Cells show value · colour scales red (low) → green (high) within each row across months.
Card view of styles in the current store & attribute selection — uses the filters above.
Buckets are by age since first inward: <30d, 30–60d, 60–90d, >90d. Replen % = share of bucket SOH units that received a fresh inward in the last 30d. Not-selling % = share of bucket SOH units on a line in stock ≥30d that sold <2 units in the last 30d. SOH as of . Sold L30D / L90D = units sold in the 30 / 90 days to . STR L30D = L30D units ÷ average of SOH ~30 days earlier and SOH on the snapshot. STR2 life = lifetime units at that store ÷ units received by RG at that store. Sold ₹ / ASP are lifetime. Respects store & attribute filters above.
Aging buckets
Breakdown
Stock aged >90 days in a store with 0 units ever sold there (strict) or ≤2 sold (near-dead). Age from first inward / first snapshot. Value = SOH × realised ASP. SOH as of .
Top sellers for the selected store. Units & NSV follow the period picker; L90 = units sold in the 90 days to ; SOH as of .
New-in styles (first arrival in last 3 months, ≥5 units sold) ranked by velocity = units sold ÷ days live. STR = units ÷ average stock (opening 0 at launch, closing = today) — can exceed 100%. STR2 = units ÷ units received (RG). SOH as of .
Week-on-week · Mon–Sun. NSV = net sales value, net of returns.
Store week-on-week (NSV ₹)
Tagging coverage —
Bottom-Up AnalysisAcross your current store + attribute selection & period.
Best performers — across selected stores (network)
Best sell-through per store — each store’s top styles (min units floor)
HSR Layout · zone-wise
Zone × Category
Attribute DNA · store-wise contribution (category → attribute blocks)