Otterly.ai vs HubSpot AEO vs Ahrefs Brand Radar: Price, Engines, Metrics and Fit in 2026

Otterly.ai vs HubSpot AEO vs Ahrefs Brand Radar is a comparison of a dedicated tracker and two products sold inside larger platforms. Otterly.ai lists plans from $29 to $489 a month with a seven-day trial. HubSpot AEO lists $50 a month for 25 prompts on three engines, in Beta. Ahrefs sells Brand Radar custom prompts from $50 a month, and includes a small allowance in each paid Ahrefs plan from $129. Each counts usage in a different unit, so the prices are not like for like.

This comparison reads each vendor's pricing, product and help pages as published in October 2026. It is not a hands-on test, and no product was run. Prime AI Visibility publishes this site, competes with all three and appears later with its own limitations.

Otterly.ai vs HubSpot AEO vs Ahrefs Brand Radar: the short answer

• Otterly.ai fits teams that want a standalone monitor with a published price ladder, daily tracking of four engines, and audits and recommendations. It reads answers from each engine's public website, with Claude read through an API.
• HubSpot AEO fits teams already working in HubSpot. It tracks ChatGPT, Gemini and Perplexity, suggests prompts from company, competitor and industry context, and its page says CRM data in Marketing Hub makes recommendations more specific.
• Ahrefs Brand Radar fits teams already paying for Ahrefs. It offers two products: custom prompts, and an AI Visibility Index built on a database of modeled prompts that Ahrefs says covers 512 million prompts a month.
• The units differ. Otterly.ai sells prompts, HubSpot sells prompts and answers, and Ahrefs counts checks, where one prompt on one platform, location and update is one check.
• None of the three pages replaces a baseline. A saved set of answers to your own questions shows what each product should reproduce.

Who the three vendors are

Otterly.ai. OtterlyAI, also written Otterly.AI, is based in Vienna, Austria, and was founded by Thomas Peham, its CEO, Josef Trauner and Klaus-M. Schremser. Its About page says 40,000 marketing professionals were using the product by August 2026, which is the company's own figure.

HubSpot AEO. HubSpot sells CRM, marketing, sales and service software. Its AEO tool is labelled Beta and is sold both as a standalone $50 a month product and inside Marketing Hub. HubSpot's page says the tool works regardless of where a website is hosted, so HubSpot's CMS is not required.

Ahrefs Brand Radar. Ahrefs is an SEO software company. Its Brand Radar page says more than 3,000 companies use the product, which is Ahrefs' own figure, and describes it as the largest AI visibility database, which is also Ahrefs' own claim.

For a closer look at how the four-way set of Otterly.ai, Profound, HubSpot AEO and Mangools compares, read our four-product comparison. For Ahrefs against a different vendor, see Profound vs Ahrefs.

What do the three cost, and what is included?

Prices are list prices in US dollars as shown on each vendor's page. A row reads Not verified where the pages read did not state a fact.

Product and plan	Monthly price	What the page lists
Otterly.ai Lite	$29	15 prompts, 4 engines
Otterly.ai Standard	$189	100 prompts, API and MCP
Otterly.ai Premium	$489	400 prompts
HubSpot AEO	$50	25 prompts, 3 engines
Ahrefs Lite	$129	150 checks, 5 prompts
Ahrefs Advanced	$449	600 checks, 20 prompts
Ahrefs custom prompts	From $50	Add-on to a paid plan
Ahrefs AI Visibility Index	From $199	Index of 512M prompts

Notes:

• Otterly.ai. Billing annually saves 15%, so Lite, Standard and Premium become $25, $160 and $422. Every plan includes ChatGPT, Google AI Overviews, Perplexity and Microsoft Copilot, and Claude, Google AI Mode and Gemini are paid add-ons. Extra prompts cost $99 per 100. Enterprise is custom from 1,000 prompts.
• HubSpot AEO. The product page lists $50 a month, or $45 billed annually, and says you can buy more prompts without a stated limit. HubSpot's Marketing Hub pricing table lists 25 prompts a day across three engines, 2,500 answers a month, in its Professional column and 50 prompts, 5,000 answers, in its Enterprise column. That table shows Marketing Hub Professional at $800 a month and Enterprise at $3,600 a month, and the table does not state the billing terms behind them.
• Ahrefs. Brand Radar prompts come with a paid Ahrefs plan: Lite $129, Standard $249 with 300 checks and 10 prompts, Advanced $449, and Enterprise from $1,499. The price includes the rest of the suite. Custom prompts are free on every paid plan from Lite and sold as an add-on from $50 a month, and the AI Visibility Index starts at $199 a month.
• Free options. Otterly.ai's help centre describes a seven-day trial with 50 prompts and no card. HubSpot says you can track 25 prompts in three engines free, with no card, and continue for $50 a month. The Ahrefs page read describes a free AI visibility preview, not a Brand Radar trial.

