We make your catalog legible to the new generation of AI shoppers
Product discovery is shifting from keyword search to AI agent recommendations. Retailers who win that shift will be the ones whose catalog data AI agents can read, evaluate, and trust.
The catalog problem we kept running into
For years, retailers invested heavily in SEO to win keyword rankings. Then product listings ranked because of title keyword density, backlinks to category pages, and structured data tuned for Google crawlers.
AI shopping agents work differently. When a shopper asks ChatGPT "what is the best lightweight tent for three-season backpacking," the agent does not rank by keyword match. It evaluates whether a listing provides enough structured information to answer the question with confidence: material weight, packed dimensions, temperature rating, compatible accessories. If the data is not there in a parseable form, the listing is not considered.
We built ReFiBuy after seeing the same catalog pattern across a range of retail categories. Stores with excellent products, solid SEO scores, and thousands of monthly search visitors were not appearing in AI shopping result sets at all. The problem was not the products. It was the listings.
We started with a scoring model, then built the rewriting engine, then realized the monitoring problem was at least as important as the initial fix. AI agent behavior evolves on a fast cycle. We built ReFiBuy to stay current with that cycle so our clients do not have to.
Building from direct experience in retail and ecommerce
Scot has spent his career at the intersection of retail and online marketplace dynamics. He has led organizations through multiple cycles of ecommerce platform change and has seen catalog quality become a decisive competitive factor each time distribution channels shifted. When AI shopping agents began delivering product recommendations through conversational interfaces, he recognized the same pattern forming again and built ReFiBuy to solve the catalog-readiness problem before it became the crisis it had been in earlier platform transitions.
"Every major shift in how products are discovered has come down to the same question: does your product data match the format the new distribution channel expects? We are at that inflection point again with AI agents. The retailers who get their catalog structure right now will have a compounding advantage over the next two to three years."
"Every product deserves to be found by the shoppers looking for it."
That belief shapes every decision we make: how we score listings, what we rewrite, how we structure our monitoring system. The problem is not that AI agents are hard to optimize for. The problem is that most catalog tooling was built for a different era of discovery. We exist to close that gap.
Ready to see how your catalog scores?
Start with a free audit of up to 200 SKUs. No credit card required. Results delivered within 48 hours.