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Answer Engine Optimization Tools: What Each One Measures and What It Publishes

Answer engine optimization tools compared by what they measure and publish: engines, runs per prompt, position vs share, and what each leaves out.

Answer engine optimization tools (also called AEO tools, GEO tools or generative engine optimization tools) send prompts to AI engines and count how often your brand appears. The best question to ask any vendor is how many times it runs each prompt. ChatGPT answers change from run to run, so one run proves little. Ask for a share across many runs, not a position.

Lourdes Paul Agilan, founder of Aquinel

Founder, Aquinel · Published · 9 min read

Note on verification: We took every tool fact below from the vendor's own pricing page, docs or help centre, read on 12 October 2026. A page can render differently for you. Where a page said nothing, we write "not published." We used no "best tools" list for facts. Reddit was not checked.

What are answer engine optimization tools?

These tools ask AI engines questions for you. They then count how often your brand shows up in the answers. Vendors use many names: AEO tools, GEO tools, AI visibility tools. We read nine product pages. They all do the same core job.

Interest is real. In US data from DataForSEO in September 2026, "answer engine optimization tools" drew 590 searches a month. "Geo tools" drew 720.

Our post on AI visibility tools or an agency covers price. This post asks what each tool measures and what it says about its own data.

Why does the number of runs matter?

ChatGPT does not give the same answer twice. SparkToro published a study on 27 January 2026. Rand Fishkin and Patrick O'Donnell ran it. We label it vendor-linked. O'Donnell works at Gumshoe.ai, an AI tracking startup, and the study says so.

The study used 600 volunteers. They ran 12 prompts through ChatGPT, Claude and Google's AI, which made 2,961 runs.

SparkToro found under a 1 in 100 chance of the same brand list twice. That held for ChatGPT and Google's AI. It put the chance of the same list in the same order at about 1 in 1,000.

SparkToro drew two lessons. It advised at least 60 to 100 runs per prompt, then averaging them. It also said any tool that gives a "ranking position in AI" is "full of baloney."

That is one vendor-linked study. It does not set a standard. No vendor or standards body has set one.

Our view is that ChatGPT has no fixed ranking. So we put two questions to every vendor:

  1. How many times does the tool run each prompt?
  2. Does it report a share across runs, or a position?

How do the tools compare?

We read each vendor's own pages on 12 October 2026. The table covers eight tools and shows what the pages say. Search Atlas, the ninth, is below it. "Not published" means we found no statement.

ToolEngines namedHow it collectsRuns per promptPosition or sharePrice on its site
ProfoundTrial: 3. Enterprise: up to 9Not publishedDaily. Count per prompt not publishedVisibility share, plus an Average Position metricFree trial. Enterprise custom
Peec AIChoose 3 models on paid tiers. Enterprise up to 13UI scrapingOne answer per prompt per model per day (from its answer-count formula)Visibility share, plus PositionNo dollar amounts on the pricing page we read
Otterly.AI4 core, 3 as add-onsPublic web interfacesDaily. Count not publishedShare of voice, plus Avg. Brand PositionPage shows $29 Lite to $489 Premium, and also $25 to $422
Semrush AI Visibility ToolkitChatGPT, Google AI, Gemini, PerplexityNot publishedDaily updates. Count not publishedScore relative to rivals$99/month per domain, billed annually
Ahrefs Brand RadarSix, plus Claude on Custom PromptsRuns prompts through each platform and stores the responsesOne check per platform per updateNot publishedFrom €47/month (Custom Prompts)
ScrunchSevenNot publishedNot publishedNot published$250/month annual, $300 monthly
Rankscale9 named on the Pro planNot publishedSet by you: hourly to monthlyNot published$99/month (Pro)
Writesonic GEOStarter: 3. Enterprise: 8Not publishedDaily. Count not publishedNot published$79/month annual (Starter)

None of the nine pages mentions run-to-run variance.

What does each tool say about itself?

Profound

Profound's help page says it "queries these answer engines and builds a dataset from the responses." It does not say whether it uses an API or the web interface. Its Visibility score divides responses that name you by responses that name any brand. Its pricing page, read on 12 October, showed a free trial and a custom Enterprise plan. A self-serve Agency Growth plan appears in the FAQ with no price. Our earlier post listed a $99 plan. We could not find it on the page today.

Peec AI

Peec states its collection method in its docs. They say Peec "uses UI scraping technology" to act like a real user. The docs also say most platforms choose the model themselves, as for a logged-out user. Peec's pricing page counts "AI answers" as prompts times models times days. Its Starter figure of 4,500 matches 50 prompts, 3 models and 30 days. So Peec publishes a clear run rate: one answer a day.

