Showing up in Gemini

A surface we watch and deliberately do not score, and the reasoning matters more than the page.

Chapter last reviewed 2026-07-26. AI platform behaviour changes quickly, so read anything here against that date.

Is Gemini in Mindflow Marketing's counted set?

Gemini is not in our counted set. Our published protocol counts three surfaces: Google AI Overviews, ChatGPT and Perplexity. Gemini is not one of them. That is a deliberate scoping decision, not an oversight, and stating it plainly is the point of this page.

A protocol that never names what it excludes is a claim rather than a protocol.

Why is Gemini excluded from the score?

Gemini sits outside the score for one reason, and that reason is sampling. Deterministic, repeatable sampling under controlled conditions is what makes an X/12 figure mean anything. Where we cannot hold conditions steady enough for a repeat run to be comparable, a score would look like measurement while being closer to anecdote.

We would rather report three surfaces honestly than four surfaces where one number is doing decorative work.

What does Mindflow Marketing do with Gemini instead?

Gemini is watched rather than scored. We look at it. Where a client's presence in Gemini is visibly different from the counted surfaces, that shows up in the report as an observation with the evidence attached, described, dated, and not scored.

The underlying work is the same regardless. Entity clarity, citation surfaces and citable content are what move every one of these systems, and none of them are Gemini-specific tactics.

What happens if Gemini becomes measurable?

Nothing on this page is permanent, and a change would be published rather than made quietly. The protocol is versioned and dated. If sampling conditions become stable enough to count Gemini properly, it goes into the counted set, the version increments, and the report says which version produced the number.

The measurement protocol behind this chapter is published in full on the methodology page.

Rankings are never guaranteed. Anything we could not trace to a primary source is absent from this page, not estimated. The audit runs the same six layers described on the pricing page, and Share of Answer is scored quarterly.

Read in order, or jump

The order here is the order of the work: twelve chapters, the first four structural, the last of them covering two platforms we decline to score and why we decline.

01 How AI search picks local businesses 02 Eligibility: can AI even see your site? 03 Robots.txt: block AI crawlers or allow them? 04 Measuring AI visibility honestly 05 Entity foundations for local businesses 06 Reviews as AI input 07 Citation surfaces: where AI engines look 08 Getting ChatGPT to recommend your business 09 Showing up in Perplexity 10 Showing up in Google AI Overviews 11 Showing up in Gemini 12 Copilot, and why we don't sample it

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