How to Optimize Content for Claude and Gemini

While ChatGPT dominates AI referral traffic at 87.4%, Claude (by Anthropic) and Gemini (by Google) are growing rapidly and represent important secondary channels for AI visibility.

Claude has built a reputation for thoughtful, nuanced responses and is popular with researchers, professionals, and enterprise users. Gemini powers Google AI Overviews — the AI-generated summaries that appear atop Google search results for millions of queries daily. Together, they represent a significant and growing share of AI-driven content discovery.

Importantly, each model has distinct preferences for what it cites. Optimizing for one doesn't automatically optimize for the other. Understanding their differences lets you maximize visibility across all AI platforms.

Claude has distinct content preferences shaped by Anthropic's training approach:

Nuanced Analysis: Claude favors content that acknowledges complexity and presents multiple perspectives. Rather than making absolute claims, provide balanced analysis that considers different viewpoints and edge cases.

Genuine Expertise: Claude is particularly good at distinguishing genuine expertise from surface-level content. Include specific examples, detailed technical explanations, and evidence of first-hand experience.

Factual Accuracy: Claude is trained to be especially careful about factual claims. Content with verifiable data, cited sources, and accurate information is more likely to be cited. Avoid exaggeration or unsubstantiated claims.

Readable Formatting: Claude values content that's well-organized and easy to parse. Clear headings, logical structure, and concise paragraphs help Claude identify and extract relevant information.

Ethical Framing: Content that considers ethical implications and acknowledges limitations tends to align with Claude's training approach. This is especially relevant for topics like AI, healthcare, and finance.

Gemini is deeply integrated with Google's existing search infrastructure:

Knowledge Graph Integration: Gemini leverages Google's Knowledge Graph for entity recognition. Strong Organization schema, Google Business Profile optimization, and consistent entity information across platforms significantly influence Gemini's citations.

Structured Data Priority: Because Gemini powers Google AI Overviews, it heavily leverages JSON-LD schema markup. Comprehensive schema implementation (14+ types) provides Gemini with structured signals that other models may not use as directly.

Search Index Alignment: Gemini's web-grounded responses pull from Google's organic search index. Pages that rank well in traditional Google search have a higher baseline for Gemini citation.

Content Freshness: Like Google Search, Gemini values content freshness — especially for time-sensitive topics. Regular updates with current-year references improve your citation chances.

Multimodal Capability: Gemini processes images, video, and audio alongside text. Including relevant visual content with proper alt text and structured data creates additional citation opportunities.

Despite their differences, several strategies work for both Claude and Gemini:

Comprehensive Schema Markup: Both platforms benefit from rich structured data. Implement 8-14+ JSON-LD types per page including Organization, Article, FAQPage, Speakable, and BreadcrumbList.

Answer Capsules: Start each major section with a clear, direct answer. Both Claude and Gemini use these passages for citation.

Strong E-E-A-T Signals: Author bios, cited sources, factual accuracy, and verifiable claims matter for both platforms.

Content Clusters: Building topical authority through interlinked content clusters signals expertise to both Claude and Gemini.

Regular Updates: Keep content fresh with current data, updated references, and visible modification dates.

The bottom line: content that is genuinely helpful, well-structured, factually accurate, and comprehensively marked up with schema performs well across ALL AI platforms — not just Claude and Gemini.