Which engines does each one track?

Product	Engines	Where it says so
Otterly.ai	4 included, 3 add-ons	Pricing page
HubSpot AEO	ChatGPT, Gemini, Perplexity	AEO page
Ahrefs Brand Radar	AI Overviews, AI Mode, ChatGPT, Perplexity, Copilot, Gemini	Brand Radar page

Ahrefs' page also lists Claude, available on the larger index plan, and says Claude consumes eight checks per update. HubSpot lists three engines and does not list Claude, Google AI Overviews or Google AI Mode. If a particular engine matters to your buyers, find its row before reading a price.

How is usage counted? Prompts, answers and checks

This is the part most price comparisons skip.

Product	Unit	Rule on the page
Otterly.ai	Prompts	Plan allowance; extra blocks of 100
HubSpot AEO	Prompts and answers	25 prompts daily on 3 engines
Ahrefs	Checks	One per prompt, platform, location and update

HubSpot's pricing table says 25 prompts, each run daily across three engines, make 2,500 answers a month. Ahrefs states the rule directly: each prompt is checked daily on every selected platform, so 5 prompts on 1 platform make 150 checks a month. Its page also says prompts can be tracked daily, weekly or monthly, which changes how many checks a prompt uses. Otterly.ai does not say whether a prompt runs once on each included engine.

For that reason this page does not compute a price per answer across vendors. A calculation across three units would imply an equivalence the pages do not give. Instead, compare each product in its own unit against your prompt list. An invented example: a team with 40 prompts on three engines needs 40 prompts at HubSpot, which means a limit increase beyond the base 25. At Ahrefs, 40 prompts on three platforms refreshed daily would be about 3,600 checks a month by the stated rule, and the plan table shows Advanced stopping at 600, so that team would be looking at add-ons or Enterprise.

How does each product collect answers?

The collection method decides what a score can tell you.

Otterly.ai. Its help centre says it posts questions through each AI platform's website, such as chatgpt.com, and adds that it only uses an API for Claude. It monitors every prompt daily and queries each prompt from the country you assign to it. It also says AI engines differ between users depending on session, location and account, and that Otterly.ai provides a neutral baseline, so your own view may differ.

HubSpot AEO. The page says prompt tracking shows the exact response ChatGPT, Gemini or Perplexity returned, and you can filter by answer engine and buyer's journey phase. A customer quote on the page says HubSpot's data is grounded in real web search. The pages read do not describe the collection interface, so ask HubSpot whether answers come from the consumer apps or from APIs.

Ahrefs Brand Radar. Ahrefs says visibility is measured by running 512 million-plus search-backed prompts through AI Overviews, AI Mode, ChatGPT, Perplexity, Gemini and Copilot and storing every response. Those prompts are modeled from the keyword database, which means the index shows what your market's search-derived questions return, not your own questions. Ahrefs says the index may have limited coverage for brands with little or no search volume, which is why custom prompts exist.

What the numbers mean: a metric definition crosswalk

Similar names do not always mean the same measure. This table sets each vendor's published definition side by side.

Idea	Product and label	Defined as
Visibility	Otterly.ai Brand Coverage	Prompts naming you ÷ all prompts
Visibility	HubSpot visibility score	How often you appear, as a %
Mentions	Ahrefs Mentions	Brand name in answer text
Share of voice	Otterly.ai	Your mentions ÷ all brand mentions
Share of voice	HubSpot	Your mentions against competitors
Share of voice	Ahrefs	Responses mentioning or citing you
Sentiment	Otterly.ai	Net score, −100 to 100
Sentiment	HubSpot	Scale from −100 to +100
Citations	Ahrefs Citations	AI links to your pages

Notes:

• Visibility. Otterly.ai counts per prompt, engine and day and leaves out Google AI Overviews runs where no overview appeared. HubSpot defines competitor visibility as a brand's visibility divided by the total answers analyzed. Ahrefs does not use the word visibility for one number: it reports mentions, citations and share of voice.
• Share of voice. Otterly.ai counts a brand once per answer even when it is named twice. Ahrefs counts a response as a hit when it mentions or cites you, so it blends two signals that the other two keep apart.
• Sentiment. Otterly.ai's score is positive mentions minus negative mentions, divided by all mentions, times 100. HubSpot reports sentiment on a scale from −100 to +100 and does not publish a formula on the page read. Ahrefs lists a sentiment skill among its Letaido workflows, which is a separate product.
• Demand. Ahrefs lists estimated impressions, which weight potential visibility by the real search volume behind each prompt. Otterly.ai offers an estimated intent score in its prompt research tool. HubSpot does not describe a demand figure. All of these are estimates, not counts of questions asked. Our explainer on prompt volume covers how the sources differ.

