Resource library
Everything we publish about measuring AI answer visibility, in one place. No gated PDFs, no email wall, no “download the whitepaper” form standing between you and a page that already exists.
How the measurement works
Read these two before you evaluate any AI visibility tool, including ours. They are the pages that tell you what a number can and cannot mean.
- MethodologyThe full measurement contract: collection modes, per-engine surfaces, validity rules, scoring weights, confidence thresholds and the claims we refuse to make.
- SecurityThe controls implemented today — database-level tenant isolation, client read-only measurement data, encrypted integration credentials, strict response headers — plus what is not yet certified.
How each engine is collected
One page per engine, each stating the surface we call, the collection mode recorded on the data, and the boundary of what that measurement supports.
- OpenAIOpenAI web-grounded APITracked using OpenAI’s Responses API with the hosted web search tool enabled. Citations are the sources the API itself attributes.
- ClaudeClaude web-search APITracked using the Anthropic Messages API with the server-side web search tool. Citations come from the tool’s own search results.
- GeminiGemini + Google Search groundingTracked using the Gemini API with Google Search grounding. We store the grounding metadata, including the search queries Gemini issued.
- PerplexityPerplexity web-grounded APITracked using the Perplexity Sonar API, which is web-grounded by design and returns its search results alongside the answer.
- Google AI OverviewsObserved Google AI Overview SERP dataObserved through a licensed structured SERP provider that captures the AI Overview element for a given query, location and device.
What each part of the product does
Capability pages, written to be read before a demo rather than after one.
- Product overviewHow the Track, Compare, Explain, Improve and Prove loop fits together.
- AI visibilityWhere your brand appears across engines, and how often it does not.
- CompetitorsWho is recommended instead of you, and how they are characterised.
- CitationsThe sources behind the answers, classified by ownership and type.
- Site auditHow readable your pages are to the systems assembling answers.
- RecommendationsGaps turned into specific, prioritised work with the evidence attached.
- ExperimentsBefore and after on an identical prompt set, with a refusal to declare a result on a thin sample.
Notes from building this
Working notes on AI answer visibility, measurement traps, and what we are learning as the engines change underneath us.
Documents your reviewers will ask for
Published as templates so a legal team can read them early. Each carries a notice that it needs qualified review before commercial use.
- Privacy noticeWhat we collect, why, how long we keep it, and how to ask us about it.
- Terms of serviceThe terms proposed for using AnswerRank, published as a reviewable template.
- Data processing agreementOur processor commitments in template form, published so your legal team can read them before any conversation starts.
If you need a document for a procurement or security review that is not listed here, ask. We would rather write it once and publish it than send a different answer to every reviewer.
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