Content Depth
Content depth refers to how comprehensively and thoroughly a topic is covered. AI systems prioritize deep, comprehensive content (1500+ words) over thin, surface-level content. Content depth signals expertise and authority.
Definition
Content depth measures how comprehensively and thoroughly a topic is covered in a piece of content. Deep content goes beyond surface-level information to provide detailed explanations, examples, context, and actionable insights. AI systems like ChatGPT, Claude, and Perplexity prioritize deep, comprehensive content when selecting sources to cite. Content depth is typically measured by word count (1500+ words is minimum, 2500+ is ideal), but also includes factors like subtopic coverage, examples provided, actionable advice, and comprehensive explanations. Deep content demonstrates expertise and authority, making it more likely to be cited by AI systems than thin, superficial content.
Examples
A 3000-word comprehensive guide covering all aspects of "Schema Markup" (types, implementation, examples, best practices) has high content depth
A 500-word article with only basic information about "AI Citations" has low content depth
A 2000-word tutorial with step-by-step instructions, code examples, and troubleshooting has high content depth
How to Apply
- 1.Aim for 1500+ words minimum (2500+ words ideal) for comprehensive topic coverage
- 2.Cover subtopics, related concepts, and edge cases thoroughly
- 3.Include practical examples, case studies, and real-world applications
- 4.Provide actionable advice and step-by-step instructions
- 5.Add context, background, and explanations that demonstrate deep understanding
- 6.Use Content Expander to identify opportunities to increase content depth
Related Tools
Related Tools
Complement your analysis with these AI citation optimization tools: