How to Get Cited in Gemini — Google's AI Search
Gemini draws from Google's index and uses schema markup to verify claims. Strong traditional SEO is the prerequisite. Here's how to optimise specifically for Gemini citations.
Gemini draws directly from Google's search index, making it the only major AI platform where traditional SEO is a genuine prerequisite for visibility. It uses schema markup to verify factual claims and weighs entity relationships heavily. At 8.65% market share, Gemini has overtaken Perplexity to become the second-largest AI search platform.
How Gemini differs from other AI platforms
Gemini is unique among AI search platforms because it sits directly on top of Google's infrastructure. This creates a fundamentally different optimisation path compared to ChatGPT (Bing-indexed) or Perplexity (multi-source).
| Feature | Gemini | ChatGPT | Perplexity |
|---|---|---|---|
| Search index | Bing | Multi-source | |
| Schema verification | Yes — actively uses schema to verify claims | Partial | No |
| Entity relationships | Heavy weighting via Knowledge Graph | Moderate | Low |
| Freshness signal | Strong — inherits Google's freshness algorithms | Moderate | Real-time |
| Market share | 8.65% | 78% | 7% |
Gemini's market position
Gemini holds 8.65% of the AI search market, having recently overtaken Perplexity. As Google integrates Gemini deeper into Search, Gmail, Workspace, and Android, its share will likely grow significantly. Optimising for Gemini is effectively optimising for the future of Google Search itself.
Key metrics
- 8.65% market share — second largest after ChatGPT
- Overtook Perplexity in early 2026
- Integrated into Google Search via AI Mode and AI Overviews
- Available across Google Workspace — Docs, Gmail, Sheets
- Default on Android devices — massive mobile audience
What drives Gemini citations
1. Schema markup for verification
This is Gemini's standout feature. Unlike other AI platforms that primarily read page content, Gemini actively uses structured data to verify factual claims. When your Organisation schema says you're headquartered in London, and your Google Business Profile confirms it, and your Wikidata entry agrees — Gemini trusts your content more.
Priority schema types for Gemini:
- Organisation schema with @id, sameAs, areaServed
- Person schema for authors and experts
- FAQPage schema for question-answer content
- Article schema with author, dateModified, publisher
- Product schema with AggregateRating for ecommerce
2. Google-indexed content
If Google hasn't indexed a page, Gemini cannot cite it. This means:
- Submit sitemap to Google Search Console
- Fix any indexing errors or crawl issues
- Ensure pages load without JavaScript rendering issues
- Pages excluded from Google's index are invisible to Gemini
3. Entity consistency across Google's ecosystem
Gemini leverages Google's Knowledge Graph extensively. Entity relationships matter more for Gemini than any other AI platform. Build consistency across:
| Platform | Why it matters for Gemini |
|---|---|
| Google Business Profile | Primary entity source — categories, description, attributes |
| Google Knowledge Panel | Direct Knowledge Graph presence |
| Wikidata | Structured entity data Gemini cross-references |
| Wikipedia | Authority signal for entity recognition |
| YouTube | Google-owned, transcripts analysed |
| Google Merchant Centre | Product entity data for ecommerce |
4. Freshness signals
Gemini inherits Google's freshness algorithms. Content that ranks well in Google's "freshness-sensitive" queries will also perform well in Gemini. Keep your key pages updated — dateModified in schema, genuinely revised content, not just timestamp tricks.
Step-by-step: Getting into Gemini
Step 1 — Ensure Google indexation
Verify all important pages are indexed in Google Search Console. Fix crawl errors. Submit sitemap. If a page isn't in Google's index, it cannot appear in Gemini.
Step 2 — Implement comprehensive schema
Add Organisation, Person, Article, and FAQPage schema. Use the @graph pattern to connect all entities. Include sameAs links to your Google Business Profile, LinkedIn, Wikidata, and other authoritative profiles. See our complete schema implementation guide.
Step 3 — Build entity consistency
Ensure your brand name, description, location, and key attributes match across Google Business Profile, website schema, Wikidata, LinkedIn, and industry directories. Gemini cross-references these sources.
Step 4 — Optimise for traditional SEO
Since Gemini uses Google's index, strong traditional SEO is the foundation. Page speed, mobile experience, E-E-A-T signals, topical authority, and quality backlinks all feed into Gemini visibility.
Step 5 — Structure content for extraction
Clear heading hierarchy. Answer capsules after each heading. Comparison tables. Specific data points. Structure your site for AI crawlers with clean HTML.
Step 6 — Allow Google's AI crawlers
In robots.txt, ensure Google-Extended is not blocked (controls Gemini training data use):
User-agent: Google-Extended
Allow: /Gemini vs AI Overviews
Gemini and AI Overviews share the same underlying technology but behave differently:
- AI Overviews appear automatically in Google Search results — you must rank in the top 10 to be cited
- Gemini is a standalone chatbot — draws from the full Google index, not just top results
- Optimising for one generally helps with the other
- Schema verification applies to both
What to do next
Oliver Mackman
AI Search Analyst, SEOCompare
Oliver leads SEOCompare's editorial and comparison research. With over a decade in digital marketing, he oversees agency evaluation, tool testing, and AI search data analysis.
Last reviewed: 7 April 2026
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