From raw data to ranked decisions — without a data warehouse.
Retailloom is built for category teams that work in POS exports and Excel — not for data engineers. Setup is a single 90-minute call. After that, your ranked SKU decision sheet arrives every Monday without any manual report-building on your end.
The five steps
Connect your data sources
Upload a POS export (CSV or Excel), connect directly via Shopify POS, Square, or NCR API, or drop an ERP export file from SAP Retail or Oracle Retail. We also accept shelf planogram files (JDA Spaceman, Prospace CSV, or a simple facing-count spreadsheet). No transformation required on your end — we handle the mapping.
Map your SKU catalog and store hierarchy
During onboarding, we walk through your SKU naming conventions and store numbering with you. This mapping step takes about 90 minutes and only happens once. After that, your data files load automatically on each weekly cycle.
Retailloom processes signals weekly
Each week, Retailloom calculates sell-through rate by SKU and store, gross margin per SKU against your category baseline, shelf-space efficiency (velocity per facing), and deviation from your starting-season plan. The signals are weighted together into a priority score. Store clusters are re-run from current performance data — not locked to last reset's groupings.
Your category decision sheet is delivered
Every Monday morning by 7 AM, your ranked decision sheet arrives by email — or is available in your Retailloom dashboard. Each row is a SKU-store combination, ranked by priority score, with a clear recommendation: CUT, KEEP, or REORDER with suggested quantity. No interpretation required.
Export decisions to your buyer workflow
Download the decision sheet as a CSV or Excel file formatted for your planogram tool, buyer order system, or ERP purchase-order workflow. Regional plan users can export in JDA Space format directly. The output is designed to be forwarded, not transcribed.
You don't need a data warehouse.
The most common objection we hear from category teams is "our data isn't clean enough." Every regional chain says this. What they usually mean is: the POS export has inconsistent store IDs, the SKU catalog hasn't been reconciled in two years, and the planogram file lives in a shared drive in some format no one fully remembers. Retailloom is built around that reality — not a clean data warehouse.
| Data Type | Format Accepted | Minimum Required | Update Frequency |
|---|---|---|---|
| POS Sales Transactions | CSV, Excel, Shopify/Square API, NCR export | SKU ID, store ID, units sold, date | Weekly (daily on Regional plan) |
| SKU Catalog | CSV, Excel | SKU ID, name, category, cost, retail price | At onboarding; update on new launches |
| Store List | CSV, Excel | Store ID, name, location, store type | At onboarding; update on openings/closings |
| Shelf Planogram (optional) | CSV facing counts, JDA Spaceman, Prospace | SKU ID, store/bay, facing count | At each reset or on demand |
| Beginning-of-Season Plan (optional) | CSV, Excel | SKU ID, planned units, planned weeks of supply | At season start |
From sign-up to first decision sheet in 48 hours
Onboarding is short by design. We built the setup flow for busy category managers, not IT projects.
Upload first data file
Upload your most recent POS export and SKU catalog. 90-minute onboarding call with Greg to map data fields.
Retailloom processes signals
We run your first store-cluster analysis and build the baseline sell-through and margin thresholds for your category.
First decision sheet delivered
Your first ranked SKU decision sheet arrives. Review it together with Greg in a 30-minute call to tune thresholds.
Start your first 14-day trial free.
Upload your POS export today. Your first decision sheet arrives by Wednesday.