Cross-retailer pricing already matched by entity resolution. Structured specs for real comparison, not marketing copy. Variant grouping that collapses duplicates into options. Buying guides and cost of ownership data that turn browsing into confident buying.
Your users don't want ten blue links. They want to know which product is best, where to buy it cheapest, and whether it's worth the money.
Keyword search across retailers gives duplicate results, inconsistent names, and no way to compare the same product across stores. Users scroll endlessly instead of deciding.
A price is meaningless without specs, lifespan, and alternatives. Is $849 good for this dishwasher? How long will it last? What does it actually cost to own? Raw pricing data can’t answer.
Same product in 4 finishes shows as 4 separate results. Users see clutter instead of options. There’s no grouping, no “also available in” — just noise.
One product, prices from 20 retailers. Entity resolution by GTIN barcode and model number links every listing to a single canonical product. No matching logic needed on your end.
Structured specs enable real side-by-side comparison. Filter by noise level, energy rating, capacity, dimensions — not marketing copy. Let users compare on the dimensions they actually care about.
Finishes, sizes, and configurations collapsed into a single view. Users browse options, not duplicates. One product card shows all available variants across retailers.
Buying guides, cost of ownership, and lifespan data help users buy smarter, not just cheaper. Surface the information that turns browsing into a confident purchasing decision.
A user searching for a quiet dishwasher gets structured results, cross-retailer pricing, variant options, and ownership context — all from one API.
User searches “quiet dishwasher” — Covala returns products sorted by noise_level spec, not keyword relevance.
User picks Bosch 500 Series — sees prices from 3 retailers and 4 finish variants in a single view.
App shows the full picture: 44 dBA (excellent), $849–$899 depending on retailer, 10–12 year lifespan, $975 total cost of ownership over 5 years.
44% of AI search users say it’s their primary source of buying information. The next generation of shopping apps will be built on structured data, not links.
Total cost of ownership queries are almost entirely unserved. Consumers ask “how much does it cost to run?” and get marketing pages, not answers.
RTINGS gets 18M monthly visits with structured product data and spec-based comparisons. The market rewards depth over breadth.
Cross-retailer pricing, structured specs, variant grouping, and buying intelligence — already done for 50K+ products across 19 retailers. Focus on your product, not your data pipeline.
Entity resolution + structured specs + cross-retailer pricing + buying intelligence