> ## Documentation Index
> Fetch the complete documentation index at: https://docs.qwairy.co/llms.txt
> Use this file to discover all available pages before exploring further.

# What keywords should I target to appear in more AI answers?

> Build a research list from prompts, observed search queries, citations, and GSC data without treating keywords as guaranteed AI targeting signals.

## Direct answer

Use keywords as research labels, not as a promise of inclusion in AI answers. Combine configured prompts, observed Query Fan-Out records, citation-source language, and Google Search Console data to identify audience needs worth testing with content.

## Data required

Use your configured prompts, topics and tags, stored answers, observed Query Fan-Out records, Source Explorer, and connected Google Search Console queries. Keep GSC search queries distinct from Qwairy prompts and from provider-generated web queries.

## Workflow

<Steps>
  <Step title="Collect candidate language">
    Export relevant prompts, observed web queries, source titles, and GSC queries for a defined topic and period.
  </Step>

  <Step title="Group by audience need">
    Cluster terms by the question or decision they represent. Use topics as the primary semantic grouping and tags as reusable secondary labels.
  </Step>

  <Step title="Check current evidence">
    Read the stored answers and cited sources for each group. Note where your brand or first-party sources are present, absent, or represented inaccurately.
  </Step>

  <Step title="Prioritize tests">
    Select terms that are relevant to the business and supported by observed demand or coverage gaps. Define the content change and the metric slice you will monitor.
  </Step>
</Steps>

## Interpretation

A keyword list is a planning artifact. It does not show the exact input a model used or guarantee a citation. Evaluate changes on stable prompt and provider cohorts. Product Mention Rate is answers with a SELF mention divided by answers with at least one SELF or DIRECT brand mention; it is not a keyword ranking metric.

## Possible next actions

* If GSC demand is present but SELF citations are limited, test content that answers the same audience need with verifiable evidence.
* If Query Fan-Out reveals recurring observed searches, consider adding a representative configured prompt before creating content.
* If one topic contains unrelated intents, split the topic and keep cross-cutting labels as tags.

## Limitations

Query Fan-Out is an observed subset, not an exhaustive list of what people or models search for. GSC and Qwairy measure different surfaces. Correlation between a term, a ranking, and an AI citation does not establish causation.

## Related pages

<CardGroup cols={2}>
  <Card title="Exports" href="/documentation/workspace/exports">
    Export the selected dataset for research.
  </Card>

  <Card title="Keyword Performance" href="/looker-studio/sources/keyword-performance">
    Review the Looker Studio source for keyword reporting.
  </Card>

  <Card title="Google Search Console" href="/documentation/measure/google-search-console">
    Understand the connected traditional-search data.
  </Card>

  <Card title="Choose what to create" href="/use-cases/content/what-content-to-create">
    Turn a research list into content hypotheses.
  </Card>

  <Card title="Google rank versus AI presence" href="/use-cases/content/rank-in-google-invisible-in-ai">
    Compare two distinct measurement surfaces.
  </Card>

  <Card title="Gap to article" href="/use-cases/content/content-gap-to-cited-article">
    Run a documented publishing experiment.
  </Card>

  <Card title="Pages cited by AI" href="/use-cases/content/pages-most-cited-by-ai">
    Inspect the URLs recorded as citations.
  </Card>
</CardGroup>


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