Every SKU. Every store. Ranked by what matters.
Most assortment tools show you what happened. Retailloom tells you what to do next: cut, keep, or reorder. The call is grounded in three signals that every experienced category manager tracks separately — sell-through rate, gross margin, and the shelf space each SKU is occupying — weighted together into a single ranked priority list.
Stop reviewing aggregates. Start acting on individual SKUs.
Retailloom scores every active SKU in your category across three weighted axes: sell-through rate, gross margin versus category baseline, and shelf-space efficiency (velocity per facing). The output is a priority table — not a dashboard to interpret, but a ranked list you can act on directly. SKUs at the bottom with sub-25% sell-through and 4+ facings are your cut candidates. SKUs trending toward stockout get a reorder quantity. The middle holds.
Signal weighting adapts to your category's margin structure and velocity norms. A seasonal gift item operates on different thresholds than a commodity staple. Retailloom learns the difference from your first 4 weeks of data and recalibrates each cycle.
See the full methodologyOne plan for all stores is costing you margin.
Most chains run a single assortment plan — or at best two or three regional clusters, set at the beginning of the season and never revisited until the next planogram reset. Retailloom surfaces store-performance clusters from your actual POS data: stores with similar sell-through velocity and margin profile are grouped automatically, not by geography.
Mid-season drift is the real problem. A cluster that looked right in January looks different by March. Retailloom re-clusters on each weekly cycle so your category decisions match current performance, not last reset's assumption. Retailloom does not replace your judgment about which cluster strategy to run — it gives you the data to make that call confidently and revisit it more than once a year.
The shelf space they're fighting over.
Sell-through rate is not enough. A SKU with 40% sell-through is excellent if it has 2 facings — and a problem if it has 8. Retailloom reads your planogram or shelf-map data to normalize every SKU's performance by the space it's occupying.
This changes your cut list. SKUs you would have kept (because their raw sell-through looked fine) turn out to be occupying 3x more space than their velocity justifies. And the SKUs you would have cut were actually your best items per facing.
Connects to your existing retail stack.
Retailloom reads from POS systems, ERP exports, and planogram files. No new data warehouse. No ETL project.
Ready to put store-level data ahead of the plan?
Start a 14-day free trial. Your first ranked category sheet arrives in 48 hours.