A proprietary, point-in-time panel of the home-improvement and building-products complex — per-store price and inventory, active assortment, and review-velocity demand with history back to 2006. Aggregated, ticker-mapped signals that track comps and revenue direction well ahead of the quarterly print.
A continuous, timestamped observation of the same SKU and store universe across the US big-box retailers, the pro-distribution channel and the branded fixtures makers — plus the UK trade counter. Every metric is point-in-time and reconstructable as of any past date, with review history reaching back nearly two decades.
Each signal is an aggregated time series at the retailer × geo (or SKU-category) level, pre-mapped to the tickers it informs — engineered for comp nowcasting and margin modeling.
Net new product reviews per month, aggregated by retailer and category, with history back to 2006. A long, clean proxy for unit demand and same-store sales momentum that turns before the comp print.
A matched-basket price index computed per store and rolled up by region and banner, rebased to 100. Reads pricing power, promotional cadence and gross-margin trajectory across the retail and pro channels.
Share of panel SKUs in stock by store and category. Falling availability flags supply strain and lost sales; a sustained recovery precedes revenue normalization — a direct read on the pro-distribution names.
Live count of distinct active SKUs by banner and category, plus additions and discontinuations. Assortment expansion signals category investment; contraction and brand-mix shifts read through to the fixtures makers.
Every banner and brand is normalized to one schema and mapped to the equity whose fundamentals it drives, so the desk pulls a single blended read per name.
Engineered to pass a fund's data-diligence: point-in-time integrity, transparent aggregation and a compliance posture that keeps it usable across the desk.
Every price, stock state and review count is archived with its capture timestamp. Series reconstruct exactly as they stood historically — no survivorship, no look-ahead in backtests.
We deliver retailer × geo aggregates and matched-basket indices mapped to tickers. The product is relative direction and rate of change — the reads that lead comps, not a claim on absolute sales.
Derived only from publicly observable retail surfaces. No personal data, no reviewer identities, no material non-public information. GDPR-aligned and DDQ-ready.
An illustrative slice: the aggregated review-velocity demand index for the US big-box panel, rebased to a prior-year quarter, shown against the reported same-store comp — the lead-lag the desk trades.
| Quarter | Vel. index YoY | Reported comp | Lead (wks) |
|---|---|---|---|
| 2025-Q3 | +2.4% | +1.1% | ~7 |
| 2025-Q4 | +0.9% | +0.3% | ~6 |
| 2026-Q1 | -0.8% | -0.6% | ~7 |
| 2026-Q2 | -1.9% | -1.4% | ~6 |
| 2026-Q3* | -1.2% | — | lead |
Request a point-in-time sample — a retailer × geo slice with full review history and ticker mapping. We'll send a data dictionary and a backtest walkthrough.
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