Here’s a simple way to see how 30+ AI SEO tools stack up, not just by what they promise, but by what they actually do.
This quadrant ranks each tool on two fronts:
Coverage Score: How much real GenAI SEO work the tool claims to handle: from chunk structuring to vector index presence and more. There are 36 points to be collected here across 12 segments. This is binary, either they cover/do/enable the work item or they do not.
Confidence Score: How clearly and credibly the tool explains that work: real documentation, examples, and evidence instead of vague buzzwords. Again, 36 points over 12 segments, however, this also relies on my own experience and knowledge to help refine the score.
And yes, I’m keeping the finer details of the scoring rubric under wraps for now. Sorry, but the point here isn’t to give away all my information. It’s to help folks with a tool to help with decision making. It’s entirely fine if you disagree with me and choose not to use this resource. But I can re-share some previously published content, that is part of the scoring approach here:
12 GenAI SEO Work Areas
These are areas that are important in today’s generative AI optimization landscape. This is the work that needs to be done, so I’m tracking how aligned the tools are with the work.
Machine-Validated Authority
Tests whether AI systems see your content as trustworthy enough to surface or cite.
Chunk Retrieval Frequency
Helps you structure and surface content blocks so AI systems find and pull them more often.
Embedding Relevance Score
Uses vector embeddings to model your content’s meaning and improve its relevance in AI results.
Attribution Rate in AI Outputs
Checks if your content actually gets credited when an AI answer uses your information.
AI Citation Count
Tracks how many times your content is directly cited in GenAI answers.
Vector Index Presence Rate
Shows if your content is stored and retrievable in modern vector indexes powering AI models.
Retrieval Confidence Score
Estimates how strongly your content is likely to be pulled into an AI-generated answer.
RRF Rank Contribution
Looks at how your content ranks when blended with other signals in re-ranking and fusion systems.
LLM Answer Coverage
Checks whether your pages actually appear in large language model outputs.
AI Model Crawl Success Rate
Measures whether AI crawlers can access, parse, and index your content.
Semantic Density Score
Tests how deep and rich your topic coverage is for AI to interpret and match user prompts.
Zero-Click Surface Presence
Shows if your content appears in instant AI answers that don’t require a click.
Use this as a quick map, not an absolute ranking. It’s meant to help you sort hype from substance before you spend your budget. A high score doesn’t mean “buy now” — it means “check if it fits your real workflow.”
If you’re evaluating tools, I hope this gives you a better starting point.
