Our methodology, and what we do not claim.
citeproduct is a GEO (AI search readiness) audit: give it a URL, it scores how well AI engines can read and cite your page, asks 5 named engines the questions your buyers actually ask, and hands you copy-paste fixes. Every number in a report should be explainable. This page is that explanation, and we show our work.
The readiness score (0 to 100)
AI Search Readiness is a structural score of one page across 7 dimensions: Crawlability, Entity Clarity, Answerability, Trust Signals, Structured Data, Content Depth, and AI Citation Readiness. In plain terms: can an AI engine fetch the page, understand who you are, and quote you? We check what the crawler actually receives (raw HTML, not the JavaScript-rendered view), structured data, answerable content blocks, llms.txt, robots/sitemap signals, and content depth. A Page audit scores this with fixed rules, so the same page scores the same every time. An AI visibility check has a model read the page and ask buyer questions, so its result can move from run to run. SEO Foundation is the classic search hygiene baseline, scored separately. A page can be strong on Google and still invisible to AI answers.
The AI Visibility Snapshot
We generate realistic, brand-agnostic buyer questions for your category (you can refine them with your product description, goal, and competitors), then ask 5 real engines (ChatGPT, Claude, Gemini, Perplexity, and DeepSeek), web-grounded and live. We detect in code whether each answer names your brand or names a competitor instead. This is the pain we measure: when a buyer asks AI, it may recommend a competitor and never name you. Product aliases count for the brand (an answer that says a product name instead of the company name is still a mention).
Sampling, and why we report a range
AI answers vary between runs. A single ask would make the score jitter, so each question is asked multiple times per engine. A result like 3 to 4 of 5 is an honest range: the floor is questions where you were named in every sample, the ceiling is questions where you were named in any sample. A wide range means the engine is genuinely undecided about you, and that is information, not noise. We would rather show you an honest range than invent a single confident number.
Where AI actually gets its answers
Grounded engines search the live web and report which URLs they actually cite for your buyer questions. From those citations we map where AI gets its answers in your space: your site, competitor pages, review sites, communities. That tells you where to invest next, and it is the input for the fixes we hand you (JSON-LD schema, llms.txt, FAQ, and content rewrites).
Awareness, not a live ranking
The visibility snapshot measures whether AI is aware of you right now. It is not a live ranking, and it is not a guaranteed outcome. AI visibility is not a stable rank: it varies by engine, time, and wording, so we measure it as a dated snapshot and say so on every report. The way to use it: fix what the report shows, re-run, and compare trends over weeks (the Monitor page automates this), not minutes.
What we do not claim
We never promise that any AI engine will recommend you, and we never fabricate figures or visibility we did not measure. When a check cannot run, the report says it was skipped and why. We report awareness, not a guaranteed ranking, and results vary by engine, time, and wording. The fixes we generate target how reliably engines can understand and cite your pages: the structural lever you actually control. Re-run the same questions to measure what changed.