Every comparison page in this category, this site included, is arguing a conclusion. That is fine, but it is the wrong input for a decision you have not framed yet. Score the criteria first, against your own buyers, and the comparison pages become evidence instead of persuasion.
Before you compare anything
Write down two things. First, the ten to twenty questions your buyers actually ask an assistant on the way to a purchase, in their words, not your keywords. Second, which engines those buyers use. Almost every disagreement about tooling in this category dissolves once those two lists exist, because most of the criteria below are only meaningful relative to them.
If you cannot write the question list yet, that is the finding. A tool will not generate demand you have not understood, and the cheapest way to build the list is to read your own Search Console queries and your sales call notes.
The nine criteria
1. Engine coverage. Which engines, and can you see the list before you buy? Coverage claims are often written to imply breadth that the plan you are looking at does not include.
2. Refresh cadence. How often is each engine actually re-asked? Check per engine, not per product. It is common for one surface to update continuously while the rest refresh monthly, and for the headline to describe only the first.
3. Pricing model. Does cost scale with engines, prompts, seats, or none of those? This is the criterion that compounds. Per-engine pricing makes breadth expensive; per-prompt pricing makes depth expensive; flat pricing makes neither, and instead puts the ceiling on the plan.
4. Prompt control. Can you write and edit the exact questions, or are you scored against a fixed set someone else chose? A fixed set is fine for benchmarking a category and useless for tracking the questions your buyers actually ask.
5. Mentions versus citations. Does it distinguish being named from being linked? Both are worth knowing. Only one of them tells you which page did the work.
6. Honesty about non-answers. Ask directly: what happens when an engine errors, refuses, or returns nothing? If a non-answer is recorded as “not cited”, every score the tool produces is quietly pessimistic and unstable, and you will chase drops that never happened. This is the least-asked question on this list and one of the most revealing.
7. The Google join. Does it connect to Search Console? The two most useful diagnoses in this whole discipline, “we rank on Google but AI never cites us” and “we are invisible to both”, need different fixes and you cannot tell them apart without both datasets side by side.
8. Does it tell you what to fix? Measurement is table stakes now. The gap between tools is whether the output is a dashboard or a queue of specific, page-level changes. Ask to see a real fix list for a real site, not a screenshot.
9. Data portability and API access. Can you export, and is there an API or MCP server so the data reaches the tools you already use? This is easy to skip during evaluation and expensive to discover afterwards.
The question nobody asks:
A scorecard you can copy
Weight the criteria by your own situation rather than treating them equally. A rough default that works for most B2B teams:
| Criterion | Weight | What a good answer looks like |
|---|---|---|
| Engine coverage | High | Names every engine, and the list does not change by plan tier |
| Refresh cadence | High | States cadence PER ENGINE, not one headline number |
| Pricing model | High | You can predict next year’s invoice from this year’s plan |
| Prompt control | Medium | You write the questions; editing them is not a support ticket |
| Mentions vs citations | Medium | Two distinct numbers, defined in the docs |
| Non-answer handling | Medium | A third state exists: cited, not cited, did not run |
| Search Console join | Medium | Native, not a CSV you reconcile by hand |
| Fix guidance | Medium | Named pages and specific changes, not generic advice |
| Export and API | Low to high | Depends entirely on whether you have somewhere to put it |
Weights are a starting point. If your buyers only use one engine, coverage drops to low and cadence rises.
Four traps specific to this category
The coverage-tier trap. A tool lists eight engines on the marketing site and includes two on the plan you can afford. Check coverage against the specific tier, not the product.
The averaged-score trap. A single “visibility score” that blends mentions, citations and position across engines will move for reasons you cannot decompose. Ask what it is made of. If nobody can tell you, it will not survive its first unexplained drop.
The stale-corpus trap. Some tools report from a large pre-collected corpus rather than asking the engine your question now. That is genuinely valuable for category-wide landscape work and misleading if you read it as your current position.
The demo-data trap. Ask for a scan of your own domain during evaluation. Sample dashboards are built on brands with strong results, and the tool that looks best on a well-known brand is not always the one that gives you a usable answer.
Once the scorecard is filled in, the comparison pages are worth reading. Ours are here, and which tools AI engines actually cite is the closest thing we have to an outside view, since it counts what the engines said rather than what any vendor claims.