. AI improves forecasting by predicting likely performance outcomes for different business lines, whether investment, commercial, or retail banking. In a single dashboard, predictive AI can surface relevant insights to deepen existing relationships or capture new clients for the bank. Generative AI can integrate data from third parties as well as internal sources to make suggestions in the flow of work, which increases the accuracy and relevance of those recommendations. With the power of both predictive and generative AI, the relationship manager can understand the best channel to reach the client, with a relevant and compelling offer. These functions help reduce the time relationship managers require to fully understand customer needs across the bank while improving their experience. Marketing: Scale next-level personalization Creating marketing segments and subsegments used to take weeks, and results could be lacklustre and generic. Generative AI is changing that, enabling marketers to create segments within the client database using natural language prompts — and the results are available in just seconds. These tools help marketers quickly build the most relevant offers or promotions, then test and learn from each, to further refine segmentation. For example, marketers using Einstein Copilot can target customers with low savings coverage by creating an offer recommending products or services that improve financial security. The marketers can then use generative AI-powered, prebuilt email templates to share that offer with the targeted customer. Over time, the messaging gets refined as the AI engine learns how customers respond to the content. The net result: Offers become super-personalised and conversion rates improve. One bank testing Einstein Copilot has seen engagement jump three to four times. The reason? The messaging is rooted in real-time customer behavior and actions, making the recommendations connected and authentic. Service: Improve agent training and customer satisfaction Turnover among contact centre agents is an industry-wide problem. Continuously training and onboarding an endless queue of new employees is expensive and ineffective. Using AI to improve the training experience and the day-to-day workflow enables agents to onboard faster, which can contribute to better retention rates. It also makes the service experience more pleasant for the customer. Generative AI can help surface the precise information contact agents need to quickly resolve issues, by populating content for known answers based on the actual language the customer uses to describe a problem. This empowers agents to make smart decisions, and that’s important in cases that require judgment calls — like whether it’s OK to reverse a charge for an unhappy customer. Plus, AI provides smarter tools for spotting fraud and verifying identity, which helps agents understand their next best actions. LIKE.TG, for example, now has an out-of-the-box, know-your-customer (KYC) protocol for identity verification and credit scoring. PenFed Credit Union plans on adding Einstein to internal (and eventually customer-facing) processes with generative AI. Einstein will act as a virtual assistant, suggesting chat and email responses service agents can use to answer questions faster and reduce queues. The assistant will propose responses to a chat or member question, beginning with PenFed’s internal employee support line before it expands to its members. AI in banking is just getting started AI in banking has the potential to help banks offer customers more while streamlining costs and effort behind the scenes. In the back office, AI has the potential to shave an estimated 6%–10% off operating budgets spent on compliance by making customer identification, verification, and risk screening more efficient. And, when it comes to clients, AI can help your commercial bankers or wealth managers turn chats into actions — like calendar invitations, automated emails that summarise conversations, and even suggestions for new engagements. To take advantage of that potential, you need to be laying the groundwork for success now. That means determining your goals for your institution and then getting your data ready for all that AI can do for you in the world of banking.

If you asked any customer service professional to describe how the last few years have been, they’d probably say “intense.” With budgets in flux and customers expecting more, service teams are constantly figuring out how to answer an important question: how do you actually do more with less? The answer is AI in customer service.Since the pandemic, customer service has been a rollercoaster ride. Customer expectations are higher than ever — 72% of consumers say they will remain loyal to companies that provide faster service. And 78% of service agents say it’s difficult to balance speed and quality, up from 63% since 2020. All of these pressures have led to a turnover rate of 19% in service organisations.While predictive AI is not new to customer service, generative AI has stepped into the spotlight just a year ago. With the powerful potential of this new technology, business leaders need a generative AI strategy, while remaining mindful of budgets. And service professionals and customers alike are curious how AI-powered customer service will impact their experience. Let’s dive into what AI does, its benefits, and how you can get started.What is AI in customer service?There are many different ways you can use AI in customer service. For example, you can embed AI-powered chatbots across channels to instantly streamline the customer service experience. Beyond answering common questions, these chatbots can greet your customers, serve up knowledge base articles, guide them through common business processes, can send out a field technician for field requests, and can route more complex questions to the right person.Imagine this from the customer perspective: you want to return a pair of shoes and you need some help. You start an online chat with an agent, but then wait 30 minutes for a response.With customer service AI, you get a personalised response in seconds. Think of it like a virtual buddy who’s not only knowledgeable, but also understands your exact needs and preferences. All you have to do is tell it what you need help with, and it will take care of the rest. No need to find your tracking number, provide your email, or explain the details of your purchase, it already has all that information and knows exactly what to do.So many organizations are already using AI for customer service. In fact, the share of service decision makers who report using AI has increased by 88% since 2020 — up to 45% from 24%.What are the benefits of AI in customer service?Let’s look at six ways AI in customer service can help your team, especially if you’re interested in getting started with generative AI:Higher productivity: An AI tool like Einstein Copilot can empower service teams to get work done faster — for example, AI can act as an assistant built directly in an agent’s flow of work. In fact, recent research shows that 84% of IT leaders believe AI will help their organisation better serve customers. Case in point: AI-based conversational assistants can increase productivity by 14% for support agents.Better efficiency: Manual processes can be a heavy lift for service agents. This includes tasks like swivelling back and forth between systems and screens to view customer history, searching for knowledge articles, routing field workers to service locations, and manually typing responses — all of which tend to be error-prone when done by a human. AI in customer service can give customer service workers intelligent recommendations across knowledge bases, conversational insights, and customer data. Our recent research found that 63% of service professionals say AI will help them serve their customers faster.A more personalised service interaction: For AI to be useful, it needs to understand your customer, which means it needs access to your company’s data. When a customer initiates a conversation with a chatbot, AI can populate important information — such as the customer’s name, location, account type, and preferred language in real time. If the request requires a field service technician, AI can send all of the important information to the field worker so they can provide personalised service the moment they walk in the door.Optimised operations: AI in customer service makes customer service operations smoother and more efficient. You can use AI to analyse customer calls, emails, and chatbot conversations to determine the signs that a customer is likely to escalate an issue, the time it will take to resolve an issue, and more. These insights help find new ways to improve the customer experience. For example, if customers often ask for an agent when they want to return a product, a chatbot can proactively share a knowledge base article to minimise escalation.AI can also analyse your company’s case history and identify the top reasons your customers contact customer service. If a knowledge article doesn’t exist to address one of these reasons, you can use generative AI to draft a knowledge article or update an existing one. Once your team approves the article, it then helps agents to provide quick and exceptional support and can be used to deflect cases in a self-service portal or with a chatbot.Less burnout and improved morale: AI allows agents to eliminate repetitive, time-consuming work and focus on situations that require creative problem solving, social intelligence, and complex critical thinking — activities that will move the needle on overall customer experience. It’s not a surprise that 79% of IT leaders say generative AI will help reduce team workload and thereby reduce burnout.A proactive service experience: AI can draw info from your customers’ contracts, warranties, purchase history, and marketing data to surface the next best actions for agents to take with your customers — even after the service engagement is over. For instance, AI can let customers know that it’s almost time to renew their subscription, remind them when it’s time to book a maintenance appointment, or that a product upgrade or discount is available. And taking that to the next level, generative AI can even summarise customer conversations and produce knowledge base articles for future reference.8 examples of AI in customer serviceWhether you’re in the contact centre or in the field, AI in customer service can transform the customer experience. Here are a few examples:1. Content Generation: Generative AI can analyse customer conversations, extract relevant details, and generate human-like replies to customer questions, improving response times and overall customer satisfaction. This is especially true when the AI pulls from CRM data and knowledge.2. Chatbots: AI-powered chatbots can handle basic customer inquiries, provide instant responses, and assist with tasks such as order tracking, product recommendations, and troubleshooting. They are available 24/7, reducing response times and improving customer service accessibility.3. Natural Language Processing (NLP): NLP is a technology that enables AI systems to understand and interpret human language. It helps in analysing customer sentiment, identifying customer needs, and providing relevant responses. NLP can also facilitate unstructured search — which allows systems to understand and respond to more flexible and conversational queries (versus a structured keyword search). This capability enhances the effectiveness of chatbots, voice assistants, and sentiment analysis tools. This helps businesses provide a more intuitive and personalised customer experience.4. Sentiment Analysis: AI-powered sentiment analysis tools monitor and analyse customer feedback, reviews, and social media interactions to gauge customer sentiment. This helps companies identify areas of improvement, respond to customer concerns, and provide personalised experiences based on customer preferences.5. Recommendation Systems: AI-driven recommendation systems analyse customer behaviour, purchase history, and preferences to provide personalised product or content recommendations. By understanding individual customer preferences, companies can enhance cross-selling and upselling opportunities.6. Predictive Analytics: AI-based predictive analytics uses customer data to anticipate customer needs, behaviour patterns, and potential issues. This helps companies proactively address customer concerns, optimise resource allocation, and personalise customer interactions.7. Self-Service Solutions: AI-powered self-service solutions, such as knowledge bases or FAQs, leverage natural language processing to understand customer queries and provide relevant information or troubleshooting steps. This allows customers and agents to find answers quickly without requiring human assistance.8. Intelligent Routing: AI-based intelligent routing systems analyse incoming customer inquiries and route them to the service representative or department with the most relevant experience or knowledge. This ensures that customers are connected to the right person who can address their needs efficiently.How to use generative AI to improve customer serviceHere are a few ways that AI can help organisations provide even better service to their customers:Increase productivity by acting as a trusted assistant: With a generative AI tool like Einstein Copilot, agents can quickly generate personalised replies to service inquiries. And the generated responses aren’t one-size-fits all: AI can create trusted, natural language responses based on relevant customer data, knowledge articles, or trusted third-party data sources on any channel.Create work summaries and mobile work briefings: Customer service AI can drive agent productivity by automating the time-consuming but crucial task of writing wrap-up summaries based on case data and history. This is especially helpful in the field. You can summarise the most relevant data to start the job — saving your frontline workers time.Preserve and share knowledge across your business: You can connect a generative AI tool to your service console and have it create the first draft of your knowledge base article based on conversation details and CRM data for your experienced agents to review. This will save you time and help you get your articles out faster. An extra bonus: you can also use these knowledge base articles to help customers find their own answers to questions in a self-service portal.Search for answers: As your agents or customers are looking for answers to a question, AI in customer service can surface a generated answer from your knowledge base, directly into the search page — saving everyone time.3 things to consider when implementing AI in customer serviceDespite the benefits of AI in customer service, there’s still a ways to go in terms of adoption. According to recent research, less than half (45%) of service decision-makers told us they’re using AI. So what’s holding organisations back?1. Impact on the workforce: Since AI, especially generative AI, is a new field, service leaders are struggling with a skill gap. For example, 66% of leaders believe that their team doesn’t have the skills needed to handle AI. And similarly, service professionals are concerned that AI could take over their jobs, which can make them apprehensive about embracing the technology. As you bring AI into your service organisation, communicate how AI will help your teams get more done and that their human-skills are still very much needed to provide a great experience for your customers.2. Trust and reliability issues: AI technology, although rapidly advancing, is not perfect. For one, most learning language models are trained on data that’s almost two years old. Similarly, there may be concerns about the accuracy of AI systems in understanding and resolving complex customer queries or handling sensitive information. Similarly, concerns around privacy and trust should be taken seriously — and must be managed carefully to keep your business and customer data secure. When the data for AI is grounded in your trusted CRM data and knowledge base, you can solve this challenge.3. Investment and implementation: Depending on whether or not you decide to develop your own AI or bring in customer service software that includes AI, it may require significant investment in technology infrastructure and training. Small businesses or organisations with limited resources may find it difficult to fund AI implementations or lack the technical expertise to deploy and maintain such systems.The future of AI in customer serviceAs AI in customer service rapidly evolves, more use cases will continue to gain traction. For example, generative AI will move from the contact centre into the field. This technology will ensure frontline field service teams have the right customer, asset, and service history data for the job at hand. Through AI in customer service, field service teams will offload more of the mundane work — through automated work summaries, knowledge articles, and more.How to get started with AI in customer serviceAI in customer service doesn’t have to be difficult to understand — or implement. The first step is learning more about what it can do for your business.Begin by learning more about how generative AI can personalise every customer experience, boost agent efficiency, and much more. Then check out how you can make the most of AI in customer service.Then you can start small. For example, deploy an AI assistant using a set of standard actions (like find, summarise and update records or answer questions using knowledge articles inside LIKE.TG) that pull from data that already exists in LIKE.TG.You can then extend Copilot to fit your business needs with Copilot Studio. Here, you can build and deploy custom actions using existing flows and apex code. Actions can be customised using technology that you already have with LIKE.TG.

