Article · in the insurance report
Finance · Industry benchmark
Stage 0 · Framework live · benchmark pendingTerm, health, motor — AI shortlists 3 insurers before your agent ever calls. Are you on it?
CiteRank measures who AI engines recommend in insurance — across ChatGPT, Gemini, Claude, Perplexity, Google AI Overviews, Microsoft Copilot, xAI Grok and Meta AI, in both grounded and ungrounded modes — and fixes why it isn't you.
Vertical benches currently run 8 engines; full tracking covers all 8.
8 × 2
Engines × modes (grounded + ungrounded)
250
Insurance tracked prompts per run on Platform
Weekly
Re-runs · 95% confidence bands
Who AI recommends today
The insurance leaderboard, measured.
Top-5 brand mention rate, first-mention rate and Share of Voice — straight from the citerank-bench scoring tables, recomputed weekly.
Benchmark for Insurance runs with our first customer in this vertical. The leaderboard below is an illustrative sample built from the blueprint's brand registry — numbers are placeholders, not measurements.
#
Brand
Mention rate
First-mention
Share of Voice
01
LIC
62%
31%
34%
02
HDFC Life
48%
22%
24%
03
ICICI Prudential
39%
14%
18%
04
Max Life
27%
9%
14%
05
Policybazaar
18%
5%
10%
Illustrative sample — benchmark not yet completed.
Category intelligence
Insurance Citation Patterns: The Aggregator Moat
Direct citations inside AI answers are governed by three signals: prompt-intent alignment, engine-specific grounding skew, and domain authority in the Knowledge Graph.
Top observed buyer prompts
- "best term insurance for NRI in UAE"
- "HDFC Ergo vs Star Health for senior citizens"
- "car insurance with zero dep for EV"
- "is Acko reliable for high claim amounts?"
Engine-specific grounding skew
PerplexityClaim-settlement & IRDAI data focus
ClaudePolicy exclusion & fine-print analysis
AI OverviewsAggregator-led comparison tables
Top cited domains (Insurance)
01policybazaar.com
SOV
02irdai.gov.in
SOV
03livemint.com
SOV
04hdfcergo.com
SOV
This view summarises prompt replays captured across 8 AI engines during scheduled monitoring runs. CiteRank platform users access the full graph, refreshed on their plan's monitoring schedule.
Sample prompt set
Real insurance prompts, eight engines, one question: did you get cited? Gartner predicts a 25% shift from search to AI agents by 2026 (Gartner).
Buyer prompt
ChatGPT
Gemini
Claude
Perplexity
AI Overviews
Microsoft Copilot
xAI Grok
Meta AI
You cited?
"best term insurance for a 30-year-old non-smoker"
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—
—
—
—
—
—
Not yet
"health insurance that covers parents above 60"
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—
—
—
—
—
—
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Not yet
"claim-settlement ratio comparison 2026"
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Not yet
"cheapest motor insurance with cashless garages in Bengaluru"
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Not yet
Where the citations leak
Three failure modes specific to finance.
01
Hallucinated rates, fees and APRs surface as a compliance exposure, not a marketing one.
02
Aggregators (Policybazaar, Bankbazaar, ETMoney) capture comparison prompts.
03
Product pages that win Google rank don't win LLM citations — the format the engines need is different.
Methodology
How a insurance benchmark gets built.
01
Onboard
URL, competitors, prompt seed list. 5 minutes.
02
Audit
25 prompts × 8 engines × 2 modes, 10–20 replays each.
03
Fix
Schema, llms.txt, entity hygiene, content briefs — shipped.
04
Re-run
Weekly re-runs, deltas with 95% confidence bands.
Illustrative pattern
What a 90-day citation delta looks like.
Illustrative pattern based on our methodology — first customer results publish Q4 2026.
Before
1 / 25
Cited in 1 of 25 high-intent insurance prompts across 8 engines (4%).
After · 90 days
9 / 25
Cited in 9 of the same 25 prompts (36%) — schema, llms.txt and entity fixes shipped over 3 weekly re-runs.
Category Intelligence
Insurance Citation Patterns: The Aggregator Moat
This section contains Verified Category Data observed during current Insurance monitoring runs. These patterns define how AI engines rank your competitors and why certain brands are cited over others.
Top Category Prompts
- "best term insurance for NRI in UAE"
- "HDFC Ergo vs Star Health for senior citizens"
- "car insurance with zero dep for EV"
- "is Acko reliable for high claim amounts?"
Engine Citation Skew
PerplexityClaim-settlement & IRDAI data focus
ClaudePolicy exclusion & fine-print analysis
AI OverviewsAggregator-led comparison tables
Dominant Source Domains
policybazaar.comirdai.gov.inlivemint.comhdfcergo.com
Case study
Insurance case study publishes after the first 90-day window.
We don't ship anonymous success stories. Every case study card on this page becomes a real logo, real prompts and real deltas after the customer's 90-day window closes.
Insights
Coming in the Insurance visibility report.
Article · in the insurance report
The aggregator moat in insurance AI answers — and three ways around it
Notify me when publishedArticle · in the insurance report
When AI invents exclusions: monitoring hallucinated policy terms
Notify me when publishedFAQ
Insurance questions, answered.
How is CiteRank different from Policybazaar / Bankbazaar style comparison sites?+
Those surfaces optimise for their own funnel. CiteRank measures how often ChatGPT, Gemini, Claude, Perplexity, Google AI Overviews, Microsoft Copilot, xAI Grok and Meta AI actually name your brand for insurance buyer prompts, then fixes the schema, entity and content gaps so the engines have something to cite besides the aggregator.
Which segments / cities do you cover for this vertical?+
We start with your highest-intent buyer prompts (250 tracked prompts on Platform, 500 on Platform + GEO) — segmented by city, persona and price band as relevant — and expand the prompt graph weekly. Coverage scope is set during the 5-minute onboarding.
How fast to first new citation?+
First measurable citation lift is typically 3–5 weeks after the first fix pass (schema, llms.txt, entity, content briefs). Re-runs are weekly with 95% confidence bands so you can attribute deltas to specific fixes.
Is our data sent to LLMs?+
Only the public buyer prompts we run on your behalf reach the engines — exactly what a prospective customer would type. We do not send your CRM, customer data, or internal documents to any LLM.
How to start
Start with one snapshot. Scale into weekly monitoring.
Snapshot Audit
One-time
25 prompts × 8 engines × 2 modes. Brand-mention report and gap analysis.
Monitor
Ongoing
Weekly re-runs, deltas with confidence bands, alerting on rank/citation changes.
Visibility + Fixes
Ongoing
Monitor + shipped fixes: schema, llms.txt, entity, content briefs and re-measurement.
Keep exploring