AI assistants now discover, compare, and choose products on shoppers' behalf. PickRate simulates them shopping your catalog, shows why products lose, fixes the data — and proves the lift.
of online shoppers expected to use AI shopping agents by 2030
YoY growth in AI-engine traffic to retail sites
YoY growth in orders from AI-powered search on Shopify stores
monthly drift in the sources AI models cite — fixes decay fast
The new buyer is an algorithm — and most catalogs were never built for it.
Agents pass over listings with missing specs, thin attributes, or unparseable data — and recommend a better-structured competitor instead. You never see it happen.
Visibility tools show you appear in 8% of answers while a rival appears in 60%. None of them can prove which change would close the gap.
AI models reinterpret catalogs continuously. One-time optimization decays in weeks — merchants can't keep up by hand.
Not another dashboard. An experimental engine that tests, explains, repairs, and proves — automatically.
Fleets of AI shopping agents shop your live catalog across ChatGPT-, Gemini-, and Perplexity-style behaviors.
Causal analysis pinpoints exactly why products lose — down to the single unparseable field.
Attributes inferred from images, reviews, and text. You approve; nothing ships without consent.
Re-simulation measures the real Pick Rate lift from every change. Causation, not correlation.
Every result feeds the AI Commerce Graph — compounding data on what makes agents choose.
Monitoring tools tell you that you're losing. PickRate proves what wins.
A predictive score per product: how often agents select it for real buyer intents in your category — benchmarked against the competitors agents actually compare it to.
How PickRate stacks up against AI visibility monitors and feed managers.
| Capability | AI visibility monitors | Feed managers | PickRate |
|---|---|---|---|
| Sees where you appear | Yes | Partially | Yes |
| Explains why you lose (causal) | No — observational | No | Yes — controlled experiments |
| Predictive Pick Rate before launch | No | No | Yes |
| Auto-infers missing attributes | Limited | Enrichment only | Yes — vision + reviews + text |
| Proves lift after each fix | No | No | Yes — re-simulation |
| Learns across merchants (graph) | No | No | Yes — compounding data |
Join the waitlist for early access. Founding merchants get a free Pick Rate audit of their catalog and priority onboarding.