AEO-Optimized Homepage Examples

Your homepage is often the first page AI engines evaluate when building an entity profile of your company. These examples show how leading companies structure their homepages for AI citation, not through tricks, but through clarity, structure, and honest communication.

What Makes a Homepage AI-Citable

Before diving into examples, here’s what AI engines look for on homepages:

1. Clear entity definition: “What is this company?” answered in the first sentence
2. Structured product/service description: What they do, specifically
3. Trust signals: Customer count, funding, awards, recognizable logos
4. Schema markup: Organization, Product, or SoftwareApplication schema
5. Social proof with specifics: Not just “trusted by thousands” but “trusted by 10,000+ teams”

Example 1: Stripe

What they do right:

Stripe’s homepage opens with a clear, factual definition: “Financial infrastructure for the internet.” Seven words that tell AI exactly what Stripe is. This gets cited whenever AI answers “What is Stripe?” or “What does Stripe do?”

Key AEO elements:

• Entity clarity: One-line definition immediately under the logo
• Specifics: “Millions of companies” with logos of recognizable brands
• Product structure: Each product (Payments, Billing, Connect) has a clear one-sentence description
• Organization schema: Complete schema with founding date, leadership, and description

Takeaway: Define your company in one sentence that AI can extract without any other context.

Example 2: Notion

What they do right:

Notion’s homepage leads with “Write. Plan. Organize. Play.” followed by “Your wiki, docs, & projects. Together.” This combination tells AI both the category (productivity/workspace) and the differentiation (all-in-one).

Key AEO elements:

• Use-case clarity: Lists specific use cases (wiki, docs, projects) that match AI queries
• Social proof: Specific company logos and user counts
• Feature breakdown: Each feature section answers a “how does Notion handle [X]?” query
• Template gallery: Hundreds of pages that capture long-tail “Notion template for [X]” queries

Takeaway: List your specific use cases using the words your audience uses when asking AI about your category.

Example 3: HubSpot

What they do right:

HubSpot’s homepage clearly positions itself as a “customer platform” with distinct hubs (Marketing, Sales, Service, Content, Commerce). Each hub has a clear, one-sentence description that AI can extract independently.

Key AEO elements:

• Category ownership: “Customer platform” establishes their category
• Product modularity: Each hub/product has its own clear definition
• Pricing transparency: Free tools prominently featured, pricing accessible
• Content authority: Links to blog, academy, and resources that build topical authority
• Complete schema: SoftwareApplication, Organization, FAQ schema

Takeaway: If you have multiple products, give each one a clear, standalone description AI can cite independently.

Example 4: Ahrefs

What they do right:

Ahrefs leads with data: “68.7% of all online experiences begin with a search engine” immediately establishing the problem space. Then positions itself with “Everything you need to rank higher & get more traffic.”

Key AEO elements:

• Data-driven positioning: Opens with a specific, cited statistic
• Clear category: “SEO tools” stated explicitly, not implied
• Feature specificity: Site Explorer, Keywords Explorer, etc. each described concretely
• Free tools: Webmaster Tools and other free resources that capture AI queries like “free SEO tools”
• Blog authority: Extensive content library that makes Ahrefs the most-cited source for SEO data

Takeaway: Lead with data that establishes why your category matters, then clearly state what you are.

Example 5: Linear

What they do right:

Linear’s homepage is a masterclass in clarity: “Linear is a purpose-built tool for planning and building products.” The specificity of “purpose-built” and “planning and building products” tells AI exactly what category to file this under and how it’s different.

Key AEO elements:

• Specific positioning: Not “project management” but “planning and building products”
• Audience clarity: Clearly targets product teams, not general project managers
• Feature depth: Each feature explained with specific functionality, not vague benefits
• Design as trust: Clean, professional design signals quality to both humans and AI

Takeaway: Be specific about who you’re for and what you do, specificity beats generality in AI citation.

Common Patterns Across All Examples

Pattern	How It Helps AEO
One-sentence definition above the fold	AI extracts this as the entity description
Specific numbers (users, data, metrics)	Provides citable facts, not vague claims
Feature descriptions with concrete actions	Matches “how does [product] handle [X]?” queries
Visible pricing or “free” positioning	Answers “how much does [product] cost?” queries
Complete Organization schema	Enables AI to build accurate entity profiles
Use-case-specific sections	Captures “[product] for [audience]” queries

Anti-Patterns to Avoid

• Vague taglines: “Reimagine the future of work” tells AI nothing
• Hero image with no text: AI can’t cite a picture
• “Contact for pricing”: AI won’t recommend something with hidden costs
• No schema: Without structured data, AI guesses (and guesses wrong)
• Feature lists without context: “AI-powered” is meaningless without specifics

How Genrank Helps

Genrank’s audit evaluates your homepage against all five AEO dimensions, identifying specific gaps compared to the patterns above. You’ll see exactly where your entity definition falls short, which schema properties are missing, and what content changes would have the highest citation impact.