Redefining Successful REX Strategies

With access to more products and social media channels than ever before, it’s a consumer’s world and CPGs are all just living in it. Manufacturers face the ongoing challenges of accessing up-to-date sales data, ensuring efficient communication with field teams, and optimizing merchandising and promotional activities. With so many purchasing channels at consumers’ fingertips, manufacturers must keep pace and sharpen their retail execution strategies. Just six years ago, there were about 15 social media channels, and now there are up to 60, observes Oliver Wright, global lead for consumer industries at Accenture. “It’s safe to say this is the most complicated landscape we’ve seen today, and we believe it’s only going to get more complicated,’’ he says.Fortunately, today’s manufacturers can glean more insights than ever before. Learn how CPGs like PepsiCo, Unilever, AB InBev, and more are preparing for the future of digital assistants, conversational commerce, and micro-level retail experiences. Two-thirds of respondents in CGT’s annual Sales & Marketing Study are using AI and machine learning for social media marketing/analytics, followed by e-commerce/omnichannel (35%).“The topic I hear the most about right now is … the shift from cost-savings to growth for consumer goods companies,’’ says Lokesh Ohri, EY Americas consumer products sector leader. “When you peel that back, it is a lot about commerce growth and how you drive organic commercial growth in the business.”There are two sides to that equation — one is developing the perfect store strategy and the other is the retail execution piece, Ohri says. Manufacturers are specifically seeking to leverage digital capabilities powered by data and AI to optimize growth. At the store level, the challenge is doing this to execute efficiencies and drive growth — down to the physical shelf. 1. Understand that consumers’ wants are moving targetsIf consumers don’t find what they want in one store, they will move on to a competitor’s, Wright notes. “That’s the heart of this … As soon as you have individual consumers defecting, that can become more and more pronounced over time.”Another complicating factor is that what consumers are interested in buying is shifting more quickly, he says. “You’ve got consumers doing more research and they are exposed to more influences, which will shape what they buy and where they buy it.”Part of that research now involves asking tools like ChatGPT where to buy things. “It’s not always going to be fully accurate yet, but it’s increasingly insightful in terms of the questions you can ask,’’ Wright says. “That will add further disruption to the retail environment as well.”2. Marry in the retail magicWhile it used to be “super costly” for manufacturers to have control over inventory, now they can equip field teams with insights about a neighborhood and shopper demographics. This will make it easier to “sell more consultatively to the store manager,’’ says Ed Johnson, a principal in Deloitte’s retail and consumer products practice. “We have seen a lot of success from that approach from CPG companies that are mining store-level data … and building sales opportunities against that.”Nearly one-quarter (24%) of CG professionals want to monitor consumers’ general consumption habits along with their omnichannel/digital shopping habits (12%), according to CGT’s 2024 Sales & Marketing Research Report. Getting the data, ingesting it, and cleansing it have always been issues, says Ohri. “Now what you're able to do is to put raw data into these massive data lakes or in these massive unstructured data formats,” which the AI can use much more effectively.Getting data AI-ready translates to better results. Over 90% of retailers and leading CGs will invest in these areas in the next year “to ensure they have the right predictive engines available to them” for decision-making, according to Ohri. That is where the magic is in the world of retail execution — using predictive AI to determine the right types of products, the right price pack combinations, and at which store and where in the store layout, he says. This way, retailers can do targeted promotions. Historically, CG companies bought closed-loop data from syndicated sources. Now they're able to get it directly from retailers. “First-party data, which has sort of been the holy grail, is now available in so many more formats to them,’’ he says. They have their own brand interactions that they could integrate into this” from marketplaces and e-commerce channels.“So when you bring those new data sets [from] online shelf data to an offline environment, that's what's unlocking that real predictive nature,’’ Ohri says. Brands can receive the next-best action with the lowest error rate.3. Get ready to respond to digital assistantsOver half of consumers expect to use some type of digital assistant very soon to support what they are doing, according to Accenture research. “What this will mean for retailers is … there will be more and more transparency for consumers on what they should be buying and where they should be buying from,” Wright says.Retailers need to respond in a way that is much more dynamic than before, he says. This will result in an “agility and relevance problem that will grow over time” because two conflicting things will occur: digital assistants will address questions about products but retailers will have to be able to shift product demand quickly, Wright says.“What we can do now that we couldn’t do a year ago is when you see the volumes of issues on social media … convert that information, which is unstructured data, into lightly emerging signals for demand,’’ he says. For example, if people on social media are discussing meeting at a particular ice cream shop, the manufacturer needs to look at that store and do proactive replenishment as quickly as overnight by integrating more information up the supply chain.