Advertised prices, availability, and assortment across dealer networks, readable as compliance evidence or competitive benchmark.
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Almost everything about outdoor and sportswear distribution is deliberate. Brands sell through authorized dealer networks, publish MAP policies with real teeth, and launch on a seasonal rhythm. That discipline creates a visibility problem in both directions: brands can't easily see whether their pricing policy survives contact with fifty dealers, and retailers can't see how their own position compares across the network they're part of.
| Brand compliance manager | Retailer category manager | |
|---|---|---|
| Watches | Advertised prices across authorized dealers | Competing retailers carrying the same lines |
| The rows answer | Who's under MAP, since when, on which SKUs | Where my price sits, who's discounting, what's sold out elsewhere |
| Acts by | Bringing per-dealer evidence to enforcement conversations | Timing price and assortment moves around launches and promos |
That table describes one dataset, read two ways. Advertised prices, availability, and assortment across the retailers that matter, per SKU, with history, at the cadence the season demands.
Launch weeks and promo windows are when MAP stress peaks and when benchmark data is worth the most, so collection cadence can tighten around them and relax between them. Coverage runs per region and locale, because a dealer network in the US and one in the EU rarely behave the same way, and compliance judged across a blended average is compliance misjudged.
Everything is validated before it reaches you, so a flagged price is a real price on a real dealer page, with a timestamp you can stand behind. The feed lands wherever your compliance or pricing workflow already lives: warehouse tables, flat files, or an API. The enforcement-specific workflow is covered under MAP and MSRP monitoring, and the mechanics of assessment, sampling, and recurring delivery are on the product page.
Whether you're policing a dealer network or benchmarking inside one, the first step is identical: name the brands and retailers, and we'll assess feasibility and send a free sample of the actual data. Start the conversation.
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