In our judgement, a 40% visibility score from one product equals a 40% from another only when the prompts, engines, markets and run counts are the same. Prime AI Visibility uses its own four measures, each defined on the metrics page, and they are not interchangeable with any of these.

The five AI visibility signals

Each signal moves on its own, so check which product reports which:

1. Mention (the answer names the brand): all three, as Brand Coverage, visibility score and Mentions.
2. Citation (the answer links your site or a source about you): all three list citation analysis, with Ahrefs counting links to your pages and HubSpot grouping sources by owned, competitor, third-party, social and other types.
3. Recommendation (the answer suggests your brand over others): HubSpot and Ahrefs publish no recommendation measure, and Otterly.ai reports position and sentiment. Read the answer text for an explicit recommendation.
4. Referral (someone clicks through to your site): Ahrefs lists free Web Analytics for AI-referred visits and Bot Analytics, free while in beta, for AI crawler visits. Otterly.ai's Standard plan lists Agent Analytics. HubSpot says it connects AI data to campaign metrics inside its own platform.
5. Conversion (the visit becomes a lead or sale): HubSpot's CRM is where this would sit. Confirm what reaches your CRM or analytics with each product.

Claim check: what each vendor's own pages say

This table checks claims on the three product pages against what each page supports. A claim is a vendor's own statement, not a finding.

Claim	Where	What it shows
"The largest AI visibility database"	Ahrefs	Ahrefs' own claim about its index
Prompts "modeled from real user searches"	Ahrefs	Modeled, not your questions
"Grew leads from AI by 1,850%"	HubSpot	HubSpot's result on its own site
Data "grounded" in real web search	HubSpot	A customer quote; method unstated
Responses "identical" to customers'	Otterly.ai	Same page says yours may differ
Claude "only" via an API	Otterly.ai	Mixed collection by engine

Notes, row by row:

• The largest database. Ahrefs' index is built from its keyword database, so it can show an established brand's footprint quickly, and the vendor says it may be thin for new brands.
• Leads from AI. HubSpot reports its own lead growth as a first-party claim; treat it as the vendor's result for its own site, not a prediction for your account.
• Grounded data. The statement is attributed to a customer, and the page does not explain how HubSpot collects answers.
• Identical responses. Otterly.ai's help page says responses are identical to what customers experience and, further down, that results can differ from what you personally see because of session, location and account settings. Both statements can be true of a neutral baseline, and the second is the one to plan around.
• Claude through an API. Otterly.ai itself says an API reading can differ from what an interface shows, so ask how its Claude answers differ from the Claude app.

Plans change quickly, so treat this check, and any vendor's comparison including this one, as a list of points to confirm in a demo or trial.

An operator checklist for scoping AI visibility work

Before you compare tools, scope the job. These seven decisions apply to any of the three.

1. Buyer persona. Write who asks the question, such as a first-time buyer, a researcher or a returning customer, and keep one persona per prompt group.
2. Brand variants. List every spelling, abbreviation and product name an answer might use, because a miss on a variant reads as an absence.
3. Prompt inventory. Write 25 to 50 questions in buyers' own words, grouped by decision, and keep the exact text outside every tool.
4. Baseline. Save five full answers with their cited links before any trial, so each product is judged against the same evidence.
5. Sources. Record the domains each answer cites, because your brand's presence often depends on pages you do not own. Google's SEO Starter Guide is a sound reference for the owned side: it says a sitemap helps Google find your pages but is not required, and it recommends descriptive URLs and reducing duplicate content.
6. Cadence. Decide how often you need to see change. HubSpot and Otterly.ai list daily runs, and Ahrefs lets you set daily, weekly or monthly.
7. Reporting. Decide who reads the report, and keep mention, citation, recommendation, referral and conversion in separate columns.

A question-by-question sample scorecard

The scorecard below is an invented example to show the structure. It is not data from any product or any real site. A public example from another field helps. Pulse Terminal, at its homepage and its stocks page, describes a market research application that grades stocks and ETFs and answers questions with sources shown. It is an illustrative public website, not a Prime AI Visibility client, endorsement or paid partner, and this page says nothing about how any AI engine treats it. Financial content is regulated, so any answer or page that discusses securities needs a compliance review before it is published.

