Compare assortment overlap, category mix, price ranges, and availability across the stores you collect. Turn recurring observations into a clearer view of your category.
Assortment and catalog analysis
+28%
Observed listings · 250 → 320
Listing count
Running shoes · Same 3 stores
Counts reflect the catalog observations collected.
Compare repeated collections to see how listing counts and category mix change. Results cover the stores and dates you collected.
31%
Brand A’s share of observed listings
500 listings · Running shoes · Selected stores
Compare brands by their share of observed listings. Keep the selected stores and unmatched records in view; listing share is not sales share.
+142
First-observed listings over 12 months
Listing count
Example Co. · Selected stores
First seen in your dataset, not a launch date.
Track when listings first appear in your dataset. Compare one brand’s observed assortment across the stores you selected.
Build a view of your category
Start with the stores and markets relevant to your team. Enrich gives their catalogs consistent categories, attributes, and matching variants so you can compare them together.
Break down collected listings by brand, category, attribute, or price tier. See where each store puts its assortment.
Compare exact matched variants shared by two stores. Keep unmatched listings visible alongside the result.
Compare repeated collections to follow changes in listing counts, category mix, and price ranges.
Find listings that first appeared in your dataset during a selected period, then inspect their original pages.
Every comparison is grounded in the stores, countries, and dates you collected. Check observation times, matching coverage, and the original records before acting on a result.
Catalog composition describes what a store lists. It does not measure sales, demand, or market share. A newly observed listing tells you when it entered your dataset, rather than confirming its launch date.
Use the dashboard agent or SQL query tools for custom questions across the connected product data. Export Captures as JSON or Parquet when your own application needs the original observations.
Choose your stores and markets. Collect their pages, connect matching products, and give your next assortment review a dataset to work from.
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