Artificial intelligence (AI) news is everywhere! Whether you’re baffled by AI or becoming increasingly knowledgeable each day, one thing is for sure: AI is the future of work, and we’re here to help you learn AI skills on Trailhead, LIKE.TG’s free online learning platform. As you hear about how new advancements in AI will enhance your life, naturally, you might have fears about what the future holds or even whether you might lose your job to AI. However, the outlook is much more optimistic. Successful AI means enhancing — not replacing — the human workforce. IDC predicts the LIKE.TG economy, powered by AI, will generate a net gain of $2.02 trillion in worldwide business revenues and 11.6 million jobs worldwide between 2022 and 2028. AI is the future of workLearn AI skills on TrailheadMachine Learning and AI FundamentalsGenerative Artificial IntelligenceEthical and Responsible Use of AIData ManagementCritical Thinking and Problem-SolvingDiscover generative AI innovation at LIKE.TGBecome a LIKE.TG Certified AI AssociateBe a Trailblazer with AI Skills Quest Trailblazers who commit now to learning the skills needed to work collaboratively with machines will weather the coming AI revolution across markets and industries. They will also be more likely to realise the massive opportunities AI will bring. AI is the future of work There’s so much potential for using AI in the workplace, and 60% of global workers reported excitement about the prospect of using Generative AI for their jobs. Can you imagine how productive you could be with AI assisting you with menial tasks? Executives surveyed estimated that 40% of workers will have to reskill in the next three years due to AI. And 62% of workers say they don’t yet have the skills to effectively and safely use AI. For many, the challenge is determining which tools and skills to focus on. If it hasn’t become clear yet, AI is not just for developers or data scientists. Utilizing today’s AI technology, salespeople can write stronger prospecting emails, service reps can solve issues with fast-track case swarming, and marketers can create increasingly personalised journeys for their customers and prospects. AI isn’t for someone else. If you’re in business, AI is for you. Learn AI skills on Trailhead As more companies recognise the value of AI, they are scrambling to take advantage of all it has to offer. To realise ‌gains in efficiency, automation, and increased personalisation, they need people to help implement AI-based systems. This technology is so new that there aren’t many existing experts. We’re here to help you skill up and position yourself as the AI hero your company needs. Now is the time to skill up on AI, but with so many complex pieces and a finite amount of time to spend learning, where should you focus your efforts? We’ve identified the five areas of AI expertise that employers are looking for. Here’s where to focus if you’re looking for a new job, working toward a promotion, or focused on being the absolute best you can be at your current job. Machine Learning and AI Fundamentals Machine learning — designing and using intelligent machines to mimic human-like cognitive functions — is the foundation of AI. Start your learning by learning what deep learning and natural language processing are. Content we recommend: Artificial Intelligence Fundamentals Artificial Intelligence for Business Natural Language Processing Basics Large Language Models Model Fine-Tuning Machine Learning Predictions: Quick Look Generative Artificial Intelligence Generative Artificial Intelligence focuses on machines generating content, like text or images, based on existing data. This is the most recent AI advancement and the buzzy topic in 2023. It’s what allows DALL-E to make an image or LIKE.TG to write a sales email based on prompts. You’ll want to skill up on what GPT and Generative Adversarial Network (GAN) are and dedicate a good amount of time to prompts and prompt engineering. Good prompts will distinguish successful AI practitioners from casual users. Content we recommend: Generative AI Basics Generative AI for Organisations Prompt Fundamentals Prompt Builder: Quick Look Generative AI for Images Prompt Builder Basics Ethical and Responsible Use of AI Employers are increasingly seeking professionals who can develop AI systems responsibly and ethically. Skill up on the ethical implications of AI, including bias mitigation, fairness, transparency, and accountability. Content we recommend: Responsible Creation of Artificial Intelligence Ethical Data Use Best Practices: Quick Look Artificial Intelligence and Cybersecurity The Einstein Trust Layer Data Management Data management isn’t new, but it has never been more important. AI does all its work by analysing your data, so the data needs to be complete and accurate. If clean data is something your organisation could improve upon, now is the time to invest here. It may be the most important thing your company can do to prepare for using AI. Study up on managing an organisation’s data through data governance, architecture, integration, and quality. Slightly more advanced, though still extremely important, are data mapping and data migration. Content we recommend: Data Quality Data Literacy Basics LIKE.TG Data Cloud: Quick Look BYOL Data Shares in Data Cloud: Quick Look Improve Data Quality for Your Sales and Support Teams Data Management Critical Thinking and Problem-Solving AI is excellent at answering questions and creating what we ask of it, but it still requires someone to ask the right question. Finding just the right prompt requires thinking critically and creatively. Practice innovation, troubleshooting, and analytical skills to excel in this skill. Content we recommend: Critical Thinking and Decision Making with Data and AI Innovation Basics Best Practices for Troubleshooting Change Management for AI Implementation No matter which topics you spend your time on, learning about AI will be time well spent. We’re at an inflection point where nearly every organisation knows they want to use AI, but few have people who understand what’s behind the scenes. By learning more, you’re making yourself even more of a unique asset to your company, and that’s always a smart career move! Discover generative AI innovation at LIKE.TG In addition to preparing yourself and your org for AI solutions, you should also understand what technology is available to power your company. LIKE.TG is bringing trusted generative AI technology to its apps, platforms, and workflows. Discover how generative AI and GPT are transforming the future of business in these quick bite-sized units called Trailhead Quick Look modules: Einstein Generative AI: Quick Look LIKE.TG Data Cloud: Quick Look Sales AI: Quick Look Service AI: Quick Look Marketing AI: Quick Look Commerce AI: Quick Look Tableau AI: Quick Look Slack AI: Quick Look Become a LIKE.TG Certified AI Associate As your AI knowledge base grows, be sure to market your skills in this highly sought-after area. We recently launched the new LIKE.TG AI Associate Certification to help you validate your foundational AI skills. This certification is designed for individuals from all backgrounds, including business leaders and professionals who may or may not have prior knowledge of AI. This certification will validate foundational skills in the ethical and responsible handling of data as they apply to AI in CRM. Be a Trailblazer with AI Skills Quest Trailhead is all about making learning fun, so let’s crank up the fun-meter another notch! Join the Be a Trailblazer with AI Skills Quest to learn AI fundamentals, become an AI whiz, and be entered to win* a voucher for the LIKE.TG AI Associate Certification exam And be sure to spread the word with your friends and colleagues—everyone can learn AI skills on Trailhead.

