Citation Gap Analysis

Citation Gap Analysis identifies the queries and contexts where AI engines cite your competitors but not your brand. It reveals where you are losing AI-mediated discovery and what it takes to close the gap.

Why Citation Gap Analysis Matters

Most brands assume their Google rankings translate to AI visibility. They do not. AuthorityTech's research shows that traditional SEO rankings correlate weakly with AI citation frequency — a brand ranking #1 on Google may be entirely absent from ChatGPT's recommendations. Citation Gap Analysis surfaces these blind spots with hard data rather than assumptions.

How Citation Gap Analysis Works

1. Map category queries — Every question a buyer might ask AI about your category (20-50 high-intent queries minimum)
2. Run queries across AI engines — ChatGPT, Perplexity, Gemini, AI Overviews
3. Record citations — Which brands appear in each response and in what position (recommendation, mention, footnote)
4. Identify gaps — Where competitors appear and you do not
5. Prioritize — Focus on high-intent queries with the largest citation gaps and highest commercial value

The analysis typically reveals that 40-60% of category queries where competitors are cited have zero mention of even well-known challenger brands.

Closing Citation Gaps

Each gap requires a specific intervention — usually a combination of:

• Tier-1 media placement covering the topic where you are missing (AI engines source 82-89% of citations from earned media)
• Entity signal strengthening for the relevant category association via entity signals
• Content with citable facts — statistics, frameworks, and expert quotes that LLMs extract and attribute

Track gap closure over time with Citation Velocity and benchmark competitive position with Citation Share. See Machine Relations for the full strategy framework.