How we build the data.

What we cover.

Amazon US and Amazon UK. Both marketplaces are monitored on the same daily cadence from our own infrastructure. Walmart US is covered separately with its own daily dataset.

How fresh the data is.

Daily refresh across the active catalog. Coverage stays current through continuous monitoring that's paced to be sustainable, not abusive.

Optional SP-API integration adds real-time notifications on buybox changes and new sellers for customers who authorize it (Scout + Protect tier).

Observations, not estimates.

2+ years of daily history — observation-level records of what actually happened on each ASIN, each day. Per-seller buybox win counts, per-brand seller trajectories, price movements, and BSR rank changes. Not revenue models derived from rank signals.

This distinction matters: when we say “Seller X held the buybox on 47 of the last 60 days,” that's a count of observed events — not an estimate. Analytics tools that rely on modeled revenue can tell you approximately how much a seller is doing. We tell you exactly when they were there and who they displaced.

What we intentionally leave out.

We skip several BSR categories on purpose: Books, Kindle, Audible, Movies, Music, Apps, and Magazines. These categories don't match the buyer segments we serve, and excluding them keeps brand attribution tight across the catalog we do cover.

What's in and what's out.

Our dataset covers the Amazon BSR top-ranked products — the highest-selling products across all non-excluded categories. This means strong coverage of brands that actively sell on Amazon, with high brand attribution across the catalog.

Long-tail products that never appear in BSR rankings may have limited or no history. For most brand intelligence, sourcing, and protection use cases, BSR coverage captures the products that matter.

Intelligence that per-ASIN tools can't produce.

Because we observe across the entire marketplace daily — not per-ASIN on demand — we can compute things that per-ASIN lookup tools structurally cannot:

• —Cross-brand operator graphs: which sellers operate across hundreds of brands simultaneously
• —Brand similarity matching: brands with overlapping seller footprints
• —Seller similarity matching: sellers with comparable brand portfolios
• —Seller pressure scoring: automated ranking of brands by unauthorized seller density
• —Acquisition radar: brands where seller control is deteriorating over time
• —Category heat heatmaps: visual comparison of competitive intensity across entire categories

These features are available from Scout Pro ($179/mo). Browse and historical trends start at Scout ($89/mo). Free accounts can browse brands and seller counts.

Web-wide MAP discovery.

Web-wide enforcement runs weekly per watched product, with new additions scanned within minutes of being added to your watchlist. The combination ensures fresh data on new ASINs while keeping recurring scan cost bounded.

For Scout + Protect subscribers, we extend MAP monitoring beyond Amazon using search-engine-based discovery. We find unauthorized sellers on Shopify stores, niche retailers, and marketplaces that pre-configured monitoring tools don't cover — then extract prices with AI and compare against your MAP floors.