Generative AI is changing … well, everything. And it’s causing commerce leaders to ask the hard questions as they plan for 2024: With a fixed budget, where should we invest? How do we drive loyalty without driving up costs? If we implement AI, what resources will we need and how do we make sure the technology is powered by secure data? To succeed in the future of commerce and adapt quickly to all the changes, it’s critical to be strategic and methodical. Here’s what to expect in the world of ecommerce over the next few years — and how you can stay ahead. Customer trust will take center stage Today, 68% of customers say advances in AI make it more important for companies to be trustworthy. Customers want to know that their data is used responsibly, their privacy is respected, and that businesses use AI ethically. As AI becomes more advanced and widely adopted, trust will be paramount. This means your company (and those you partner with) should have ethical guardrails in place to address how data is collected and how AI for commerce is implemented. AI can personalise prices, offers, and products in real time. It can help you automate tedious manual tasks and save teams hours per day. But this all requires a thoughtful approach to mitigate risk and keep data safe. Always get customer consent to collect and use data, and ask your technology partners how they avoid AI pitfalls like hallucinations, inaccuracies, biases, and toxicity. The future of commerce isn’t just about leveraging AI to move fast and drive revenue; it’s about building trust and customer loyalty.How you can stay ahead: Most customers (71%) are more likely to trust a company with their personal data if its uses were clearly explained. Build trust by creating transparent guidelines and sharing them with your customers. Businesses will make moves to harmonise data The average business uses over 1,000 different apps to run their organisation — that’s a lot of data from disparate sources. Before you can use all that data to create truly connected, personalised experiences, you need to harmonise it. Data harmonisation is key if you want to uncover insights fast and implement AI in a meaningful way. The first step to harmonisation: a customer data platform (CDP). This powerful tool unifies your data, creates a singular view of each customer, and opens up a new realm of possibilities for your business. That’s why 73% of business leaders say a CDP will be critical to their customer experience efforts. Once you harmonise data from across your organisation, you can apply AI (including generative AI), automation, and machine learning to help you market, serve, and sell to customers more efficiently. If you want to take advantage of all the new AI capabilities in the future of commerce, data harmonisation should be a top priority.How you can stay ahead: Make sure your data is clean. Remove duplicates, outliers, errors, and other things that can negatively affect how you make decisions. Personalisation will get better, easier, and faster It’s no surprise: Customers expect personalised experience on every channel and at every touchpoint. However, more than half (56%) still say they’re treated like a number. That’s a huge opportunity for improvement. Fortunately, generative AI and other new solutions make it easier to create hyperpersonalised experiences at scale — no matter where or how your customers shop. As AI trains on large, rich datasets and continuously learns more over time, businesses will be able to create increasingly impactful personalised experiences. And as customer behaviours change, new commerce tools for sales and service teams will help businesses adapt by offering new ways to shop and pay. Here’s what personalisation and user experience will look like in the future of commerce: Dynamic product descriptions: Imagine the lift in your conversion rate if you could tailor your product descriptions to each customer. Now, it’s possible. In an instant, generative AI can use behavioural, demographic, and attitudinal data to whip up personalised product descriptions that speak to each shopper’s specific needs and preferences. Metatags are also instantly updated for each product detail page. AI can also analyse return reason codes, product reviews, and comments to create more accurate, helpful descriptions and reduce returns. Hyperpersonalised promotions: With generative AI, personalisation is no longer reactive — it’s predictive. Based on ecommerce data like order and search history, you can anticipate customers’ needs, generate content, and tailor promotions to meet the moment. Transactions on any touchpoint: Personalisation also lets customers shop how and where they prefer. Today, both consumers and B2B buyers want to be able to make purchases outside of a digital storefront. More and more, they’re buying on social media, through messaging apps, with QR codes, and in live-stream videos. To give your shoppers this freedom, you need the right tools. With embedded commerce for sales and service teams, any agent can send Pay Now links across any touchpoint. How you can stay ahead: Create a segment of your highest-value customers and focus on making their experience shine. Customer acquisition can be costly, and prioritising loyal customers can help you drive more revenue, fast. Commerce teams will skill up for AI Contrary to many fears, AI isn’t eliminating jobs — it’s making people more productive. When you train AI on secure customer data from across your business, your merchandisers, marketers, and ecommerce teams gain a trusted, whip-smart advisor. Consider a merchandiser tasked with increasing average order value (AOV). In the past, she’d spend days (or even weeks) tracking down behavioural data for specific customer segments, details about which items are often bought together, and the success of past promotional strategies. Now? AI can help her quickly reach her goals. She can use generative AI to build a plan, receive step-by-step guidance, and track progress with data-powered insights. This turns weeks of work into a few simple clicks. More than half of retailers already use generative AI to boost commerce productivity. Creative teams use it to produce assets for ads, emails, social media, and websites. In-store associates use it to generate product recommendations. And technical teams use it to create conversational digital shopping assistants that help customers find the right product or service. As teams are asked to do more with less, the future of commerce will be a rush to automate growth and implement AI in a way that makes every employee’s job more efficient and effortless.How you can stay ahead: Before you implement new AI tools, clearly define the business value they will bring, create a detailed plan for training and change management, and determine how you’ll measure success. Are you ready for the future of commerce? The landscape is changing fast and competition is heating up, but companies with the right tools and strategies will find success. As you plan for 2024, focus on the areas of your business that will increase customer trust, boost productivity and revenue, and garner customer satisfaction. First, make sure your data is harmonised and complete. Then, prioritise productivity and personalisation to boost revenue and loyalty.

With over 8.5 billion searches performed on Google globally each and every day, your pool of potential customers is massive. It’s no surprise, then, that you need to make sure your content ranks high in Google and reaches the people most likely to take an action with your brand. That’s where doing keyword research, and choosing the right SEO keyword, comes in. It’s an art and a science. As a search engine optimisation (SEO) marketing manager at LIKE.TG, I know what works, and how to get eyeballs on your content. Let’s say you’ve been tasked with writing a page around “customer service.” Since it’s a broad and often complex topic, you might think that a long-form guide would be the best type of content. But how do you know for sure? Are you certain there are enough potential customers searching for this term? Is the audience large enough to justify creating the page? Are searchers even looking for long form content on this topic? Are they using the same terms to search for content? Do you know what kind of content Google is ranking for your target term? Proper keyword research can answer these questions and help you create content that’s user-focused and SEO optimised. Follow these six steps to develop better content, and get better search results. 1. Verify search volume Start by entering your topic or keyword idea into a SEO research tool such as BrightEdge or SEMRush. These paid tools show the average monthly search volume for your keywords. When verifying keyword search volume, look for terms with an average monthly search volume of 100 searches or greater. However, keep in mind that terms with the highest monthly search volume may not be the most relevant or focused terms to target. You should research and explore all options to find the term with the highest volume and most relevant search results. 2. Research related terms Always ensure that the term you are targeting is the same your audience is using to find content. SEO keyword research tools can help you identify similar or semantically related terms to see if there is greater search volume with another keyword variant. For example, “customer service best practices” returns 590 monthly searches versus “service best practices” with only 30. Additionally, using related terms throughout the copy in addition to your target keyword can help your SEO rank by preventing keyword spamming or stuffing. Remember to write naturally, so Google does not penalise your SEO efforts by hurting your ability to rank well on the first page. Don’t feel that you need to cram the keyword into every other sentence. Google itself warns against it with this example: “We sell custom cigar humidors. Our custom cigar humidors are handmade. If you’re thinking of buying a customer cigar humidor, please contact…” You get the idea. Not only is it open to penalisation by Google —and less likely to be discovered by searchers — it’s a bad experience for the reader. 3. Explore long-tail keywords Longer, more specific keywords often indicate searchers who are closer to taking an action. The specificity of the search lets you know they have a specific need or problem. While these terms may have lower search volume than their broader counterparts, they will often lead to more qualified conversions. For example: “customer service” vs. “customer service best practices” or “what is customer service?” Additionally, some of these longer tail keywords may help land you in one of the coveted “People also ask” answer boxes in Google, especially if used in the page title or a sub-heading. Google search “People also ask” example: 4. Beyond keyword research: Identify search intent So you’ve found a high volume, relevant keyword. But do you know what types of content Google is presenting on the first page? Based on your keyword research, what types of content are searchers looking for? Do they want guidance, how-to articles, a list of nearby shops, or something else completely?To quickly check, we recommend opening an incognito browser window and searching your keyword to see what Google reveals on the first page. You’ll want to open an incognito or private browsing window so your previous searches and browser cookies don’t influence the presented search results. Based on what’s ranking, will your page topic address the same first page search intent?In the example below, you’ll see that most of the top ranking first page content around the term “customer service best practices” is in listicle format (i.e. “X Best Practices for Customer Service…”). Given these results, it’s best to target your topic in a similar way to increase your chances of ranking on page one. Search intent example: 5. Study your competition Are any of your competitors ranking on the first page? If so, what terms are they targeting? What types of content are they creating? How long is their content? What makes them successful? Identifying this will help inform the content strategy for your page, and give you an opportunity to expand on their success. 6. Don’t cannibalise yourself Always ensure that there are no existing web pages on your own site ranking for or targeted to your selected SEO keyword. Check with your internal SEO team to confirm, or if that’s not an option, perform a site search on Google by typing site:[your website domain] [search query/keyword]. This will bring up a list of pages currently on your site with the target keyword in the copy.If you find a page targeting the same term, you should determine if that page should be optimised further or removed. Before removing any pages, work with your analytics or marketing team to identify the business impact of removing a page. This could consist of traffic loss or a drop in form completes and leads. If you must remove an existing page, always use a 301 redirect to automatically send the searcher to the newly created page. These redirects pass more of the SEO page equity from the page being redirected to the new page. If you follow these tips you’ll be on your way to finding the right keywords for SEO and creating targeted, meaningful content which searchers are looking for and need. Want a deeper dive on keyword research? Check out our SEO Best Practices blog for more guidance on how to write and optimise SEO content for your site.

