How is CiteRank AI different from legacy SEO tools?

Legacy SEO tools measure Google rankings. CiteRank AI measures whether ChatGPT, Gemini, Claude, Perplexity, Google AI Overviews, Microsoft Copilot, xAI Grok and Meta AI 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.

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. Basic tracks 5 competitors, Growth tracks 25, and Premium is unlimited with local per-branch tracking. 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.

Education · Industry benchmark

Stage 0 · Framework live · benchmark pending

'Best app to prepare for UPSC/JEE/NEET' — millions of decisions, now made inside AI answers.

Q: 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.

CiteRank measures who AI engines recommend in edtech — 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 3 engines; full tracking covers all 8.

Run free audit See sample report Book a demo

8 × 2

Engines × modes (grounded + ungrounded)

250+

EdTech buyer prompts per run

Weekly

Re-runs · 95% confidence bands

Who AI recommends today

The edtech 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 EdTech 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

PhysicsWallah

62%

31%

34%

02

Unacademy

48%

22%

24%

03

Vedantu

39%

14%

18%

04

BYJU'S

27%

14%

05

Adda247

18%

10%

Illustrative sample — benchmark not yet completed.

Sample prompt set

Real edtech prompts, eight engines, one question: did you get cited?

Buyer prompt
ChatGPT
Gemini
Claude
Perplexity
AI Overviews
Microsoft Copilot
xAI Grok
Meta AI
You cited?

"best app for UPSC preparation in 2026"

—

—

—

—

—

—

—

—

Not yet

"PhysicsWallah vs Unacademy for JEE"

—

—

—

—

—

—

—

—

Not yet

"free vs paid tracks for NEET — which app is best?"

—

—

—

—

—

—

—

—

Not yet

"live batch teachers reviews {brand} 2026"

—

—

—

—

—

—

—

—

Not yet

Where the citations leak

Three failure modes specific to education.

01

Aggregator capture: Shiksha, Collegedunia, CareerWise absorb 'best college / app for X' citations.

02

Fee and placement hallucinations leak admissions-funnel intent to the wrong shortlist.

03

Faculty and course catalogs aren't structured as AI-citable entities, so AI invents the answer.

Methodology

How a edtech benchmark gets built.

01

Onboard

URL, competitors, prompt seed list. 5 minutes.

02

Audit

250+ prompts × 8 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 customer results publish Q4 2026.

Before

1 / 25

Cited in 1 of 25 high-intent edtech 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.

Case study

EdTech 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.

Talk to sales

Insights

Coming in the EdTech visibility report.

Article · in the edtech report

Exam-prep share of voice across 8 engines, exam by exam

Notify me when published

Article · in the edtech report

Course-catalog GEO: keeping AI current on live batches

Notify me when published

Article · in the edtech report

Teacher entities: making faculty AI-citable assets

Notify me when published

FAQ

EdTech questions, answered.

How is CiteRank different from marketplace listings?+

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 edtech 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.