A new category of software exists to answer one question: does your brand show up when someone asks ChatGPT, Gemini, or Perplexity about your category, and if so, how? Dozens of products now sell some version of that answer, under labels like AI visibility, answer engine optimization, or generative engine optimization. They differ more than their nearly identical marketing pages suggest, and the differences matter to whether the number on the dashboard means anything.
This page describes the framework the Tools Desk applies to every product we review, and it is honest about the limits of what a review published this month can tell you.
What we mean by an "AEO tool"
For this section, an AEO tool is a product that samples AI systems with prompts, records how a brand appears in the responses, and reports that back as a metric — visibility, share of voice, sentiment, or similar. That covers standalone AI-visibility platforms and the AI-tracking features now bolted onto established SEO suites. It does not cover general analytics platforms that only measure referral traffic from AI sources, though we note that capability when a product has it.
The framework
Engine coverage
Which AI systems does the tool actually query, and how many of them are included at the price you'd pay, rather than gated behind an enterprise tier? ChatGPT, Google AI Overviews, Gemini, Perplexity, and Microsoft Copilot are the common baseline; Claude, Meta AI, DeepSeek, and Grok appear less consistently. We report the full list and flag when "coverage" in the marketing copy is narrower than coverage on the plan you'd actually buy.
How answers are sampled, and how transparent the vendor is about it
AI-generated answers vary from run to run, by account state, location, and model version. A credible tool samples repeatedly rather than once, and says so. We look for a vendor that documents its prompt-execution frequency (daily, weekly), whether it discloses sample size, and whether it explains how prompts are chosen or written — vendor-suggested, user-authored, or derived from real query data. A tool that is vague about sampling is a tool whose headline number is hard to interpret.
Citation vs. mention tracking
A brand can be named in an AI answer without being linked as a source, or linked as a source without being named — a distinction covered in more detail in HubSpot's overview of AI citation tracking. Our own methodology treats mention, citation, and recommendation as distinct outcomes, and we hold vendor tools to the same distinction: does the product separate "you were mentioned" from "you were cited," or does it collapse both into one undifferentiated visibility score?
Share-of-voice methodology
Share of voice is only meaningful relative to a defined competitor set and a defined prompt set. We check whether a tool lets you see and control that competitor set, whether the metric is calculated per prompt or aggregated across an entire tracked list, and whether the vendor explains the formula anywhere a customer can read it before buying.
Sentiment
Several tools score whether a brand is discussed favorably, neutrally, or unfavorably inside an AI answer. This is the softest metric in the category — it depends on a classifier the vendor built and rarely documents in detail. We note when sentiment is offered, and we treat it as a directional signal rather than a precise score in every review.
Data freshness
How often are prompts actually re-run: daily, weekly, on demand? A dashboard that updates weekly but is marketed as "real-time monitoring" gets flagged. Freshness also interacts with pricing — refresh frequency is one of the more common levers vendors use to gate cheaper tiers.
Exports, API access, and pricing transparency
Can you get your data out, and at what tier? We record whether CSV export, API access, and white-label reporting are available, and at which plan they unlock, since agencies and in-house teams have very different requirements here. On pricing, we prefer vendors who publish real numbers over "contact sales" for every tier — where a vendor publishes tiers, we quote them with the date we checked; where nothing is public, we say so rather than guess.
Data-collection method: API vs. UI scraping
This is the dimension most reviews of this category skip, and it changes what the number on the dashboard actually represents. Some vendors query the official API of each AI system; others use browser automation to interact with the consumer-facing interface, the way an actual person would; several use a mix, chosen per platform. The two approaches can produce different answers to the identical prompt, because a consumer interface may apply system prompts, live browsing, or interface-level context that an API call does not. Neither method is strictly "more correct" — an API call is reproducible and cheaper to run at scale, while UI automation more closely tracks what a real user sees but is more fragile to interface changes and harder to verify independently. We report which method a vendor documents for which platform, because a tool that is silent on this point is asking you to trust a number it hasn't explained.
What this review series is, right now
At launch, every review on this site is a desk review: written from a vendor's own documentation, product pages, pricing pages, and other publicly available material, checked as of September 2026 and dated as such in each piece. We have not yet put these products through hands-on testing on a shared set of accounts and prompts. Where that changes for a given product, we will publish it as a dated update to the existing review rather than a quiet edit, consistent with our editorial standards.
We do not fabricate test results, invent benchmark numbers, or assign numeric star ratings to compensate for that gap. Each review instead gives a verdict, a "best for" recommendation, a pricing summary, and pros and cons drawn strictly from what the vendor and credible third-party coverage state publicly.
Independence
No vendor can pay for placement, for a favorable review, or for inclusion in a ranking or list on this site. We do not accept vendor-supplied review copy, and where we get something wrong, we correct it and note the change — see corrections for how that process works.
