How is CiteRank AI different from Competitor 1, Competitor 2 or other SEO tools?

Legacy SEO tools measure Google rankings. CiteRank AI measures whether ChatGPT, Gemini, Claude, Perplexity and Google AI Overviews actually recommend a brand when buyers ask a question. The two are complementary, but AI search is a separate surface with its own ranking signals that traditional rank trackers do not audit.

Which AI engines does CiteRank AI track?

CiteRank tracks citations across ChatGPT, Google Gemini, Anthropic Claude, Perplexity, Google AI Overviews, Microsoft Copilot, xAI Grok and Meta AI. Each prompt is fired 10 to 30 times per engine to control for model variance.

How accurate is the visibility score?

The visibility score is a composite of citation share, recommendation order and sentiment, aggregated across 10 to 30 replays per prompt per engine, and is reported with 95% confidence bands so users can distinguish signal from model variance.

Can I track competitors with CiteRank AI?

Yes. Starter tracks 5 competitors, Growth tracks 25, and Agency is unlimited across 10 workspaces. There is no per-competitor charge on any plan.

What does the free audit include?

A 14-day free trial includes AI citation audits across keywords and all tracked LLMs, monitoring, PDF export, and a competitor view showing which brands AI cites instead of yours. No credit card is required to start.

Finance · Industry benchmark

Stage 0 · Framework live · benchmark pending

Term, 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 and Claude, in both grounded and ungrounded modes — and fixes why it isn't you.

Run free audit See sample report Book a demo

3 × 2

Engines × modes (grounded + ungrounded)

250+

Insurance buyer prompts per run

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 founding 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%

14%

05

Policybazaar

18%

10%

Illustrative sample — benchmark not yet completed.

Sample prompt set

Real insurance prompts, three engines, one question: did you get cited?

Buyer prompt
ChatGPT
Gemini
Claude
You cited?

"best term insurance for a 30-year-old non-smoker"

—

—

—

Not yet

"health insurance that covers parents above 60"

—

—

—

Not yet

"claim-settlement ratio comparison 2026"

—

—

—

Not yet

"cheapest motor insurance with cashless garages in Bangalore"

—

—

—

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

250+ prompts × 3 engines × 2 modes, 10–30 replays each.

03

Fix

Schema, llms.txt, entity hygiene, content briefs — shipped.

04

Re-run

Weekly re-runs, deltas with 95% confidence bands.

Read the full sample report

Illustrative pattern

What a 90-day citation delta looks like.

Illustrative pattern based on our methodology — first cohort results publish Q4 2026.

Before

1 / 25

Cited in 1 of 25 high-intent insurance prompts across 3 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.

Founding cohort

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.

Founding seats · openApply for a founding seat

Insights

Coming in the Insurance visibility report.

Article · in the insurance report

Claim-settlement prompts: which insurers AI trusts, and which data it's citing

Notify me when published

Article · in the insurance report

The aggregator moat in insurance AI answers — and three ways around it

Notify me when published

Article · in the insurance report

When AI invents exclusions: monitoring hallucinated policy terms

Notify me when published

FAQ

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 and Claude 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 250+ highest-intent buyer prompts — 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.