Over the last 12 months, organisations were really scrappy, and now it’s time to lean into automation, scale, and efficiency to harden much of the innovation that has been held together by baling wire and masking tape. 2020 unraveled many of our retail trends and predictions entirely — and taught us important lessons about the resilience of retailers. Among the many eye-opening moments that happened as a direct result of the pandemic, digital shopping saw an unprecedented 50% year-over-year (YOY) increase in revenue over the holidays. And those retailers with creative pickup options – curbside, in-store, drive-through – grew more than 60% higher than those that didn’t during the last five days before Christmas. Meanwhile, shoppers turned to social media for more than just inspiration: purchases from a social channel referral skyrocketed 104%. And we’re just getting started. Given the massive disruption and changing consumer expectations due to COVID-19, retailers are looking to accelerate digital transformation. In fact, based on our research of 500 retail leaders last summer, 76% plan to increase technology spend, and 44% plan to increase their human resources. I’ve asked our LIKE.TG thought leaders to put together observations from an expectation-shattering year and their best ideas about what it all means for retail industry trends. Among the common themes: the continued rise of digital, a shift in the role of brick-and-mortar locations, the rise of loyalty, and the value of experience. Here’s what they had to say. 1. Shopping at the edge endures — and expands Anna Rosenman, Vice President Marketing, Commerce Cloud, and Experience Cloud When we launched our State of Commerce Report, we saw that 66% of high performers in retail had replaced aspects of the physical shopping experience with digital. More than 70% also experimented with live chat, video, livestreaming, and social shopping. At LIKE.TG, we call this phenomenon “shopping at the edge.” Looking ahead, with 88% of high performers reporting that they are investing even more in digital experiences, we expect to see commerce become prevalent in newer channels, such as online gaming. We will also see businesses that previously were highly reliant on in-person selling embrace digital as a means of reaching existing and new audiences. In addition, I believe that in 2021 the post-purchase digital experience — from convenient payments to embedded service and loyalty — will become priorities as brands work to keep their customers. Additionally, the data captured beyond the buy button will enhance the broader customer journey. This first-party data will help retailers better segment and personalise marketing to capture new audiences, deliver a more intelligent commerce experience, and increase the lifetime value of customers. 2. Coherent storytelling will win the social commerce game Vinod Kumar, Product Management Director, Commerce Intelligence As Anna Rosenman mentions above, the biggest takeaway from 2020 was increased universal comfort with online shopping for almost everything. Capabilities that were considered nice-to-have just a few months ago suddenly became essential for survival. “Contactless” and “curbside” come to mind. The big revelation was social commerce. While TikTok’ers were chasing their 30 seconds of fame shuffle-dancing to siren jams, all the major social “walled gardens” rolled out some form of commerce capability. My prediction is that coherence is the one key difference between winners and losers in the upcoming retail gold rush to social; the difference between fad chasers and tastemakers. Brands that deliver great products with amazing experiences on social, anchored by coherent storytelling and a narrative that’s consistent with their brand ethos, will win. Those that jump in with random acts of content, won’t. 3. Physical experiences will snap back, but digital will remain the priority Matt Marcotte, Senior Vice President, Industry Go-To-Market 2020 was a year of forced change — building new muscles, trying new channels, and replacing physical contact with digital connection. It accelerated change that was already on the horizon, but its artificial nature will result in some snapback once we are able to go back out in the world. We’re also likely to see an even greater reliance on technology to make our lives easier, more convenient, and frictionless. But physical experiences are still critical. Touch is a powerful factor in creating emotional connection — and the one sense that has been most repressed during the pandemic. Brands need to divide their store strategy into two lanes: efficiency and experiential. Efficiency is about using stores as mini-distribution sites for buy-online-pick-up-in-store (BOPIS) and curbside pickup. Make the last mile easier for customers, and connect the digital shopper with product and services. Experiential is about creating a moment that inspires, excites, and takes the customer on a multisensory journey that builds brand affinity, advocacy, and amplification. Existing stores, pop-ups, brand collaborations, and events are some areas brands can focus on to create distinctly emotional experiences. Despite this return to shopping in stores, “digitally enabled” is still the way of the world, period. On average, we spend 12 hours a day connected to technology — essentially, most of our waking hours — which means that we are constantly influenced by our computers, digital screens, and mobile devices no matter where we are. Brands need to embrace this reality and build experiences that connect all touchpoints to complement each other without competing. Imagine shopping in a store as your phone serves up information about a product you have been looking at online. You’re directed to the aisle where it’s located, making it easier for you to buy and enable your purchase. Now imagine playing Fortnite and dressing your avatar in real-world designer gear through the game – and then being able to purchase those items for yourself from those designers as you play. That type of synergy is the future, and the brands and retailers that can find ways to use technology to connect the customer experience will win. 4. Personalisation is the new black Alex Drinker, Global Leader, Retail Go-To-Market 2020 changed the retail industry forever. The massive surge in digital forced the industry to look at everything from its supply chain to its customer engagement tech stack. In almost every case, retailers found gaps in what they needed to serve this new digitally enabled consumer. This change in consumer behaviour was, and will continue to be, a catalyst for the industry to improve upon all areas of the customer journey and to force some leaders to reevaluate traditional business models. However, 2021 isn’t just going to be the year of the digital consumer. I believe it will be the year of a more informed, connected consumer who has higher expectations for personalisation, service, and the ability to transact in every channel. Seventy-nine percent of consumers say the experience a company provides is as important as its products and services. With that in mind, I expect that during 2021, brick and mortar will remain the most important channel for the majority of retailers. Conversely, for digitally native brands, the store will be a new growth channel. A little less than a third of all orders came from digital this holiday, more than double that of 2019. However, that means that two-thirds of all orders came from offline channels. I wouldn’t expect that number to change anytime soon. This means that omni-channel experiences must be personalised and seamless. When brands build a new engagement channel, they will enable that channel to do anything a customer wants. For example, through an SMS conversation, a shopper might want to receive promotional offers and transact, but also reach back out to the retailer for help. Customers may not know what omni-channel means, but their behaviour demands it from retailers. Together, these factors mean that personalisation will take on a whole new meaning. Consumers are willing to provide their personal information for a more curated experience. When we asked 10,000 consumers what made their favourite brands stand out, the top answer was catering to their unique needs. In order to meet those needs, I predict more retailers will have a well-defined artificial intelligence (AI) strategy to drive personalisation at scale. 5. The last mile will be reimagined JR Linne, Global Director, Retail Industries Solutions The last mile will get a much needed tune-up. With the constraints on last mile coming to a head during the peak holiday 2020 season, retailers have started to reimagine ways to get their goods into the hands of customers. Courier services expanding beyond food delivery mean that the reliance on traditional carriers will decrease as customer options become more diverse. I could even see retailers repurposing store headcount to a delivery mechanism themselves to ensure they own the customer experience to the very end. That was a big lesson from the 2020 holiday shopping season, by the way. Safety concerns and overloaded shippers drove consumers to retailers with curbside, drive-through, and in-store pickup options. They were rewarded with a 49% increase in digital revenue on average YOY, and 54% digital revenue growth YOY in the five days leading up to Christmas. Retailers who didn’t offer these options saw only 28% average growth on average YOY, and 34% digital revenue growth YOY in the five days leading up to Christmas. 6. Loyalty will win big this year Hilary Englert, Director, Product Marketing Customer loyalty will be redefined as the world emerges from the limitations required by COVID-19, and it will be more important than ever. Brands that have capitalised on shifting trends in 2020 need to build on those new routines and loyalty as the world makes its next transition. That means building loyalty will be top of mind in 2021. While value, convenience, and availability were the critical factors in 2020 (I go back to the toilet paper saga), they’re now table stakes. Consumers will return to looking for connectedness with a brand, what it stands for, and its purpose. The experience that a brand provides through meaningful and relevant communications creates the authenticity that shoppers will crave. Also, as categories re-emerge (e.g., formal wear for weddings and school supplies for on-campus learning), loyalty will be even more important for brands to become part of new routines and capture mindshare. Brands that remain relevant, consistent, and authentic are primed to grow. 7. Retail recovery might take longer than expected Vinay Vaswani, Retail Industry Business Development Lead, LIKE.TG EMEA The view from my perch in Europe allows me to look at these trends from a global retail perspective. I realise that it’s been a frustrating year for retail, and there is a lot of optimism on the vaccines bringing things back to normal soon. However, I believe that retailers should prepare for retail recovery to take a bit longer than expected around the world. The current retail situation is likely to continue through the first half of 2021, with more store closures and companies entering administration. We may see improvements after the summer or more realistically, in late 2021 and early 2022 as easing of lockdowns (and vaccinations) allow shoppers to come back into the stores. On the flip side, the potential for revenue growth might help to buoy the 2021 numbers. Meanwhile, digital shopping will continue to grow in 2021, almost becoming the norm. We’re already seeing a permanent shift in consumer shopping behaviour, especially in grocery. We should also expect more of: Social commerce (through livestreaming and influencers) Direct-to-consumer sales by consumer companies Innovations around augmented reality and virtual reality In terms of what that means for stores, I believe stores will continue to be very relevant – but their role will continue to change to support online shopping. The stores that do remain open will have more technology and tools to support online shopping (such as click and collect), or they will offer different in-store experiences, such as new layouts. Conversely, digital native brands will be likely to open brick-and-mortar locations. Retailers will have to adapt their stores while expanding their digital shopping capabilities at the same time. 8. Young consumers will reward uniqueness Adriana Bourgoin, Chief Customer Officer, Commerce Cloud Consumers will continue to seek uniqueness, heritage, and sustainability. Expect retailers to respond with creative collaborations, limited productions, and recycle/resell/sustainability efforts to build loyalty. 2021 will see more activism positioning, front and centre. Gen Z will solidify its position as a force for change. These digital natives brought their parents and grandparents into new shopping behaviours in 2020, and drove significant increases in digital sales for emerging categories, such as alcohol. While their true spending power may not be recognised for a few years, their outsized influence will be seen not just in retail but in any industry ripe for disruption, including higher education, banking, and travel. The lines between creators, buyers, and sellers will continue to blur. Customised sneakers have already become the norm. Influencers regularly launch products in partnership with major brands. Online marketplaces and the introduction of ecommerce on social platforms have created a digital bazaar on a global scale. In 2021, expect to see more of this, but with greater adoption by professionals, such as beauty advisors and hair stylists, with corporate sponsorship. Learn how Saleforce for Retail makes every shopper experience feel custom tailored. This post originally appeared on the U.S.-version of the LIKE.TG blog.

Digital transformation isn’t just a buzzworthy phrase — it has quickly become the reality for marketing organisations around the world. Eighty-four percent of marketers surveyed in our latest State of Marketing report said customer expectations are changing their digital strategies. As that transformation continues, they also indicated their jobs have become more important. Seventy-seven percent of marketers surveyed said they feel their work adds more value than it did a year ago. This year’s State of Marketing report, now in its seventh edition, is our largest-ever pulse check on global marketing trends, with insights from more than 8,200 respondents across 37 countries. Representative of marketing roles from the event marketer to the CMO, this survey taps into what has inspired and challenged marketers over the past year, and what they’re expecting in the times ahead. For instance, working from anywhere is here to stay. Eighty-two percent of marketers say their company is adopting new policies around remote work. Despite the harsh challenges of the past year, marketers have found innovative ways to connect with their customers — and each other. Yet 69% of marketers still say collaboration is tougher than before the pandemic. How do marketers grapple with our new reality as we emerge from one year of transformation into the next? Read on for five key takeaways from the report. 1. Collaboration is now a top priority and challenge Some of marketers’ top priorities and challenges are evergreen — innovation and real-time customer engagement, for example. It’s what’s new to the list that paints a vivid picture of what marketers are excited about — and concerned by. Top priorities and challenges of marketers in Southeast Asia. Visit Tableau to learn more. We’ll start by talking about what’s new to both marketers’ top priorities and top challenges lists — collaboration. During the shift to remote-first work, marketers may feel like they’ve lost touch with their colleagues. Given employees’ and companies’ interest in continuing flexible and remote work, marketers will likely continue to use an evolving set of technologies, such as video conferencing and messaging platforms. Marketers had two other new priorities in their top five this year — creating a cohesive customer journey across channels and devices, and improving marketing ROI and attribution. Collaboration is essential to achieving both of these. Collaboration within the marketing org — and with sales and service departments — is the only way marketers can deliver a cohesive experience at every customer touch point. It’s no wonder that 78% of marketing organisations have adopted new work-collaboration technology due to the pandemic. Coordination across marketing campaigns and activities (as well as solid digital savvy) will help marketers find new, innovative ways to measure marketing ROI. Since only 31% of marketers are completely satisfied with their ability to measure marketing ROI and performance, leaders should make a concerted effort to improve their measurement capabilities. Aside from collaboration, there was another new challenge in marketers’ top five this year: insufficient organisational structures and processes. It’s natural for marketers to feel unprepared for the rapid pace of business transformation that they experienced over the past year. But now is the time to step back and look at how to improve processes to better serve customers, operate internally, and drive growth. 2. Innovation and resilience help marketers deliver on customer demands in digital Since the start of the pandemic, 60% of consumer interactions with companies have been digital, compared to 42% pre-pandemic. Although pursuing digital innovation can be daunting due to the overwhelming amount of new channels and technologies in the market, marketers are leaning in. Even digital channels we might have classified as “emerging” recently are seeing widespread adoption, such as podcasts and streaming (OTT) ads. Marketing organisations in Southeast Asia use these media channels. Visit Tableau to learn more. In the end, it’s innovation and resilience that separates those digital marketers who are best prepared for the digital long-haul from the competition. Forty-eight percent of underperforming marketers — those moderately or less satisfied with their overall performance and investment outcomes — say they struggle to innovate their marketing strategies, tactics, and technology. That’s compared to just 31% of high performers — those completely satisfied — who say the same. 3. More data doesn’t mean better data or smarter data decisions Marketers are planning to use 75% more data sources on average by 2022 than they did in 2020. Yet only 33% of marketers are completely satisfied with their ability to use data to create more relevant customer experiences. Parsing that out between high-performing marketing organisations and underperformers reveals another striking statistic. Compared to 47% of high performers, only 8% of underperformers were completely satisfied with their use of data to craft relevant customer experiences. There’s a clear problem in the world of customer data. How do we fix it? Marketers must know that more data sources doesn’t necessarily mean richer customer insights. In fact, marketers felt that across the board, their data quality left much to be desired. Percentage of marketers in Southeast Asia who are completely satisfied with various aspects of their customer data. Visit Tableau to learn more. Marketing leaders can take advantage of the opportunity to improve their data management by becoming data champions within their organisation and by boosting the data literacy of their teams. Data literacy will help marketing leaders improve on things like data quality by being purposeful in choosing data sources, and data integration by being fluent enough to partner closely with IT. The future of marketing strategy is data-driven, so improving our data practice is an investment in long-term success. 4. Account-based marketing soars — with caveats Last year’s State of Marketing report found that account-based marketing (ABM) programs had rapidly gained in popularity. This year, 79% of B2B marketers said they’re using an ABM platform, and account-based marketing comprised an average of 16% of B2B and B2B2C marketing budgets. B2B buyers expect the same level of empathy and personalisation that B2C consumers have come to enjoy, especially during the pandemic-era shift to digital-first B2B selling — a trend that ABM programs address. How marketers in Southeast Asia feel about various aspects of their ABM programmes. Visit Tableau to learn more. Despite the resources being dedicated to ABM, fewer than half of marketers are completely satisfied with any one element of their account-based marketing programs — including technology, measurement, personalisation capabilities, and the identification of target accounts. Where’s the disconnect? Although ABM programs are relatively new to the B2B marketers’ toolkit, marketers shouldn’t be complacent when adopting these strategies. They require dedication to coordinating with sales teams, as well as digital and technology skills that evolve as quickly as the market does. We’ll continue to see ABM in B2B marketers’ toolboxes. But marketers should make plans now to improve the requisite digital skill sets and internal sales and service processes that make account-based marketing programs successful. 5. Marketers need relevant training to prepare for the future There are two main approaches to improving a marketing team’s skills: Hiring to fill knowledge gaps and upskilling or reskilling current staff members to keep up with the pace of change. What’s the best option to future-proof a team’s success? It may depend on the quality of the internal training resources at hand. Unfortunately, that’s a cause for concern for many teams: only 44% of marketers rate the employee training they receive as excellent. Even marketers’ top-requested skills training is falling short. The No. 1 skill marketers said they want to improve is creativity, yet only 44% of companies offer training in that area. Even critical data analytics skills that are in high demand are falling behind, with only 39% of companies offering analytics training. So marketing leaders must make the choice: Do I rely on the quality of the reskilling resources I have, or do I look elsewhere? The choice starts with making the conscious decision to be proactive. Marketing leaders should take a hard look at their existing training resources to decide whether they are enough to prepare teams for the future of marketing strategy. Having the right skills on your team means marketers can react to dynamic market conditions and embrace new trends in what customers want and need. For marketers around the world, future-proofing success can feel unattainable given the rapid pace of transformation across all industries. But preparation, and being willing to look outside the box for resources to upskill your teams, can be the solution marketers need. This post originally appeared on the U.S.-version of the LIKE.TG blog.

