Ask any seasoned retailer where the real complexity lives in their store, and they will tell you it is not in Center Store. It’s in Fresh.
That is not a new observation. But it is one that the merchandising software industry has been quietly avoiding for years, defaulting to practices and tools built for the predictability of packaged goods and hoping Fresh categories will fit neatly inside them, even though they do not.
For retailers competing on the strength of their Fresh departments, the gap between what a generic approach offers and what Fresh actually demands is widening; this requires a fundamentally different approach to data, planning, and decision-making.
The data foundation is not the same
In Center Store, the product unit is a UPC. It’s stable. A can of soup is a can of soup — same barcode, same spec, same supplier relationship, week after week.
Fresh does not work that way. Most Fresh categories are managed at the PLU or SLU level, not the UPC level. Grade, program, and specifications shift and supplier relationships change. The strawberry category you analyzed last month may not map neatly to what you are selling today. This is not a data quality problem you can easily solve by updating a spreadsheet, but rather a structural reality of how Fresh supply works.
This is precisely why so many solution providers quietly sidestep — or mishandle — Fresh. The data is harder, the hierarchies are messier, and the margin for error when you get it wrong is far tighter than in Center Store. Where a bad Center Store decision might cost you a few weeks of underperformance, a bad Fresh decision can cost you margin you cannot recover, and a customer you might not get back.
The merchandising levers behave differently
In Center Store, you can promote something wrong on Monday and course-correct by Thursday with minimal damage. In Fresh, you often do not get that window.
Pricing and cost in Fresh can shift daily. Margin moves with it. When you’re running a promotion in produce or meat, your forecast has to be right. Buy too little, and customers leave disappointed. Buy too much, and you are managing shrink instead of sales. Neither outcome is acceptable when Fresh margins are already razor-thin.
Meat adds another layer of complexity. When a retailer puts one cut on promotion, that decision cascades. Remaining cuts need to be planned, priced, and placed in concert, or the economics fall apart. That is a level of interdependency that most general-purpose merchandising tools simply are not built to model.
Assortment and space are not one-size-fits-all
Fresh assortment is inherently local. The cuts of meat that move in one community don’t necessarily match what sells three zip codes away. Demographics, cultural preferences, and shopping patterns all shape what belongs on a Fresh shelf, and what doesn’t. Layouts vary by store, not by chain. Whether strawberries live in the fixed shelving or the middle floor display changes the entire traffic pattern and impulse dynamic.
This store-by-store variability is not a nuisance to work around; it’s a requirement that drives performance. And it requires capabilities that can hold that complexity, not flatten it.
What worked before is not a reliable guide to what will work next
Fresh is not a department where last year’s playbook — or even last month’s — can be applied with confidence. Consumer demographics shift and communities evolve. A trade area that looked one way in your loyalty data twelve months ago may look meaningfully different today, particularly in markets experiencing population growth or cultural change.
Decisions rooted in experience and intuition have real value. But they are most powerful when coupled with current data — including external signals like census-level demographic and economic indicators. The retailers who consistently win in Fresh are the ones who treat historical performance as context, not prescription, and who build in enough analytical rigor to know when the past is a reliable guide and when it isn’t.
The stakes are high enough to demand the right tools
Fresh is where customers decide which store they shop at. It accounts for 30 to 40% of grocery sales, but research consistently shows it drives 60% or more of how shoppers perceive and choose their store. The stakes are high enough to demand tools and expertise built for this department, not borrowed from the one next to it.