Working on it

1Translating the keyword into one real question
2Running it through ChatGPT + AI Overviews
3Reading the answers, finding brand mentions + citations
4Calculating volume-weighted visibility
iris datasetin ChatGPT and AI OverviewsUK market · Q3 2026 snapshot320/mo

iris datasetAI visibility in ChatGPT and AI Overviews

320 monthly Google searches
#software#data science2 brands named5 brands named
Keyword report
1

How we read this intent i

A keyword searched in Google carries the same intent as a question asked in AI. Your keyword anchors the report, because its demand is measurable and verifiable (Google search volume); the answer side shows what AI says when it gets asked the same thing.

Your keyword in Google
iris dataset
320 searches/mo i
The report anchors here: Google search volume is the one demand number anyone can verify.
The same intent, asked in AI
“What is the iris dataset and where can I find it?”
One of the many ways people ask AI for the same thing. Different phrasings, the same underlying intent.
2

What AI answered i

Brands AI named
UCIscikit-learn
Sources cited
#1datalab-12.ics.uci.edu#2scikit-learn.org#3archive.ics.uci.edu#4github.com
3

Similar searches i

Similar searches

Every search with a similar intent: each keyword, its volume and the brands AI names on it. Free accounts unlock it.

4

Share of voice across similar searches i

Share of voice

Who owns these searches in AI answers, weighted by real search demand.

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