Ever been overwhelmed by the sheer volume of sales data you’re tracking — and confused by the metrics that matter? You’re not the only one. Research firm McKinsey highlighted this as a troubling trend: Too much data and no focus has made it difficult for sales leaders to reach clear “aha” moments that drive confident decisions and sustainable growth. Fortunately, there’s a clear path forward. To ensure you’re maximising the ROI of tools, teams, and customer relationships, zero in on sales key performance indicators (KPIs) that make the most of what you have while delivering recurring revenue: a combination of tried-and-true targets, like lead conversion rate, and those that measure long-term value, like customer and employee retention. Below, we give you everything you need to know about sales KPIs that ensure a healthy, productive, and growing business. What you’ll learn: What are KPIs in sales? Why are sales KPIs so important? What are sales metrics vs. sales KPIs? What are the most important sales KPIs? How do you track sales KPIs? What sales KPI dashboards should you use? What are KPIs in sales? Key performance indicators (KPIs) in sales are the metrics used to measure how closely the performance of a sales team tracks to predetermined goals and how this performance impacts the business as a whole. This includes metrics like average leads generated per quarter and deal conversion rate. Why are sales KPIs so important? Instead of different reps focusing on different metrics — or leaders eyeing a definition of success that sales reps aren’t thinking about — KPIs keep everyone aligned on the metrics that contribute to company growth. It’s important to note that KPIs themselves are not sales targets, but metrics that gauge activity with significant business impact. Sales leaders define target KPIs to ensure teams are tracking to specific revenue goals. Here’s an example: Joy’s Toys, a toy manufacturer, is focused on growth but doesn’t have a clear target KPI for lead generation that incentivises reps to keep their pipelines full. Fast-forward a quarter or two and its revenue is “stop-and-go” with reps scrambling to find new opportunities after periods of focusing only on closing deals already in the pipeline. As a result, company growth stalls. Competitor Saul’s Dolls, on the other hand, has mapped out a clear path to revenue growth that includes target KPIs for lead generation, quota attainment, and customer retention. These are shared with every rep so they can prioritise their time and efforts on prospecting, nurturing, and closing deals with new customers while upselling existing customers — and no critical sales effort is ignored. With this focus, Saul’s Dolls is more likely to hit or surpass its revenue goals. What are sales metrics vs. sales KPIs? Your sales KPIs have a close relationship with your sales and business goals. For example, if the overarching business goal is 1,200 sales in a year, the KPI might be 100 sales each month. (100 sales per month x 12 months = 1,200 sales) Sales metrics are any quantifiable measure of sales performance. This could look like the number of activities completed by sales reps, the number of leads in the sales pipeline, or anything else sales-related that can be measured. The key difference is that your sales metrics don’t necessarily have to connect with these broader goals. What are the most important sales KPIs? Historically, sales KPIs have focused on things like new leads in the pipeline, number of closed deals per quarter, and individual quotas. These are still important, but they often hinge on unpredictable one-off sales. To ensure your company is generating long-term, predictable revenue and maximising ROI, it’s important to track both foundational sales KPIs and those that gauge the lifetime value of customer and employee relationships. Here’s a closer look at the most critical sales KPIs: 1. Annual contract value (ACV) What it measures: The average sales amount of a customer contract over the course of a year. Why it’s important: ACV helps sales reps and managers identify opportunities for upselling and cross-selling that increase customer contract value and, ultimately, company revenue. If upselling or cross-selling are not possible (due to product portfolio, pricing structures, etc.), a low ACV may indicate a need for new customers that can drive revenue growth. How to calculate: (Total sales value of contracts in a year) / (number of contracts) = Average ACV 2. Customer lifetime value (CLV) What it measures: The value of all purchases, including upsells, cross-sells, and renewals, that a customer makes over the course of their relationship with your company. Why it’s important: CLV is a clear indicator of how successfully your team is building the kind of trusting, value-first, and loyal customer relationships that lead to upsells, cross-sells, and renewals, and, as a result, predictable revenue. If your CLV is on the lower end, then try going over the call transcripts from your best customers. Use AI to generate call summaries that identify what moved the deal forward, then use these same tactics in future deals. How to calculate: (Average purchase value per year) x (average number of purchases per year for each customer) x (average customer lifespan in years) = Customer lifetime value 3. New leads in pipeline What it measures: The number of new leads added to each rep’s pipeline during a single quarter. Why it’s important: Based on your conversion rates (four deals closed for every seven leads, for example), you will likely need a specific number of leads to hit sales targets. If reps’ lead count falls below your target KPI, it can be a sign that you need to spend more time on prospecting. A popular way to engage with more prospects is to up your presence on LinkedIn. Follow potential prospects, interact with them by liking and commenting on their posts, and then send a connection request. 4. Average age of leads in pipeline What it measures: How long leads remain in the pipeline without becoming a closed deal. Usually calculated per rep. Why it’s important: Reps know a full pipeline is a healthy one — but only if leads are actively moving toward a sale. Stalled deals are a drain on rep time that could be spent moving more viable deals down the pipeline. If you see a trend in stale leads for a particular rep, consider examining their pipeline and remove leads unlikely to close. AI insights help to quickly identify the stallers in real time so you’re not spending hours scanning through your pipeline and analysing the data. How to calculate: (Total age of all active leads per reps) / (Number of active leads) = Average age of leads in pipeline 5. Conversion rate What it measures: Also known as win rate, this is the percentage of each rep’s leads that are converted to closed deals. Usually tracked by quarter, per rep. Why it’s important: If a single rep’s conversion rate is higher than the target conversion rate, that rep may be using sales strategies or processes that are particularly effective and can be operationalised for the entire sales team. If lower, you might need to fine-tune or streamline sales tactics to increase conversions. Call recording and analysis tools, alongside regular one-on-one coaching, can help. How to calculate: (Number of deals closed during a quarter) / (number of leads in the pipeline) x 100 = Conversion rate 6. Rep retention What it measures: Percentage of reps who remain in your organisation a set period of time after hire. Typically measured yearly. Why it’s important: A low rep retention rate can disrupt carefully nurtured customer relationships, which can result in lost upsells/cross-sells — or just lost customers. It can also mean more money spent onboarding reps hired to replace those who leave. When rep retention is high, customer relationships remain intact and team stability is maintained. How to calculate: (Number of total reps at the end of the year – new reps hired during the year)/(total number of reps at the start of the year) x 100 = Rep retention 7. Average rep ramp time What it measures: The amount of time it takes a rep to get from the first day on the job to first prospect outreach. Why it’s important: A quicker ramp time indicates your sales enablement platform and training are effective, your tools and processes are intuitive, and you’re hiring qualified candidates. This results in faster sales and more engaged reps. If you find ramp time is slow, consider revisiting onboarding programs and sharing AI transcripts of winning sales calls with new reps, changing your tools, or streamlining your processes. How to calculate: (Total time in days it takes all new reps to get from day one to first prospect outreach) / (total number of new reps) = Average rep ramp time 8. Referrals What it measures: The number of referrals for new customers from existing customers secured by each rep during a given quarter. Why it’s important: When your customers are over-the-moon happy with your products or services, they can serve as advocates, promoting you to prospects who otherwise may not be familiar with your brand. This makes it easier for reps to sell, leading to faster sales cycles and more closed deals. 9. Customer retention What it measures: The percentage of customers who continue to buy and use your products/services. The inverse is churn rate — the percentage of customers who decide to stop buying or using your products/services. Why it’s important: While new customers add to revenue, they also take significant resources to secure. By watching customer retention and focusing on opportunities to upsell and cross-sell, you’re generating predictable revenue with a loyal customer base — and maximising ROI. If you see customer retention slip, you may need to revisit rep engagement strategies to ensure your team is prioritising existing customer relationships. How to calculate: (Overall number of customers at the end of the year – net new customers acquired during the year) / (number of customers at the start of the year) x 100 = Customer retention How do you track sales KPIs? A CRM uses customer and sales performance data to gauge progress toward sales KPIs. To help with interpretation, most CRMs offer visualisation tools or dashboards that can be customised with the KPIs most relevant to your business. The dashboard provides a clear picture of sales and company health so everyone from sales reps to leaders can make decisions that keep revenue flowing. What sales KPI dashboards should you use? To make sure everyone is in the loop, you need dashboards that provide high-level status updates to C-suite executives and more granular, deal-based dashboards for your reps. You don’t have to worry about updating dashboards manually — automation and AI-powered CRMs can pull data directly into customised dashboards to help you see progress toward KPIs without manual lift. Use these insights to improve performance, like tracking the fastest rep ramp times and checking in with those reps to see what worked that you could replicate. Here are the dashboards we recommend for how to track sales KPIs: For chief revenue officers (CROs) and sales leaders: Home “State of the Union” Dashboard: This provides an overview of top-level, year-to-date performance by target KPIs. It gives you the most important metrics for your business on one screen, including notable open and closed deals (usually the biggest accounts by value), top sales reps by quota attainment, and overall sales performance vs. forecast. For sales managers: Pipeline Dashboard: Get a snapshot of each rep’s pipeline with this dashboard, including average sales cycles, average deal amounts, and conversion rates. You’ll get clarity on the progression of deals in each pipeline and identify problem areas you need to address quickly. Team Activities Dashboard: See what your team’s doing to stay on top of active deals. Look at their total, completed, and overdue tasks and review each rep’s call and email logs. Dive deeper into conversations by looking at AI-generated call summaries. Use these summaries to identify customer sentiment and help move deals forward. Overall, this dashboard is key for monitoring rep engagement and sales process efficiency. For sales operations (sales ops) teams: Performance Dashboard: Drill into closed deals by region, account, or product so you can see what’s contributing to high deal win rates or slowing conversions. Once you know the “why,” you can recommend strategy shifts for your team. Stage Analysis Dashboard: This dashboard shows how deals across all reps are moving through the stages of the sales process, revealing bottlenecks and at-risk opportunities. Trends and patterns identified with AI can reveal opportunities for process improvements. For sales reps: Rep and Team Leaderboard Dashboards: This is an overview of individual rep and team performance data, including sales quotas attainment, leads in pipe, pipe generation, closed/won deals, average sales cycle time, and sales activities. For more guidance, check out our article on key sales KPI dashboards that can help you hit or exceed your revenue targets. Home in on the sales KPIs that matter to you There’s no shortage of sales KPIs to track — but zeroing in on the right ones depends on what’s important to your business right now. First, identify overarching goals. For example, are you focused on driving growth or maximising revenue with existing resources and investments? Once you’re aligned on larger goals, you can select relevant sales KPIs to track and target metrics that will ensure you hit your broader business goals. Be sure to set up dashboards in a CRM accessible to all teams so you can see a clear view of progress toward the goals you’ve defined.

