For insurers
The AI answer layer for insurance
Buyers ask an AI which cover to get and who to get it from, long before they request a quote. LBOX measures what the engines say about you, finds where an aggregator is answering in your place, and builds the evidence that changes it.
Measured across
Perplexity
Gemini
Google AI
Claude
Copilot
Meta
DeepSeekGrok... and moreEvery one of them is competing for the same answer. One name comes back when a buyer asks.
What makes insurers different
Not general marketing advice. These are the constraints your category actually operates under.
What you may say depends on where they live. The engine does not know or care.
Licensing, permitted language and product availability change by state and by jurisdiction. An engine answering a buyer in a state you are not admitted in will still recommend, describe or price you, with none of the disclosures you are bound by.
Aggregators own the answer.
NerdWallet, Policygenius and Bankrate are what the engines cite when asked who to insure with. Those tables were built for affiliate economics, and they are now the source a model paraphrases as neutral advice.
The shortlist forms before the quote request.
By the time someone reaches your form, an answer has already named three carriers or brokers and explained why. The quote is not the start of the funnel any more; it is the end of one you never saw.
Claims reputation is written by other people.
How you pay claims is the deciding factor in this category, and the engines learn it from complaint indexes, review threads and forum posts. It is the most important thing said about you and the least controlled.
What you get back
The console, measuring a insurers company against the questions its buyers ask. Every brand named, every domain cited, every engine separately.
A worked example on an illustrative company, shown to display the console. Your own numbers come from measuring your questions through the engines’ own APIs.
See how every model describes your cover
Visibility and position on the unbranded questions buyers ask, measured per engine, before any quote request exists.
- Ranked against the carriers the engines actually named
- See where a model reads your policy pages without naming you
You against the field, engine by engine
unbranded questions| Brand | Gemini | AI Overviews | OpenAI | Perplexity | Claude | ChatGPT |
|---|---|---|---|---|---|---|
| Harrow Assurance | 32% | 28% | 27% | 23% | 15% | 31% |
| Stonebridge Cover | 25% | 22% | 20% | 18% | 12% | 24% |
| Wexford Mutualyou | 21% | 12% | 18% | 14% | 8% | 2% |
| Ardent Insurance Group | 14% | 11% | 10% | 12% | 6% | 11% |
Turn what the answers get wrong into work compliance can approve
Findings arrive as a worklist sorted by who can act: what LBOX drafts, what needs compliance sign off, what needs your web team.
- Scored against your category, not a generic checklist
- Nothing publishes without your approval
The worklist
Prove the change, quarter after quarter
Every measurement is stored, so the line lengthens each cycle and the movement is on the record rather than asserted.
- The same questions, asked again and checked
- Sources broken out per model, per page
Visibility over time
every measured runKnow when the models come to read your policy pages
Crawler activity captured at the edge, so you can see which models fetch your product and disclosure pages, and how often they return.
- Every model, every page, logged over time
- Robots and content signals kept current
Crawler activity
hits by model, last 30 daysWhere you disappear as the buyer gets closer to a quote
Presence falls away as intent rises. The who-should-I-buy-from questions are the ones that convert, and the ones aggregators win.
- Visibility split by where the question sits in the journey
- Names the stage that costs you the quote
Visibility by buying stage
where you show up in the journeyThe sources the engines trust in insurance
Comparison sites, complaint indexes and forum threads decide what the engines repeat about you. Almost none of it is yours, which is exactly why it can be changed.
- Owned versus earned, so you know what to build and what to earn
- Every citation traced to the answer it supported
Which domains the engines cite
812 citationsThe insurers program
Everything below is included. Measured through the engines’ own APIs, so the same questions can be asked again and the result checked.
- Measure what every major AI engine says about your products today, through the engines own APIs
- The cover questions buyers actually ask, mapped by product, life event and jurisdiction
- Where an aggregator or comparison site is answering in your place
- Which sources the engines cite for your category, and which of those you control
- Whether the engines describe your cover, exclusions and eligibility correctly
- Evidence pages built from your own policy and claims documentation, in a form engines can read
- Re-measurement on the same questions, so the change is provable rather than asserted
What this does not show: what any individual user saw. LBOX measures what the engines answer through their own APIs, which is repeatable and checkable. It is not a record of any one person’s session, and it does not predict revenue.