Connecting Category Management To Shopper Experience

Connecting Shelf and Strategy

Retailers will be better able to meet shopper needs if they break down silos and take advantage of store-level insights.

“Execution teams are the frontline storytellers of shopper behavior,” said Heather Campain, vice president, growth strategy, at Epsilon. “When their insights feed back into planning, the organization moves from reactive to responsive, closing the loop between shelf and strategy.”

While larger retailers may have more silos, they also may have access to huge troves of information to identify trends that can be capitalized on nationally or at the local level. This can be done through promotions or product assortments designed to meet a community’s needs.

For example, shopper data is making assortment and merchandising far more precise and customer-led than before, said CVS Media Exchange head of marketing Kristen DiCorleto. 

“Instead of relying solely on broad category forecasts, retailers can now use loyalty insights, first-party front-store data, and retail media reporting to understand what products resonate with specific customers in specific locations," said DiCorleto. 

Having category, brand and store teams work together from the beginning of a marketing campaign removes inefficiencies from duplicate spending and makes it easier to share KPIs. CMX combines in-store activations, offsite media and seasonal promotions for campaigns integrating existing shopper data that can gather new learnings to shape the next round of planning.

Closed-loop CMX campaigns enable them to see how ads perform, as well as how they can drive incremental sales, attract new-to-brand buyers, or generate excitement around emerging categories, according to DiCorleto. 

“Those insights feed directly into merchandising decisions, helping inform which products deserve more shelf space, which categories are ready for expansion, and how to design in-store activations that reflect real shopper behaviors," she noted. 

Being able to track loyalty, POS, retail media and real-time in-store data across the path to purchase makes it easier to plan product assortment while also enabling digital discovery that will drive trips.

“The future of category management is shared,” stressed Campain. “When retailers and brands plan off the same people-based data and AI models, you align shelf, screen and shopper. Collaboration isn’t just a nice-to-have; it’s how everyone wins.”

Retail Experiences for Real Shoppers 

Traditional planograms were designed for a time when trips tended to follow predictable patterns, but stores need to adapt to changing behaviors. In-store retail execution data, as well as data from loyalty programs and retail media, can be used to help retailers design their stores and selection based on what is bringing shoppers in when, moving beyond linear shelf sets to add dedicated grab-and-go zones, occasion-specific displays and cross-category solutions.

“A format serving grab-and-go trips needs different merchandising than a format catering to weekend stock-ups,” said Kate Garner, PepsiCo senior vice president of insights and intelligence. 

PepsiCo has worked with its partners to fuel growth by maintaining core category efficiency while creating space for innovation, seasonal relevance and local preferences. 

"It's about being efficient where it matters and flexible where it drives differentiation," said Garner. 

Rising cost and economic uncertainty has driven shoppers to make more trips to chase promotions, but shoppers will also pick which retailers to visit based on their product selection.

“Because of the diversity of choices in channel that consumers have, they’ve never had more power in that retailer-brand-consumer dynamic, so retailers have started to figure out really quickly that consumers are demanding more,” PDG Insights' Sheehan said. “Retailers are thinking outside the box in how they approach assortment, and localized, unique and exclusive products are a key aspect of that.”

Companies need to break down the silos between e-commerce and brick-and-mortar teams to combine insights gathered from apps, social media and in-store purchases to create a cohesive shopping experience and maximize the effectiveness of each touchpoint. That is especially important for connecting with Gen Z shoppers, who are digital natives but still love in-store experiences.

“They use technology to enhance physical shopping, not replace it,” Garner said. “That might mean checking inventory on their phone before visiting a store, or comparing options online while standing in the aisle. Category management needs to account for these ‘phygital’ behaviors — ensuring that online assortments reflect in-store availability, that search complements physical layouts, and that promotions work seamlessly across channels.”

The AI Advantage in Merchandising

Retailers and brands have historically struggled to turn the huge amount of customer data they gather into actionable insights, but AI is helping to bridge that gap.

"AI allows us to connect the dots across a much wider set of data, from qualitative to quantitative, social, in-store and loyalty data,” said Storesight's Kasperbauer. 

He noted that companies are now using the data for everything from market research for new product launches to identifying and fixing phantom inventory issues in near real time.

AI-driven marketing campaigns could guide shoppers to specific aisles in stores with personalized offers based on their purchase behavior, but retailers will have to test the technology carefully to avoid being too intrusive.

“Retailers could start to explore if their consumers want that type of communication while they’re sitting at home unengaged,” Sheehan said. “Do they want text messages reminding them to buy milk? Do they want text messages telling them about the new flavor of a brand they’ve just bought or the new product on shelf from their favorite brand? I think there are ways to capture people where they are, to drive the traffic to the store while also making their digital experience just as valuable.”

It also holds the opportunity to bolster retailer/brand collaboration by providing an outsized impact on go-to-market teams, added Kasperbauer. "This is a call to arms to differentiate yourself with your buyers. Those who bring the best 'gifts' — insights and analytics — are the ones who will be at the table to win."

Sheehan anticipates that, within the next three years, every U.S. retailer will be using AI to help make assortment decisions.

“If retailers aren’t using AI in some way to better understand what the right products are on shelf, they’re missing out,” she said. “It’s not going to replace merchants and buyers, but it will help guide them in the same way that using data analytics has become an integral part of decision-making.”