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Mehul Jain
Mehul Jain

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Your insurance brand is missing from the AI answer. Here is how to measure why.

#insurance #ai #seo #marketing

If you work on growth or SEO for an insurance brand that is not State Farm, you have probably typed your own category into ChatGPT and watched it recommend seven companies, none of them yours. The instinct after that is to go rewrite a landing page. That is almost always the wrong first move, because you have not measured anything yet. You do not know which questions you lose, which engines you lose them on, or which sources those engines are actually reading.

This is a measurement problem before it is a content problem. Here is how to instrument it.

What the data says you are up against

Geology ran the version of this test that most teams never get around to. In its June 2026 insurance study, 100 insurance buyer prompts went through ChatGPT, Perplexity, Gemini, and Google AI Overviews, tracking 15 insurers. Incumbents took 78 to 82 percent of insurer mentions on ChatGPT, Perplexity, and Gemini, and 66 percent on the more balanced Google AI Overviews.

Two details from that study are the ones you will build your measurement around:

  1. The engines cite external surfaces, not carrier sites. On ChatGPT, only about 1 percent of the roughly 16 sources per answer were carrier-owned. The rest were aggregators and editorial (MoneyGeek, Forbes, NerdWallet). On Perplexity, Reddit was the single most-cited source, in 75 of 100 answers.
  2. Challengers win by niche. Next Insurance took its share almost entirely in small business; Lemonade in renters and pet. General-purpose challengers barely registered.

You cannot act on either of those until you have your own version of the numbers for your own brand. So build it.

Step 1: build a prompt set that mirrors how people actually ask

Do not test one query. Insurance buyers ask in predictable shapes, and your visibility differs wildly across them. Build 40 to 100 prompts across four buckets:

  • Category: "best renters insurance", "cheapest small business insurance"
  • Problem: "how do I insure a side business", "renters insurance for a home studio"
  • Comparison: "Lemonade vs State Farm renters", "best alternatives to GEICO"
  • Niche: the specific situations where you think you have a right to win

Store them as data, not as a doc, so the run is repeatable:

[
  { "id": "cat-01", "bucket": "category", "prompt": "best renters insurance 2026" },
  { "id": "niche-04", "bucket": "niche", "prompt": "renters insurance for a freelance photographer with gear" }
]
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Step 2: run each prompt across the engines and log two things

For every prompt on every engine, record two fields: were you named, and which sources were cited. That second field is the one most audits skip, and it is where the strategy actually comes from.

{
  "prompt_id": "cat-01",
  "engine": "perplexity",
  "brands_named": ["State Farm", "Lemonade", "Progressive"],
  "you_named": false,
  "sources_cited": ["reddit.com/r/insurance/...", "nerdwallet.com/...", "moneygeek.com/..."]
}
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Run it manually for a first pass if you have to. If you want it repeatable, the Perplexity and Gemini APIs return citations directly, and for ChatGPT and AI Overviews you can script the browser. The point is a table you can rerun next month and diff.

Step 3: compute the two numbers that matter

From that log, derive:

  • Share of voice per bucket = the fraction of prompts in a bucket whose answer named you. Do this per engine. You will almost certainly find your share is near zero on category prompts and higher on a niche or two. That split is your whole strategy.
  • Cited-source mix = across the prompts you lose, which domains keep getting cited. Rank them. This is your target list. If MoneyGeek, NerdWallet, and one subreddit account for most of the citations in your niche, those three surfaces are where your visibility is decided, not your blog.

Step 4: act on the surfaces, not the homepage

Now the fixes are obvious because the data pointed at them.

  • Pick the one bucket where your share of voice is already non-zero and go all in. That is the niche the engines are willing to let a challenger own. Next Insurance and Lemonade did not win by breadth. They won one room.
  • Get accurate, specific facts about your niche onto the cited surfaces. For the aggregators, that means being includable: clear coverage details, real pricing ranges, honest eligibility rules, in the liftable format a writer needs. For community surfaces like Reddit, it means being genuinely useful in real threads, not planting anything, because that gets caught and it poisons the exact signal you want.
  • Re-run the whole test on a fixed cadence and watch share of voice per bucket move. That diff is the only proof your work did anything.

Geology's breakdown of how insurance brands win in AI answers covers the content side of this in more depth, and its insurance AI-visibility service is the same measure-then-act loop run end to end. But the sequence starts here, with measurement. You cannot fix a visibility gap you have not located, and for insurance the gap is almost never on the page you were about to go rewrite.

Mehul Jain writes about generative engine optimization at Geology, where the team studies how AI engines decide which brands to recommend. This piece draws on Geology's June 2026 insurance visibility study.

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