The short answer
A good AEO tool should do four things: measure, compare, diagnose, and help you fix. It runs your category’s prompts across ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews and reports citation rate, share of model, and sentiment per engine. It compares you to competitors so your presence reads as share of model, not an isolated number. It checks the technical signals behind the numbers, like AI-crawler access, llms.txt, sitemap, JSON-LD, metadata, and entity salience. And it closes the loop by surfacing fixes and re-checking.
Measure and compare
The baseline is honest measurement across engines, kept per engine so a strong result in one place does not hide a gap in another. On top of that, a good tool frames your numbers against competitors, because knowing you are cited 30 percent of the time means little until you know whether rivals are cited more or less. That competitive framing is share of model, and it is where most of the useful decisions come from.
Diagnose and fix
Numbers alone do not tell you what to change. A good tool checks the signals that drive citations (can AI crawlers reach you, is your llms.txt and sitemap in place, is your JSON-LD valid, are your entity signals clear) and then helps you fix them and re-check. The ones worth your time also carry classic SEO signals (keyword research, daily rank tracking, backlink analysis with a DR-weighted Domain Score, technical site audits, AEO Rank) so you see the full picture in one place.
Make it repeatable
Finally, it should let AEO run as a process: scheduled reports and an API or MCP connector so the data lands in your workflow instead of a one-off export. Compare options fairly on the best AI SEO tools page, and run the free AI visibility scan to see where your own site stands.