In the current business sphere, achieving sales and marketing alignment is crucial for organisations that want to thrive. Sales and marketing misalignment can lead to missed opportunities, wasted resources, and decreased revenue, underscoring the urgent need for businesses to address this issue for growth. It’s the key to ensuring a seamless customer experience, driving revenue growth, and boosting overall business performance. This blog post will explore the essential steps to help businesses establish effective sales and marketing alignment, which is pivotal for successful sales. From breaking down silos and fostering collaboration to leveraging technology for seamless integration, we’ll provide practical strategies to help you create a cohesive sales and marketing team that works together towards achieving common business goals. What Is Sales and Marketing Alignment? Sales and marketing alignment is a strategic approach emphasising the collaborative efforts between sales and marketing teams to achieve a common business goal, specifically aligning sales for maximum effectiveness. It involves a tightly integrated relationship where both departments work seamlessly to attract, engage, and retain customers. Effective sales and marketing alignment ensures that the marketing team generates qualified leads for sales while the sales team provides valuable insights and feedback to marketing. When sales and marketing are aligned, it creates a cohesive customer experience, resulting in increased customer satisfaction, higher revenue, and improved overall business performance. Aligning sales and marketing is essential. It can significantly shorten the sales cycle, increase conversion rates, and foster greater interest in products and services by ensuring that both teams work towards shared KPIs and strategies. Customers receive consistent messaging, personalised interactions, and efficient problem resolution, leading to increased loyalty and repeat business. Alignment also fosters a culture of collaboration and communication between sales and marketing teams. They share data, insights, and best practices to develop targeted strategies that address customer needs and drive business growth. This collaborative approach eliminates silos, promotes teamwork, and ensures that both departments are working towards the same objectives. Sales and marketing alignment isn’t just an option but a necessity. It is the key to unlocking both teams’ full potential and achieving sustainable business success. What Does Marketing Do for Sales? Marketing is vital when it comes to supporting sales. It provides valuable insights, generates leads, and builds brand awareness. Marketing departments are necessary for aligning sales and marketing efforts to work towards shared objectives, offering assistance through cross-departmental shadowing, ensuring sales-focused marketing efforts, and facilitating the sharing of valuable information. Here are some essential functions that marketing performs to assist the sales team: Market Research and Insights: The marketing team conducts thorough market research to understand industry trends, customer behaviour, and competitor activities. They provide sales with comprehensive insights into target markets, customer needs, and pain points. This information enables sales representatives to tailor their pitches and strategies to address customer challenges and preferences better. Demand Generation and Lead Nurturing: Marketing creates demand for the company’s products or services. They develop and execute campaigns that attract potential customers and generate leads. This can include various strategies such as content marketing, search engine optimisation (SEO), social media marketing, email marketing, and paid advertising. The marketing team nurtures these leads by providing valuable content, building relationships, and guiding them through the sales funnel. By focusing on marketing qualified leads, marketing assists sales by not only generating but also qualifying leads, ensuring that the sales team can concentrate on the most promising prospects. Branding and Positioning: Marketing develops and manages the company’s brand identity, positioning, and messaging. They create compelling brand narratives, visual identities, and unique selling propositions that differentiate the company from competitors. Effective branding helps sales representatives communicate the company’s value proposition and build customer trust. Content Creation and Thought Leadership: The marketing team creates high-quality content that educates, informs, and engages the target audience. This content can take various forms, including blog posts, articles, infographics, videos, podcasts, etc. By establishing thought leadership and providing valuable insights, marketing supports sales in building credibility and positioning the company as an industry expert. Online Presence and Social Media Management: Marketing manages the company’s online presence, including the website, social media channels, and online reputation. They create and curate engaging content, respond to customer inquiries, and monitor online conversations. A solid online presence and effective social media management help sales teams connect with potential customers, build relationships, and generate leads. By aligning marketing and sales efforts, businesses can create a seamless customer journey, deliver a consistent brand experience, and more effectively achieve their revenue goals. What Does Sales Do for Marketing? Sales reps, through their close collaboration and communication with the marketing team, play a significant role in providing valuable insights and feedback. This partnership enhances the creation and utilisation of sales content, aligns goals, and leverages data to improve lead quality and customer insights. In return, sales also play a vital role in supporting marketing. Here are some key functions that sales perform to assist the marketing team: Customer Insights and Feedback: Sales representatives interact directly with customers and have a deep understanding of their needs, preferences, and pain points. They provide valuable insights and feedback to the marketing team, which helps refine marketing strategies, improve messaging, and develop more effective campaigns. Lead Qualification: Sales representatives qualify leads generated by marketing efforts. They evaluate the potential and readiness of leads to determine if they are a good fit for the company’s products or services. This helps marketing focus its resources on high-quality leads and optimise its lead generation strategies. Content Validation and Improvement: Sales representatives can provide feedback on marketing content, ensuring it aligns with customer needs and effectively communicates the company’s value proposition. Their input helps improve marketing materials’ relevance, accuracy, and effectiveness. Building Customer Relationships: Sales representatives build customer relationships, establishing trust and credibility. They can provide valuable insights into customer behaviour, preferences, and buying patterns, which helps marketing develop more personalised and targeted campaigns. Competitive Intelligence: Sales representatives are often at the forefront of competitive activities and have a good understanding of competitors’ strategies, strengths, and weaknesses. They can provide valuable intelligence to the marketing team, enabling them to develop more effective competitive strategies and differentiate the company’s offerings. By working together and sharing information, sales and marketing teams can create a synergistic relationship that drives business growth and success. Aligning these two critical functions ensures that the company’s efforts are cohesive, effective, and focused on achieving common goals. Understanding the benefits of sales and marketing alignment for revenue growth Achieving alignment between sales and marketing functions offers numerous advantages that can significantly enhance the overall success of a business, especially in driving revenue growth and improving customer experience through collaboration, unified communication, and mutual support. One of the primary benefits is the potential for increased revenue. When sales and marketing teams are aligned, they work cohesively to generate qualified leads, shorten the sales cycle, and increase conversion rates. This collaborative effort leads to improved sales performance, resulting in higher revenue growth for the organisation. Another advantage of aligning sales and marketing functions is cost reduction. Businesses can save valuable resources and reduce operational costs by eliminating duplicate efforts, optimising marketing campaigns, and streamlining lead management processes. This cost efficiency allows companies to allocate resources to other strategic initiatives that drive business growth. Sales and marketing alignment also contributes to improved customer satisfaction. When sales and marketing teams work together, they better understand customer needs and preferences. This knowledge enables them to deliver a consistent and seamless customer experience, from the initial marketing interaction to the final sale. Satisfied customers are more likely to become loyal brand advocates, increasing customer retention and positive word-of-mouth referrals. Furthermore, sales and marketing alignment enhances brand reputation. When both teams collaborate effectively, they create a unified brand message and present a cohesive brand image to the market. This consistency builds trust and credibility among customers, stakeholders, and industry peers. A strong brand reputation attracts new customers, improves customer loyalty, and differentiates the business from competitors. Last but not least, sales and marketing alignment facilitates better organisational decision-making. By sharing data, insights, and feedback, sales and marketing teams can make informed decisions based on real-time information. This data-driven approach minimises guesswork and allows businesses to allocate resources effectively, optimise marketing campaigns, and improve sales strategies. Breaking down silos and promoting collaboration between sales and marketing teams The first step to achieving sales and marketing alignment is to break down silos and promote collaboration. This can be challenging, as sales and marketing teams often have different goals and priorities. However, it is essential to overcome these challenges to create a cohesive customer experience. One way to break down silos is to foster a culture of open communication and transparency between the two teams. This can be done by holding regular cross-functional meetings, sharing information and data, and encouraging employees to collaborate on projects. Another way to promote collaboration is to create shared goals and incentives. When sales and marketing teams work together towards common goals, they are more likely to be successful. To further this goal, aligning marketing and sales teams is needed to break down silos and foster collaboration, ensuring both departments work together seamlessly. To foster a culture of open communication and transparency, it is important to create opportunities for sales and marketing teams to interact with each other. This can be done through regular meetings, workshops, and social events. It is also important to encourage employees to share their ideas and feedback and create a safe environment where they feel comfortable doing so. Aligning the sales and marketing teams on the company’s overall objectives is important for creating shared goals and incentives. This can be done by developing a shared vision and mission statement and setting clear goals and metrics for success. Incentives that reward sales and marketing teams for working together, such as bonuses or commissions, are also important. By breaking down silos and promoting collaboration, sales and marketing teams can create a more cohesive customer experience and achieve more tremendous success. Establish clear roles and responsibilities Establishing these clear roles and responsibilities for sales and marketing departments is an all-important step for achieving alignment and ensuring that both teams work cohesively towards shared objectives. Establishing a clear understanding of roles, continuous communication, and joint efforts towards shared objectives between sales and marketing departments is essential. Here are some key considerations for defining roles and responsibilities: Define Objectives and Key Performance Indicators (KPIs): Clearly outline the overall goals and objectives for both sales and marketing departments. Set specific and measurable KPIs that align with the company’s strategic priorities. These KPIs should be tied to the business’s overall success and should be regularly monitored and evaluated to ensure alignment and improve business performance. Outline Specific Tasks and Responsibilities: Detail each team member’s specific tasks and responsibilities within sales and marketing. This includes defining who is responsible for lead generation, qualification, nurturing, and closing deals. It also outlines who is responsible for market research, content creation, branding, and online presence management, ensuring a shared understanding of roles. Empower Teams to Make Decisions: Empower both sales and marketing departments to make decisions within their respective domains. Provide them the autonomy to execute their strategies and make necessary adjustments based on market conditions and customer feedback. This fosters a sense of ownership and accountability, leading to more effective decision-making. Regular Review and Updates: Roles and responsibilities should not be set in stone. They should be regularly reviewed and updated to ensure they align with changing market dynamics and business priorities. This adaptability allows sales and marketing departments to respond swiftly to new opportunities and challenges, maintaining alignment and optimising performance. Create a unified sales and marketing strategy This is essential for achieving alignment between the two departments. This involves developing a shared vision and objectives for both departments, ensuring their goals align with the overall business strategy. Regular joint planning sessions should be held to discuss strategies, brainstorm ideas, and ensure that both teams are on the same page. Creating a content calendar supporting sales and marketing goals is critical, as it allows for consistent messaging and campaigns. Additionally, sharing customer insights and data between sales and marketing teams is essential for understanding customer needs and preferences and developing targeted strategies that meet those needs. By fostering a collaborative environment and breaking down departmental silos, businesses can create a unified sales and marketing strategy that drives revenue growth, improves customer satisfaction, and enhances overall business performance. Leverage technology for seamless integration Technology is vital in achieving seamless integration between sales and marketing teams. One essential tool is customer relationship management (CRM) software. CRM systems provide a centralised platform for managing customer interactions, including contact information, communication history, and sales opportunities. By sharing this data, sales and marketing teams can comprehensively understand customers, enabling them to deliver personalised and consistent experiences. Marketing automation tools are another valuable technology for sales and marketing alignment. These tools help automate repetitive tasks like email marketing, social media management, and lead generation. By automating these tasks, teams can focus on higher-value activities, such as building customer relationships and closing deals. Integrated sales and marketing platforms offer a comprehensive sales and marketing alignment solution. These platforms combine CRM, marketing automation, and other tools into a unified system. This allows teams to access all the information they need in one place, making collaborating and executing campaigns easier. Finally, analytics and reporting tools are essential for measuring the success of sales and marketing alignment efforts. These tools provide insights into customer behaviour, campaign performance, and overall business results. By analysing this data, teams can identify areas for improvement and make data-driven decisions to optimise their strategies. Technology is essential for achieving sales and marketing alignment. By leveraging the right tools, businesses can break down silos, improve communication and collaboration, and create a unified customer experience. This leads to increased customer satisfaction, higher revenue, and improved business performance.

Do you have a to-do list of pesky tasks lingering over you? We’re talking about the ones that must be done to execute a campaign: gathering and analysing data, creating catchy email subject lines, determining the right audience to target, and so much more. These tasks can steal your time — and maybe even your sanity. But now there’s a way to reduce that heavy lifting, helping you focus on campaign success. Let us introduce you to your new digital assistant: AI. As brands look for ways to get closer to consumers, more than half of marketers (62%) say they’ve invested in the power of AI. Our most recent State of Marketing survey found that three out of the top four AI use cases are related to automation, highlighting the importance of scaling up speed and effectiveness. Let’s take a look at 9 ways using AI as a digital assistant can increase the effectiveness and efficiency of your campaigns. It’s time to say goodbye to the redundant manual campaign tasks marketers wish they didn’t have to do – and let AI help make the most of your time. One click away from campaign success Generative AI technology is transforming the future of marketing — and we’ve got you covered. Take a quick look on Trailhead, LIKE.TG's free online learning platform. Kickstart your campaign +100 points Trail AI Technology for Marketing Learn the ways of this trail. 1. Make better decisions with automated data analysis and insights AI can analyse large volumes of campaign data, including customer behaviour, campaign performance metrics, and market trends. It can identify patterns, extract insights, detect correlations, and provide actionable recommendations to improve campaign strategies and targeting. You’ll get a deeper understanding of customers and campaign performance, enabling you to make informed decisions and find success faster. 2. Increase engagement and conversions with audience segmentation After analysing the customer data, your AI digital assistant can then segment audiences based on demographics, behaviour, preferences, purchase history, and other important attributes. AI eliminates the manual effort required for segmenting audiences and targets specific customers with more relevant offers. When you’re able to personalise messaging for different segments, you’ll see campaigns succeed more. Get articles selected just for you, in your inbox Sign up now 3. Anticipate your customer’s needs with predictive analytics AI predictive models use historical data to forecast customer behaviour, such as likelihood to convert, churn, or engage with specific campaign elements. This helps you stay one step ahead to proactively address customer needs and budget resources effectively. 4. Save time with content generation and optimisation Creating unique content frequently can be one of the most time-consuming tasks for many marketers — but one an AI digital assistant can help with. AI, powered by natural language processing (NLP) can generate content — such as ad copy, email subject lines, and social media posts — that resonates with your customers. You can provide the finishing touches to make sure the content is in your voice and tone. It can also optimise your content by analysing performance data, identifying high-performing elements, and suggesting improvements. 5. Streamline workflows with campaign automation AI can automate various aspects of campaign execution, such as scheduling and deploying ads, sending targeted emails, or managing social media posts. This reduces manual effort and ensures that your campaign runs on time. What can you do with the time freed up, thanks to AI? Focus on strategy and innovative ideas, helping you build better customer relationships. 6. Clearly show campaign success with performance tracking and reporting According to our State of Marketing report, 72% of high-performing marketers are able to analyse data in real time, giving them an advantage when it comes to responding to and optimising campaign performance. Your AI digital assistant can automate the tracking and reporting of campaign performance metrics — in ways that anyone can understand. AI can generate real-time dashboards and visually-pleasing customised reports, giving you and your stakeholders a clear view of campaign performance and key metrics, without the need to do it all by hand. This helps you make data-driven decisions, optimise campaigns on-the-go, and demonstrate the value of your efforts to stakeholders. 7. See what works best with A/B testing AI can perform A/B tests on campaign elements, such as ad variations, landing pages, or email designs. It analyses performance data, identifies winning variations, and helps you continuously refine your strategies. 8. Grow revenue with lead scoring and nurturing With AI, you can automate lead scoring by analysing lead data, behaviour, and engagement history. It assigns scores to leads based on their likelihood to convert and delivers personalised content to move prospects through the sales funnel. With AI’s lead scoring, your team can focus on the most promising leads and nurture relationships at scale. 9. Improve communication with internal collaboration tools AI shines as your digital assistant when handling internal collaboration needs. You can use this technology to automate messaging in your department, as well as project management, task assignment, and file sharing. Teams can even apply workflow automations that schedule meetings, send reminders, or organise files — taking care of the little details so you can focus on campaign success. AI is transforming campaign management by allowing teams to automate manual tasks, freeing marketers to work on more big-picture ideas. With AI as your ally, you can streamline your campaigns, see better results, and start focusing on your next successes.

