Analyze price spread across retailers for a category or department
Analyze the spread of current prices within a category - mean, stddev, coefficient of variation, and percentiles (p10..p90) with IQR outlier exclusion. The population is representativeness-filtered: refurbished/used listings, accessory/parts subtrees, and rows under a category-aware price floor are excluded from headline stats, with the counts disclosed in excluded.
Query Parameters
Product category. Accepts a human-readable name (e.g. 'electronics', 'beauty') or a taxonomy slug path (e.g. 'electronics/headphones'); matched against the catalog's category tree (exact node, subtree, or path substring). Also accepts a GS1 GPC code (exactly 8 digits, e.g. '10001159') to filter by PRODUCT TYPE instead of by shelf placement — the same product type is shelved under different categories by different retailers, so a category filter answers from a fraction of the data while a GPC code spans them. Coarser codes (class/family/segment) match every brick beneath them. Resolve a phrase to a code with /v1/reference/classify?q=... ; when a code is used, resolved.match_source is 'gpc'. For analyst endpoints, supply either category or department; both may be supplied to narrow the scope.
1Top-level department (root category), e.g. 'Electronics', 'Beauty', 'Home & Kitchen'. Case-insensitive; matched against the category tree's root segment. For analyst endpoints, supply either category or department; both may be supplied to narrow the scope.
1Country (us or ca)
us, ca Filter to a specific retailer platform (long-tail specialty stores are also present; any platform key is accepted)
amazon, walmart, target, bestbuy, homedepot, costco, ikea, samsclub, cvs, dillards Response
Price dispersion data
Transparency counts: rows in scope but excluded from the headline statistics by the representativeness policy.

