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When an AI platform answers a question, it often proposes what to ask next. Those suggestions are fan-outs, and they’re a direct read on how the model thinks your category branches — which makes them a ready-made list of queries worth tracking. Open Intelligence → Fan-outs.

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Headline numbers

Every rate and average on this page divides by responses that produced at least one fan-out — never by all responses in the period. That’s why Avg per Response can never drop below 1.0, and why adding models that don’t emit fan-outs won’t move it.
Uniqueness is an exact-text match. Best CRM 2026 and best CRM 2026 count as two distinct fan-outs.

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Top Fan-Outs

A word cloud of the most frequent follow-up queries, with Unigrams / Bigrams / Trigrams toggles.
This is a cloud of terms extracted from the top 50 fan-out texts, weighted by how often each text occurred — not a cloud of the fan-out queries themselves. Stop words and very short tokens are dropped. Bigrams and trigrams are usually the readable views.

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Fan-Outs by Query

Which of your queries generate follow-ups, and how many: Only queries that produced at least one fan-out appear. Sort by any numeric column. Expand a row to see that query’s individual fan-outs, each with its occurrence count and rate. The header tells you the denominator explicitly — “(n responses with fan-outs)”. The ⋮ menu exports the current page along with every fan-out belonging to those queries.

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Turning fan-outs into queries

The practical loop:
  1. Read the bigram/trigram cloud for themes you don’t currently track.
  2. Expand your highest-volume queries and skim the actual follow-up texts.
  3. Add the good ones as new queries in Project settings → Queries.
A fan-out that appears in most responses is a question the model considers unavoidable in your category. If you have no visibility on it, that’s a gap worth closing.
View as has no effect here — fan-outs belong to a response, not to a brand, so the page is never re-scoped to another entity.

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Exporting

Project settings → Export data → Fan-Outs By Query produces two CSVs: per-query aggregates, and one row per unique fan-out per query with its occurrence count and rate.