Experimentation at scale for Google Shopping, catalog ads, and Meta DPA

Large catalogs evolve faster than static PDPs can. Enterprise catalogs suffer from incomplete product data: missing videos, sparse descriptions, inconsistent tech specs. This is especially true for multi-brand retailers where content quality depends on vendor integrations that are often broken or incomplete.

FERMÀT's Commerce Brain automatically enriches your PDPs by pulling content from first and third-party sources: product videos from your DAM, specs from brand sites, user reviews from Amazon or Reddit. The system matches this content to the right products without manual tagging or taxonomy work.

DPPs keep pace by letting you A/B test tailored experiences for different product groups, all outside your core site, with no disruption to navigation or performance.

FERMÀT’s Dynamic Product Pages connects ad intent, shopper behavior, and catalog data in one closed loop. Each interaction teaches the system which layouts, products, and offers work best, and then applies those learnings across your catalog.

Not every category should look the same. Apparel benefits from wider assortment above the fold. Technical categories like bikes often need spec-heavy layouts. DPP lets you test both and deploy the right pattern by category.

The Commerce Brain doesn't just optimize layout; it continuously identifies and fills content gaps across your catalog, pulling relevant product information from wherever it lives.