Ahrefs vs Profound (2026) — Which AI Visibility Tool is Better?

Ahrefs vs Profound: which tool is better for tracking AI visibility? In this comparison, I explore the key differences to help you choose the right platform for your needs.

The rise of AI visibility tracking tools

As AI tools like ChatGPT, Gemini and Perplexity become more widely used, the way people discover information online is starting to change. Instead of scrolling through lists of links in traditional search engines, users are increasingly receiving direct answers from generative AI systems.

For businesses, this raises a new question: how visible is my brand in AI answers?

To help marketers get a handle on this, a new category of AI visibility tracking tools has emerged. These analyze how brands, websites, and products appear in AI-generated responses, and help organizations optimize their content to increase visibility in them. You’ll often see this optimization process described using terms like AEO (Answer Engine Optimization) or GEO (Generative Engine Optimization).

Two of the more prominent platforms in this emerging area are Ahrefs’ Brand Radar and Profound. Both tools are designed to help organizations understand their presence in AI responses — but they approach the challenge from different directions.

Profound is primarily built around prompt monitoring. It allows teams to track how their brand appears for specific queries across multiple AI platforms, and provides metrics like visibility scores, sentiment signals and citation share.

Ahrefs’ Brand Radar, meanwhile, puts more emphasis on analyzing large datasets of AI answers. Instead of focusing on a predefined list of prompts, it allows users to explore how brands, websites and sources appear across a much broader set of AI conversations.

That said, the distinction isn’t completely black and white. Profound also includes tools for researching prompts and analyzing brand narratives, while Brand Radar provides some prompt monitoring capabilities.

In practice, however, the two platforms tend to emphasize different types of insights: Profound leans more toward structured monitoring and reporting, while Brand Radar is designed more for exploratory research into how AI answers are constructed.

In what follows, I’ll take a closer look at how these two approaches differ — and in which situations each platform may have the edge.

I’ll start with the key advantages that Ahrefs has over Profound, and then move on to the areas where Profound might be the better solution.

Reasons to use Ahrefs over Profound

1. Ahrefs analyzes a far larger dataset of AI prompts

One of the biggest differences between Ahrefs’ Brand Radar and Profound comes down to how the tools collect and use data.

Ahrefs’ Brand Radar is built on a very large, pre-collected dataset of AI prompts and responses (around 190 million prompts per month are covered by the tool). In simple terms, this means it already has information about how AI tools respond to a huge number of questions.

Because of this, you can explore a wide range of topics straight away. For example, instead of just tracking a few prompts you’re interested in, you can look at an entire category — like “email marketing tools” — and see which brands AI tools mention most often.

Profound works differently. Instead of giving you a big dataset to explore, it focuses on tracking specific prompts that you choose.

So, you might enter a list of important queries — for example, “best ecommerce platform” or “Shopify alternatives” — and then monitor how your brand appears in AI answers for those queries over time.

In short:

So, Profound’s model works well for structured monitoring. However, it also means the scope of analysis is typically limited to the particular prompts being tracked (and on Profound’s non-enterprise plans, monitoring is capped at just 50–100 prompts).

By contrast, Brand Radar’s indexed dataset allows users to explore visibility across a far larger prompt universe — without first defining what those prompts should be.

This architecture also ties into Ahrefs’ broader data infrastructure. The company has spent more than a decade building some of the biggest SEO datasets on the web, including:

Because Brand Radar sits on top of this broader data infrastructure, it functions less like a simple monitoring dashboard — it’s more like a research engine for understanding how brands appear across AI-generated answers.

2. Ahrefs reveals where AI recommendations actually occur

Another advantage of Brand Radar’s large prompt dataset is that it helps marketers understand where AI platforms actually introduce products and brands within conversations.

Many companies begin their AI visibility strategy by monitoring obvious commercial prompts such as:

These queries are certainly important. However, they represent only a small portion of the situations where AI platforms mention brands.

In practice, AI systems often introduce products within problem-focused or informational prompts, such as:

In these cases, the user may not be asking for a product recommendation. But AI engines often introduce tools or brands to consider when trying to help them solve their problem.

Because Brand Radar analyzes a very large dataset of prompts and AI responses, marketers can explore these sorts of contexts, and identify the types of conversations where their brand surfaces.

In my testing, this made it easier to uncover the informational and problem-solving queries where brands naturally surface in AI answers — contexts that might otherwise go unnoticed.

For example, a company might discover that its product rarely appears in “best product” prompts but frequently surfaces in how-to queries, industry explanations or problem-solving discussions.

Prompt monitoring platforms like Profound can also track visibility for individual queries — including informational or “how-to” prompts. However, because monitoring usually begins with prompts defined by the user, uncovering these broader recommendation contexts often requires more manual prompt research and experimentation.

