Best Tools for Generative Engine Optimization (GEO)
A comparative look at the toolset available to teams optimizing content for generative engines and LLM recommendations.
We recently evaluated the current market of SEO tools to see which ones have successfully adapted for Generative Engine Optimization (GEO). Most marketing teams want to know if their existing stack is sufficient for tracking LLM mentions, or if they need specialized software.
GEO tools combine content optimization with model sampling. The most effective solutions provide both the content changes and the ability to test model outputs so you can measure changes in mention rate and context accuracy.
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| Feature | BrightEdge | Semrush | Surfer |
|---|---|---|---|
| AI Visibility Reporting | Yes (Enterprise) | Yes (SERP Filters) | Partial |
| Content Editor | Integrated | Available | Strong |
| LLM Sentiment | Partial | No | No |
Actionable Recommendation
For most SaaS teams, a blended approach works best. Use a content editor to ensure extraction quality and a SERP/AI tracker to measure model outputs.
For enterprise catalogs, consider a platform with cross-model scanning and scheduled reports. BrightEdge and Semrush now explicitly offer AI-visible features, which makes them pragmatic choices for scaling GEO work.
However, we are building GenRankEngine specifically to address the lack of sentiment analysis in these tools. We focus on telling you not just if you were mentioned, but how the model recommended you (sentiment and context accuracy).
References:
- BrightEdge. "Generative Parser: SearchIQ." BrightEdge Product Page.
- Semrush. "AI Overviews: What Are They & How to Optimize for Them." Semrush Blog.
- Surfer SEO. "Surfer AI Features." SurferSEO.com.