“It’s about managing the tension/opportunity with the increasing sophistication of the consumer,’’ Wright says. “It’s almost a data analytics arms race between the two sides.” We are entering a time where people will become used to having a digital assistant to support their daily lives, he says. This will happen as people increasingly use conversational tools, which will become more and more sophisticated over the next few years.“The more you interact with [the digital assistant], and the more it understands about your lifestyle, the more it will give practical guidance about what you do,’’ Wright says. While these generative AI-embedded tools will be able to flag when it’s time to reorder more dog food, for example, manufacturers will enable these tools to interact with retailers so they can learn more about customers’ preferences.This will spill over to work, with CG employees using digital assistants in the next two years also to support their retail customers, Wright says. While some retailers are already making handhelds available, “they’re typically AI or normal machine language-driven,” and not as conversational. Anheuser-Busch, for example, is infusing GenAI into an ordering tool that goes into traditional stores and pubs, enabling retailers to manage their commercial relationship with the beer manufacturer, Wright says. Besides ordering, retailers can also schedule deliveries, receive updates, make substitutions, and participate in loyalty programs.Wright estimates that the tool generates between 80% and 90% of Anheuser-Busch’s volume. The GenAI overlay enabling conversational commerce will become “more pervasive across all the technologies we’re familiar with over the next few years,’’ Wright says. The technology will query a traditional analytical tool and come back with a conversational response that a human can understand. From there, the tools will provide prompts on the next best actions to take, he adds. “In the same way we can give consumers guidance on a product they might want to buy … we can [provide the same guidance] to a retailer and salesperson … on what we think you should do next.”4. Elevate retail experiences at the micro levelInstead of making macro decisions, retailers should move toward micro decision-making to figure out the right product combinations, says Ohri. “Historically, that didn't quite work because it was very hard to execute,’’ he says. “Now you can, because you have the tools and the technologies to be able to make those decisions and … execute against that.”Retailers must think about that from a store format as well as a shopper segment perspective — and get both correct. “Think from an omnichannel perspective; don't just think about advertising in the store and in the aisle and forget everything else,’’ he says. “How is your digital advertising complementing your in-store advertising?” How can all of that complement your broader marketing strategy?Optimizing promotion execution is critical, notes Ohri. “Because of all the price increases that have happened, a lot of CPG companies are starting to see flattening, if not declining volumes, because consumers are shopping down and shopping away because they're trying to find more value,’’ he says.PepsiCo is reporting success with its Pepviz data science practice, in which the CPG shares consumer insights with retailers to partner for better experiences. After commissioning a deep dive into Gen-Z buying habits, the CPG is developing phygital selling environments with retailers that merge digital discovery and personalized social experiences with in-store activations. One example: After data showed that lemon-lime indexes highly among Black and Hispanic audiences, the CPG launched a Super Bowl commercial and Tinder data app activation that helped capture Gen Z's attention and spend through retail media networks, e-commerce, and in-person brand recall. The efforts ultimately helped push Starry to reach 47% general market awareness and 53% awareness among Gen Z, according to PepsiCo. Indeed, CPGs need to figure out how to optimize retail media networks and leverage their data to create an effective omnichannel consumer experience, says Ohri. Image recognition comes into play here because many stores, as part of their media networks, have cameras in aisles to see how much time a person spends in front of one product versus another, he says. Wright agrees, saying that with cameras in stores, officials can look at images, count products, and see their placement and positioning. In the ice cream example, he says the depth of the ice cream products can be determined because they will have the case dimensions. Unilever, for example, is starting to deploy visual sensors in ice cream store freezers to understand how inventory is changing and shape replenishment, Wright says. “The idea is very simple — if you’re the ice cream team at Unilever, you can put this in place and it will dramatically reduce the likelihood of someone coming in … and not getting the ice cream they want. So adoption will be high.”Visual sensing technology “massively simplifies the retail partner’s life,’’ he says. “What it does is change the ordering process to being something that becomes more and more real-time” because the camera will sense when products are low.Wright says there needs to be greater in-depth collaboration between manufacturers and retailers to “dramatically reduce the complexity of retailers’ lives.”He adds that “there is no point in solving for this in the store if it doesn’t flow through the entire supply chain. So you need end-to-end solutions, and it requires you to think about that end-to-end answer.”This is something Accenture is talking about more and more with executives. “The world we’re heading to increasingly is thinking about the value chain and processes in the organization as longer and how far upstream in the supply chain process you can look,’’ Wright says. “You want to get that longer and further up to your suppliers than ever before. It’s a super interesting world we’re in now.”

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