AEO Articles

What you'll learn:

• How AI models parse heading tags differently from human readers
• Why question-based headings increase citation rates in generative search
• The definition-heading pair pattern that drives extraction
• Common heading mistakes that block AI visibility
• How to audit your heading structure for extraction readiness

What you'll learn:

• Lists and bullet points earn the most AI citations
• Comparison tables extract data 81 percent more than prose
• Question-format headings boost extraction rates
• Definitions and FAQ pairs map directly to user prompts
• Schema markup improves citation accuracy across engines

What you'll learn:

• Why writing for keywords instead of conversational queries blocks citations
• How answer-first structure and heading hierarchy affect AI extraction
• Why schema markup, entity density, and E-E-A-T signals matter for citations
• The importance of testing across multiple AI platforms
• How to track zero-click visibility and citation rates separately

What you'll learn:

• How AI search engines differ from traditional search and why extractable content drives citations
• The answer-first content framework and schema markup strategies that boost AI visibility
• Platform-specific tactics for Google AI Overviews, ChatGPT Search, Perplexity, and Copilot
• Off-site optimization, co-occurrence strategies, and measurement tools for AI search performance