Comparison · Practitioner
Best AI Visibility Tools (GEO/AEO): How to Choose, Tested
The best AI visibility tool is the one whose answers match what your buyers actually see, across the engines and markets you sell in, with raw answers you can audit. Choose by testing: run 20 of your own prompts manually, run the same prompts in each shortlisted tool, and compare agreement, coverage, settings control and time saved. This page gives the criteria and test plan.
Key takeaways
- Test on your prompts and competitors, never only on a vendor demo.
- Raw answer access is non-negotiable; without it you can't audit a score.
- Ask exactly how answers are collected (interface vs API, mode, location).
Which criteria matter?
| # | Criterion | What good looks like |
|---|---|---|
| 1 | Engine coverage | The engines your buyers use, including AI Overviews and AI Mode separately |
| 2 | Collection method | Documented; matches consumer answers closely in your spot checks |
| 3 | Location/language | Country and language settings per prompt |
| 4 | Runs per prompt | Configurable; variance shown |
| 5 | Raw answers | Every answer viewable and exportable |
| 6 | Citation capture | All cited URLs and domains, not only yours |
| 7 | Brand matching | Name variants; manual correction |
| 8 | Metrics | Mention, recommendation, citation rates and SOV, with formulas |
| 9 | Exports/integrations | CSV, Sheets, BI, API |
| 10 | Pricing | Clear limits on prompts, engines, runs |
What should you ask vendors?
- How do you collect answers for each engine: consumer interface, API or both?
- For ChatGPT, is search enabled? For Google, which AI surface?
- Where are queries issued from, geographically?
- How do you handle variation between runs?
- How is your score calculated, and has it changed?
- Can I export every raw answer and citation?
- What happens to my data if I cancel?
How do you run a two-week test?
- Pick 20 prompts from your real set across learn, compare and buy.
- Run them manually in clean sessions in two engines, twice each.
- Run the same prompts in each tool with matched settings.
- Compare per answer: same brands mentioned? Same position? Same cited domains?
- Time setup and weekly effort.
How do you score the results?
| Criterion | Weight (example) | Tool A | Tool B |
|---|---|---|---|
| Agreement with manual results | 30% | ||
| Coverage of your engines/markets | 20% | ||
| Raw answer and citation access | 20% | ||
| Settings control | 10% | ||
| Time saved | 10% | ||
| Price for your volume | 10% |
Weights are an example; set your own before testing so results don't bias them.
What are the red flags?
- A score with no formula or raw answers behind it.
- No way to set location or engine mode.
- Results that never vary between runs (may indicate caching).
- Prompt limits that force you to track only head terms.
- Claims of "guaranteed visibility".
Should you build your own?
Possible with engine APIs and a sheet, but API answers may differ from what users see in consumer apps, and maintenance is ongoing. Compare the build cost to a subscription honestly; see manual vs automated tracking.
A note on our own tool
MentionX makes an AI visibility tool. Apply the same test to us that you apply to anyone else.
How do you score the trial?
Use a simple weighted scorecard so the decision isn't driven by the best demo.
| Criterion | Weight | How to score (1-5) |
|---|---|---|
| Agreement with manual results | 25% | Share of prompts where brands mentioned match your manual runs |
| Engine and mode coverage | 15% | Covers the engines your buyers use, with modes separated |
| Raw answer access | 15% | Every answer and citation viewable and exportable |
| Location and language control | 10% | Settable per prompt or project |
| Brand matching quality | 10% | Variants caught; few false positives |
| Reporting and exports | 10% | Fits your existing reporting workflow |
| Time saved | 10% | Hours per month versus manual tracking |
| Price at your volume | 5% | Cost for your real prompt count and run frequency |
Agree the weights before you start testing, then score each tool independently. If two people score, compare and discuss differences rather than averaging silently.
What red flags should end a trial early?
- You can't see the raw answer behind a score.
- The vendor can't explain how answers are collected for a given engine.
- Scores change after a methodology update with no notice or changelog.
- Brand matching misses obvious variants of your name.
- Results disagree with your manual runs on most prompts and nobody can explain why.
- Pricing hides limits on prompts, engines or runs until after signup.
How should different teams weigh the criteria?
| Team | Weight more heavily | Can weight less |
|---|---|---|
| In-house marketing, one market | Agreement, raw answers, reporting | Multi-market control |
| Agency | Multi-client workspaces, exports, price at scale | Deep single-brand features |
| Global brand | Location and language control, engine coverage | Price |
| Content team | Citation capture and URL-level data | Executive dashboards |
What should you do after choosing?
Run the new tool alongside your manual check for at least one more month. Document the settings (engines, modes, locations, runs per prompt) in a method note, so a future change of tool or settings doesn't silently break your trend line. Recheck agreement every quarter, because engines change and so can a tool's collection method.
Which questions do buyers forget to ask?
- Can I import my existing prompt history?
- Who owns the prompt sets and results if we leave?
- How quickly are new engines or modes added?
- Is there an API, and what does it cost?
- How are seats and client workspaces priced?
How do you calculate agreement?
For each prompt, compare the set of brands the tool reports with the set you saw manually. Count a prompt as agreeing when your brand's status (mentioned or not) matches. Agreement = agreeing prompts ÷ prompts tested. Illustrative: 15 of 20 prompts agreeing gives 75%. Also compare cited domains for a few prompts; tools differ more on citations than on brand lists. Record disagreements with notes, because they usually trace back to settings like location, mode or logged-in state.
Sources
- Google Search Central, AI features and your website
- OpenAI, Overview of OpenAI crawlers
Questions
What is the best AI visibility tool?
It depends on your engines, markets, prompt volume and budget. Test shortlisted tools against your own manual results before buying.
What should I test during a trial?
Agreement with manual results, engine and mode coverage, location control, raw answer access, citation capture and brand matching.
Are visibility scores comparable between tools?
No. Each tool uses its own prompts, engines and formulas.