Here’s a customer service statistic that will stop you in your tracks: 80% of customers say the experience a company provides is as important as its products and services. The same study reveals that 88% of customers say good customer service makes them more likely to purchase again.With so many customers staking their purchasing decisions on high-quality experiences, it makes you wonder — are you doing enough to meet customer expectations? Are you using the right technologies to deliver what customers want? And is your customer service the best possible representation of your brand?Whether you’re fine-tuning your customer service strategy, looking for insights about call centre burnout, or curious about the latest technological advancements, these 36 customer service statistics offer valuable benchmarks so you can put your best foot forward.Are customer expectations changing?Oh, yes they are. Customers demand more than ever: they want better service across more channels, and they want it now.The good news is service organisations are getting better at meeting those expectations. Our research shows that 69% of agents say balancing customer service speed and quality is difficult — down from 76% in 2022.Here are a few more key insights from the latest “State of Service” report:86% of agents and 74% of mobile workers say customer expectations are higher than they used to be82% of agents and 76% of mobile workers say customers ask for more than they used to81% of agents and 73% of mobile workers say customers expect a personal touch more than they used to78% of agents and 72% of mobile workers say customers seem more rushed than they used to (back to top)How will service leaders meet customers’ demands?The short answer: by increasing budgets and headcount. Maybe that’s why decision makers expect service budgets to increase by an average of 23% over the next year.Check out these numbers:70% of service team leads, 62% of mobile workers, and 55% of agents say they can’t reach their goals without more budget80% of decision makers expect to see an increase in budget, 76% expect an increase in headcount, and 76% foresee higher case volumeIf higher budgets aren’t enough to keep pace with rising case volume, then technologies like customer service AI and automation could help bridge the gap. (back to top)Are agents and mobile workers under pressure to keep up?The data is clear: today’s customer service professionals are spread thin. In fact, 77% of agents and 74% of mobile workers report increased and more complex workloads compared to just one year ago.How does that affect morale? Our research suggests a few answers:79% of agents and 73% of mobile workers say they support more products and services than they did a year ago65% of agents and 66% of mobile workers say their cases are more complex than ever56% of agents and 57% of mobile workers say they’ve experienced burnout at work69% of service decision makers say agent attrition is a major or moderate challenge (back to top)How are high-performing companies responding to these customer service trends?You might be thinking: OK, research is fine. But what do I actually do about it? Here are five practical ways that high-performing service leaders are tackling today’s most pressing challenges:1. They’re enabling self-serviceOur research shows that 61% of customers would prefer to use self-service to resolve simple issues.When self-service is done right, it’s a win-win: your customers can resolve problems faster, and your agents can focus their time and attention on more complex issues. Just as important, data from the latest “State of Service” report shows that self-service is a major differentiator between high-performing and underperforming companies: 80% of high-performing service organisations provide a self-service solution, compared to just 56% of low performers.2. They’re unifying their dataWe found that 26% of agents say they often lack context about a customer’s situation, while 80% believe that better access to other departments’ data would improve their work.Perhaps that’s why the highest-performing service organisations are unifying their data to achieve more cohesive and compelling customer experiences. For example, many teams are connecting customer relationship management (CRM) systems and sharing accountability for metrics like customer satisfaction scores (CSAT), customer effort scores, and Net Promoter Scores (NPS).3. They’re investing in field service technologyOur research shows that 90% of decision makers at organisations with mobile workers are embracing the future of field service by investing in specialised technology to improve field service metrics and enhance mobile worker productivity. (You can find more of our research about the latest field service trends right here.)4. They’re automating processesInefficient processes and manual taskwork monopolise agents’ time and jeopardise the customer experience. That might explain why so many service organisations are turning to customer automation software to enable greater efficiency at scale, with 83% of decision makers planning to increase investments in automation over the next year.5. They’re making the most out of generative AIIf you’re like most service professionals, you might be curious how generative AI will impact your work. The preliminary results are in — and the results are already impressive: over 90% of organisations with AI report time and cost savings, and 87% of service decision makers say this technology helps them better serve customers. (back to top)Discover more customer service statisticsWhen you consider these 36 customer service statistics, the conclusion is clear: by understanding customer needs, embracing innovation, and committing to continuous improvement, high-performing service organisations are finding new ways to navigate a highly competitive landscape.Looking for even more insights into the latest customer service statistics? Take a deeper dive into our new findings by downloading the “State of Service” report — and find out what your peers are doing to prepare for the future of customer service. (back to top)Devon McGinnis contributed to this blog article.

Performance analytics is the process of collecting, analysing, and visualising data to gain insights into the performance of a business or organisation. It enables organisations to identify strengths, weaknesses, and opportunities for improvement. By leveraging performance analytics, businesses can make informed decisions and strategies to optimise their operations and achieve better outcomes. In this blog post, we will explore the concept of performance analytics, its significance, and how it works. We will also discuss various examples of how performance analytics is used across different industries, the benefits and challenges associated with its implementation, and the role of key performance indicators (KPIs) in performance analytics. Additionally, we will draw a distinction between performance analytics and performance appraisals and delve into the integration of performance analytics with LIKE.TG. What is performance analytics? Within business and organisational success, performance analytics stands as a beacon of data-driven insights. It’s the systematic process of gathering, analysing, and presenting data to gain a profound understanding of how a business, organisation, or individual is performing. This powerful tool enables the identification of trends, patterns, and areas that demand improvement. Equipped with performance analytics, businesses can meticulously assess the effectiveness of their marketing campaigns, sales strategies, and various initiatives. This empowers them to allocate resources wisely, ensuring maximum return on investment. Moreover, it allows organisations to monitor the progress of individuals toward their objectives, fostering a culture of accountability and continuous growth. Performance analytics goes beyond mere data collection; it’s about transforming raw information into actionable insights. By leveraging this data-driven approach, businesses can identify their high-performing teams and individuals, acknowledging their contributions and implementing strategies to replicate their success across the organisation. This fosters a culture of excellence, where continuous improvement becomes the driving force. Today, performance analytics are an indispensable tool for organisations seeking to stay ahead. It provides a comprehensive understanding of operational efficiency, customer satisfaction, and overall performance. Armed with this knowledge, businesses can make informed decisions, optimise processes, and achieve sustained growth. Performance analytics is not just a tool; it’s a mindset, a commitment to data-driven decision-making and a relentless pursuit of excellence. Why Performance Analytics are Important Performance analytics is a critical tool for businesses and organisations striving for success in the current market. By collecting, analysing, and visualising data on various aspects of performance, businesses can gain invaluable insights that empower them to make informed decisions, optimise operations, and achieve sustained growth. One of the primary reasons why performance analytics is so important is that it provides a clear understanding of how a business or organisation is performing. By tracking key performance indicators (KPIs) and measuring progress against set goals, businesses can identify areas of strength and weakness. This enables them to allocate resources effectively, prioritise improvement efforts, and ensure that their strategies are aligned with their overall objectives. Furthermore, performance analytics offers valuable insights that enable businesses to make data-driven decisions. Rather than relying on intuition or gut feelings, businesses can leverage data and analytics to gain a deeper understanding of customer behaviour, market trends, and operational inefficiencies. This empowers them to make informed choices that are backed by evidence, leading to improved outcomes and increased profitability. In addition to facilitating data-driven decision-making, performance analytics also plays a vital role in improving efficiency and productivity. By analysing performance data, businesses can identify bottlenecks, inefficiencies, and areas where processes can be streamlined. This allows them to optimise their operations, reduce costs, and deliver better value to customers. Moreover, performance analytics provides businesses with a competitive advantage. By continuously monitoring and analysing performance data, businesses can stay ahead of the curve and adapt quickly to changing market conditions. They can identify emerging trends, anticipate customer needs, and develop innovative strategies that differentiate them from competitors. How Performance Analytics Works Performance analytics, a powerful tool in the business world, transforms raw data into actionable insights, driving success and growth. The process begins with the careful collection of data from various sources, such as financial records, customer interactions, and operational metrics. Advanced statistical techniques and data visualisation tools are then employed to analyse this data, revealing hidden patterns, trends, and correlations. The interpretation of these findings is a critical next step, where experienced analysts and business leaders come into play. They identify key performance indicators (KPIs) and assess progress against predefined goals, pinpointing areas of excellence and opportunities for improvement. This empowers businesses to make informed decisions, driving growth and success. Performance analytics is an ongoing process, enabling continuous monitoring and refinement of strategies. Regular performance assessments guide businesses toward sustained improvement, ensuring agility and responsiveness to changing market dynamics and customer preferences. By incorporating feedback mechanisms and implementing necessary adjustments, businesses can stay ahead in a competitive landscape. Embracing performance analytics transforms data into a valuable asset. It empowers businesses to make informed decisions, optimise operations, and achieve sustained growth. Whether the goal is enhancing customer satisfaction, driving operational efficiency, or gaining a competitive edge, performance analytics is an indispensable tool in the pursuit of business excellence. In summary, performance analytics is a strategic process that leverages data to drive business success. It involves data collection, analysis, interpretation, and continuous monitoring. By transforming data into actionable insights, businesses can make informed decisions, optimise operations, and achieve sustained growth, staying ahead in a competitive market. Examples of How Performance Analytics Is Used In education, performance analytics plays a pivotal role in enhancing student outcomes. By collecting and analysing data on student performance, attendance, and engagement, educators can identify at-risk students and provide targeted interventions to support their academic success. Performance analytics also helps in evaluating the effectiveness of teaching methods, enabling educators to make data-driven adjustments to improve learning outcomes. In the healthcare industry, performance analytics is crucial for improving patient care and reducing costs. Hospitals and clinics use performance analytics to track patient outcomes, identify trends in patient care, and optimise resource allocation. By analysing data on patient readmissions, lengths of stay, and medication adherence, healthcare providers can identify areas for improvement and implement evidence-based practices to enhance patient care. Performance analytics is also a powerful tool in the sports industry. Sports teams and athletes use performance analytics to gain insights into player performance, identify strengths and weaknesses, and optimise training strategies. By analysing data on player statistics, game footage, and physiological metrics, sports teams can make informed decisions about player selection, tactics, and training programs. These examples illustrate the diverse applications of performance analytics across various industries. By leveraging data and analytics, businesses, organisations, and individuals can gain valuable insights, make informed decisions, and drive continuous improvement. Benefits of performance analytics Performance analytics stands as a game-changer, empowering organisations to unlock their full potential and thrive. By harnessing the wealth of data at their disposal, businesses can embark on a transformative journey, propelling themselves to new heights of success. One of the key benefits of performance analytics lies in its ability to pinpoint areas ripe for improvement. Through meticulous data analysis and comparison against benchmarks or industry standards, businesses gain an eagle-eyed view of their strengths and weaknesses. Armed with this knowledge, they can allocate resources judiciously, prioritising initiatives that promise the greatest impact and implementing targeted strategies to tackle specific challenges head-on. Performance analytics also serves as a guiding light, illuminating the path to setting realistic goals and objectives. By gaining a deep understanding of their current performance outlook and identifying areas for growth, businesses can establish achievable targets that align seamlessly with their overarching strategic vision. These well-defined goals serve as a compass, ensuring that efforts are channelled into the most impactful areas, maximising the chances of success. Moreover, performance analytics acts as a catalyst for enhanced productivity and efficiency. By employing data analysis, businesses can uncover hidden inefficiencies and bottlenecks that may be hindering their progress. Armed with these insights, they can streamline processes, eliminating time-consuming tasks and optimising resource allocation. The result? A dramatic boost in productivity, a significant reduction in costs, and an overall enhancement in operational performance. Within today’s business environment, performance analytics emerges as a strategic imperative. By continuously monitoring and analysing performance data, businesses gain the agility to stay ahead of the curve and adapt swiftly to the ever-shifting market. They develop the foresight to identify emerging trends, anticipate customer needs, and craft innovative strategies that set them apart from the competition. In essence, performance analytics serves as the cornerstone of data-driven decision-making, enabling businesses to navigate the complexities of the modern business world with confidence and precision. It empowers them to optimise operations, set realistic goals, and gain a decisive