3. Ahrefs makes competitor research in AI search much easier

Another advantage of Brand Radar’s indexed dataset is that it makes it easy to compare how competing brands appear across AI-generated answers.

Instead of analyzing prompts one by one, users can enter a brand and add competitors to quickly see how often different companies are mentioned across key AI platforms.

For example, you could use Brand Radar to compare how sports brands like Nike, Adidas and Puma appear across ChatGPT, or analyze how competing ecommerce platforms are Shopify, WooCommerce and BigCommerce are surfaced within Google’s AI Overviews.

Because Brand Radar’s dataset is indexed in advance, these comparisons can be explored immediately. And this makes it easier to understand which brands AI systems most frequently associate with a particular topic or industry.

Now, Profound can also be used for competitive research. However, because it typically relies on running predefined prompts and collecting results over time, building a comparable competitor-level view often requires defining a larger set of prompts and waiting for monitoring data to accumulate.

4. Ahrefs makes it easier to identify the publishers shaping AI answers

When AI platforms respond to questions, they typically synthesize information from multiple sources across the web — and understanding which domains appear most frequently in these responses can provide valuable insight into how AI systems construct their answers.

Brand Radar makes it easy to see the websites and publishers that are cited most often in AI-generated responses. Marketers can investigate:

In many industries, a relatively small number of websites tend to supply a large share of the content that AI engines draw upon — and Brand Radar lets you spot these easily.

In practice, the pages cited most often in AI-generated answers frequently share characteristics associated with strong SEO performance — such as authoritative domains, strong backlink profiles and well-structured informational content.

In other words, many of the same signals that influence traditional search visibility still appear to shape AI citations.

Understanding these signals can be extremely useful when developing a strategy for AI visibility. If you know which websites AI engines consistently reference in response to queries relating to your niche, you can analyze the content they contain and create your own material that covers similar topics and uses similar keywords.

(Note however that you really will have to focus on quality and depth of coverage here — it’s not enough just to create a few articles that are similar to those of your competitors.)

Profound also provides visibility into citation sources within monitored prompts, allowing users to see which domains and pages are referenced in specific AI responses. However, because this analysis is tied to the prompts you’ve defined, identifying broader publisher influence typically requires expanding the monitored prompt set (something that can involve a bit of guesswork).

By revealing which websites shape AI responses, Brand Radar helps marketers understand not just whether their brand appears in AI answers, but which sources — and which authority signals — influence those answers in the first place.

5. Ahrefs tracks brand discovery across creator and community platforms

Another distinctive capability of Brand Radar is its ability to track brand visibility across creator and community platforms (specifically YouTube, TikTok, and Reddit).

These platforms generate enormous volumes of user-generated product reviews and brand comparisons. As a result, they often play an important role in shaping online discovery — both within AI tools and, thanks to Google’s insistence on placing Reddit threads at or near the top of organic results — within traditional search.

Brand Radar now includes dedicated indexes that track brand mentions across:

For video platforms, Brand Radar scans video titles, descriptions and transcripts for brand mentions. Rather than indexing entire videos, the system surfaces short snippets around those mentions, allowing teams to quickly identify which creator content references their brand, and to understand the context in which it appears.

The platform also tracks Reddit threads that surface in Google search results, highlighting discussions where users recommend, compare or criticize products. These conversations often influence both search visibility and brand perception.

By tracking brand mentions across these ecosystems, Brand Radar helps marketers monitor the conversations that contribute to brand discovery across the wider web — and, if need be, to contribute to them.

By contrast, Profound focuses more directly on tracking how brands appear within AI-generated responses themselves. While this provides useful visibility data, it gives you less insight into the origins of these answers.

6. Ahrefs doesn’t just give you AI visibility insights — it provides SEO data too

A key advantage of Brand Radar over Profound is that it sits inside the broader Ahrefs SEO platform, rather than operating as a standalone AI visibility tool (note: it can be purchased separately, but many users will access it through the main Ahrefs tool).

Founded in 2010, Ahrefs has spent over fifteen years building one of the largest SEO data infrastructures on the web. Its platform includes tools for:

Because Brand Radar is integrated into this ecosystem, users can move directly from AI visibility insights to practical optimization work.

For example, if Brand Radar reveals that a competitor frequently appears in AI answers for a particular topic, a marketer can immediately investigate:

This ability to move quickly from insight to execution is particularly important, because AI visibility is still very much dependent on web content in general. As a result, improving AI visibility often still involves strengthening the same signals that influence traditional search rankings.

And although AI platforms are growing rapidly, traditional search engines remain the dominant source of website traffic. Traditional search still drives a large share of global web referrals, while AI engines such as ChatGPT currently generate only a small fraction of visits.

Ultimately, because Ahrefs combines AI visibility research with a full SEO toolkit, teams can investigate opportunities and implement improvements within a single platform.