As the world’s #1 CRM, LIKE.TG brings companies and customers together. This is possible through LIKE.TG Customer 360. It’s an integrated, AI-powered customer relationship management (CRM) platform that unites departments and gives them a single view of your customer. This enables your teams to create connected, personal customer experiences that build stronger relationships. LIKE.TG Customer 360 is designed to be tailored to the needs of every business. We have specialised solutions to support the capabilities you need to thrive and grow. We also have an extensive network of ecosystem partners offering apps and guidance to help you craft a truly customised experience. Read the infographic below to learn about the various LIKE.TG Customer 360 solutions and apps. These include: sales, service, marketing, IT (platform), commerce, Tableau analytics, data integration (MuleSoft), and partners (AppExchange). No matter your business type, LIKE.TG Customer 360 helps your teams come together, serve customers better, and grow your business. For details on this infographic, please click here.

It’s an exciting time to be a marketer. Customers are increasingly engaging online through new innovative formats. Disruptive trends and technology continuously shake up the virtual landscape. Through it all, marketers have been at the forefront of digital transformation, adapting to meet the challenges and opportunities of a changing business landscape. In this digital-first era, marketing’s responsibility has evolved around two critical roles: the stewards of customer relationships and the engine fueling growth. Eighty percent of marketers say their organisation leads customer experience initiatives across the business, while 94% of marketers globally view the marketing function as critical for driving growth — up from 87% last year. In our latest marketing research, the third edition of the Marketing Intelligence Report, we surveyed more than 2,500 marketing decision makers around the world to uncover how marketers are using data for growth and customer experiences. Plus, we discover how marketers are adapting to a privacy-focused data ecosystem and the trends shaping cross-channel marketing. Let’s take a look at some of the key findings. You can download the whole marketing report here. 1. Those in marketing report that proving impact is crucial Today’s marketer has a dual mandate: growing revenue and nurturing customer relationships. This is reflected in how marketers define success. In Singapore, the top three metrics for defining success are: Customer acquisition Brand awareness Conversions, or desired action Fewer than two in five marketers around the world report that they feel completely successful in evaluating any of these metrics definitively. When asked to name the challenges they face in evaluating performance, marketers in Singapore named the following: Manual data integration processes Siloed data Alignment across teams on measurement and reporting 2. Privacy changes have led to shifts in marketing strategies and investments Over the past few years, data privacy regulations — such as GDPR, Apple Mail Privacy Protection, and Google’s deprecation of the third-party cookie — have encouraged marketers to adopt a consumer-first, consent-based approach to data collection. At the same time, marketers are feeling downstream effects in their analytics as popular performance metrics like email opens are now less relevant as privacy policies preventing tracking are implemented. In fact, 98% of marketers in Singapore agree that recent data privacy changes have fundamentally changed how they measure marketing performance. Marketers are relying on technology to ensure they can continue to measure performance, understand their customers, and provide them with individualised experiences. In Singapore: 92% of marketers plan to either increase or maintain investments in marketing analytics 91% of marketers plan to either increase or maintain investments in customer data platforms 96% of marketers plan to either increase or maintain investments in real-time interaction and personalisation Speaking of investments, more than half of marketers around the world have increased their investment in paid social, mobile marketing, and web experiences — places where customers shop and do business online. This comes as no surprise as 58% of consumers expect to do more online shopping after the pandemic than before, and 80% of business buyers expect to conduct more business online. 3. Data quality is paramount — but not universally accounted for Regardless of their objectives, marketers need dependable data to demonstrate the value of their programs and drive outcomes. Nearly four in five marketers around the world say data quality is key to driving marketing-led growth and customer experiences. Though marketers globally are investing in analytics technology, only 51% of marketing teams currently have employees dedicated to analytics, according to the marketing report. As with all challenges, there’s room for opportunity. It’s time for organisations to use AI and automation to accelerate manual data integration and analytics processes, and free up marketing resources for more strategic, creative work. 4. Data-driven marketing cultures require a centralised view Without a clear, holistic view of data, it’s hard to give meaning to data-driven marketing efforts. Our marketing report found 99% of marketers in Singapore emphasise the importance of having a complete, centralised view of all cross-channel marketing. Yet, 68% still evaluate the performance of their cross-channel marketing in silos, leaving plenty of room for improvement and integration. Not only do marketers need to integrate data across business units and sources, they also need to share it to generate value, foster team-wide collaboration, and connect marketing to business outcomes. With data unified in one place, marketers are positioned to lead growth in their organisations and engage their customers.

As we face four major crises — global health, the economy, equality, and leadership — how can business leaders help guide the way? In an interview with LIKE.TG CEO Marc Benioff, Workday Co-Founder and CEO Aneel Bhusri says it takes a mindset change. “Companies can step up and show that we have a soul and we want to do the right thing. We all need to think about more than our share price. We’ve got to think about our community, our employees, and our customers in a far more complex way than we have historically.” In this installment of our Leading Through Change series, Bhusri shares his thoughts on leading with values in the midst of a crisis, and what enterprises can do to ensure their efforts translate into a better world. His words have been lightly edited for content and clarity. On valuing employees We’ve always been “employee-first,” [but] you never know if your value system really works until you hit a crisis. When we realised the pandemic would go on much longer than predicted, we wanted to assure our employees they would be taken care of right out of the gate. We gave every employee in the company a two-week bonus just to get ahead of issues they might have. It allowed them to bring their whole selves to work and know the company was looking out for them. And when you lead with your employees, happy customers come next. On addressing racial injustice There’s nothing like a crisis to force you to lean on your core values. If we lose this moment of opportunity, shame on all of us. I feel really energized right now because this is a time where the right conversations are happening. There has to be a major change in mindset. Great Places to Work CEO Michael Bush makes a great point — you’ve got to listen and understand, and then you’ve got to take action. Companies like ours can step up and be forces for good and forces for change. In our product, we have diversity dashboards where you can [track the progress of your workforce diversity initiatives]. I’ve always believed that if you can measure it, then you can change it. There’s not a chief human resource officer (CHRO) in the country I’ve talked to that doesn’t want to do the right thing. On technology’s role in recovery We have to get the economy going, but we have to do it in a safe way. Innovation, new ideas, and creativity are going to help us get through this. For example, marrying the employee and skills data we have in Workday with Work.com makes reopening for our customers a lot easier because the data and solution sets are complementary and powerful. I’m amazed at how quickly our customers are reinventing themselves to fit this new world using our technology. A large manufacturer built an app on Workday to track COVID-19 cases and inform them where to move manufacturing capacity. A major retailer delivered more than a million one-time hazard paychecks to take care of their employees. Use of our workforce and financial planning applications grew 30 times in the last few months as customers continue scenario planning. I do think being a cloud company is both a technology advantage and a mindset advantage. We just see the world differently — we see it as open and connected. On reskilling the workforce Forty-one million people in the US are out of work, but many of the jobs they had aren’t going to come back. Through private-public partnerships, we have a real opportunity to retrain millions of people and give them skills that are going to make them successful for the next decade. We’re working with states to identify the hiring needs of their largest employers, while those governments invest in the training programs we need to reskill these workers. On hope for the future We’ve learned a lot about how to deal with pandemics and we’ll learn a lot about how to be resilient. We will come out a stronger country in dealing with racism. It gives me hope we’re taking on these issues and not being silent while trying to do the right thing. We’re going to look back at this as one of the most meaningful times in our life. Watch the full interview with Aneel Bhusri and a performance by Leon Bridges below. window.SfdcWwwBase && window.SfdcWwwBase.videoComponent && window.SfdcWwwBase.videoComponent.updateChapter(document.scripts[document.scripts.length - 1].getAttribute("data-uuid")); if(!window.vidyardEmbed){ window.videoUtils && window.videoUtils.loadScriptOnce("https://play.vidyard.com/embed/v4.js", "Vidyard", true); } else { window.vidyardEmbed.api.renderDOMPlayers(); } (function($) { // Add 'Configuration' global object with details of our Adobe Analytics instance window.Configuration = window.Configuration || {}; var rsid = (typeof Server !== 'undefined') ? Server.getAccount() : ''; $.extend(window.Configuration, { PUBLISHER: '8D6C67C25245AF020A490D4C@AdobeOrg', MCID: '8D6C67C25245AF020A490D4C@AdobeOrg', NAMESPACE: 'LIKE.TG', CHANNEL: 'LIKE.TG', RSID: rsid, TRACKING_SERVER: 'LIKE.TG.sc.omtrdc.net', HEARTBEAT_TRACKING_SERVER: 'LIKE.TG.hb.omtrdc.net', DEBUG: false }); }(jQuery)); // End of IIFE This conversation is part of our Leading Through Change series, providing thought leadership, tips, and resources to help business leaders manage through crisis. This post originally appeared on the U.S.-version of the LIKE.TG blog.

