How should you read the result?
Forty subquery occurrences describe the selected context, not page quality or Google search demand. The readiness score is a separate technical metric.
AI Visibility
What question does it answer?
Investigate a specific page in the context of a selected question or topic, combining technical checks, available performance data, and observed query fan-out. An accessible URL and appropriate permissions are required. Analytics and search data require active authorised connections. Fan-out uses stored results, rather than launching a new search campaign for every subquery.
Sample project
Explore this feature with sample data
Northstar · illustrative project · comparable 30-day periods. These examples explain how to use and interpret the measurements.
Investigated URLs
1Sample readiness
84 / 100Subquery occurrences
40Figures shown are illustrative sample data.
Forty occurrences overall. Changes also depend on retrieval counts and provider coverage.
Figures shown are illustrative sample data.
- Enter a URL and select a relevant prompt or tag
- Start the background investigation
- Compare technical status with sources and subqueries
- Identify evidence-based follow-up investigations
| Metric / scope | Sample value | Interpretation |
|---|---|---|
| northstar.example/services | HTTP 200 | Successful retrieval |
| Selected prompt | Choosing an SEO agency | Investigation context |
| Pricing subquery | 18 occurrences | From related stored results |
| Google indexing | Unknown | Inspect source availability separately |
Figures shown are illustrative sample data.
Which decision does it support?
Pricing-related subqueries can focus review of whether the page provides clear, current information about service terms.
What should you check first?
Context relevance and provider coverage matter. Missing subqueries or analytics do not prove zero performance.
What do you see?
- Targeted technical checks and PageSpeed snapshot
- Available URL 360 and selected prompt or topic context
- Connected search and analytics data plus stored provider query fan-out
How do you use it to decide?
- Enter a URL and select a relevant prompt or tag
- Start the background investigation
- Compare technical status with sources and subqueries
- Identify evidence-based follow-up investigations
An illustrative use case
A provider-selection question produces subqueries about pricing and references. URL analysis places these stored search signals alongside the service page’s technical and available performance context.
An illustrative scenario, not a customer result or a promise of results.
What does measurement require?
An accessible URL and appropriate permissions are required. Analytics and search data require active authorised connections. Fan-out uses stored results, rather than launching a new search campaign for every subquery.
Frequently asked questions
How does it use query fan-out?
It collects subqueries from stored results in the selected prompt or topic context and groups them by provider.
Does it run every subquery again?
Stored subqueries provide context; their inclusion does not imply a separate new SERP retrieval for each phrase.
What happens with HTTP 403?
Access denial may end the investigation with limited technical results. Investigate access first.
What should I check before comparing periods?
Check the selected question or URL, filters, sample size, source coverage, and data freshness. Different scopes can produce differences unrelated to a real change.
Does missing data mean zero performance?
No. A source connection, retrieval, or processing step may be missing. Check availability before interpreting an empty block.
Can I use this to guarantee an AI recommendation?
The feature supports evidence-based investigation. It does not control provider answers or guarantee recommendations or citations.
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Request a quote for your project
Tell us which brand and website you want to measure and what question you need to answer. We will discuss the subscription and data connections your project requires.