This article explains how Wiser defines and measures coverage, and what to look for when evaluating whether your data is truly complete.
The four coverage metrics that matter
Match rate (how many of your SKUs we found) is just the starting point. Wiser tracks four distinct metrics to give you a complete picture of data health:
Match rate: Of all your catalog products carried on a specific domain, how many did Wiser successfully match? Calculated as: matches found ÷ potential matches.
Match accuracy: Of the products we matched, how many were matched correctly? Calculated as: correct matches ÷ total matches validated.
Data freshness: Of the matches we have, how recently was each one validated? Stale data on fast-moving categories (electronics, FMCG) can be worse than no data.
Mission success rate: For in-store and field data programs: of all validated datasets (missions) reviewed, how many were successfully completed and passed QA? This metric applies to physical retail data collection.
What good coverage looks like in practice
Strong data coverage doesn't just mean a high match rate, it means consistent coverage across your full catalog, including:
Key Value Items (KVIs) tracked at high frequency (hourly or daily)
Long-tail SKUs covered even if refresh frequency is lower
New SKUs automatically discovered when retailers add them to their catalogs
Historical data accessible for seasonal comparison and promotional ROI analysis
Automatic SKU discovery: Wiser's system continuously checks for new products added to retailers' catalogs. You don't need to manually add new SKUs; they're identified and matched as soon as they appear.