AI Visibility Benchmark 2025: How India’s Top General Insurers Rank in ChatGPT & Perplexity
🔍 Introduction: The Rise of AI-First Search in Insurance
For over two decades, SEO was simple — rank high on Google, get clicks, and win customers.
But in 2025, a quiet revolution is reshaping how discovery happens.
Today, users aren’t searching like they used to.
They’re asking AI assistants like ChatGPT, Perplexity, and Bing Copilot directly:
“Which is the best general insurance plan in India?”
“Which insurer has the highest claim ratio?”
“Which company is most trusted for car and health coverage?”
And the AI doesn’t show 10 blue links. It gives one synthesized answer, backed by a few cited brands.
Those mentions — not rankings — are shaping public trust faster than traditional search results ever did.
This marks the emergence of AI Visibility — the new competitive frontier for insurers and agencies.
In traditional SEO, Google ranks pages.
In AI-first discovery, AI ranks brands.
📘 Index
1️⃣ Background: Why Google ≠ AI Visibility
For years, SEO success was defined by one rule —
“Rank high on Google, and you’ll be discovered.”
But in 2025, users are bypassing Google altogether.
They’re asking AI directly — and AI decides which brands to recommend.
There are no blue links.
No ad sections.
No scrollable results.
Just a short, authoritative summary — with 3–5 cited brands.
If your brand isn’t mentioned, you’re invisible in that moment of truth.
That’s the new challenge facing insurers in the age of AI-first discovery.
2️⃣ The Experiment: Benchmarking India’s General Insurers
To understand how AI assistants perceive India’s general insurance landscape, we conducted a first-of-its-kind AI Visibility Benchmark using LLMClicks.ai.
Scope of the Study:
- 💬 100 real-world LLM queries across multiple intents
- 🧠 Tested across ChatGPT and Perplexity
- 🔗 Logged every brand mention, citation source, and response type
The dataset included leading players like ICICI Lombard, Reliance General, HDFC ERGO, SBI General, Bajaj Allianz, and Star Health.
3️⃣ The Results: AI Search Has Its Own Winners
| Rank | Brand | AI Visibility Share (AIVS) |
|---|---|---|
| 🥇 | ICICI Lombard | 64% |
| 🥈 | Reliance General Insurance | 51% |
| 🥉 | Bajaj Allianz | 50% |
| 4️⃣ | SBI General Insurance | 49% |
| 5️⃣ | HDFC Ergo | 46% |
While ICICI Lombard led the pack, it captured just 6.5% of total AI mentions, showing how early and open this space remains.
The AI layer isn’t just another search channel — it’s a new trust ecosystem waiting to be defined.
🧠 Platform Performance: GPT vs. Perplexity
The visibility gap between platforms was striking — while Perplexity cited ICICI Lombard in 100% of relevant queries, ChatGPT only recognized it in 65%.
This suggests that different LLMs prioritize different types of citations — with Perplexity preferring authoritative sources (PolicyBazaar, IBEF, Pazcare), and ChatGPT leaning toward context-rich, content-driven pages.
For insurers, this highlights the need to optimize across multiple AI systems, not just one model.
4️⃣ Intent Mix: What AI Users Are Really Asking
Unlike Google, where search queries are evenly spread, AI assistants concentrate visibility on high-information and commercial content.
Based on our benchmark of 100+ LLM queries, we found:
- Informational & General Queries: 100% visibility on both ChatGPT and Perplexity — indicating strong coverage for broad awareness questions like “What is general insurance?”
- Commercial / SME Insurance: 50–60% visibility — showing partial awareness of niche business-related products.
- Comparative Queries (Trusted): 90–100% visibility — AIs handle brand comparisons effectively, e.g. “ICICI Lombard vs HDFC Ergo”.
- Digital / Experience Queries: Only 40–50% visibility — suggesting low optimization around digital experience topics (like app features or online policy management).
- Health & Property Insurance: 70–80% coverage — moderately strong in these sub-categories.
- Problem / Solution Queries: Below 60% visibility — the biggest growth opportunity for insurers to dominate in practical, troubleshooting content.
Insight: AI visibility favors broad informational and comparative content, but undervalues transactional or problem-solving queries — a clear opportunity for strategic content expansion.
5️⃣ Understanding Query Intent — The Shift from Keywords to Context 🧩
For decades, SEO was built on keywords — short, transactional phrases like “car insurance India”.
Marketers stuffed pages with those words, assuming higher density meant higher rank.
But users — and search systems — have evolved.
Now, people ask questions that reflect thought, not syntax.
“Which general insurance policy is best for families in India?”
“How does cashless claim settlement work?”
These are intent-driven queries — and they’re fundamentally different from keyword-based ones.
💡 What Is Query Intent?
Query intent is the reason behind a user’s search.
It reflects what they want to accomplish, not just what they typed.
| Intent Type | User Motivation | Example Query |
|---|---|---|
| Informational | Learn, research, or compare | “What is general insurance?” |
| Transactional | Take action or purchase | “Buy car insurance online” |
| Comparative / Trusted | Evaluate options | “ICICI Lombard vs HDFC Ergo” |
| Local / Geo-specific | Find nearby or region-based | “Best car insurance in Mumbai” |
| Navigational / Brand | Reach a known site | “Visit SBI General portal” |
Each intent corresponds to a different stage in the user journey — from awareness to purchase.
⚙️ Why Intent Is Different from Keywords
Old SEO matched exact words.
AI search interprets context and meaning.
“Compare motor insurance plans in India”
“Which general insurers are most trusted?”
Both lead to similar answers — because AI models understand semantic similarity, not literal matches.
That’s why modern optimization isn’t about keyword targeting, it’s about intent clustering.
