ShelfSight · Methodology
Stability counts, conservative matching, and honest gaps. Every claim on this page maps to shipped, tested code.
Every claim on this page maps to shipped, tested code. When the methodology changes, this page changes in the same release. Methodology changes never silently rewrite history.
ShelfSight asks the same buying-intent questions your customers ask, across ChatGPT (OpenAI), Perplexity, Gemini, Claude, and Google AI Overviews, and records whether the answers mention or cite you or named competitors.
Which engines a scan covers depends on where it runs. Paid plans scan all five every week, within a monthly engine budget (half the plan price on Starter and Growth, three fifths of it on Pro); if a month's budget runs out, scans pause and resume on the 1st. The free first scan in the app covers as many engines as its budget allows. The free public report on this site drafts 3 buying questions from your public product feed, asks each once on Perplexity, Gemini and Google AI Overviews, counts the decisive answers that recommend you, and checks the feed.
Shopify's admin has a free agentic storefronts page, under Sales channels > Agentic. Its search preview shows "the raw outputs of Shopify Catalog search", and Shopify calls it "a directional signal, not an exact prediction". Shopify also says AI channels "often re-rank results based on their own logic" (Shopify Help Center). As Shopify describes it, it shows how your products might rank; it doesn't show what an assistant actually answered.
ShelfSight asks the assistants themselves, records every answer, and counts how often you and the competitors you track are recommended, with the sources each answer cited. The two answer different questions: Shopify's page shows how its catalog search sees your products; ShelfSight shows what shoppers are told.
Deterministic rules, strongest signal first:
Anything that doesn't clear these bars is not mentioned. We do not use fuzzy guessing; "smart wool" does not match "Smartwool" unless you configure it as an alias.
AI answers are messy. When we can't decide honestly, we say so: unsure results are left out of the decisive count. They are never silently treated as absence (or presence). An engine that returns an empty answer is recorded as unsure, because no answer is not evidence you're invisible.
The per-product view on your dashboard shows where engine answers reference individual products from your catalog. A reference means distinctive words from a product's title, beyond the words of the question, appeared together in an answer: the same conservative rule 3 above. It is token-level evidence, deliberately labeled referenced: weaker than a confirmed mention, and never a recommendation count. We show it because knowing which products surface (and which never do) is actionable; we label it honestly because the evidence is circumstantial.
A single AI answer is one sample; engines vary run to run. So we lead with counts: "recommended in 3 of your last 5 scans", per question and engine, with the answers behind each count shown.
The 14-day view shows, per day, how many decisive answers there were and how many of them recommended you; unsure answers are left out, exactly as in your counts. A day with no decisive answers shows no bar, not a zero. The weekly view puts the last 7 days next to the 7 days before, as a count for each week. We never turn the two into a percentage or a points change, and a week with no decisive answers says so.
On Growth and Pro, each day we compare, for every prompt on every engine, your last 5 decisive answers with the 5 before them. The two sets never share an answer, and unsure answers are left out, exactly as in your counts. You get an alert when the newer 5 recommend you fewer times than the older 5: at least 2 fewer on high sensitivity, 3 on standard (the default), 4 on low.
This is optional and off until you turn it on in the app, which asks Shopify for permission to read your orders. The option only appears once Shopify has approved ShelfSight's access to order data, and even then nothing is read until you turn it on. We then read your orders from the last 60 days, up to the 2,500 most recent (if there were more, we say the older ones weren't read), and look at the visits Shopify recorded before each one.
What we check instead: whether your product data (category, identifiers, options, price and stock) is complete for the feeds AI shopping surfaces read, and whether your robots.txt lets the crawlers behind AI search (OAI-SearchBot, PerplexityBot, Claude-SearchBot, Googlebot, Bingbot) read your product pages, and whether those pages show the same price and stock as Shopify. Blocking training-only crawlers such as GPTBot doesn't change whether assistants can cite you, and we say so. Google-Extended is different: it doesn't affect Google Search, but Google says it controls whether Gemini Apps use your pages to ground answers, so we flag it on its own.
We query engines through their public APIs with web search/grounding enabled. API responses are a statistical proxy for what consumers see in the apps: close, current, and reproducible, but not pixel-identical. This is standard practice across the AI-visibility industry; we state it plainly because the alternative (pretending otherwise) would be dishonest.
The feed audit has no proxy problem: it checks your actual product data with fixed rules, against the published product feed requirements of the Agentic Commerce Protocol and against what Shopify Catalog uses to place and match a product (a standard product category, and option values on every variant). Every finding shows the exact rule and the exact fix.
An AI model writes the weekly report from your scan and audit data, instructed to use only the counts we measured, to compare weeks only as counts (never as a percentage or a score), not to invent numbers or causes, and to say "no decisive data yet" when that is the truth; tests check those instructions.
Check your own store’s product feed with the free AI visibility report, no install and no signup. To run the scan on your own buying questions, install free on Shopify.