Sales budgets are essential for businesses that want to succeed. They provide a roadmap for financial success, helping businesses set realistic goals, allocate resources effectively, and make informed decisions. Without a sales budget, businesses are flying blind, and are more likely to make costly mistakes. Creating a sales budget doesn’t have to be complicated. By following a few simple steps, you can create a sales budget that will help you achieve your business goals and reach your expected sales. In this blog post, we will walk you through the process of creating a sales budget, and provide tips for best practices. We will also show you how to build your sales budget with LIKE.TG, a powerful customer relationship management (CRM) tool. What is a sales budget? When you’re preparing a sales budget, you’ll find it acts as a financial roadmap that guides businesses toward achieving their sales objectives. It serves as a blueprint for revenue generation and expense management over a specific time period only, typically a year. By creating a sales budget, businesses gain a clear understanding of their financial trajectory and can allocate resources strategically to drive growth and profitability. Sales budgets play a pivotal role in setting realistic sales targets. They provide a benchmark against which actual performance can be measured, enabling businesses to assess their progress and make necessary adjustments. To continue, sales budgets facilitate informed decision-making in areas such as pricing, marketing, and hiring. By aligning financial resources with sales goals, businesses can optimise their operations and maximise returns. Beyond setting targets and allocating resources, sales budgets serve as valuable tracking tools. They allow businesses to monitor their financial performance closely, identify trends, and detect potential deviations from the projected path. This enables timely interventions and course corrections to ensure that the business stays on track towards achieving its financial objectives. To put it simply, a sales budget is a key financial tool that empowers businesses to navigate the competitive landscape with confidence. By providing a framework for strategic planning and informed decision-making, sales budgets contribute significantly to the success and sustainability of businesses. The Purpose of the Sales Budget Process Business can be a competitive landscape, which is why a sales budget is such a vital instrument for organisations to chart a course toward success. It’s not simply a compilation of financial statements and projections; it serves as a beacon, illuminating the path to growth, profitability, and sustainability. The primary purpose of a sales budgeting period therefore lies in its ability to transform aspirations into actionable strategies. It provides a framework for businesses to meticulously set achievable sales volumes, ensuring that they’re not just wishful thinking but realistic milestones. With these targets in place, businesses can then allocate resources judiciously, channelling them into the most promising avenues for revenue generation. A sales budget is not just a static financial document; it’s a tool that empowers organisations to navigate the ever-changing market landscape. It enables them to identify potential challenges and opportunities that lie ahead, ensuring they’re not caught off guard by unforeseen circumstances. With contingency plans in place, businesses can pivot swiftly, minimising risks and capitalising on emerging opportunities. A sales budget also helps to foster a culture of transparency and collaboration within an organisation. It serves as a shared roadmap, aligning the efforts of sales teams, finance departments, and other key stakeholders. By communicating sales targets and financial expectations, everyone is on the same page, working in unison towards a common objective. This alignment ensures that resources are utilised efficiently, eliminating waste and maximising returns. Essentially, a sales budget is an indispensable tool that propels businesses towards financial stability and sustained growth. It’s a compass guiding organisations through the complexities of the market, providing a clear direction and empowering them to make informed decisions. With a well-crafted sales budget in hand, businesses can navigate the challenges and seize the opportunities that lie ahead, positioning themselves for long-term success in the ever-evolving marketplace. What elements should a sales budget include? A sales budget is a crucial tool for businesses seeking financial success and sustainability. To ensure its effectiveness, several important elements must be incorporated into its design. Sales Projections: At the core of any sales budget lies the projection of future anticipated revenue. This involves analysing historical sales data, market trends, and industry forecasts to arrive at realistic and achievable sales targets. Accuracy in these sales forecast projections is essential, as they serve as the foundation for all subsequent budgeting decisions. Cost of Goods Sold: Determining the cost of goods sold (COGS) is another critical component of a sales budget. COGS encompasses the direct costs incurred in producing or acquiring the goods or services sold by the business. Understanding COGS allows businesses to calculate their gross profit and set appropriate pricing strategies. Sales Incentives and Commissions: Sales incentives and commissions contribute to motivating and rewarding sales personnel. These elements should be clearly defined in the sales budget, ensuring that compensation aligns with what the company expects sales-wise, performance, and organisational goals. Overhead Expenses: Overhead expenses encompass the indirect costs incurred in the sales process, operating expenses such as rent, utilities, salaries of the sales reps and support staff, and marketing expenses. Accurately budgeting for overhead expenses is essential to ensure the overall profitability of sales operations. By incorporating these necessary elements into a sales budget, businesses gain a comprehensive overview of their financial landscape. This enables them to make informed decisions, allocate resources effectively, and seize opportunities for growth and success. How to Prepare a Sales Budget To prepare a sales budget, businesses should begin by setting realistic sales goals. These goals should be based on historical sales figures, historical data used, market conditions, and industry trends. When setting sales goals, it is important to consider factors such as seasonality, competition, and economic conditions. Once sales goals have been established, businesses can begin estimating their expenses. This includes variable costs such as the cost of goods sold, sales commissions, and shipping, as well as fixed costs such as rent, utilities, and salaries. It is important to be thorough and accurate when estimating expenses, as this will impact the overall budget. After estimating expenses, businesses can allocate budget for new initiatives or projects. This could include investments in marketing, product development, or hiring additional staff. When allocating budget for new initiatives, or other budgets, it is important to consider the potential return on investment and the impact on the overall business strategy. Finally, businesses should create a timeline for annual budget, preparation, execution and review. This will help to ensure that the budget is implemented effectively and that any necessary adjustments are made in a timely manner. Regular budget reviews will also help businesses to identify trends, monitor progress, and make informed decisions about future investments. By following these steps, businesses can prepare a sales budget that will help them to achieve their financial goals and objectives. A well-prepared sales budget is essential for businesses of all sizes, as it provides a roadmap for financial success and sustainability. 10 steps to creating a sales budget Creating a sales budget is an essential step in planning for the success of your business. By following these ten steps, you can create a realistic sales budget that will help you achieve your financial goals. Set a Time FrameThe first step in creating a sales budget is to set a time frame. This could be a month, a quarter, or a year. Once you have set a time frame, you can start to gather the data you need to create your total net sales budget. Determine Your PricingNext, you need to determine your pricing. This will depend on a number of factors, including your competition, your target market, and your product or service. Once you have determined your pricing, you can start to calculate your projected revenue. Define Your Sales GoalsOnce you know your pricing, you can start to define your sales goals. These goals should be realistic and achievable. When setting your sales goals, it is important to consider your past, sales trends and performance, as well as your current market conditions. Estimate Your Sales VolumeThe next step is to estimate your sales volume. This can be done by using historical sales data, as well as market research and industry trends. When estimating your sales volume, it is important to be conservative. Calculate Your Cost of Goods SoldThe cost of goods sold (COGS) is the direct cost of producing your product or service. This includes the cost of materials, labour, and overhead. When calculating your COGS, it is important to be accurate. Factor in Sales Incentives and CommissionsIf you offer sales incentives or commissions, you need to factor these into your sales budget. Sales incentives and commissions can be a great way to motivate your sales team, but they can also add to your costs. Estimate Your Overhead ExpensesOverhead expenses are the indirect costs of doing business. This includes rent, utilities, salaries, and marketing. When estimating your overhead expenses, it is important to be thorough. Create a Timeline for Budget Execution and ReviewOnce you have a production and smaller sales budget spreadsheet and completed all of the above steps, you need to create a timeline for budget execution and review. This will help you stay on track and make sure that your sales budget is being followed. Monitor Your BudgetOnce your sales budget is in place, you need to monitor it regularly. This will help you identify any variances between your actual sales and your budgeted sales. By monitoring your sales budget process, you can make adjustments as needed. Adjust Your Budget as NeededYour sales budget is not set in stone. You may need to adjust it as needed throughout the year. This could be due to changes in your market conditions, your sales goals, or your costs. By being flexible with your budget, you can ensure that it remains realistic and achievable. Examples of Sales Budgets This section provides five examples of sales budgets, one for each of the following types of businesses: small business, large corporation, non-profit organisation, SaaS company, and startup. These examples are designed to help businesses understand the different elements that should be included in a sales budget and how to tailor a sales budget example to their specific needs. Small Business A small business sales budget might include the following elements:– Sales revenue: $100,000– Cost of goods sold: $50,000– Sales incentives and commissions: $10,000– Overhead expenses: $20,000 Large Corporation A large corporation’s sales budget might include the following elements:– Sales revenue: $1 billion– Cost of goods sold: $500 million– Sales incentives and commissions: $100 million– Overhead expenses: $200 million Non-Profit Organisation A non-profit organisation’s sales budget might include the following elements:– Sales revenue: $500,000– Cost of goods sold: $250,000– Sales incentives and commissions: $0– Overhead expenses: $100,000 SaaS Company A SaaS company sales budget might include the following elements of sales prices:– Sales revenue: $10 million– Cost of goods sold: $5 million– Sales incentives and commissions: $2 million– Overhead expenses: $3 million Startup A startup sales budget might include the following elements:– Sales revenue: $0– Cost of goods sold: $0– Sales incentives and commissions: $0– Overhead expenses: $50,000 These are just a few examples of sales budgets. The specific elements that should be included in a sales budget will vary depending on the type of business and its individual needs. Sales Budget Best Practices When it comes to sales budgeting, embracing certain best practices can elevate your organisation to new heights of financial success. One such practice is the adoption of rolling forecasts. This bold approach involves regularly updating your sales budget to reflect the latest market trends, customer behaviour, and economic conditions. By incorporating real-time data into your financial plan, you can make more informed decisions and stay ahead of the curve in a rapidly evolving business landscape. Another best practice is empowering your sales team to actively participate in the budget process. Their firsthand insights into customer interactions, market dynamics, and sales challenges can provide invaluable input for creating a realistic and achievable sales budget. By involving your sales team in the budgeting process, you foster a sense of ownership and accountability for sales price, aligning their efforts with the organisation’s strategic objectives. Regular monitoring and adjustment of your sales budget are essential to ensure its effectiveness. Regularly review actual sales performance against budgeted targets, and be prepared to make necessary adjustments based on market conditions and customer feedback. This proactive approach allows you to stay on track, identify potential deviations, and take corrective actions promptly. Leverage your monthly sales budget, as a tool for continuous improvement. Use quarterly budgets and reviews as an opportunity to analyse sales strategies, identify areas for optimisation, and implement changes that drive revenue growth and profitability. By fostering a culture of learning and adaptation, you can continuously refine your sales approach and increase your organisation’s financial performance. Lastly, embrace change and be willing to adjust your sales budget as needed. Unforeseen circumstances, such as economic downturns, industry shifts, or technological advancements, may necessitate revisions to your financial plan. By maintaining a flexible mindset and being open to change, you can ensure that your sales budget remains aligned with your organisation’s evolving needs and market realities. Building Your Sales Budget with LIKE.TG LIKE.TG is a powerful customer relationship management (CRM) tool that can also be used to create and manage sales budgets. The Sales Budget Template from the AppExchange is a great starting point for creating a sales budget in LIKE.TG. This template includes pre-built reports and dashboards that make it easy to track your sales performance and adjust your budget as needed. In addition to the Sales Budget Template, you can also use LIKE.TG Reports to create custom reports on your sales data. These reports can be used to track a variety of metrics, such as total revenue made, expenses, and profits. You can also use LIKE.TG to create a custom dashboard that displays your sales data in a visual format. This makes it easy to see your sales performance at a glance and identify any areas that need improvement. The Opportunity Forecasting tool in LIKE.TG can be used for sales forecasts during a specific period of time. This tool takes into account a variety of factors, such as past sales data, current market conditions, and your sales pipeline. The Sales Performance Management tool in LIKE.TG can be used to track the performance of your sales team. This tool provides insights into your team’s activities, such as the number of calls they make, the number of emails they send, and the number of deals they close. By using LIKE.TG to create and manage your sales budget, you can gain a better understanding of your sales performance and make more informed decisions about your budget. LIKE.TG can help you improve your sales forecasting, track your sales team’s performance, and make adjustments to your budget as needed.

As a LIKE.TG App Developer, you get to work with Customer 360, gain access to a wide range of learning opportunities, and be part of the inclusive LIKE.TG community. According to the International Data Corporation (IDC), by 2024, LIKE.TG and its ecosystem of partners may create 8,500 direct and 17,000 indirect jobs in Singapore alone. This is driven in large part by increased demand for cloud solutions and services. The ASEAN Developer Challenge introduces you to the LIKE.TG ecosystem. Think of it as an opportunity to learn, earn, and connect. Register for the challenge and see how easy it is to begin building enterprise apps on the LIKE.TG Platform. Eventually, you will also get an opportunity to showcase your app-building skills to LIKE.TG customers and partners at an official LIKE.TG Demo Day. LIKE.TG Developer Advocates will guide you through the challenge, and help you convert your enterprise app idea into a marketable asset. It’s also a great way to get LIKE.TG certified for free, says Joey Chan, a LIKE.TG MVP based in the Philippines. “Starting as a LIKE.TG Developer is the best decision I’ve made for my career,” he says. “I have joined programming competitions since my university days to hone my skills. This is a great opportunity for everyone in the region to learn and get certified for free!” How to join the ASEAN Developer Challenge Participating in the challenge couldn’t be easier. All you need to do is follow these three simple steps: First, sign up for a free Trailblazer.me account and register for the challenge. Don’t forget to read the program terms. Next, register for our three training webinars. Complete the Trails on Trailhead that we’ll share with you after each webinar. The first webinar will be held at 1:30 p.m. SGT on September 1, 2021. Finally, build an app and submit it by 6:30 p.m. SGT on Sunday, October 17, 2021 What happens next? We’ll feature your app on our Developer community blog. You’ll also reveal your app to LIKE.TG customers and partners at an official LIKE.TG Demo Day at 11:00 a.m. SGT on Wednesday, October 27, 2021. All participants who complete the required Trails on Trailhead will receive a US$200 Certification Voucher. All participants who attend the Demo Day will receive a US$400 Certification Voucher. Get your ticket to the LIKE.TG community Your LIKE.TG journey doesn’t end on Demo Day. As a certified LIKE.TG Developer, you’ll be a valued member of the LIKE.TG community. Johan Yu, a LIKE.TG MVP based in Singapore, says the challenge is a great way for ASEAN developers to showcase their talent, build their careers, and become an integral part of the growing LIKE.TG ecosystem. “It’s great to see such programs for the ASEAN community,” he says. “It will help to showcase our expertise, the power of the LIKE.TG platform, and build networks within the community. “I’d like to ask all ASEAN developers to join this program and use it to get LIKE.TG certified. I’m excited to see what our developers build!” Start your LIKE.TG App Developer journey and register for the ASEAN Developer Challenge now.

Mobile technology adoption is accelerating across the Asia Pacific. In The Mobile Economy Asia Pacific 2020 report, GSMA estimates that the total number of mobile internet users in the region will grow to around 2.7 billion by 2025 (that’s 61% of the population). Mobile apps, in particular, are immensely popular in the Asia Pacific. Today, apps like Grab and Shopee are an indispensable part of everyday life for many people. The bottom line? Businesses need to harness the power of mobile apps if they want to stay engaged with their customers and employees. The good news is that, unlike a few years ago when mobile app development was the domain of IT teams, today low-code app development platforms have made launching digital marketplace and workplace app solutions easier and more inclusive. Here’s how you can benefit from mobile app development in a low-code environment: Low-code app development with clicks, not code The accelerated pace of digital transformation demands rapid development of business applications, which is possible in a low-code environment. Out-of-the-box PaaS (Platform-as-a-Service) solutions allow organisations to build functional business apps with just a few clicks, without the need for an extensive IT team. These solutions are cost-effective and considerably reduce the time taken to build and deploy apps by using customisable templates, drag and drop tools, and other app building components. Solutions like the LIKE.TG Lightning App Builder can help you build customised business apps by integrating ready-made components such as API services, data integration services, authentication, event log framework, analytics, and collaboration. Rapidly test and deploy apps Performance and vulnerability testing are essential even for low-code apps and need an environment that can support such rapid development. Testing spaces like Sandbox and Scratch.org allow developers to test apps and make any changes in a secure, isolated environment. They also ensure there is no business disruption during the app testing or while making any changes. Enable business-critical customisations in-house There is a growing demand for digital skills across the region. For example, in Singapore, 91% of managers believe that the COVID-19 pandemic has accelerated the need for digital skills in their organisation. But hiring expert talent on a budget is also a challenge. Empowering the existing team to become citizen developers can address this issue. Even business admins, managers, and team leads can build apps that can extend LIKE.TG’s out-of-the-box functionalities to deliver critical customisations. These stakeholders can, among other things: Automate complicated business processes into seamless workflows Set triggers for alerts and notifications (for instance, when a new or big sales opportunity arrives) Set security levels and access permissions based on role and hierarchy in the team Build custom validations for data entry to ensure compliance with business rules (for example making certain fields mandatory or setting rules on password strength, etc) Prepare your workplace for successful remote working With the shift to remote work environments over the past year, your employees have also become the consumers of your remote working setup. This includes file sharing and transfer, remote collaboration, 24/7 access to data, etc. Hence, there is a need to focus on improving the overall digital experience for employees as well. Low-code app development platforms help organisations champion this internal mandate too. Using LIKE.TG Platform, you can easily build productivity-driving enterprise mobile applications for your employees. Integrate these with back-end systems to give employees access to all critical data anytime, anywhere. The apps can be fully customised to support a team or employee’s unique line of work and responsibilities. You can also update these apps using simple click-and-point and drag-and-drop tools that let you try-test-launch easy and fast. Low-code app development will rise to prominence in the new normal, as ‘digital first’ becomes the modus operandi of every business. According to Gartner, low-code application building will consolidate more than 65% of all app development functions by 2024. Organisations can leverage the benefits of LIKE.TG Platform to create powerful, intuitive, and engaging mobile apps in no time with easy-to-use components like no-code builders. This post originally appeared on the I.N.-version of the LIKE.TG blog.