competitive edge. By harnessing the transformative power of data and analytics, businesses unlock the key to sustained growth, long-term success, and enduring prosperity. Challenges of performance analytics Performance analytics is a powerful tool for businesses and organisations, but there are also a number of challenges that need to be considered. This section will discuss some of the key challenges of performance analytics, including lack of data, data quality issues, complexity of data, and bias in data. One of the biggest challenges of performance analytics is the lack of available data. This can be due to a number of factors, such as the difficulty of collecting data, the cost of data storage, or the privacy concerns of individuals. Without sufficient data, it can be difficult to get an accurate picture of performance and identify areas for improvement. Another challenge of performance analytics is the issue of data quality. Data can be inaccurate, incomplete, or inconsistent, which can lead to misleading results. Ensuring the quality of data is essential for getting accurate and reliable insights from performance analytics. The complexity of data is another challenge of performance analytics. With the increasing amount of data available, it can be difficult to analyse and interpret it all. This is where data visualisation tools and advanced statistical techniques come in handy. However, using these tools effectively requires skilled analysts and data scientists who can understand the data and communicate the results effectively. Finally, bias in data is a significant challenge of performance analytics. Data can be biassed due to a number of factors, such as the way it is collected, processed, or analysed. This can lead to inaccurate or misleading results. It is important to be aware of potential biases and take steps to mitigate them. Despite these challenges, performance analytics is a powerful tool that can help businesses and organisations improve their performance. By carefully considering and addressing the challenges of performance analytics, businesses can gain valuable insights and make informed decisions to drive growth and success. Key performance indicators (KPIs) in performance analytics Key performance indicators (KPIs) are an essential component of performance analytics. KPIs are specific, measurable, achievable, relevant, and time-bound metrics that can be used to track and measure progress towards organisational goals. They can be financial or non-financial, and should be aligned with the organisation’s overall strategy. KPIs are important for several reasons. First, they provide a clear and concise way to measure progress and identify areas for improvement. By tracking KPIs over time, businesses can see what is working and what is not, and make adjustments accordingly. Second, KPIs help to align employee efforts with the organisation’s overall goals. When employees know what KPIs they are responsible for, they can focus their efforts on those areas that will have the greatest impact on the organisation’s success. Third, KPIs can be used to motivate employees. By recognising and rewarding employees who achieve their KPIs, businesses can create a culture of high performance. There are many different types of KPIs that can be used in performance analytics. Some common examples include: – **Revenue:** This is a measure of the total amount of money that a business brings in over a given period of time. – **Profit:** This is a measure of the amount of money that a business has left over after subtracting its costs from its revenue. – **Customer satisfaction:** This is a measure of how satisfied customers are with a business’s products or services. – **Employee satisfaction:** This is a measure of how satisfied employees are with their jobs and the company they work for. – **Productivity:** This is a measure of how efficiently a business uses its resources to produce goods or services. The specific KPIs that a business uses will vary depending on its industry, size, and goals. However, all businesses should have a set of KPIs in place to track their progress and identify areas for improvement. KPIs are an essential tool for performance analytics. By providing a clear and concise way to measure progress and identify areas for improvement, KPIs can help businesses improve their performance and achieve their goals. Performance Analytics or Performance Appraisals? Performance analytics and performance appraisals are both important tools for measuring and improving employee performance. However, they have different strengths and weaknesses, and are therefore best used in different situations. This section will discuss the key differences between performance analytics and performance appraisals, and help you decide which tool is right for your organisation. Performance analytics is a data-driven approach to measuring employee performance. It involves collecting and analysing data about employee activities, such as sales figures, customer satisfaction ratings, and project completion times. This data can then be used to identify trends, patterns, and areas for improvement. Performance analytics can also be used to set goals and track progress towards those goals. Performance appraisals, on the other hand, are a more subjective approach to measuring employee performance. They involve managers sitting down with employees and discussing their performance over a specific period of time. During these discussions, managers may provide feedback on the employee’s strengths and weaknesses, and set goals for the future. Performance appraisals can also be used to make decisions about pay raises and promotions. So, which tool is right for your organisation? If you’re looking for a way to measure employee performance in a data-driven way, then performance analytics is a good option. If you’re looking for a way to provide employees with feedback and set goals for the future, then performance appraisals are a good option. Of course, you can also use both performance analytics and performance appraisals to get a more complete picture of employee performance. Performance analytics with LIKE.TG Performance analytics in LIKE.TG is a powerful tool that can help businesses improve their performance by providing insights into key performance indicators (KPIs), identifying trends, and making accurate predictions. With LIKE.TG’s performance analytics tools, businesses can track and monitor KPIs in real-time, create customisable dashboards and reports, and integrate performance analytics with other business processes. LIKE.TG’s performance analytics capabilities also extend beyond traditional business data, including social media sentiment analysis and customer feedback. One of the key benefits of using LIKE.TG for performance analytics is its ability to provide a exhaustive view of business performance. By integrating data from multiple sources, such as CRM, ERP, and marketing automation systems, LIKE.TG can provide a holistic view of how different parts of the business are performing. This allows businesses to identify areas for improvement and make data-driven decisions to improve overall performance. Another advantage of using LIKE.TG for performance analytics is its flexibility and scalability. LIKE.TG’s performance analytics tools can be customised to meet the specific needs of any business, regardless of size or industry. Businesses can easily add new data sources, create custom reports and dashboards, and share insights with stakeholders throughout the organisation. Additionally, LIKE.TG’s performance analytics tools are scalable, meaning that they can grow with the business as it expands. Finally, LIKE.TG’s performance analytics tools are designed to be user-friendly and accessible to users of all skill levels. The intuitive interface makes it easy for users to create reports and dashboards, and the drag-and-drop functionality allows users to quickly and easily customise their analytics experience. Additionally, LIKE.TG provides extensive documentation and training resources to help users get the most out of its performance analytics tools. Performance analytics in LIKE.TG is a powerful tool that can help businesses improve their performance by providing insights into KPIs, identifying trends, and making accurate predictions. With its comprehensive view of business performance, flexibility, scalability, and user-friendly interface, LIKE.TG is an ideal solution for businesses looking to improve their performance analytics capabilities.

Sales data is a powerful tool that can help you understand your business, make informed decisions, and improve your sales performance. Regularly analysing sales data is crucial for gaining real-time insights into the sales cycle, driving improvement, and setting the team up for success. By doing so, you can track your progress, identify trends, and forecast future sales growth. You can also segment your customers, evaluate your marketing campaigns, and make data-driven decisions about your business. In this blog post, we will show you how to collect, analyse, and use sales data to improve your business. We will also discuss some of the key sales data metrics that you should track, and how to present your sales data in a way that is easy to understand. What is sales data? Sales data is a valuable asset for businesses of all sizes. It provides insights into customer behaviour, sales performance, and market trends. By analysing sales data, businesses can make informed decisions about product development, marketing, and sales strategies. Sales data can be collected from various sources, including point-of-sale systems, customer relationship management (CRM) software, and e-commerce platforms. Once collected, the data can be analysed using various tools and techniques, such as business intelligence (BI) software and data visualisation tools. Sales data can be used to track key performance indicators (KPIs), such as revenue, profit, customer acquisition cost, and customer lifetime value. By tracking these metrics, businesses can measure their progress and identify areas for improvement. Additionally, sales data can be used to identify trends and patterns, such as seasonal fluctuations in demand or changes in customer preferences. This information can be used to make informed decisions about product development, marketing, and sales strategies. For example, a business might use sales data to identify which products are most popular with customers, or which marketing campaigns are most effective. This information can then be used to make decisions about which products to invest in, or which marketing campaigns to continue. In summary, sales data is a valuable tool that can help businesses improve their performance. By collecting and analysing sales data, businesses can gain insights into customer behaviour, sales performance metrics, and market trends. This information can be used to make informed decisions about product development, marketing, and sales strategies. Key sales data metrics Businesses need to track a variety of sales metrics to measure their performance and make informed decisions. Some of the most important sales data metrics include: Total Revenue:This is the total amount of money that a business brings in from sales over a given period of time. It is calculated by multiplying the number of units sold by the price per unit. Total revenue is a key metric for measuring the overall success of a business and can be used to track growth over time. Profit Margin: This is the percentage of revenue that a business keeps after subtracting all costs associated with producing and selling its products or services. It is calculated by dividing the gross profit (total revenue minus the cost of goods sold) by the total revenue. Profit margin is a key metric for measuring the profitability of a business and can be used to identify areas where costs can be reduced. Customer Acquisition Cost: This is the average amount of money that a business spends to acquire a new customer. It is calculated by dividing the total marketing and sales expenses by the number of new customers acquired over a given period of time. Customer acquisition cost is a key metric for measuring the efficiency of a business’s marketing and sales efforts and can be used to identify ways to reduce costs. Customer Lifetime Value:This is the total amount of money that a business can expect to earn from a customer over their lifetime. It is calculated by multiplying the average customer lifespan by the average revenue per customer. Customer lifetime value is a key metric for measuring the profitability of a business’s customer relationships and can be used to identify ways to increase customer retention and loyalty. Average Deal Size:This metric is crucial for calculating Customer Lifetime Value (CLV) and monitoring upsell performance. It reflects the average revenue generated from each deal, helping businesses to determine pipeline velocity and provide targeted training to sales reps to maximise deal values. Average Order Value: This is the average amount of money that a customer spends on a single purchase. It is calculated by dividing the total revenue by the number of orders over a given period of time. Average order value is a key metric for measuring the effectiveness of a business’s pricing strategy and can be used to identify ways to increase sales. These are just a few of the key sales data metrics that businesses should track. By understanding these metrics, businesses can make informed decisions about their product development, marketing, and sales strategies to improve their sales teams overall performance. How to collect sales data There are several methods for collecting sales data, each with its own advantages and disadvantages. Some common methods include: Tracking website analytics:Website analytics tools, such as Google Analytics, can provide valuable insights into how customers interact with your website. This data can include information such as the number of visitors to your site, the pages they visit, and the amount of time they spend on each page. By analysing this data, you can gain insights into customer behaviour and identify areas where you can improve your website to increase sales. Sending surveys to customers:Customer surveys can provide valuable feedback about your products, services, and customer experience. By sending surveys to your customers, you can gather information about their satisfaction levels, identify areas for improvement, and collect suggestions for new products or services. Surveys can be conducted online, via email, or over the phone. Using a CRM system: A customer relationship management (CRM) system can help you track customer interactions and manage your sales pipeline. CRM systems can store customer contact information, track sales activities, and provide insights into customer behaviour. By using a CRM system, you can improve your sales efficiency and effectiveness. Monitoring social media mentions and online reviews: Social media and online reviews can provide valuable insights into customer sentiment and brand reputation. By monitoring social media mentions and online reviews, you can identify areas where you can improve your products or services and address customer concerns. You can also use social media and online reviews to generate leads and build relationships with potential customers. By collecting and analysing sales data, you can gain valuable insights into your business and make informed decisions to improve your sales performance. The importance of sales data analysis Sales data analysis is important because it can help businesses make more informed decisions, understand customer behaviour, identify their most profitable products and services, track their progress, and stay ahead of the competition. Informed Decisions With accurate and timely sales data, businesses can make more informed decisions about their product development, marketing, and sales strategies. For instance, by analysing historical sales data, businesses can identify seasonal trends, customer preferences, and market demands. This information can then be used to develop new products or services, target specific customer segments, and optimise marketing campaigns. Additionally, analysing sales per region helps in determining where products or services are selling the best, enhancing sales and marketing efforts through intelligent performance insights and actionable suggestions for improving these efforts. Understanding Customer Behaviour Sales data analysis provides valuable insights into customer behaviour, including their buying patterns, preferences, and pain points. By using sales analytics and understanding customer behaviour, businesses can develop targeted marketing campaigns, improve