Check fanout questions against Search Console data
Search Console shows search performance for your website, while fanout supplies possible research questions. Connect them through the reader task and target page. An exact phrase match helps, but is not required; a missing phrase does not establish that the question has no demand.
You need access to the correct GSC property and an existing export or question plan. The example file deliberately contains no real GSC queries, impressions or positions.
Start with a clearly labelled query listUse an existing export or run a short topic. Keep native observations and modelled ideas separate.Open the toolDefine the data scope and target page first
Open the correct property and choose Web search. Record the displayed range and data freshness. Viewing Search Console today does not mean the last few hours are complete. Use equal-length windows and the same filters for later comparisons.
Copy the question and its origin into the CSV. candidate_page is the strongest existing page for that reader task, or a destination explicitly labelled as a draft. A fanout string is not search volume. Connect each row to the input and cluster worksheet through query_id.
Identify the reader tasks in the clustering worksheet.
The example continues q01 and q03 from the fictional SEO buying guide. Both refer to one page, with q03 referring to its cost section. gsc_query, gsc_date_range and country_device_scope stay empty; evidence_status is not_checked. This is a prepared mapping whose data check has not been performed.
Keep your own GSC data in your intended working environment. The downloads here are static editorial templates. You do not need to send Search Console data to ai-fanout.com to use this guide.
Map visible search queries to the task
Start with the relevant page in the performance report and inspect its search queries. Look for appropriate wording, not just the exact fanout string. Different team and business phrases may express the same selection decision. Review the meaning of each visible row before mapping it.
Record the actual visible GSC query and the page, country and device filters. Do not compare an English US desktop subset with unfiltered German data. Average position summarises appearances for that filtered row; it is not a stable daily individual rank.
For a new URL, Search Console may have no history for that page yet. Use relevant existing pages for orientation and record the limit. Your website's data describes its own visibility, not the whole market. Missing market metrics require a separate source with a named market and date.
Distinguish relevant visible data, unchecked data and a question not visible within the chosen scope in evidence_status. next_action states the task: inspect an existing section, obtain evidence or observe a longer window. The mapping should make the decision reviewable rather than automatically publishing content.
Observation and supported next step
Decision rules, not claimed measurements.
| Finding | What it supports | Next step |
|---|---|---|
| Relevant visible query | This site had appearances in the chosen scope | Review target page and actual reader question |
| No matching row | Question not visible in this subset | Review filters, coverage and a longer window |
| New URL without history | No page baseline yet | Record publication and recrawl |
| Fanout branch without GSC check | Research hypothesis | Check demand and evidence separately |
Handle missing rows honestly
Search Console omits anonymised queries. Query rows and filtered reports may also cover different totals, so the sum of your visible questions need not equal the overall value. Carry this limitation into your review.
The API does not guarantee every query row either. A cut or subset is not complete proof of zero demand. Distinguish no matching row found from demand equals zero. First check whether the range, property, page and filters fit the question at all.
Pass the completed mapping and clusters into the content brief. If a question remains unchecked, assign research to the editor. Keep release and recrawl dates and the same filtering scope for follow-up; this makes observations comparable without presenting fanout as the cause of every change.
The reviewed questions become part of your content brief.
Sources used
These sources support the functions and limits described here. They do not prove claims beyond that scope.
- Original query-clustering, content-brief and GSC-mapping worksheetsOpen source
Blank worksheets and completed teaching examples. Seven illustrative questions and fictional website paths support the walkthrough only. No real provider output, client result, GSC measurement or keyword volume is published in these files.
- Google Search Console: dimensions and data groupingsOpen source
Explains query, page and filter scope and the omission of anonymised queries. Missing visible query rows do not establish zero market demand.
- Search Console API: getting performance dataOpen source
Explains extraction and data-coverage limits. It supports a careful measurement workflow, not a claim that the tutorial or fanout ideas have measured search demand.
- Optimizing for generative AI features on Google SearchOpen source
Normal SEO foundations remain relevant; pages made primarily for fan-out variations are not the accepted content model.