The trail to net zero is a shared journey explains Boon Poh Mok, Director of Government Affairs & Public Policy, Southeast Asia & Greater China, LIKE.TG. When the public sector, private businesses, and people come together, they can accelerate sustainable outcomes for business and the planet. Businesses in Asia Pacific are increasingly committing to net zero. By the end of 2021, 86% of companies across the region were already setting net zero targets or intended to do so over the next 12 months. ASEAN countries in particular are forging ahead on the path to net zero. In March 2021, the Singapore government announced The Singapore Green Plan to advance the nation’s agenda on sustainable development. Committed action is also being taken by other countries in the region — Malaysia is implementing the Green Technology Master Plan 2017-2030 to create a low-carbon and resource efficient economy. Vietnam’s government has issued the country’s National Climate Change Strategy to 2050 to implement its COP26 commitments. In 2022, LIKE.TG commissioned Access Partnership to prepare the Trail to Net Zero for Singapore report to investigate the sustainability efforts in the nation. The report also provides recommendations to accelerate the path to net zero. While it examines Singapore’s net zero journey, its recommendations are also useful to policymakers and business decision-makers across the ASEAN region. Here are some of the key findings and recommendations: Sustainability requires a public-private-people approach Climate change is a global challenge. Being a low-lying city-state, Singapore is particularly vulnerable to extreme weather events and rising temperatures. The Singapore Green Plan charts ambitious targets over the next 10 years to enable the nation to achieve its net zero aspirations with committed actions. Singapore’s climate initiatives focus on lowering emissions through efficient power generation and energy demand, and boosting green spaces. A successful trail to net zero for Singapore will need the public sector, private sector, and people to work together. The public sector has taken the lead by setting the climate policy for achieving net zero. It is also partnering with the private sector in developing and implementing cutting-edge climate technologies. It provides incentives and grants to promote startups and ecopreneurs who build innovative solutions that merge business with positive social impact. It is equally important for the people to take advantage of opportunities to upskill themselves on sustainability initiatives. This can help them appreciate the importance of committed climate action and align their decision making with larger sustainability goals. The business opportunity in net zero YouGov surveys commissioned by LIKE.TG found that Singapore businesses strongly support action on climate change. The government’s net zero commitments resonated well in the business community — with 81% of managers supporting Singapore setting net zero emissions target by 2050. When asked whether enough is being done to address climate change, 54% of managers believed the government should be doing more, while 66% believed businesses should do more. Businesses also had a sound understanding of the potential for growth opportunities in the transition to net zero. Singapore managers were three times more likely to think that achieving a net zero economy by 2050 will result in more jobs than less jobs (39% compared to 13%). The Singapore Green Plan 2030 projects a green economy will create 55,000 new jobs in Singapore over the next 10 years, with at least 4,000 created to date. Businesses are also more conscious of emissions across their value chain. Almost two-thirds (61%) of Singaporean managers are more likely to purchase products or services from a supplier business with a net zero target. Technology has an important role to play On the trail to net zero, it is critical to adopt technologies that help reduce emissions and increase energy efficiency. Technology can open up opportunities for business innovation and growth, while helping to switch to more sustainable solutions. Artificial intelligence (AI) offers many use cases to achieve sustainability outcomes. It is already being used in Singapore to monitor pollution levels and mitigate extreme rainfall events. Other potential uses include smarter decision making for decarbonisation and efficient allocation of renewable energy. Adoption of cloud computing can also enable businesses to lower their environmental impact, while offering greater flexibility, cost efficiency, speed, and business continuity. A study by S&P Global Market Intelligence has shown significant energy savings of 79% from moving business applications and IT workloads to the cloud. Trail to Net Zero for Singapore reveals that a reduction of one million metric tons of carbon dioxide emissions can be achieved in 2022 by migrating to the cloud. Emissions reductions can be further boosted if cloud operators begin sourcing 100% renewable energy for their operations. Walking the talk on net zero While many businesses today talk about sustainability, it is critical to take actions and track progress to build credibility with customers and stakeholders. One of the ways to do this is to have a third party audit of your sustainability initiatives and provide recommended actions to achieve net zero. Public and private organisations can also adopt a shared digital platform to forecast and track emissions. This can provide a single source of truth to ensure better decision making across an organisation’s operations, including its supply chain. Sustainability is one of LIKE.TG’s core values, and we continually put it into action. For over a decade now, LIKE.TG has been on a sustainability transformation journey. We are a net zero company, and have achieved net zero emissions across our value chain, and are sourcing 100% renewable energy for our operations. We have funded more than 40 million trees as part of our 100 million trees goal. Our commitment to sustainability transformation has helped inform our Climate Action Plan and forms the basis of the Net Zero Cloud platform to help businesses go carbon neutral faster. Sustainability is a shared journey. We walk the talk and walk together with businesses on their trail to net zero. Learn more about Singapore’s sustainability mission in Trail to Net Zero for Singapore Go carbon-neutral faster with Net Zero Cloud. WATCH DEMO

You’ve decided that you’re ready for digital transformation, you’ve developed a strategy, and you might have even begun implementing it. Now, it’s time to configure the Customer 360 platform to serve the specific needs of your business. Customer 360 consists of more than a dozen independent products, or ‘apps’, which can either be used on their own or linked together. This modular approach means you only implement the components your business actually needs. You and your team can enjoy streamlined workflows, with the option to add or remove apps if and when you need to. Further customisation is possible within each app, or you can use them straight out of the box — whichever suits you better. How do you figure out which products are right for your digital transformation? It’s simple: just complete the Create Your Own Customer 360 Package quiz for an accurate summary of which apps will benefit you the most. Read on for a couple of examples of how LIKE.TG Customer 360 can be configured, plus some top-line questions to think about before you dive into the quiz. Unique solutions for every sector LIKE.TG’s core industry solutions are for Financial Services, Media, Communications, Energy, Utilities, and Manufacturing. That said, Customer 360 can be configured to provide solutions for any business. For example, a growing retail business that has just started selling online might add the Commerce Cloud and Marketing Cloud apps to its Customer 360 platform. The business can use the Commerce Cloud app to personalise each customer purchase and to sell through any channel. It can also use the Marketing Cloud app for curating hyper-personalised customer journeys, based on deep customer insights Another example: a subscriber-based media business in the midst of a digital transformation might select the Sales Cloud and Service Cloud apps. The Sales Cloud app helps maintain in-depth records for each subscriber, track sales opportunities, and review sales forecasts. Service Cloud provides advanced call-centre management and insights into every customer interaction. Which Customer 360 apps should I choose? Which apps could benefit your business the most? To prep for the LIKE.TG Customer 360 quiz, consider the following questions: What is it you want to do? Every business wants to prosper, but each has different ideas about how to achieve that prosperity. Is the goal of your digital transformation to achieve more leads? Shorten your sales funnel? Improve customer satisfaction? Or something else? The answer (or answers) to this question will lead you to the Customer 360 apps that can make your digital transformation a success. Who’s going to use the platform? Knowing which of your departments will start using Customer 360 is another effective way to identify the specific apps you need. As time goes on and you roll out the platform to other departments, more apps can be considered. Each app you choose can be tailored for use by certain people within a department. Therefore, it’s a good idea to know from the outset who those people will be. For example, Sales Cloud can be used differently by sales reps, sales leaders, and service agents. Should you opt for a package designed for small or new businesses? If your business is young, you may not yet know exactly how you will use the Customer 360 platform, and that’s OK. LIKE.TG has off-the-shelf solutions for fledgling businesses, such as our LIKE.TG Essentials package. If you are new to using a CRM, this package contains everything you need to get up and running. As your business grows, the Customer 360 Package quiz or a LIKE.TG rep can help you modify your platform. Could you benefit from a business collaboration space? Any business that’s planning digital transformation should consider how its team members will communicate while working. That’s especially important if employees are working remotely in various parts of the world. Consider using Slack. In July 2021, LIKE.TG acquired Slack. Slack is a channel-based messaging platform that brings people and tools together in one place. This helps teams to stay productive and aligned from anywhere. Slack is used by millions of people around the world and enables entire organisations to work far more efficiently and effortlessly. Adapting to every step of your digital transformation As your organisation grows and you begin to reap the rewards of digital transformation, you can add functionality to your Customer 360 platform in order to amplify your gains. In fact, using more apps within the Customer 360 platform directly correlates with positive business outcomes. Almost three quarters (72%) of businesses using more than one Customer 360 app report improved time to ROI, while 95% of those with two or more apps report improved efficiency and productivity. Want to ensure your digital transformation succeeds but aren’t sure where to start? We can help you. Take the Customer 360 Package quiz to learn which LIKE.TG apps will benefit you the most. Soon, you’ll be on your way to realising your digital transformation vision.

Dreamforce is the crown jewel of the LIKE.TG event universe — and it was epic. From amazing keynote sessions to demos showcasing the tools to solve your biggest challenges, Dreamforce had something for everyone (including the very best swag!). But are you ready for the understatement of the year? That’s right – AI pretty much stole the show. From generating hyper-relevant sales emails to prospects to anticipating a customer service issue with a VIP, AI is here to serve and support every aspect of the business.Here’s the thing: it’s IT that enables everyone else to leverage AI.As an IT leader, you’re already feeling the pressure to pivot to an AI-led approach across your organization. But you’re faced with the harsh reality of connecting and harmonizing your data while adhering to security and data governance standards? How can you build AI-powered applications that you can trust? And how can you do it now? AI for IT: 3 launches you can use Let’s take a look at how these new AI launches, all announced at Dreamforce 2023, are helping IT teams get more done – and how you can, too! 1. Unlock the full power of your data According to our latest State of IT report, 86% of IT decision-makers worldwide believe that generative AI will play a significant role in their organizations in the near future.However, the average organization reported more than 1000 distinct applications used across the enterprise. Scarier still, fewer than a third of these apps are integrated. This is a problem when AI depends on accurate, unified data to deliver critical insights and predictions. In MuleSoft’s 2023 Connectivity Benchmark Report, enterprise IT leaders estimated spending an average of $4.7 million per year on custom integration efforts. That’s an increase of 31% from their 2022 estimate of $3.6 million. With this in mind, it’s critical to have the right tools and development environments at the ready to implement and build the experiences customers expect. All of this with security and powerful generative AI capabilities built right in. One way to get connected quickly is with MuleSoft, loaded with new generative AI capabilities to make integration faster than ever before. Connect to any data or system, wherever it resides, with security and governance built in. The MuleSoft Accelerator for Data Cloud can help you unlock and connect to critical industry systems quickly and securely. Once unlocked, your teams can finally harmonize with existing data sources through the power of LIKE.TG Data Cloud. This enables you to get a unified view of every customer so that you can deliver the right experiences at the right time every time.Harmonizing data quickly? That’s music to our ears. Get IT articles selected just for you, in your inbox Sign up now 2. Put your data to work If your teams have tackled the data unification challenge — bravo! After all, it’s these integration challenges that slow down digital transformation initiatives for 80% of IT teams. But it’s actually garnering insights and getting recommendations from AI that IT leaders are being pressured to deliver. With unified data in place, how can we start to see the benefits of AI? Well, IT teams can make the building of apps and automations a bit easier with Prompt Builder.Because every generative AI-powered CRM app depends on the quality of the AI prompt, it’s useful to get a boost with the provided prompt templates. These templates guide IT teams in building AI prompts that will root the AI in specific data and instructions — making it possible for the AI to deliver better suggestions more quickly. This low-code prompt management tool allows IT teams to build, test, and fine-tune trusted AI prompts within the Einstein Trust Layer. Any sensitive data is automatically masked to limit bias and toxicity. With this tool, IT teams can leverage AI to build everything from auto-generated emails to product descriptions for websites. This means freeing up time to focus on deeper, more sophisticated IT challenges. Low-code. Painless. That’s how AI should be. 3. Deploy safely and quickly With a tremendous amount of pressure to consistently deliver new solutions, IT leaders must balance speed and delivery with security.We know all too well what can happen when an organization skirts security concerns to increase deployment speed. According to our recent State of the Connected Customer Report, the average cost of not complying with data protection regulations is $14.8 million. That’s a lot, and we want to work toward avoiding any data breaches.One thing AI can help with is mitigating security concerns without compromising on deployment speed. By using secure development environments with sandboxes, IT teams can safely test AI processes without the risk of pushing any errors to the production org.Plus, sandboxes are also a great space to train teams on how to responsibly build code with the help of generative AI.When it comes to production environments, a new feature will help protect your sensitive data and stay compliant. Privacy Center will feature new data management policies where IT teams can delete stale data or de-identify at scale to protect the production org.But if something were to go awry, we’ve got you covered there, too. LIKE.TG Backup is a native solution that allows you to protect against corruption, data loss, or coding errors by providing daily backups and the ability to restore quickly.Delivering new solutions with peace of mind. Sounds peaceful. Don’t sleep on AI What’s top-of-mind for IT leaders is how to get the most out of AI — now. That starts with the right tools to pull together your data with security and governance built-in. Leading IT organizations are already transforming to accommodate the latest AI trends. Make sure you’re one of them.