🧠 Intent and Semantic SEO
Large Language Models (LLMs) don’t think in keywords — they think inconcept graphs.
They map how ideas relate: “coverage,” “claim ratio,” “renewal,” “trust,” “policy type.”
This is Semantic SEO — optimization through meaning, entities, and relationships.
By aligning content to intent clusters, insurers help AI systems understand where their brand fits in the knowledge ecosystem.
That’s exactly what LLMClicks.ai does:
It clusters every GSC keyword into intent-driven categories (e.g., Informational, Comparative, Transactional)
It identifies which queries map to which pages.
It revealsintent gaps where your brand lacks AI visibility
📊 Why Intent Matters for Insurers
Insurance buyers move through intent stages:
| Funnel Stage | User Intent | AI Opportunity |
|---|---|---|
| Awareness | Informational | Be cited in educational content |
| Consideration | Comparative | Appear in side-by-side brand recommendations |
| Decision | Transactional | Capture bottom-funnel AI mentions |
AI assistants dominate the awareness and comparison stages — where trust is built.
If your brand doesn’t appear there, you’ll never reach the purchase phase.
🧩 For Advanced Readers: Intent & Semantic Mapping
Intent is how LLMs connect your brand to topics inside their knowledge graph.
If your schema, FAQ data, or content doesn’t reflect semantic cues, you won’t be recognized — even with good rankings.
AI isn’t just finding your page.
It’s deciding whether your brand fits the context of the question.
That’s why LLMClicks.ai usesIntent-Based Query Clustering — turning hundreds of scattered queries into structured, actionable semantic categories.
6️⃣ Why AI Visibility Matters for Insurers
For insurers, trust = revenue.
AI assistants are now the new trust brokers, influencing how users perceive your brand long before they reach your site.
When ChatGPT lists “the top 3 general insurers in India,” users believe it.
That’s why AI visibility directly impacts brand perception, recall, and conversions.
If your brand isn’t being cited, you’re losing trust equity — quietly, but significantly.
7️⃣ Citation Quality: The New Ranking Signal
AI assistants don’t count backlinks; they evaluate who mentions you and in what context.
ICICI Lombard’s citations were drawn from a mix of industry aggregators (PolicyBazaar, Pazcare) and trusted domain authorities (IBEF, Economic Times, GoDigit) — reinforcing its perception as a credible brand in the AI ecosystem.
Our study foundICICI Lombard’s Citation Quality Score = 100/100, driven by trusted sources like:
PolicyBazaar
IRDAI
Economic Times
StarHealth.in
Each citation reinforces authority, just like backlinks once did for Google.
But here, the weight is semantic — rooted in expertise, reliability, and alignment with user intent.
Even within AI systems, visibility differs by model — a brand can dominate Perplexity yet remain underrepresented in ChatGPT. Tracking performance across multiple LLMs ensures comprehensive brand discoverability.
8️⃣ Missed Opportunities & Revenue Impact
Even top insurers are leaving opportunity on the table.
ICICI Lombard, despite its lead, missed 42 high-potential AI queries — queries where competitors appeared multiple times.
💸 Estimated Opportunity Gap: $8,400/month
📉 Conversion Loss: Missed early-stage exposure in ChatGPT and Perplexity recommendations
The loss isn’t traffic — it’s AI presence, which compounds over time as models learn which brands to trust.
9️⃣ For Agencies: Turning AI Visibility into Growth
For agencies managing insurance and BFSI clients, AI visibility is the next big differentiator.
With LLMClicks.ai, agencies can:
Run white-labeled AI visibility audits
Quantify brand presence in LLM results
Identify citation gaps and intent opportunities
Prove ROI through AI-first SEO metrics.
This shifts the agency narrative from:
“We got you clicks.”
to
“We got you mentioned by ChatGPT.”
That’s a game-changing conversation.
🔟 The Future: From Keywords → Citations → Knowledge Graphs
Tomorrow’s SEO is already here.
Rankings will be replaced by AI Visibility Scores (AIVS)
Keywords will evolve into intent clusters
Backlinks will be replaced bytrusted citations.
Brands that invest in entity-based optimization — schema, FAQ, authorship, structured content — will become the sources AI assistants trust most.
🔧 LLM Optimization Strategy: How to Win Across Models
AI models don’t all interpret the web the same way. ChatGPT favors semantically rich editorial content, while Perplexity relies on high-authority citations.
For insurers, the optimal strategy is a hybrid:
Build expert-led guides and explainer pages for ChatGPT visibility.
Strengthen citation network across aggregators and BFSI news sources for Perplexity visibility.
Tools like LLMClicks.ai unify these insights into one dashboard — helping brands audit, optimize, and expand visibility across multiple LLM ecosystems simultaneously.
1️⃣1️⃣ Conclusion: The AI Search Layer Is Already Here
AI-driven discovery isn’t a prediction — it’s the present.
Our benchmark shows:
64% of AI queries are informational
42% of opportunities remain untapped
Top insurers are underrepresented in AI summaries
This isn’t about beating Google anymore — it’s about beingrecognized by AI.
And that race has already started.
🚀 Join the LLMClicks.ai Benchmark Program
LLMClicks.ai is India’s first AI Visibility Intelligence Platform — built for insurance brands and agencies.
We help you measure, benchmark, and grow your presence across AI systems like ChatGPT, Perplexity, and Bing Copilot.
What You’ll Get:
📊 AI Visibility Score & Citation Map
🔍 Missed Query & Intent Gap Report
🧠 Strategic Recommendations for AI Optimization
🤝 White-Labeled Reports for Agencies
Join the AI Visibility Benchmark for BFSI & Insurance 2025
👉 Request Early Access → LLMClicks.ai