A site like that would write its prompt groups around how people research markets. Score each question with the same four fields:

Illustrative question	Observed in the answer	Source shown
How do I compare stock research apps?	Brand named in a list	Review site
Which app explains a stock's grade?	Brand not named	Competitor page
What does 24-month velocity mean?	Named, with caveats	Own page
Are AI stock screeners reliable?	Not named	News article
Where can I ask questions about a ticker?	Named first	Own page

Reading the example: "Not named" with a competitor page shown tells you which page to study. "Named, with caveats" should be logged as mixed, with the quoted sentence, and never turned into a score. Repeat the same questions after any change so the scorecard measures the change.

A side-by-side evaluation plan

A fair test keeps the inputs identical:

1. Write your prompts first. Use the 25 to 50 questions from the checklist, and keep the exact text outside all three tools.
2. Start every trial in the same week. Otterly.ai's trial lasts seven days, HubSpot does not state a length, and Ahrefs has no separate Brand Radar trial on the pages read.
3. Fix the engines. Compare ChatGPT, Perplexity and Gemini where all three overlap, or ChatGPT and Perplexity if Gemini is an add-on.
4. Ask for raw answers. Save five full answers with cited URLs from each tool for the same prompts.
5. Compare like with like. Set Otterly.ai's Brand Coverage beside HubSpot's visibility score, and do not compare sentiment figures across tools.
6. Price your real prompt list in each vendor's own unit, as in the invented example above.
7. Ask the same final questions. Which engines are in your contract, how answers are collected, how long history is kept, and what can be exported.

The guide on how to choose an AI visibility tool explains each evaluation axis in more depth, and the AI visibility audit process turns the checklist above into a baseline.

Who each product fits

Situation	Likely fit	Why
Standalone monitor, small budget	Otterly.ai	Published ladder from $29
Team already in HubSpot	HubSpot AEO	Tool sits beside CRM data
Team already paying for Ahrefs	Ahrefs Brand Radar	Small allowance included
Need benchmark of a market	Ahrefs index	Pre-collected prompt data
Need Claude without Enterprise	Otterly.ai add-on	Sold as paid add-on
Need many prompts, three engines	Compare in each unit	Units differ

Otterly.ai fits solo marketers and small teams that want published prices and a trial. Limit: four engines are included, and the others are add-ons. HubSpot AEO fits teams that already use HubSpot. Limit: three engines and a Beta label. Ahrefs Brand Radar fits teams that already use Ahrefs and want a few prompts alongside it. Limit: included checks are small, and tracking many prompts across several engines moves toward the add-on or Enterprise.

For a wider shortlist, see our guide to AI visibility tools for B2B companies, or compare Ahrefs with two other vendors in Rankscale vs Ahrefs Brand Radar vs Semrush AI toolkit.

Where Prime AI Visibility fits

The Prime AI Visibility Platform is built around saved answers. The free check runs up to five buyer questions across ChatGPT, Claude and Perplexity, keeps up to 15 answers with the links each displayed and needs no card. It is one check a month. Starter is $69 a month and adds Gemini and an AI Overview-style preview. The Prime AI Visibility features include an AI Search Predictor that finds questions worth pursuing and a Content Studio that drafts source-enriched pages as files, with nothing published without approval. The pricing page lists every plan.

As an AI visibility checker, the free check gives a baseline to test any of the three against, and as an AI visibility tracker it keeps the same questions from one month to the next.

Limitations: Prime AI does not report sentiment, rank, AI crawler visits, traffic or conversions, so referral and conversion data must come from your analytics. It has no prompt-volume data, no index of modeled prompts and no CRM link. It checks monthly by default, with weekly, temporary daily and on-demand checks on paid plans, and does not track Microsoft Copilot, Grok, DeepSeek, Meta AI or Google AI Mode. This is an affiliated recommendation, not an independent ranking.

When the next job is implementation

An AI Visibility Platform, whether Otterly.ai, HubSpot, Ahrefs or another, shows where a brand stands and suggests fixes. Earning coverage on the publications, forums and review sites that answers cite is still work for people, and no AI Search Visibility Platform writes that coverage for you.

Percepture, founded in 2004, is a company connected to Prime AI. Its generative engine optimization services cover the implementation when a scorecard shows pages that answers skip or misstate: content, sources and structure aimed at the sites answers cite. Its AI visibility tools guide covers the measurement that comes first. Fit: a team that wants SEO, GEO and content done by people. Limitation: Percepture is a services firm, not a tracking platform, so it pairs with a tool rather than replacing one. Prime AI has a commercial relationship with Percepture.

A documented AI visibility strategy makes any of these tools easier to judge.