Measuring AEO: How to track, benchmark, and improve your AI search results
Blog post from Webflow
In an AI-driven search environment, traditional SEO metrics like keyword rankings are becoming less relevant due to the emergence of large language models (LLMs) such as ChatGPT and Gemini, which provide AI-generated content rather than direct links. An Ahrefs analysis shows that AI Overviews now appear in 21% of Google searches, indicating a shift in how visibility is measured. To remain competitive, marketers should develop an AI-Enhanced Optimization (AEO) measurement practice that evaluates visibility, accuracy, and sentiment in AI-generated content. This involves tracking brand mentions, citations, and sentiment in LLMs, benchmarking against competitors, and integrating real-time feedback into decision-making processes. By doing so, businesses can transform data into actionable insights, anticipate trends, and make informed investments in content, authority, and technical strategies, ensuring a continuous feedback loop that enhances marketing impact in the AI-first landscape.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| LLM | 14 | 5,556 | 752 | 184 | +14% |
| Real-time | 3 | 4,542 | 1,005 | 235 | -31% |
| AI Coding Assistant | 1 | 951 | 205 | 85 | -2% |
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