customer service, and create products and services that better meet customer needs. Identifying Profitable Products and Services Sales data analysis helps businesses identify their most profitable products and services. This information can then be used to allocate resources more effectively, focus on high-potential opportunities, and discontinue underperforming products or services. Tracking Progress Sales data analysis allows businesses to track their progress over time and measure the effectiveness of their sales and marketing strategies. By using predictive sales analysis and comparing current sales data to historical data, businesses can identify areas of improvement and make necessary adjustments to their strategies. Staying Ahead of the Competition In today’s competitive business environment, it is crucial for businesses to stay ahead of the competition. Sales data analysis provides businesses with the insights they need to make informed decisions, identify new opportunities, and develop strategies that give them a competitive edge. You’ve recorded your sales data — now what? Understanding the sales funnel After collecting your sales data, the next step is to analyse it to gain valuable insights into your business. By identifying trends and patterns through sales analysis, you can make informed decisions about your sales strategy and improve your overall performance. One way to analyse your sales data is to look for trends over time. This can help you identify seasonal fluctuations, changes in customer behaviour, and the impact of marketing campaigns. For example, you might see a spike in sales during the holiday season or a decrease in sales during the summer months. By understanding these trends, you can adjust your sales strategy accordingly. Another way to analyse your sales data is to segment your customers. This involves dividing your customers into different groups based on shared characteristics, such as demographics, purchase history, or location. By segmenting your customers, you can target your marketing and sales efforts more effectively and increase your chances of success. For a sales cycle for instance, if you have a group of customers who frequently purchase high-priced items, you could create a targeted marketing campaign specifically for them. Or, if you have a group of customers who live in a particular region, you could hold a local sales event. Finally, you can use your sales data to evaluate your marketing campaigns. By using sales targets and tracking the results of your marketing campaigns, you can see what is working and what is not. This information can help you fine-tune your marketing efforts and get the most out of your marketing budget. For example, if you run a paid advertising campaign, you can track the number of leads generated by the campaign and the conversion rate of those leads. This information can help you determine the effectiveness of your campaign and make adjustments as needed. By analysing your sales data, you can gain valuable insights into your business and make informed decisions to improve your sales performance. So, what are you waiting for? Start analysing your sales data today! Perfecting your sales team performance and sales process Sales data can also be used to perfect your sales process. By analysing your sales data, you can identify bottlenecks and inefficiencies in your sales process and take steps to streamline it. For example, you may find that your sales team is spending too much time on administrative tasks or that they are not following up with leads quickly enough. By identifying these inefficiencies, you can take steps to improve your sales process and increase your sales. Understanding the sales funnel is crucial for evaluating the health of your sales process and the team’s ability to move prospects through the funnel to turn them into customers. In addition to identifying bottlenecks, you can also use sales data to automate your sales process. By automating tasks such as lead generation, qualification, sales pipeline analysis and nurturing, you can free up your sales team to focus on more important tasks. This can lead to increased sales and improved customer service. Finally, you can use sales data to train your sales team and develop targeted marketing campaigns. By understanding your sales data, you can identify the needs of your customers and develop marketing campaigns that reach your ideal customers. You can also use sales data to track the performance of your sales team and provide them with feedback to help them improve their sales team performance further. By following these tips, you can use sales data to improve your sales process and increase your sales. Sales data is a valuable tool that can help you make informed decisions about your business and achieve your sales goals. How to present your sales data with dashboards You’ve collected and analysed your sales data, and now it’s time to present your findings in a way that’s easy to understand and actionable. Dashboards are a great way to do this, as they allow you to visualise your data and track your progress over time. When creating a sales data dashboard, it’s important to focus on creating a data-driven narrative. This means telling a story with your data, and highlighting the key insights that you want your audience to take away. For example, you might want to show how your sales have increased over time, or how your conversion rate has improved. To do this, you’ll need to use the right charts and visualisations. Bar charts and line graphs are a good way to show trends over time, while pie charts and scatter plots can be used to show relationships between different variables. It’s also important to consider your audience when choosing your charts and visualisations. If your audience is not familiar with data analysis, you’ll need to use simple charts and visualisations that are easy to understand. Finally, keep your dashboard simple. Don’t try to cram too much information onto one dashboard, as this will only make it difficult to read and understand. Instead, focus on presenting the most important information in a clear and concise way. By following these tips, you can create sales reports and data dashboards that are informative, actionable, and easy to understand. This will help you make better decisions about your business and improve your sales performance. Sales data analysis with LIKE.TG LIKE.TG is a powerful customer relationship management (CRM) platform that can be used to analyse your sales data and gain valuable insights into your business. With LIKE.TG, you can combine data from various sources, such as your CRM, marketing automation platform, and website analytics, to get a complete view of your sales performance. You can then use LIKE.TG’s analytics cloud to create reports and dashboards that visualise your data and make it easy to understand. One of the most powerful features of LIKE.TG for sales data analysis is Einstein Analytics. Einstein Analytics is a predictive analytics tool that uses artificial intelligence to identify trends and patterns in your data. This information can be used to forecast future sales, identify at-risk customers, and develop targeted marketing campaigns. In addition to its analytics capabilities, LIKE.TG can also be used to automate repetitive sales tasks, such as your sales reps sending follow-up emails and creating sales orders. This can free up your sales team to focus on more strategic tasks, such as building relationships with customers and closing deals. Finally, LIKE.TG can be used to centralise all of your sales data in one place, making it easier to access and to analyse sales further. This can be especially helpful for businesses that have multiple sales channels or locations. By using LIKE.TG for sales data analysis, you can gain valuable insights into your business and improve your overall sales performance.

You know you have to keep up to date with the latest technology. And if you feel like this AI revolution has come on a little fast and you or your team might be falling behind, you’re not alone. While these tools are clearly valuable in transforming everything from sales to customer service to data insights, you need to understand how they work and what they can do for you. Learn new skills and win fun prizes with Trailblazer Quests There’s no better way to learn than on Trailhead, the free online learning platform from LIKE.TG. Trailhead allows individuals, teams, and companies to skill up by learning LIKE.TG skills, along with crucial interpersonal and business skills like data literacy and emotional intelligence. We know that there is a lot to learn these days, and we want to make sure you have some fun while doing it. While learning is its own reward, there’s always room for a little extra motivation. That’s where Trailblazer Quests come in. Trailblazer Quests combine the challenge of learning new skills with the chance of winning sweet prizes. Check out these expert-curated quests Data Cloud Quest Harness the power of real-time data from any source, optimise and personalise with AI, and automate across people, processes, and systems. Complete the quest to be and be entered for a chance to win* a LIKE.TG Certification Voucher for an exam of your choice. AI Skills Quest Learn about artificial intelligence and be entered for a chance to win* a LIKE.TG AI Certification Voucher. Automation Quest Create workflows that drive efficiency and learn how to automate at any skill level with LIKE.TG Flow. Complete the trailmix and learn all things Automation to earn an exclusive Flow community badge. How to participate in these Trailblazer Quests Get started on your quest with two simple steps: Sign up for your free Trailhead account, if you don’t have one already. Complete any or all of the three quest trailmixes Data Cloud Quest AI Skills Quest Automation Quest *Official rules apply. See the Trailblazer Quests page for full details and restrictions.

In a time where consumers have as many options as they do today, sifting through the endless research can feel daunting. It’s why many of us turn to reviews and recommendations from friends, relatives, and influencers. Marketers can plug into this by rewarding customers who share their positive experiences with the world. This is called referral marketing. Think about the last decision you made about a product or service. Did you look for recommendations before purchasing? You’ve probably turned to your network at some point during a decision-making process, for both personal and business matters. We all tend to value and trust recommendations from people we know. Brands are increasingly tapping into the power of referral marketing, and customers like the rewards they get from being a brand advocate. According to our State of Connected Customer report, consumers are willing to give more of their own data if they get something out of it. One in three shoppers say they’re willing to share a brand on social media in exchange for rewards. Social media has become the first stop in product research. As we found in our Connected Shopper Report, 50% of customers today have found new brands from searching their social media for recommendations. If you’re looking for a refresher or just want some tips to improve your strategy, we’ll guide you through it all. What is referral marketing and how does it work? Referral marketing is when brands identify and engage with their top brand advocates, incentivising them to recommend the brand to their network. Both the referrer (the advocate) and the new customer get rewarded if the promotion actions happen. Referral marketing isn’t a new concept. Chances are you’ve come across referral marketing promotions for years. Have you ever received an email from your credit card company asking you to invite your friends and then you both receive extra points? Or have you bought a product that an influencer you follow on your Instagram has recommended? Referral marketing is a low-cost customer acquisition strategy because it empowers your top brand advocates to become your top sales associates. Back in the day, customers would write who referred them on a form in a brick and mortar store. Today, referrals are done with unique URLs that track engagement. Companies track the URL so you both receive a promotion on your next purchase or another reward. And how is this done? With connected data, of course. As your tech stack evolves with data and AI capabilities, make sure your referral marketing strategy is doing so as well. Here are five must-haves as you build out your marketing plans. 1. You need to connect referral marketing to your CRM data Referral marketing relies on having a connected data strategy that gives you a complete view of your customers. Customer relationship management (CRM) data is key to creating targeted referral promotions. You need to know each advocate’s history with your brand before reaching out to them. Think about it: if someone has an issue with your product and is working with your customer support with an open service ticket, that’s valuable information to consider before asking them for a brand recommendation. Connecting referral marketing with your CRM will help you deliver personalised and predictive referral programs. Plus, that connected program will bring valuable zero- and first-party data back into your CRM from customers sharing with you directly. 2. Identify the right brand advocates for your goals Your referral programs need to reach the right audience to have the best results. You don’t want to waste your efforts and money reaching out to customers who won’t spread the word. You already have the information within your platform that could help indicate who might be an advocate based on actions such as purchase history, loyalty information, marketing and sales interactions. Find opportunities to activate this data in your referral strategy. As you set up your referral programs, look for software that uses AI to surface insights and helps you make sense of your data to help you build strategic targeting parameters. This will set up your programs with the best chance for results. 3. Extend referral programs to the entire marketing lifecycle Think of your referral marketing as an entry point for a larger campaign, and ensure a connected experience for the customers you’re trying to engage. Also, make sure your website gives your advocates additional opportunities to convert their networks by creating a consistent experience across all interactions. It’s fairly simple and effective to do this with LIKE.TG technology. You can reach out to advocates on their preferred channels by connecting email journeys via Marketing Cloud and e-commerce widgets via Commerce Cloud.This will allow you to weave referral marketing efforts into your marketing journeys, helping you connect based on your customers’ unique behaviour. 4. Test, learn, and optimise based on performance Clear metrics and key performance indicators (KPIs) are vital to any referral marketing strategy, so make sure you set up your program in a way that you can evaluate quickly as you go. Use predictive data to surface insights you might not be able to make on your own and be proactive where you can be to maximise performance. There are lots of options you can tweak to find out what works for your brand. Maybe it’s the email copy, the images, or the actual promotion you are pushing. For example, if you decide to run a program dedicated to a specific location but aren’t seeing the lift you initially planned for, your participation and conversion rate metrics will help you broaden your filters for a larger reach. Or, maybe you want to see what’s actually resonating with your advocates and new customers, so you test a few different offers. Create a program that lets you quickly evaluate results and then pivot toward the one making the best impact. 5. Expand your referral marketing to a loyalty strategy End-to-end loyalty programs that have different tiering and reward structures can be overwhelming. Referral marketing is an easier way to get started. As you build out your referral program, think about short and long term goals, and plan how you can bake referral marketing into a larger loyalty strategy over time. (For example, you could offer different promotions based on loyalty status.) This unlocks opportunities for additional creativity, all anchored back to what your business goals are and what motivates your customers. The cool thing about referral marketing is there is no right or wrong way to do it – look at it as an opportunity to interact and incentivise your advocates. As we enter a new era of data, AI, and engagement, marketers can make an impact by being creative and making data-driven decisions. Your customers, both old and new, will reward you for it.

