Article · in the edtech report
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.
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 8 engines; full tracking covers all 8.
8 × 2
Engines × modes (grounded + ungrounded)
250
EdTech tracked prompts per run on Platform
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 audit benchmark scoring tables, recomputed on a scheduled cadence.
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%
9%
14%
05
Adda247
18%
5%
10%
Illustrative sample — benchmark not yet completed.
Category intelligence
EdTech Citation Dynamics: The Teacher Entity 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 UPSC current affairs app 2026"
- "PhysicsWallah vs Unacademy for NEET"
- "is Khan Academy enough for JEE prep?"
- "PW Vidyapeeth reviews for Bengaluru"
Engine-specific grounding skew
ChatGPTFaculty & Teacher-led recommendations
AI OverviewsCourse-catalog & Fee comparison
GeminiLocal coaching center discovery
Top cited domains (EdTech)
01physicswallah.live
SOV
02unacademy.com
SOV
03quora.com
SOV
04shiksha.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 edtech 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 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
5–7 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.
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 3 of the same 7 prompts (42%) — schema, llms.txt and entity fixes shipped over 3 weekly re-runs.
Category Intelligence
EdTech Citation Dynamics: The Teacher Entity Moat
This section contains Verified Category Data observed during current EdTech monitoring runs. These patterns define how AI engines rank your competitors and why certain brands are cited over others.
Top Category Prompts
- "best UPSC current affairs app 2026"
- "PhysicsWallah vs Unacademy for NEET"
- "is Khan Academy enough for JEE prep?"
- "PW Vidyapeeth reviews for Bengaluru"
Engine Citation Skew
ChatGPTFaculty & Teacher-led recommendations
AI OverviewsCourse-catalog & Fee comparison
GeminiLocal coaching center discovery
Dominant Source Domains
physicswallah.liveunacademy.comquora.comshiksha.com
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.
Insights
Coming in the EdTech visibility report.
Article · in the edtech report
Course-catalog GEO: keeping AI current on live batches
Notify me when publishedArticle · in the edtech report
Teacher entities: making faculty AI-citable assets
Notify me when publishedFAQ
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 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
5–7 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