WITH THE ADVENT of Artificial Intelligence, Category Management is poised to get faster, more frequent, more connected and more accurate.
At least those are the promises we keep hearing from advocates of AI-powered decision tools: Your AI agent will access more and better data sources… Its decision tools will slash the duration of planning cycles… It will recommend actions in minutes that presently occupy countless hours for human merchants… It will plan and track personalized promotions with greater granularity… It will free human experts to focus more on strategy and less poring over spreadsheets.
If even some of this turns out to be true, CPGs could be facing some foundational changes in the way they collaborate with retailers to bring their products to market.
For Dr. Brian Harris, widely credited as the developer of the eight-step framework that solidified Category Management in 1997, AI holds the potential to re-animate a widely-used business process that has become a rote (plodding) exercise for many.
“Six months to develop a plan is no longer good enough. You need it within six weeks or even six days,” he said.
Harris’ latest business venture, Intent AI, Inc. is working to enrich the initial “category assessment” stage of the process by using AI analytics to develop keener insights, segment shoppers more intelligently, identify prime prospects and forecast consumer trends. He serves as the company’s President and Co-Founder.
“In last 10 years Category Management has really lost its connection to strategy. It’s become almost purely technical,” he said, noting that too many grocery retailers are focused on the same narrow set of tactics: low-prices, attractive produce, loyalty programs and trade deals.
“We must reconnect it to strategy,” Dr. Harris added. “The speed of change makes the cost of looking backwards very high. Nothing in the present approach is forward-looking. That’s ironic, with so much data available.”
Category Management Inputs, Outputs, Actions
AI-enabled CM decision making has a range of potential impacts on space, assortment, price and in-store implementation. Promotion too – possibly including retail media and overall account business planning. It’s likely to impact retail merchandising across three broad realms:
- Inputs – AI agents will enable far more rapid and automated access to traditional syndicated and market data sources, POS and loyalty data, and competitor data, with the ability to analyze these at a more granular level. They add the ability to fold in new forms of data, including in-store sensing, computer vision, online sales, shopper sentiment and out-of-store digital behaviors that anticipate future demand.
- Outputs – AI tools will routinely create category plans and forecasts, delivered with greater pace and accuracy. Merchandising plans may become more store-specific, with locally optimized assortments, prices and promotions. Newer strategic frameworks, such as “most valuable shopper segments,” may emerge to the forefront.
- Actions – AI enabled breakthroughs in category planning will require new commitments to retail implementation of planograms, price changes (some using ESLs), loyalty programs, even retail media campaigns. More comprehensive forecasts will inform joint business planning conversations well beyond traditional use of syndicated and POS data.
In short, AI is set to transform every aspect of grocery merchandising — from how retailers forecast demand and manage inventory to how they engage shoppers and reimagine the store experience.
Early Adoption is Underway
Grocers expect AI will bring significant change. In its August AI in Grocery report from Grocery Doppio (Incisiv), 84% of respondents said they anticipated a “high impact” on pricing and promotions, assortment, and planogram optimization. The report authors estimate these activities could “unlock” $25.7 billion in value for the industry.
Addressing a Grocery Doppio webinar in August, Suzy Monford, CEO of consultancy Food Sport International agreed, “Category Management is absolutely going to be a great unlock there. We’ll see upgraded planogram capability. As the move to digitized shelves progresses, that will let us see how customers respond to shelf sets in real time.”
Panelist Greg Zeh, CIO at Weis Markets, concurred. “Those are some of future use cases we’re looking at with AI, along with better sales planning and promotional forecasting that lets us identify what really resonates with customers.”
Deepak Jose, VP Head of Data & Decision Intelligence at Niagara Bottling, emphasized that brands will need to develop a robust data foundation if they want their AI tools to deliver reliable recommendations. “My call to action is to start with a business-value-first mindset. You must have a clear understanding of the business problems you are trying to solve.”
He continued, “It’s often more important to find the right problem than to solve the problem right.”
Georges Mirza, Principal of the Comtask consulting firm and a veteran of multiple CM solution development projects, observed that the advent of AI in Category Management signals a shift from analyses of past shopper behavior to forecasts that detect emerging preferences and behavioral trends.
Said Mirza, “How will I use AI to differentiate my offerings? It’s no longer enough to rely on historical data for insights. It must be pursued from a forecasting perspective, not backward-looking.”
Brand marketers are keenly aware that syndicated data and service providers are all moving in the AI direction, said Manny Zayas, Senior Director of Category Development at Red Bull. “But only a handful of the tools are live today, and that is primarily those that have integrated search functions to enable more robust output.”
The shift from spreadsheet-based analytics to AI-aided decision making holds a promise to empower trading partners to make more rapid and accurate adjustments to assortments, space allocations, planograms, prices and promotions. Reorder accuracy and timeliness also stand to improve.
Further Changes in Store
As AI enables brands and retailers to increase the pace and fineness of category plans, practical consequences abound. Will merchants be able to implement more frequent space, assortment and planogram changes in physical and digital stores? What new practices will be required to keep track of those tasks?
Observed Dr. Harris, “AI is getting us closer, but it is also bringing another layer of cost to be able to use it.”
Retailers have long struggled to effectively manage in-store implementation, a fact confirmed in the Store of the Future survey from Coresight Research, released in August. Said the study authors, “84% of retailers are challenged in managing store operations. Ineffective management of store-related business functions leads to revenue and margin erosion.”
If category planning cycles are accelerated using AI, inadequate ability to implement at the shelf could become a limiting issue. As more hands-on merchandising tasks are created, retailers and brands will need to factor that into their joint plans.
“How will you know these plans are executed?” Mirza asks. “You can’t rely on sample data to do that. You need to know the initial state and then track what changes.”
Keep Humans in the Category Management Loop
Said Zayas of Red Bull, “The coupling of progressive AI ideas with practical experienced category personnel to recognize the opportunity and be able to bring it to life, is still key.”
Monford of Food Sport International added, “In many ways AI can teach humans and aid critical thinking. AI takes a human to interpret the meaning of some findings about shopper behaviors.”
Similar challenges may arise regarding prices and promotions. Account-based marketing conversations are already getting more complicated thanks to the rise of retail media.
“In joint business planning, there aspects that need definite human interaction,” said Jose of Niagara Bottling. “Some are building agents to interact with brand agent to optimize promotion planning. We may see this within 24 months, but it’s not happening yet.”
“It’s still very tactical now,” Mirza added. “Until AI becomes strategic, that’s when the ‘aha’ moments will come.”
Read more about CM and overstocks.
This article appeared originally in CPGmatters. Reproduced here by permission.