Trailblazers, AI experts and thought leaders descended on Singapore for World Tour Essentials, experiencing new ways that the #1 AI CRM can deepen customer relationships and uncover growth opportunities for the future of AI. The day may be over but the learning doesn’t have to stop. Just as generative AI can provide ‘next best actions’ to your team, we’ve compiled a list of where you should go next to continue your digital transformation journey with CRM + AI + Data + Trust. Navigate to your area of interest:Unlock All of Your Trapped Data with Data CloudLIKE.TG for Financial Services: Empower Customer SuccessRevolutionise Marketing Excellence with Marketing Cloud and AIThe Future of Sales: Supercharge Selling with Trusted AIReimagine Service with Trusted AIUnlock Profitability Through Digital Transformation with Commerce CloudTransform How Your Teams Get Work Done with the Einstein 1 Platform SlackEinstein 1: The Bold New Future of Enterprise AILearn more about the Einstein 1 Platform Unlock All of Your Trapped Data with Data Cloud You’ve already discovered how Data Cloud can enhance, not replace, systems like data warehouses and data lakes. Continue exploring how Data Cloud can seamlessly integrate with your existing environment and give your team a complete view of your customers so you can improve experiences across the entire journey. It’s how Formula 1 has achieved 88% fan satisfaction, 86% first contact resolution, and 99.6% email delivery rate. LIKE.TG for Financial Services: Empower Customer Success Financial services are embracing trusted AI and automation to deliver better outcomes for all stakeholders, including clients, employees and regulators. At World Tour Essentials Singapore, Trailblazer Siam Commercial Bank shared how they are delivering personalised customer experiences that are fully compliant by embarking on their digital transformation. Now, learn more about how AI is already changing the banking industry across data, sales, marketing and service, with the potential to add $1 trillion in value annually to banks. Revolutionise Marketing Excellence with Marketing Cloud and AI You’ve seen how Marketing Cloud and AI can deliver digital-first, personalised experiences throughout the customer lifecycle, as our customer Trailblazer Direct Asia demonstrated. At this very moment, AI digital assistants are hard at work, scaling up the efficiency and effectiveness of marketers. 62% of marketers have invested in the power of AI, and Marketing Cloud makes it easier than ever to partner your marketers with their very own AI assistant. We’ve compiled nine of the most interesting ways you can embed an AI assistant in the flow of work. The Future of Sales: Supercharge Selling with Trusted AI After learning how the #1 AI CRM for sales is helping Trailblazers like SEEK give their sellers superpowers to drive efficient growth, we also want to show you another way AI is affecting the jobs of sales professionals – by opening up more time for relationship-building and customer engagement. We’ve highlighted four ways that generative AI will make work better and more productive for sellers, including by analysing the mood of prospects and offering real-time coaching to your sales team. Reimagine Service with Trusted AI AI is helping businesses including our World Tour Essentials speaker Philippine Airlines scale service, increase productivity and reduce the cost to serve. We’ve put together a comprehensive guide to the state of generative AI in service to identify ways AI can make service better for your customers and service professionals. These include increasing productivity by 14% with AI-based conversational assistants, or reducing team workload and burnout, as reported by 79% of IT leaders. Unlock Profitability Through Digital Transformation with Commerce Cloud More than half of retailers are already using AI-powered CRM to increase commerce productivity, and our Trailblazer L’Oréal took to the stage at World Tour Essentials Singapore to show how they’re using digital transformation to boost omnichannel sales, personalisation, and operational efficiency. We’ve prepared a guide to what to expect in the world of e-commerce over the next few years – and how you can prepare for the future of AI. Transform How Your Teams Get Work Done with the Einstein 1 Platform Slack You’ve seen the newest AI features that have cemented Slack as the natural conversational interface for trusted AI. Slack has sped up processes for Singapore’s super-app company Grab, who shared their Slack story at World Tour Essentials Singapore. And with Slack, the Philippines’s Cebu Pacific Air has also saved an impressive 114,000 hours annually. Now, see how Slack can empower your employees with AI to get things done faster — get started with this e-book. Einstein 1: The Bold New Future of Enterprise AI Since 2014, LIKE.TG has been the leader in AI innovation for business. We’ve deeply embedded trusted AI across our CRM apps for sales, service, marketing, commerce and more to bring predictive insights and intelligence to your entire organisation. With the newest innovations now available in Einstein 1, you can connect with your customers in a whole new way and grow productivity and your bottom line. Establishing your organisation as a leader in the future of AI starts with understanding the potential of CRM + AI + Data + Trust. We’ve compiled the following resources for business leaders to expand their knowledge of generative AI.

Traditional online marketing techniques such as paid digital advertising work, but advertising costs have left small businesses struggling to compete. An effective alternative to paid advertising is search engine optimisation (SEO), which allows your small business to stay competitive and keep costs relatively low.All it takes are the seeds of a robust strategy, a bit of hard work, and time for the fruits of your labour to become reality.If you’re looking maximise your small business SEO, you find these tips, benefits and services beneficial.What you’ll learn:What is SEO and how does it work?What is small business SEO?Five tips to do small business SEO rightThree benefits of small business SEOHow should small businesses get started with SEO?How to choose small-business SEO servicesWhat is SEO and how does it work?SEO is a technique to improve a website’s organic visibility online. The goal is to have your web property show up as close to the top of the first page of a search engine’s results as possible (such as Google). Well-executed small business SEO can increase traffic to your website without having to pay for an ad.Many components can contribute to better organic visibility. A few that are the most important include the page’s content, targeting the right keywords, and backlinks. Good SEO also hinges on some technical aspects, such as site speed and mobile optimisation.Before jumping into the details, here’s a glossary of common SEO terms:Organic search results: This is also called the Search Engine Results Page (SERP). When a search engine user types a query or search term into a search engine like Google, a list of results is generated. This list is made up of the most relevant pages to that keyword.Keyword ranking: This is your web page’s exact position in search results for a specific keyword. Most web searches result in hundreds of pages of results, and usually there are ten or more results on a page. The closer you are to ranking number one on the first page, the more visitors and in turn the more traffic your website will receive.Local search/Local SEO: This aspect of SEO is used topromote a local business online. For example, if a user types “shoe store Boston” into the search engine, the search results willlist the web properties of any shoe stores in Boston that rank well for that keyword. This is very different from just typing in “shoe store”, which would likely turn up online retailers not specific to a geography.Backlinks: These are links from other websites to yours. Backlinks can help increase your page authority and keyword ranking. But if you’re not careful, they can decrease both and hurt your website’s ranking. Check to make sure you only have backlinks from reputable sources bringing traffic to your page. Every couple of months, keep an eye out for anything that looks spammy and disavow the links to prevent them from bringing down your ranking.Technical SEO: The technical side of SEO, as opposed to the content side, ensures that search engines can crawl and index your website (meaning “read” your content and know how to rank it against similar content). Technical small business SEO focuses on backend information like your HTML code,site speed and mobile optimisation (see below), your sitemap, and website architecture.Site speed: How long does it take for your website to load? This is your site speed. Google considers this an important factor when ranking websites in search results. The search engine favours websites that load more quickly and efficiently because it improves the user experience. If your site is bogged down by heavy images or videos, for example, and not designed to load quickly, it will take a hit in search.Mobile optimisation: How your website displays on mobile devices is another important factor in website ranking. If you built your web property on a desktop and did not check to see that it scales on a variety of mobile devices, your site will take a hit in its search results.What is small business SEO?Small business SEO is the process of improving your small business’ website presence on search engines, so it is visible in queries that relate to what you offer.There is a difference between small business SEO and local SEO. Local helps businesses appear in location-based search results. While it may overlap, some small businesses need to leverage local traffic, however, small business SEO is now global, worldwide due to digital demand. If you’re an SMB that can ship your product or service anywhere, local SEO doesn’t make sense to you.SEO is important for SMBs as it helps you increase organic traffic without spending money on advertisements — something all small business has to navigate. When your website ranks higher in search, you drive more traffic, generate more engagement, make more sales, and gain more loyal customers. You see the beautiful arc here, it’s every SMBs dream.Five tips to do small business SEO rightThese tips will help you understand how to implement SEO for your small business.1. SEO is not only for GoogleAs a small and growing business, your site should look good on Google. But depending on your audience, other sites may be equally as valuable (or more so), including Amazon, Reddit, Yelp, YouTube, Instagram, and others that have their own SEO strategies. Figure out where you want to spend the majority of your efforts and start there.2. SEO strategy is effective, but not instantWhile SEO isn’t free or instant, it is effective. How long it takes for SEO towork depends on where you start. If you are in the early stages of building out your SEO strategy, expect at least six months to see results – even more if you’re building a new website. Remember that SEO is a continual process and it builds upon itself.The foundation you lay during those first months will make the process easier later. The more effort you devote to SEO, the harder it will be for your competitors to outperform you.3. Target the right keywordsPlan your online content with keywords specific to your business. Not sure which keywords to target? Use a keyword research tool such as Ahrefs, SEMRush, AnswerThePublic or BuzzSumo; there are a few that aren’t too costly. This will help the right audience find your most relevant content and website.4. Write for humans first, and search engines secondHigh-quality, engaging, and relevant content that incorporates the targeted keyword will entice people to stay on your website, read for longer, and interact with more content. If you can, consider answering popular questions relevant to your business. Showcase solutions your customers would want to see.Tempting as it may be, do not include irrelevant keywords or content that is stuffed to the brim with the same