Does it seem like everyone around you is casually tossing around terms like “generative AI,” “large language models,” or “deep learning”? Feeling a little lost on the details? We’ve created a primer on everything you need to know to understand the newest, most impactful technology that’s come along in decades. Let’s dive into the world of generative AI. We’ve put together a list of the most essential terms that will help everyone in your company — no matter their technical background – understand the power of generative AI. Each term is defined based on how it impacts both your customers and your team.” And to highlight the real-world applications of generative AI, we put it to work for this article. Our experts weighed in on the key terms, and we let a generative AI tool lay the groundwork for this glossary. Each definition needed a human touch to get it ready for publication, but it saved loads of time. Generative AI Terms by Topic AI CORE TERMS Artificial intelligence (AI) Artificial neural network Augmented intelligence CRM with AI Deep learning Generative AI Generator GPT Machine learning NLP Transformer AI TRAINING & LEARNING Discriminator (in GAN) GAN Hallucination LLM Model Prompt engineering Sentiment analysis Supervised learning Unsupervised learning Validation ZPD AI ETHICS Ethical AI Maturity Model Explainable AI (XAI) Machine learning bias Artificial intelligence (AI) AI is the broad concept of having machines think and act like humans. Generative AI is a specific type of AI (more on that below). What it means for customers: AI can help your customers by predicting what they’re likely to want next, based on what they’ve done in the past. It gives them more relevant communications and product recommendations, and can remind them of important upcoming tasks (example: It’s time to reorder). It makes everything about their experience with your organisation more helpful, personalised, efficient, and friction-free. What it means for teams: AI helps your teams work smarter and faster by automating routine tasks. This saves employees time, offers customers faster service, and provides more personalised interactions, all of which improves customer retention to drive the business. Artificial neural network (ANN) An ANN is a computer program that mimics the way human brains process information. Our brains have billions of neurons connected together, and an ANN (also referred to as a “neural network”) has lots of tiny processing units working together. It’s like a team all working to solve the same problem. Every team member does their part, then passes their results on. At the end, you get the answer you need. With humans and computers, it’s all about the power of teamwork. What it means for customers: Customers benefit in all sorts of ways when ANNs are solving problems and making accurate predictions – like highly personalised recommendations that result in a more tailored, intuitive, and ultimately more satisfying customer experience. Neural networks are excellent at recognising patterns, which makes them a key tool in detecting unusual behaviour that may indicate fraud. This helps protect customers’ personal information and financial transactions. What it means for teams: Teams benefit, too. They can forecast customer churn, which prompts proactive ways to improve customer retention. ANNs can also help in customer segmentation, allowing for more targeted and effective marketing efforts. In a CRM system, neural networks could be used to predict customer behaviour, understand customer feedback, or personalise product recommendations. Augmented intelligence Think of augmented intelligence as a melding of people and computers to get the best of both worlds. Computers are great at handling lots of data and doing complex calculations quickly. Humans are great at understanding context, finding connections between things even with incomplete data, and making decisions on instinct. Augmented intelligence combines these two skill sets. It’s not about computers replacing people or doing all the work for us. It’s more like hiring a really smart, well-organised assistant. What it means for customers: Augmented intelligence lets a computer crunch the numbers, but then humans can decide what actions to take based on that information. This leads to better service, marketing, and product recommendations for your customers. What it means for teams: Augmented intelligence can help you make better and more strategic decisions. For example, a CRM system could analyse customer data and suggest the best time for sales or marketing teams to reach out to a prospect, or recommend products a customer might be interested in. Customer Relationship Management (CRM) with generative AI CRM is a technology that keeps customer records in one place to serve as the single source of truth for every department, which helps companies manage current and potential customer relationships. Generative AI can make CRM even more powerful — think personalised emails pre-written for sales teams, ecommerce product descriptions written based on images alone, marketing campaign landing pages, contextual customer service ticket replies, and more. What it means for customers: A CRM gives customers a consistent experience across all channels of engagement, from marketing to sales to customer service and more. While customers don’t see a CRM, they feel the connection during every interaction with a brand. What it means for teams: A CRM helps companies stay connected to customers, streamline processes, and improve profitability. It lets your teams store customer and prospect contact information, identify sales opportunities, record service issues, and manage marketing campaigns, all in one central location. For example, it makes information about every customer interaction available to anyone who might need it. Generative AI amplifies CRM by making it faster and easier to connect to customers at scale – think marketing lead-gen campaigns automatically translated to reach your top markets across the globe, or recommended customer service responses that help agents solve problems quickly and identify opportunities for future sales. Deep learning Deep learning is an advanced form of AI that helps computers become really good at recognising complex patterns in data. It mimics the way our brain works by using what’s called layered neural networks, where each layer is a pattern (like features of an animal) that then lets you make predictions based on the patterns you’ve learned before (ex: identifying new animals based on recognised features). It’s really useful for things like image recognition, speech processing, and natural-language understanding. What it means for customers: Deep learning-powered CRMs create opportunities for proactive engagement. They can enhance security, make customer service more efficient, and personalise experiences. For example, if you have a tradition of buying new fan gear before each football season, deep learning connected to a CRM could show you ads or marketing emails with your favourite team gear a month before the season starts so you’ll be ready on game day. What it means for teams: In a CRM system, deep learning can be used to predict customer behaviour, understand customer feedback, and personalise product recommendations. For example, if there’s a boom in sales among a particular customer segment, a deep learning-powered CRM could recognise the pattern and recommend increasing marketing spend to reach more of that audience pool. Discriminator (in a GAN) In a Generative Adversarial Network (GAN), the discriminator is like a detective. When it’s shown pictures (or other data), it has to guess which are real and which are fake. The “real” pictures are from a dataset, while the “fake” ones are created by the other part of the GAN, called the generator. The discriminator’s job is to get better at telling real from fake, while the generator tries to get better at creating fakes. This is the software version of continuously building a better mousetrap. What it means for customers: Discriminators in GANs are an important part of fraud detection, so their use leads to a more secure customer experience. What it means for teams: Discriminators in GANs help your team evaluate the quality of synthetic data or content. They aid in fraud detection and personalised marketing. Ethical AI maturity model An Ethical AI maturity model is a framework that helps organisations assess and enhance their ethical practices in using AI technologies. It maps out the ways organisations can evaluate their current ethical AI practices, then progress toward more responsible and trustworthy AI usage. It covers issues related to transparency, fairness, data privacy, accountability, and bias in predictions. What it means for customers: Having an ethical AI model in place, and being open about how you use AI, helps build trust and assures your customers that you are using their data in responsible ways. What it means for teams: Regularly evaluating your AI practices and staying transparent about how you use AI can help you stay aligned to your company’s ethical considerations and societal values. Explainable AI (XAI) Remember being asked to show your work in maths class? That’s what we’re asking AI to do. Explainable AI (XAI) should provide insight into what influenced the AI’s results, which will help users to interpret (and trust!) its outputs. This kind of transparency is important when dealing with sensitive systems like healthcare or finance, where explanations are required to ensure fairness, accountability, and in some cases, regulatory compliance. What it means for customers: If an AI system can explain its decisions in a way that customers understand, it increases reliability and credibility. It also increases user trust, particularly in sensitive areas like healthcare or finance. What it means for teams: XAI can help employees understand why a model made a certain prediction. Not only does this increase their trust in the system, it also supports better decision-making and can help refine the system. Generative AI Generative AI is the field of artificial intelligence that focuses on creating new content based on existing data. For a CRM system, generative AI can be used to create a range of helpful things, from writing personalised marketing content, to generating synthetic data to test new features or strategies. What it means for customers: Better and more targeted marketing content, which helps them get exactly the information they need and no more. What it means for teams: Faster builds for marketing campaigns and sales motions, plus the ability to test out multiple strategies across synthetic data sets and optimise them before anything goes live. Generative adversarial network (GAN) One of two deep learning models, GANs are made up of two neural networks: a generator and a discriminator. The two networks compete with each other, with the generator creating an output based on some input, and the discriminator trying to determine if the output is real or fake. The generator then fine-tunes its output based on the discriminator’s feedback, and the cycle continues until it stumps the discriminator. What it means for customers: They allow for highly customised marketing that uses personalised images or text – like custom promotional imagery for every customer. What it means for teams: They can help your development team generate synthetic data when there is a lack of customer data. Especially useful when privacy concerns arise around using real customer data. Generative pre-trained transformer (GPT) GPT is a neural network family that is trained to generate content. GPT models are pre-trained on a large amount of text data, which lets them generate clear and relevant text based on user prompts or queries. What it means for customers: Customers have more personalised interactions with your company that focus on their specific needs. What it means for teams: GPT could be used to automate the creation of customer-facing content, or to analyse customer feedback and extract insights. Generator A generator is an AI-based software tool that creates new content from a request or input. It will learn from any supplied training data, then create new information that mimics those patterns and characteristics. ChatGPT by OpenAI is a well-known example of a text-based generator. What it means for customers: Using generators, it’s possible to train AI chatbots that learn from real customer interactions, and continuously create better and more helpful content. What it means for teams: Generators can be used to create realistic datasets for testing or training purposes. This can help your team find any bugs in a system before it goes live, and let new hires get up to speed in your system without impacting real data. Hallucination A hallucination happens when generative AI analyses the content we give it, but comes to an erroneous conclusion and produces new content that doesn’t correspond to reality. An example would be an AI model that’s been trained on thousands of photos of animals. When asked to generate a new image of an “animal,” it might combine the head of a giraffe with the trunk of an elephant. While they can be interesting, hallucinations are undesirable outcomes and indicate a problem in the generative model’s outputs. What it means for customers: When companies monitor for and address this issue in their software, the customer experience is better and more reliable. What it means for teams: Quality assurance will still be an important part of an AI team. Monitoring for and addressing hallucinations helps ensure the accuracy and reliability of AI systems. Large language model (LLM) An LLM is a type of artificial intelligence that has been trained on a lot of text data. It’s like a really smart conversation partner that can create human-sounding text based on a given prompt. Some LLMs can answer questions, write essays, create poetry, and even generate code. What it means for customers: personalised chatbots that offer human-sounding interactions, allowing customers quick and easy solutions to common problems in ways that still feel authentic. What it means for teams: Teams can automate the creation of customer-facing content, analyse customer feedback, and answer customer inquiries. Machine learning Machine learning is how computers can learn new things without being programmed to do them. For example, when teaching a child to identify animals, you show them pictures and provide feedback. As they see more examples and receive feedback, they learn to classify animals based on unique characteristics. Similarly, machine learning models learn from labelled data to make accurate predictions and decisions. They generalise and apply their knowledge to new examples, just as humans do. What it means for customers: When a company better understands what customers value and want, it leads to enhancements in current products or services, or even the development of new ones that better meet customer needs. What it means for teams: Machine learning can be used to predict customer behaviour, personalise marketing content, or automate routine tasks. Machine learning bias We’ve all heard the phrase “garbage in, garbage out,” right? Machine learning bias is just a turbocharged AI version of that. When computers are fed biassed information, they make biassed decisions. This can be the result of a deliberate decision by the humans feeding the computer data, by accidentally incorporating biassed data, or when the algorithm makes wrong assumptions during the learning process, leading to biassed results. Example: If a loan approval model is trained on historical data that shows a trend of approving loans for certain demographics (like gender or race), it may learn and perpetuate those biases. This isn’t because of a prejudice in the system, but a bias in the training data. It will have huge implications for the accuracy and effectiveness of the system, and help build equality and trust among customers. What it means for customers: Working with companies that actively engage in overcoming bias leads to more equitable experiences, and builds trust. What it means for teams: It’s important to check for and address bias to ensure that all customers are treated fairly and accurately. Understanding machine learning bias and knowing your organisation’s controls for it helps your team have confidence in your processes. Model This is a program that’s been trained to recognise patterns in data. You could have a model that predicts the weather, translates languages, identifies pictures of cats, etc. Just like a model aeroplane is a smaller, simpler version of a real aeroplane, an AI model is a mathematical version of a real-world process. What it means for customers: The model can help customers get much more accurate product recommendations. What it means for teams: This can help teams to predict customer behaviour, and segment customers into groups. Natural language processing (NLP) NLP is a field of artificial intelligence that focuses on how computers can understand, interpret, and generate human language. It’s the technology behind things like voice-activated virtual assistants, language translation apps, and chatbots. What it means for customers: NLP allows customers to interact with systems using normal human language rather than complex commands. Voice-activated assistants are prime examples of this. This makes technology more accessible and easier to use, improving user experiences. What it means for teams: NLP can be used to analyse customer feedback, power chatbots, or automate the creation of customer-facing content. Prompt engineering You don’t need an engineering degree for this one. Prompt engineering means figuring out how to ask a question to get exactly the answer you need. It’s carefully crafting or choosing the input (prompt) that you give to a machine learning model to get the best possible output. What it means for customers: When your generative AI tool gets a strong prompt, it’s able to deliver a strong output. The stronger, more relevant the prompt, the better the end user experience. What it means for teams: Can be used to ask a large language model to generate a personalised email to a customer, or to analyse customer feedback and extract key insights. Sentiment analysis Sentiment analysis involves determining the emotional tone behind words to gain an understanding of the attitudes, opinions, and emotions of a speaker or writer. It is commonly used in CRM to understand customer feedback or social media conversation about a brand or product. What it means for customers: Customers can offer feedback through new channels, leading to more informed decisions from the companies they interact with. What it means for teams: Sentiment analysis can be used to understand how customers feel about a product or brand, based on their feedback or social media posts, which can inform many aspects of brand or product reputation and management. Supervised learning Supervised learning is when a model learns from examples. It’s like a teacher-student scenario: the teacher provides the student (the model) with questions and the correct answers. The student studies these, and over time, learns to answer similar questions on their own. It’s really helpful to train systems that will recognise images, translate languages, or predict likely outcomes. (Check out unsupervised learning below). What it means for customers: Increased efficiency and systems that learn to understand their needs via past interactions. What it means for teams: Can be used to predict customer behaviour or segment customers into groups, based on past data. Transformer Transformers are a type of deep learning model, and are especially useful for processing language. They’re really good at understanding the context of words in a sentence because they create their outputs based on sequential data (like an ongoing conversation), not just individual data points (like a sentence without context). The name “transformer” comes from the way they can transform input data (like a sentence) into output data (like a translation of the sentence). What it means for customers: Businesses can enhance the customer service experience with personalised AI chatbots. These can analyse past behaviour and provide personalised product recommendations. They also generate automated (but human-feeling) responses, supporting a more engaging form of communication with customers. What it means for teams: Transformers help your team generate customer-facing content, and power chatbots that can handle basic customer interactions. Transformers can also perform sophisticated sentiment analysis on customer feedback, helping you respond to customer needs. Unsupervised learning Unsupervised learning is letting AI find hidden patterns in your data without any guidance. This is all about allowing the computer to explore and discover interesting things on its own. Imagine you have a big bag of mixed-up puzzle pieces, but you don’t have the picture on the box to refer to, so you don’t know what you’re making. Unsupervised learning is like figuring out how the pieces fit together, looking for similarities or groups without knowing what the final picture will be. What it means for customers: When we uncover hidden patterns or segments in customer data, it enables us to deliver completely personalised experiences. Customers will get the most relevant offers and recommendations, enhancing customer satisfaction. What it means for teams: Teams get valuable insights and a new understanding of complex data. It enables teams to discover new patterns, trends, or anomalies that may have been overlooked, leading to better decision-making and strategic planning. This enhances productivity and drives innovation within the organisation. Validation In machine learning, validation is a step used to check how well a model is doing during or after the training process. The model is tested on a subset of data (the validation set) that it hasn’t seen during training, to ensure it’s actually learning and not just memorising answers. It’s like a pop quiz for AI in the middle of the semester. What it means for customers: Better-trained models create more usable programs, improving the overall user experience. What it means for teams: Can be used to ensure that a model predicting customer behaviour or segmenting customers will work as intended. Zone of proximal development (ZPD) The Zone of Proximal Development (ZPD) is an education concept. For example, each year students progress their maths skills from adding and subtracting, to multiplication and division, and even up to complex algebra and calculus equations. The key to advancing is progressively learning those skills. In machine learning, ZPD is when models are trained on progressively more difficult tasks, so they will improve their ability to learn. What it means for customers: When your generative AI is trained properly, it’s more likely to produce accurate results. What it means for teams: Can be applied to employee training so an employee could learn to perform more complex tasks or make better use of the CRM’s features. Take the next step with generative AI Generative AI has the power to help all of your teams connect more closely with your customers, unlock creativity, and increase productivity. From a business perspective, there’s almost no part of your organisation that AI can’t make more efficient. Sales, service, marketing, and commerce applications are all able to use the power of generative AI to deliver better, more tailored solutions to your customers, and to do so quickly. By letting AI assist us with the more routine tasks of helping our customers thrive, we’ll be able to free our human teams to do what they do best — come up with new ideas and new ways to collaborate, all while building those unique connections that only humans can. Now that you’re up to speed on Generative AI for CRM, see it in action.

