AI Visibility Audit
Controlled before/after across ChatGPT, Claude, Gemini, and Perplexity on a curated query bank. Citation rate, link-out behavior, competitor co-mention — all visible, all reproducible.
Platform
Agentic Shelf walks merchants through the AI commerce question in the order their team asks it: where do you stand, what's the prize worth, and how do you get there. Each capability below maps to one of those questions.
Step 1 · Measure
Today, no one tells you whether ChatGPT is recommending your products. We measure it on real LLMs across a controlled query bank — before MCP, after MCP, side by side.
Controlled before/after across ChatGPT, Claude, Gemini, and Perplexity on a curated query bank. Citation rate, link-out behavior, competitor co-mention — all visible, all reproducible.
Recurring measurement scoped to your brand against your competitor set. Save runs to your Audit History and chart citation lift over time. Weekly cadence so the trend means something.
Per-merchant history of every run. Sparklines on the result page show how your citation rate, MCP readiness, and content readiness move week over week.
Step 2 · Size
Defensible TAM math anchored in published research. Real Google Keyword Planner volumes, AIO-adjusted funnel benchmarks, measured halo where you sell on marketplaces. Sized in dollars per year, not vendor scores.
Five-layer math chain producing a defensible annual addressable market for your category. Auto-detected from your storefront URL; the methodology page shows the chain shape.
Connect Amazon for live Selling Partner API data, or paste a listing URL — either way the model swaps a category-default halo for a measured (D2C + marketplace) / D2C ratio from real data. Concrete to your own marketplace footprint.
Conservative / mid / aggressive diagonals stress-test the softest input across 12, 24, and 48-month horizons. Pick whichever you can defend.
Step 3 · Get found
AI agents need a real-time read on your stock, prices, and product details. We install the layer that lets them — one Shopify install, no scraping, no stale data.
Real AI agents query your live catalog, stock, and pricing in real time — not from a stale crawl. One install gets you on the public AI registry so any agent can find you.
Per-product audits flag the listings AI agents can't quote cleanly. Apply-fix worksheets show exactly which copy to rewrite — no vendor consulting call needed.
Watch AI agents call your store live as it happens. Coming soon: agents that complete the purchase end-to-end on your behalf — pay per request, settle in real time.
Amazon · Alexa for Shopping
Amazon shoppers now ask Alexa for Shopping (formerly Rufus) what to buy — from the search bar, with AI overviews and side-by-side comparisons. Connect Amazon and we read your live listings through the Selling Partner API, then score and fix exactly what's keeping each one from being the answer it gives.
Every listing gets a GEO content score plus an Alexa-readiness shopper Q&A — Claude role-plays the assistant answering real buyer questions from your listing, surfacing the gaps that lose the citation. Fix them, re-score, chart the lift.
Connect once with Login with Amazon — no scraping. We pull titles, bullets, descriptions, images, and category through the official Selling Partner API, the same source Amazon trusts, across your whole catalog.
Claude vision inspects your gallery and flags when an image reads as the wrong category — the silent drift that miscategorizes a listing and buries it. Caught across every SKU, not one at a time.
For agencies + multi-store brands
One measurement layer across Shopify and Amazon today (WooCommerce + BigCommerce on roadmap). Reuse audit + TAM playbooks across clients; each merchant's data stays isolated.
Every audit save is scoped to the merchant's own UID. No client ever sees another client's data. Operator view (when authorized) shows all tenants for QBR aggregation.
Once installed, your endpoint becomes findable on the public MCP registry — sell to the entire agentic economy from one integration, no per-platform re-work.
When AI agents start checking out for shoppers, your endpoint already speaks the protocol. Per-call pricing, real-time settlement — you set the rules.