Brand visibility in Gemini answers grounded with Google Search
AnswerRank runs your prompt set through the Gemini API with Google Search grounding and stores the grounding metadata alongside the answer — including the search queries the model issued.
How this measurement is collected
Tracked using the Gemini API with Google Search grounding. We store the grounding metadata, including the search queries Gemini issued.
- Surface we call
- Gemini API + googleSearch grounding tool
- Collection mode
- Official grounded API
- Collected from the provider’s own API with web grounding enabled. Citations are provider-attested.
- Label used in-product
- Gemini + Google Search grounding
- The same label rides along with every metric collected this way, so a number can always be traced back to how it was obtained.
- One check is a single prompt × engine × market execution, sent to the Gemini API with the Google Search grounding tool enabled.
- The model is a deployment setting rather than a fixed claim, and the exact model string is stored on every response we keep.
- Grounding sources are read from the grounding metadata the API returns, not scraped out of the answer body.
- Where the API discloses the queries it issued, those queries are stored with the response — useful evidence about how a question gets interpreted.
What AnswerRank reports for Gemini
Every answer is normalised into the same structure across engines, so one prompt set can be compared across surfaces without blending collection methods.
- Whether the grounded answer recommended, listed, merely mentioned, or omitted your brand.
- The grounding sources behind the answer, classified by ownership and source type.
- The competitor set retrieved for the same question.
- The search queries the model issued, where the API discloses them.
What this measurement does not support
The boundary is the point. A number is only defensible when the claim around it is narrower than the data behind it.
Grounding sources are those returned in grounding metadata. Consumer Gemini app results may differ.
- Answers are non-deterministic. A single execution is a sample, not a ranking fact, so every figure is reported with its sample size and a confidence level.
- Grounding is retrieval, not a ranking table. A source appearing in grounding metadata is evidence of retrieval, not proof of a ranking position.
Only two execution outcomes enter a metric: a successful answer, and an answer where the engine responded and your brand genuinely was not there. Provider errors, timeouts, rate limits and unconfigured engines are excluded from both the numerator and the denominator, so a provider outage can never be displayed as a collapse in your visibility.
How a check becomes a metricThe other engines we track
Each engine is collected differently and labelled differently. Comparing them is useful; blending them without labels is not.
- 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.
- 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.
See how Gemini answers your category.
Run a visibility check on your site and read the result with its sample size, its collection method and its limits stated on the page.