keyword. Your human readers won’t stand for it, and this content will negatively impact your search visibility. Search engines strongly take this into consideration when determining which results to display.5. Maximise local search to your advantageYour small business can find huge success targeting local searches. As the stats prove, people searching locally are potential customers waiting to be converted. According to Sagapixel data, almost half of all the searches on Google have local intent. Seventy-two percent of consumers that perform a local search visit a store within five miles of their current location.When doing local search optimisation, be sure to claim your Google Business page. This will help you show up in Google maps and in “near me” search results. For more localised results,weave your specific city or state in with your target keyword.Benefits of small business SEOAccording to BrightEdge research, organic search accounts for 53% of all online traffic and contributes to 44% of revenue share. SEO brings in more online readers through organic search – the largest digital channel.SEO improves brand awareness. Good SEO will help you to show up ahead of competitors in search results. If researching prospects come across your site, your brand will be top of mind when they are ready to make a purchase.If done correctly, SEO is highly effective – but it’s not something that happens overnight. It takes time and effort to set the foundation, but once you have it, the rewards are great. Like growing a plant, the more you nurture your SEO, the more it will grow.How should small businesses get started with SEO?The first step is to complete a technical audit and a content audit. Audits highlight areas where you are doing well and areas that need improvement. An audit is a great place to start whether you have done a little bit of SEO or none at all. Once your audit is completed, you will know the exact scope of work needed to improve your SEO.Conduct a content audit for SEOA content audit should do two things: Help uncover opportunities for new content, and highlight existing content needing attention. It should be a full list of all your web content, like blogs, combined with traffic, engagement, ranking keywords, and backlink data.Learn more about content audits here.Conduct a technical audit for SEOThe technical audit will show you areas where your website structure and backend need improvement. Highlight pages with missing or duplicative page titles or meta descriptions. You should also track page speed, broken links, or redirect chains on each page. You can even get more technical and dive into canonical tags, hreflang, or schema markup.Learn more about technical audits here.How to choose small-business SEO servicesNot sure you want to tackle this all yourself? There’s no shortage of SEO experts waiting to help small businesses with an SEO strategy. Finding the right agency or person should be as important as getting the right strategy.While an in-house SEO expert is probably not a viable option for your small business, there are other ways to get your SEO needs met. Many agencies offer a variety of packages to suit small businesses. Some may even propose a flat rate contract based on the services you want.This option will let you know the project’s exact cost and guarantee fulfillment. If you are willing to do the work but need guidance to get started, you can look into hourly SEO consultants.As with most business services, you get what you pay for when it comes to SEO. You want whomever you hire to provide you with quality recommendations. Here are some questions to ask a potential agency:What niches do you specialise in?What does the process look like, and what will you be working on month-to-month?What is your link building strategy?How do you track progress?How do you report?How often will you review and update the strategy?Do you have any case studies of similar projects?Is there a minimum term commitment?Whether you decide to tackle SEO on your own or hire an expert, it is critical to have the right SEO foundation and strategy. In the long run this can be a huge benefit to your business and your bottom line.Digital marketer and SEO professional Rosy Callejas contributed to this article.

Nine out of ten leaders know a strong data strategy is critical to AI success – so why are only a third of them integrating a unified data strategy across their company? In January 2024, LIKE.TG commissioned Forrester Consulting to find answers to these gaps and more in the rapidly developing AI landscape. The research, conducted with 773 business leaders in 14 countries, including Singapore, sheds light on global business decision-makers’ mindsets around AI-powered CRM. These trends prove that regardless of fast shifts in AI, there are certain foundational principles that companies must prioritise for growth. Before we explore these key success factors and recommendations, let’s understand the current state of AI-powered CRM in Singapore. Compared to the global average, business leaders in Singapore are generally more aware of the importance of data strategy and employee trust in AI but are less likely to have a formal data strategy or the data skills necessary for success. Gaps in basic AI understanding reveal room for growth The research reveals Singaporean organisations are embracing AI across various CRM use cases. But, it’s not all smooth sailing. The research uncovers critical gaps that could impact the success of AI adoption in CRM. Here’s a striking revelation: Despite all respondents making plans to adopt AI, only half were able to choose the correct definition for both predictive and generative AI when presented with both side by side. Predictive AI: analyses existing data to make forecasts Generative AI: creates new content based on learned patterns Considering that an AI strategy likely encompasses both types of AI models – which serve specific purposes and goals – this signals an opportunity for more comprehensive education. People need to know the specific use cases each type of AI enables, the anticipated business outcomes, and how to design a strategic plan for AI grounded in those goals. Another key finding is the significant gap in data maturity and readiness. While 96% of Singaporean leaders emphasise the importance of a robust data strategy, only 30% claim to have one implemented across their business. Bridging this gap is crucial to using AI effectively. Trust also emerges as a primary concern, with respondents citing security issues and scepticism about the output quality of generative AI. Fear of unintentionally exposing private customer data and potential damage to brand reputation looms large as barriers to purchasing generative AI. Three foundations for strong AI-powered CRM 1. Ready your data Data quality and availability is the crux of successful AI implementation. Over 62% of Singaporean survey respondents agree that improved data quality is essential – significantly higher than the 53% global average. Despite its importance, they indicated that their top challenges with their organisation’s CRM include data quality issues and a lack of data skills. On the flip side, companies with a higher degree of data maturity are not only more likely to have adopted AI already but also are more likely to use a unified CRM across their business, thus realising greater front-office productivity and impact to customer satisfaction.Our recommendations: Focus on cleaning your data, eliminating silos, and ensuring a holistic view of customer data. Take a balanced approach to data maturity aligned with your strategic goals. Knowing it’s not realistic to improve everything at once, work to understand the specific data requirements needed to deliver your AI use cases in a phased approach. Most importantly, keep data quality and availability front and centre as you build a strategy in tandem with AI. Data readiness in action: Lotus’s, a prominent retail brand with over 2500 outlets across Thailand and Malaysia, underwent a technological infrastructure transformation with LIKE.TG. Prior to this overhaul, the company grappled with fragmented and monolithic systems that affected its ability to understand customer behaviours and deliver personalised experiences, Leveraging Data Cloud for Marketing, Lotus’s successfully unified data from diverse sources, reduced its customer record volume by half, and gained a complete view on its 9 million-strong customer base. With the integration of Marketing Cloud, the brand now adeptly crafts tailored customer experiences through automated journeys. 2. Build trust in AI Building trust is a must in AI. Almost all Singaporean respondents (92%) said that trust is important – or even critical – when partnering with an AI vendor. Genuine concerns about unintentionally exposing private customer data, infringing copyright, or violating data regulatory compliance requirements raise a lot of questions. Specifically, organisations are seeking vendors who already have security protections – such as data masking (the practice of anonymising sensitive data) – baked into the tool. Another way to protect from potential risk is to choose a vendor that offers AI as part of their core CRM offering, so there are no extra hoops or complexities with trying to integrate an outside source. Our recommendations: Work with a trusted AI vendor that provides meticulous management of both AI inputs and outputs. Your data should be masked when shared with any large language models. When considering a vendor-hosted or external model, ensure that the context of inputs and prompts will not be stored and you never lose control over the use of your data. Beyond privacy and security concerns, prompts and outputs should be automatically scanned for harmful outputs. Finally, depending on the AI use case, consider keeping a human in the loop to ensure quality, accuracy, and trust. Trusted AI in actionWith trusted AI and data, LIKE.TG is increasing customer trust and improving experiences for Indonesia-based end-to-end delivery service Lion Parcel. Service Cloud helps it understand customer behaviours and drive personalisation with customer segmentation, leading to a 73% reduction in resolution times. And with Einstein 1 making it easier for customers to self-serve, 90% of WhatsApp interactions are now handled by AI, leading to a 40% improvement in cost efficiency. 3. Make space for education and upskilling As AI becomes embedded in organisations, 42% of Singaporean respondents agreed that continuous upskilling is necessary. This, paired with the general lack of understanding around AI concepts, highlights the opportunity for a thoughtful approach to AI education. Additionally, they noted that a lack of data skills is a primary challenge with the current use of their CRM systems. Our recommendations: Beyond ensuring employees have a general understanding of your AI strategy and goals, start tactically with employee training to create and refine prompts. A prompt is a detailed instruction provided to a large language model to help it generate an output. A better prompt yields a better, more relevant output from the AI model. Every employee can be a prompt engineer – this training will maximise the potential benefit of AI while helping people work more efficiently. In addition, establishing corporate policies that educate employees to evaluate AI outputs for accuracy, bias, toxicity, and potential harm is essential. Upskilling in action Internal communication can be a barrier to the successful implementation of any new systems, so when Lion Parcel embarked on its digital transformation with LIKE.TG, it also made sure to optimise internal workflows and connect teams with Slack. Customer segmenting from Service Cloud also means agents can be trained to provide specialised service for critical interactions, with AI able to handle more routine contacts. See how top leaders make the most of their AI investments by creating strong data practices, a culture of continuous learning, and unwavering trust. These insights and more can be found in the full study, so your team can create a foundation of excellence with your own AI-powered CRM.