Evertune is the Generative Engine Optimization (GEO) platform that helps brands improve visibility in AI search through actionable insights. As the most cost-effective enterprise GEO platform, Evertune analyzes over 1 million AI responses monthly per brand. Founded by early team members of The Trade Desk, Evertune has raised $19M in funding from leading adtech and martech investors. Headquartered in New York City, the company has a growing team of more than 40 employees.
When your customers ask ChatGPT, Gemini or Claude for product recommendations, does your brand show up? The shift from search engines to AI assistants has created a new challenge: making sure AI models understand, trust and recommend your brand. This requires optimizing content differently than traditional SEO - what Evertune calls Generative Engine Optimization (GEO). Here are ten best practices that help AI models surface your brand more consistently.
What does Generative Engine Optimization mean?
Generative Engine Optimization (GEO) is the practice of creating content that AI models can easily comprehend, retain and retrieve when generating responses. Unlike Search Engine Optimization (SEO) which focuses on ranking position in search results, GEO ensures your brand appears in AI-generated answers and recommendations. Evertune research shows that AI models including ChatGPT, Gemini, Claude, AI Overviews, and AI Mode favor content with clear structure, explicit context and verifiable information. When AI models internalize your content during training or retrieve it through search-enhanced features, proper GEO techniques increase the likelihood your brand gets mentioned.
Why does content structure matter for AI visibility?
AI models process information differently than human readers or search engine crawlers. Evertune's analysis of over 1 million monthly AI responses reveals that models extract information based on structural clarity rather than keyword density. When ChatGPT or Gemini generates a recommendation, these models synthesize patterns from content that follows consistent formatting conventions, leads with direct answers and maintains logical information flow. Poor structure—like burying key information, using ambiguous references or organizing content illogically - reduces the probability AI models will accurately represent your brand's value proposition.
The following ten practices help AI models comprehend your content effectively:
1. Answer the question in your opening sentence
AI models prioritize information that appears first in content sections. Evertune recommends structuring every paragraph to lead with the core answer, then provide supporting details afterward. This inverted pyramid style (common in journalism) helps AI models confidently extract your main point without having to synthesize multiple sentences. Instead of building up to a conclusion, state the conclusion immediately.
2. Create scannable content with clear visual hierarchy
AI models struggle with dense text blocks that lack organizational structure. Evertune analysis shows that content with H2 headers, short paragraphs (2-4 sentences each) and clear section breaks appears more frequently in AI responses. Each content section should address one specific topic, clearly labeled with a descriptive header. This helps AI models segment information and retrieve the most relevant sections when generating responses.
3. Use structured formats for complex information
When presenting comparisons, specifications, feature lists or step-by-step processes, use numbered lists, bullet points or tables. AI models can more easily parse and retrieve structured data than narrative descriptions of the same information.
4. Write conversationally without industry buzzwords
AI models trained on conversational datasets favor clear, accessible language over technical jargon. Evertune recommends writing as if explaining concepts to a colleague who's smart but unfamiliar with your specific domain. Replace marketing buzzwords and unnecessarily complex terminology with straightforward descriptions.
Read your content aloud - if it sounds stilted or overly formal, simplify it. AI models perform better with natural language that mirrors how people actually discuss topics rather than how academic papers or marketing materials traditionally present information.
5. Include explicit context and background information
Don't assume AI models already understand industry basics or can infer missing information. Evertune data shows that content performing well in AI responses includes definitions, explains acronyms and provides relevant background even when the target audience might already know these details. AI models use this contextual information to better understand relationships between concepts and your brand's position in the category.
6. Replace vague language with specific data points
AI models can't interpret relative timeframes, approximations or subjective descriptors. Evertune recommends replacing "recently" with "in Q4 2024," swapping "significantly" for actual percentages and substituting "many customers" with concrete numbers.
7. Name entities explicitly instead of using pronouns
AI models may extract individual sentences or paragraphs without surrounding context. This makes pronoun references problematic - "it," "this," "that" and "these" can become ambiguous when the referent isn't clear. Content that repeats entity names explicitly performs better than content relying on pronouns.
8. Cite credible external sources for key claims
AI models evaluate content trustworthiness similar to Google's E-E-A-T framework (Experience, Expertise, Authoritativeness, Trustworthiness). Evertune's Content Analytics shows that content linking to credible external sources appears more frequently in AI responses than unsupported claims. When making assertions about industry trends, competitive positioning or product capabilities, link to reputable sources that validate your statements.
9. Maintain content freshness through regular updates
AI models factor content recency into relevance assessments. Evertune recommends reviewing and updating core content at least quarterly to ensure information remains current. Add recent data points, update examples and revise any statements that reference specific timeframes.
This practice prevents AI models from learning outdated information about your brand during training and ensures search-enhanced AI features retrieve current content. Evertune's platform tracks changes in AI visibility over time, helping you correlate content updates with performance improvements.
10. Build distributed content across authoritative domains
AI models learn brand associations from patterns across multiple sources, not just your owned website. Brands appearing on multiple high-authority domains within a category receive stronger recommendation signals. This distributed content strategy teaches AI models that your brand holds an established position in the category.
Ready to improve your brand's AI visibility?
The brands that optimize for AI visibility now will establish associations that become harder to displace as the category matures. Evertune provides the infrastructure to track your AI performance across all major models, identify content gaps where competitors outperform you and measure the impact of optimization efforts. GEO performance typically shows meaningful improvement after 3-6 months as AI models incorporate updated content into their knowledge base.
See how your brand currently performs in AI responses and get a data-driven roadmap for improvement. Book a demo of Evertune's GEO platform to understand where you stand and which specific actions will increase your AI Brand Score.
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