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.

These days, AI seems to be everywhere and in everything — from our cars and refrigerators, to our food delivery services, sleep measurement apps, even our toothbrushes. It’s been called the holy grail of computing. But what exactly is AI? Put simply, it’s a piece of code which derives its intelligence from existing data to solve problems and make complex decisions easier and faster. That makes it extremely useful in automating repetitive business tasks, uncovering opportunities for growth, engaging with customers at scale, and saving costs. These benefits are very evident in the call centre scenario. Make every service experience memorable with AI Gone are the days when customer support was perceived as a cost centre. Today, business leaders recognise good customer service as a way to differentiate their organisation, boost customer trust, and catalyse business growth. In fact, 78% of service agents say their company views them as brand ambassadors. But to live up to these expectations, agents have to be empowered with the right tools. This is especially true in a COVID-19 world where the majority of service professionals (75%) say that managing case volume has become more challenging. Not only are they dealing with a rise in cases, but they’re also facing more complex cases with anxious customers who are harder to satisfy. Here’s where AI-powered tools can help. They enable agents to be more productive, find answers quickly, deliver smarter recommendations, and make better-informed decisions. AI chatbots can also help customers self-resolve issues faster. 6 ways AI can add value to your service organisation Here’s a look at how AI tools like Service Cloud Einstein can be used in call centres to optimise both employee efficiency and customer satisfaction: Auto-triaging cases: As case volumes go up, AI can help your call centres do more with less by quickly triaging and routing cases. For instance, Einstein Case Classification automatically predicts and pre-fills case fields based on historical data. This saves agents valuable time and effort. Meanwhile, Einstein Case Routing uses machine learning to direct cases to the right queue in real time — so, customers don’t have to be kept waiting. Recommending responses: Einstein Article Recommendations helps your agents find the right answers to customer cases quickly by surfacing the most relevant knowledge articles within the agent console itself. Einstein Reply Recommendations goes a step further by empowering agents with responses to common questions during chat and messaging conversations. This lowers case resolution time, while enhancing customer satisfaction. Enabling customers to self-serve: Most customers (65%) prefer self-service for simple matters. So, it’s no surprise that AI-powered chatbots like Einstein Bots are becoming increasingly popular. They can immediately engage with customers to answer common FAQs, check the status of a claim, or provide personalised advice. Using voice as digital medium: A solution like Service Cloud Voice can help transcribe the customer’s voice in real time, and route it to the AI engine in LIKE.TG to suggest the next best actions instantly. Let’s say a customer is on a live call with an agent, saying they’re unable to change the temperature on a recently purchased geyser. Based on their inputs, AI can automatically surface a trouble-shooting workflow. This makes it easy for the agent to choose the best course of action, and reduce the turnaround time. Cross-selling and up-selling: Every interaction with a customer is an opportunity to build trust and loyalty. The challenge for agents is to know what to offer customers at what time. AI-powered tools like Einstein Next Best Action can help by automatically recommending products, offers, discounts, or actions that are most likely to boost customer satisfaction. Say, the customer has purchased a travel package. The next best action might be to offer them a good travel insurance plan, or connect them to a local transport service partner. This way, you maximise the impact of your customer interaction. Uncovering actionable insights: Not too long ago, businesses could only analyse a fraction of customer calls — that too, manually. But with AI tools like Service Analytics, you can analyse customer interactions at scale, and derive practical insights on customer churn, CSAT scores, and contact centre performance. These insights delivered in real time can help you proactively adjust and optimise service to deliver the best possible customer experiences. 4 things to think about before adopting AI Everyone wants a piece of the AI pie. But first, identify what exactly you want AI to do in your call centre. Then, determine whether or not the solution you select actually has those capabilities. If you aren’t clear about your objectives, then your agents will only end up with one more tool that isn’t really useful. Some things to consider before you embark on your AI journey: Data quality: AI models are only as good as the quality of data on which they’re built. So, pay attention to the completeness, accuracy, bias, consistency, and labelling of your data. Employee learning curve: Ensure that your AI-enabled tools are intuitive, easy to use, and seamlessly embedded in your CRM. If employees have to struggle to use AI, then it won’t matter how powerful the tool is — it won’t yield optimal returns. Out-of-the-box technology: Look for AI tools that are already robust, comprehensive, and flexible enough that they don’t have to be customised heavily. Too many customisations could result in costly technical debt. Effort investment: You want an AI solution that can be rolled out swiftly and with minimal effort. Complex and lengthy implementation cycles will simply bog down the business. LIKE.TG’s AI offering, Service Cloud Einstein is specially designed to meet these criteria. It can be implemented quickly with minimum customisation and rapid employee adoption. The best part is that Einstein is built right into Service Cloud, your service channels, and your CRM data — which makes it super-easy to roll-out and use. Agents don’t have to toggle between multiple tools when talking to customers. With all AI capabilities they need on a single screen, agents can coordinate service requests much more smoothly, and deliver connected service experiences that your customers love. We’ve only just scratched the surface of AI’s potential. As the technology grows more sophisticated, it will undoubtedly unlock new opportunities to improve both customer and agent experiences, as well as revenue growth. Find out more about our AI offering, Service Cloud Einstein. This post was originally published on the LIKE.TG IN blog.

Everything. Everywhere. All at once. Yes, it’s an Oscar-winning movie, but it also perfectly describes the impact artificial intelligence (AI) is having on businesses, including the job market. The 360 view According to McKinsey, generative AI has the potential to add between $2.6 trillion and $4.4 trillion in value to the global economy across all industries, including banking, retail, high tech, healthcare, and life sciences. It will affect vocations such as customer operations, marketing and sales, software engineering, and research and development. And while there’s been much fear around AI taking our jobs away, the new technology will, in fact, give rise to myriad new jobs for human beings. For example, high-paying roles like prompt engineer — essentially, a master of the art of crafting prompts for GPT interfaces — and AI product manager are currently trending on popular job search sites. According to a recent Salesforce-sponsored IDC white paper of 500 organisations using AI-powered solutions, the next 12 months will also see a sharp increase in hiring for data architects, AI ethicists, and AI solutions architects. That same report predicts 11.6 million new jobs will be created within the LIKE.TG ecosystem alone over the next six years.* What you can do now AI needs people in control in order for it to work properly within our society. And members of the workforce, like you, have the opportunity now to hone existing skills across various industries and learn new skills to grow with the economy. “The exciting thing about these tools is they’re nascent and they’re largely democratised,” said David Berthy, senior director of LIKE.TG Futures. “So, if people have the volition, they can go out and learn how to increase their own value.” Platforms such as LIKE.TG’s Trailhead, Coursera, LinkedIn Learning, and Udemy all offer free and paid certification courses for in-demand AI-related skills. AI will eliminate repetition and create new skills and roles Let’s start by clearing something up: Yes, AI will likely eliminate repetitive job functions — scheduling social media posts, sifting through resumes, poring over data, answering basic customer service questions, sending follow-up emails — but that will free up people to be more strategic, creative, and productive in their current roles. People will now have time to, well, be people. If you’re in sales or customer service, you can now devote more time to interacting with customers to create even better relationships. In marketing? You can spend more focused time on strategic thinking or creative projects. And if you work in the legal or healthcare fields, AI can help analyse and research contracts or help interpret MRIs and X-rays, respectively. Not all new AI jobs will be as obvious as those in engineering or data-related fields. Jobs in healthcare, finance, graphic design, and more will evolve thanks to the assistance of smart AI. “AI will be sort of a background to everything,” said Chris Poole, AI technical consulting lead in LIKE.TG’s global AI practice in professional services. “I think it’s going to be very interesting to see.” Get articles selected just for you, in your inbox Sign up now How generative AI is creating new careers — 12 roles to consider What’s new and interesting to the AI curious? Here are a dozen jobs to look out for — some that currently exist (if only in early iterations), and some that Berthy envisions existing in the near term. Is one in your future? Prompt engineer Prompt engineers excel at writing prompts for AI tools, like a GPT product or chatbot, to get the most accurate or desired results. Some refer to prompt engineering as “AI whispering” because you’re essentially guiding the generative AI product to give you a creative solution to your question or prompt. AI trainer An AI trainer works behind the scenes to make sure an AI algorithm does what it’s supposed to do. The trainer prepares heavy data sets to teach chatbots how to think and interact with user inputs so the AI responds with more natural-sounding human language. Trainers also fine-tune the data and systems to achieve proper outcomes. Simply put: “AI trainers teach AI systems how to think, interact, and be genuinely useful,” according to Boost.AI. AI learning designer As AI technology rapidly grows and changes, organisations will need people to optimise personal learning at scale, Berthy said. Not only will these roles help train people on AI systems and how to work alongside AI copilots, but they’ll also refine the ways in which people learn. “Companies that have better versions of [learning systems] will be better equipped to adapt these new technologies,” Berthy said. AI instructor As companies continue to implement AI technologies, someone will need to teach employees how to use them. AI instructors teach people the skills they’ll need to advance their careers, whether directly or indirectly involved with AI. They’re responsible for developing curriculum and teaching methods, leading hands-on classes and lectures, and more around AI education. Sentiment analyser Even though it can understand and interpret human language, AI is not human and does not have feelings. It doesn’t understand nuance and it can’t interpret emotion. That’s where a sentiment analyser comes in. They work with a sentiment analysis program to determine whether data pulled off the internet, like social media comments or product feedback, is positive, negative, or neutral, and to identify its emotional tone. Stitcher A stitcher is a generalist who uses AI to combine a range of skills held by multiple roles into one role or workflow. For example, this job will use AI to more quickly stitch together modular software tools into workflows that create unique value for customers, Berthy said. So, instead of having multiple people work on a project from design and storytelling to engineering and overall business implementation, the stitcher will tackle it all by using AI. Interpersonal coach This role will help people living and working in a digital-first world and working with AI to gain basic interpersonal skills like relational intelligence, empathy, active listening, and connecting in face-to-face interactions. It’s similar to a business coach, but focused on helping people who work behind a screen or mostly with machines. Workflow optimiser This role will use data and intelligence to have a bird’s-eye view across a company, and determine where AI could help people be more productive. This person will use AI to review how people and teams work, and highlight productivity gaps to increase overall efficiency. AI compliance manager As AI regulations continue to get refined globally, an AI compliance manager ensures an organisation’s AI processes adhere to relevant regulations, ethical standards, and industry guidelines. They make sure data-handling practices align with privacy laws and also mitigate AI’s potential impact on an organisation. AI security manager If AI technology gets into the wrong hands, it can quickly become dangerous. The AI security manager will be an important role within an organisation to ensure AI systems are used properly. They’ll also protect against vulnerabilities and security threats. Chief AI officer The newest role to enter the C-suite, the CAIO sets the overall AI strategy for an organisation. This includes the responsible and ethical design, development, and implementation of all AI tech produced by the company. Chief data and analytics officer (CDAO) The chief data and analytics officer oversees all things related to data and analytics in a company. Sometimes this role is shared by two people, one as chief data officer (CDO) and the other as chief analytics officer (CAO). How to prepare for new AI careers With all of these new AI jobs emerging, it’s time to embrace training and start playing around with the free tools at your disposal. “Don’t be afraid of the tools,” Poole said. “Look at it as a helper that can improve your way of life and your work.” Online learning platforms are making it easier to access these tools and skill up, said Aleksandra Radovanovic, senior product manager of business technology at Okta, a cloud-based identity management service that provides single sign-on solutions for businesses. She said to identify relevant skills and look for online courses to help build them. Trying to gain practical experience, even through certification courses, will also help. “The people who embrace the changes and the opportunity they create and increase their own learning are the ones who will have the brightest futures,” Berthy said. “You can capture that ethos and give people some hope because there’s enormous opportunity to up your own marketability.” *LIKE.TG Economic Impact: LIKE.TG AI-Powered Cloud Solutions Will Generate $948 Billion in New Revenues for Customers by 2028 (doc #US51404923, December 2023)

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.