Its Position metric measures "average ranking" across responses. The metric pages do not discuss sampling error.

Otterly.AI

Otterly says it measures answers "via public web interfaces." Its help page counts each prompt-engine run as a 1 or a 0. That is a share across runs. The same help page also reports Avg. Brand Position. Otterly's research page adds a caution: results from one prompt set do not generalise to all prompts. It does not say how many runs it makes.

Semrush AI Visibility Toolkit

Semrush tracks 25 prompts on the $99 base plan. Its pricing page describes "daily AI rankings." Its knowledge base says the AI Visibility Score compares your mentions to the median of your top rivals. The score is relative, not absolute. The page does not say how often each prompt runs.

Ahrefs Brand Radar

Ahrefs describes its method. It takes real queries from its keyword data and expands them. It then runs 470M+ prompts through each platform and stores the responses. Custom Prompts use "1 check per platform, location and update." Claude uses 8 checks per update. Ahrefs says the index may have limited coverage for brands with little or no search volume. Its Index question sets are re-tested monthly.

Scrunch, Rankscale and Writesonic GEO

Scrunch lists 350 custom prompts on its entry plan. Its pricing page does not state collection method, frequency or repeat runs.

Rankscale prices by credit, not by prompt. Its FAQ says a query "typically" costs 0.25 credits per engine per prompt. You pick the schedule. That lets you buy more runs, but it makes the run count your decision.

Writesonic lists "answers tracked" per tier: 50, 300 and 600. It never defines the term. Its Starter tier shows 50 prompts and 50 answers across three engines. We could not reconcile that.

We also read Search Atlas. A help page names four engines and mentions "API integrations." It shows no price, no frequency and no run count.

What do these tools not publish?

Across the nine pages, the gaps repeat.

  • No page gives a confidence range on a score.
  • Most pages do not state how many times each prompt runs.
  • Peec and Otterly say they collect through the web interface. Search Atlas names APIs. Ahrefs describes its own pipeline. The rest do not say.
  • Three tools document a position metric: Profound, Peec and Otterly. SparkToro's study doubts such numbers.
  • Prices move. Otterly's page showed two price sets at once.

One fair counterpoint exists. A daily run adds up. Thirty days of one run a day gives 30 answers per prompt per engine. That is fewer than SparkToro's 60 to 100, but it is not one. The pages do not say if a tool averages those days into one score. Ask.

How should you choose one?

Skip the feature list. Ask the vendor five things.

  1. How many times a day does each prompt run on each engine?
  2. Does the dashboard show a share across runs, or a single answer?
  3. Does it show a range, or only one number?
  4. Does it run through the API or the web interface?
  5. Can you export every raw answer?

Raw answers (question 5) let you check the maths yourself. Our guide on how to track AI citations and traffic shows what your own analytics can and cannot see.

Check the vendor's definitions too. Profound, Semrush and Otterly define their scores in different ways. A 40% in one tool is not a 40% in another.

Where does Aquinel sit?

Aquinel is our company. We sell services, not a tool. You can read what we offer on our services page. We have a stake in the tool-or-agency question, so weigh this section with care.

Our services page says we run each question "several times" and report a ratio. "Several" is not a number, so we meet the test above only in part. A tool alone does not explain why a number moved.

Questions

What are answer engine optimization tools?

They are software products that send prompts to AI engines such as ChatGPT and Perplexity. They record whether your brand appears in the answers. Vendors call them AEO tools, GEO tools or AI visibility tools. They measure. They do not change why an engine names you.

Are AEO tools and GEO tools the same thing?

In practice, yes. We read the product pages of nine vendors on 12 October 2026. Each one does the same core job. It sends prompts to AI engines on a schedule and reports brand mentions. The labels differ. The method is the same.

How many times should a tool run each prompt?

No standard exists. SparkToro's January 2026 study, linked to the vendor Gumshoe.ai, advises at least 60 to 100 runs per prompt. Of the tools we read, only Peec states a run rate: one answer per prompt per model per day.

Should I trust an average position from an AI tracking tool?

Treat it with care. SparkToro's January 2026 study found the order of brands changes almost every run. It said any tool that gives a ranking position in AI is full of baloney. Three tools we read still report average position. A share across many runs is safer.

Do I need a tool or an agency for AEO?

A tool shows you the number. It does not explain the number or change it. We cover that choice in a separate post. Aquinel sells services, not a tool, so we have a stake in the answer. Weigh our view with that in mind.

Sources

If you would like us to walk you through how this would work for your firm, the call is free.

Lourdes Paul Agilan, founder of Aquinel

About the author

Lourdes Paul Agilan

Founder of Aquinel. Works with MSPs and IT services firms from Chennai, India, on getting recommended by ChatGPT and found on Google.

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