Solution Retail
Assortment & Merchandising Optimization
Optimize what to stock where (assortment and shelf space) from local demand instead of gut feel.
HigherSell-through rate
LowerDead stock and working capital
LocalizedStore-level assortment
Typical outcomes for this kind of engagement. Results depend on your data and starting point.
THE CHALLENGE
Assortment and shelf space are set centrally and applied broadly, so a store in a business district carries the same range as one in a residential suburb and both get it partly wrong.
- One-size-fits-all assortment ignoring genuine local demand differences
- Dead stock and stockouts coexisting across stores for the same SKU
- Manual planogram and space planning too slow to keep pace with demand shifts
OUR APPROACH
CloudGate models localized demand and profitability by store, cluster and SKU to recommend assortment and shelf-space allocation that reflects each location's actual customer base.
- Store-level assortment recommendations driven by localized demand modeling
- Shelf-space and planogram optimization weighted by margin contribution
- Store clustering by demand pattern rather than by geography alone
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