Retail / CPG
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AI-driven assortment optimization that tailors your product mix, shelf space, and planograms to each store cluster.
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Every store gets the same range, regardless of who shops there or how much shelf space is available. The result: wasted facings on slow sellers in some stores, out-of-stocks on top sellers in others. SKU rationalization without demand modeling is guesswork. You need to know what happens when a product leaves the shelf.
AI clusters stores by shopper behavior, demographics, and performance. Each cluster gets an optimized product mix tailored to local demand, within the shelf space actually available.
Demand transference models predict substitution and cannibalization when products are added or removed. You see the projected impact on sales and margin before making the change.
Store-specific planograms are built from your optimized assortment, shelf dimensions, and merchandising rules. One retailer manages 7,500 planograms across 450 stores with 2-3 FTEs.
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Assortment optimization is the process of selecting the right product mix for each store or store cluster based on local demand, available shelf space, and financial targets. AI-driven approaches use demand transference models to predict what happens when products are added or removed, replacing manual spreadsheet-based range reviews.
Traditional SKU rationalization cuts slow sellers without modeling what happens next. AI predicts substitution and cannibalization effects, so you know the projected impact on sales, margin, and customer satisfaction before making changes.
Assortment optimization decides which products need to be carried in each store. Space planning decides where they need to be placed on the shelf and how much space they get. The best results come when both are connected: the assortment is optimized within the space actually available.