A standalone AI visibility tool like Profound can show whether a brand appears in AI responses. However, turning those insights into actionable improvements typically requires additional tools for keyword research, technical SEO and competitor analysis.

7. Ahrefs offers more flexible scaling for AI prompt monitoring

Both Ahrefs and Profound allow users to track how their brand appears in AI responses for particular queries. However, the two platforms approach this type of monitoring in different ways. Profound uses a fixed prompt limit model tied to pricing tiers. For example:

These prompts are then executed across supported AI engines to generate visibility reports.

Brand Radar takes a different approach. Instead of allocating a fixed number of prompts, it measures monitoring activity through a system of “checks.”

Each check represents a prompt being executed on a particular AI platform and location. Users can also control how frequently prompts are run — for example daily, weekly or monthly — allowing teams to manage how quickly checks are consumed.

Additional monitoring capacity can be added through transparently priced packages, for example:

This usage-based model allows organizations to scale monitoring gradually rather than upgrading to entirely new plan tiers every time they want to track more prompts.

Brand Radar also supports prompt checks across around 180 countries, while Profound supports 60 markets.

Reasons to use Profound over Ahrefs

1. Profound estimates demand for AI prompts

A distinctive capability of Profound is its Prompt Volumes dataset, which attempts to estimate how frequently particular prompts are used inside AI answer engines.

To build this dataset, Profound licenses anonymized prompt data from large panels of AI platform users. These prompts are aggregated using probabilistic statistical modeling to estimate how often similar questions occur across the wider population of AI users.

This allows Profound to show demand estimates for AI prompts (in a similar way to how SEO tools provide keyword search volume).

Within the interface, users can explore:

In practice, this helps teams identify which questions appear to attract meaningful demand within AI tools, not just which prompts mention their brand.

Brand Radar approaches demand signals differently. Instead of estimating prompt frequency from AI conversations, it analyzes prompts derived primarily from Google search queries and related questions. The platform also includes a ‘Search demand’ section that surfaces relevant search queries connected to monitored topics.

However, these signals are based on traditional search demand, rather than estimates of how often prompts are asked inside AI platforms.

As a result, the two tools answer slightly different questions:

For organizations interested in understanding emerging conversational demand within AI tools themselves, Profound’s dataset arguably provides more useful early signals.

2. Profound lets you monitor a wider range of AI platforms

Another advantage of Profound is its ability to track brand visibility across a broad set of AI answer engines. On the highest tier, the platform can show you how brands appear across 10 leading AI engines:

By comparison, Ahrefs’ Brand Radar currently focuses on a smaller group of 6 AI systems: ChatGPT, Google AI Overviews, Google AI Mode, Gemini, Copilot and Perplexity. This means that the most widely used AI interfaces are covered, but the scope is still considerably narrower than Profound’s.

3. Profound analyzes AI-driven shopping results

Profound includes a shopping analysis module that tracks how products appear and are ranked within AI-generated shopping responses.

When users ask product-related questions inside AI tools — for example “best running shoes for marathon training” or “top high-performance sportswear brands” — AI systems increasingly generate structured product recommendations. Profound analyzes these responses to identify which products appear most frequently, and how their visibility compares with competing items.

Within the shopping interface, users can explore:

In addition to overall product visibility, Profound also analyzes which product attributes appear most prominently in AI shopping recommendations. These attributes can include factors such as comfort, breathability, price range or performance characteristics.

The platform also provides placement tracking metrics, competitive benchmarking data, and retailer mapping tools designed to help ecommerce teams understand how AI platforms recommend products.

Profound also offers ‘Agent Analytics for Shopify,’ which monitors when AI answer engines access a Shopify store, and which product pages they visit during product research.

This feature is powered through an integration with Nostra, a platform that detects visits from AI agents and answer engines. Once connected to a Shopify store, it can reveal which product pages AI systems are reviewing as part of their research and recommendation processes.

These capabilities are likely to be particularly useful for ecommerce brands and marketplace sellers operating in competitive product niches — and there’s not really an equivalent feature set provided by Ahrefs yet.

4. Profound tracks how AI crawlers access your website

Many AI systems use specialized bots to retrieve content that may later appear in AI-generated answers. Examples include crawlers such as GPTBot and ClaudeBot.

And Profound lets you analyze how these AI crawlers interact with your website. Using server-level log analysis, Profound’s “Agent Analytics” feature can show you:

All this gives you a greater understanding of how AI systems discover and access your content. For example, you might notice that certain documents or page types are frequently accessed by AI crawlers, suggesting those pages may influence AI-generated responses.

(This, in turn, might prompt you to create more of them.)

As for Ahrefs, its Site Audit feature can diagnose technical SEO issues that might make it harder for your site to be crawled in general — but it doesn’t currently provide visibility into traffic from AI bots.

5. Profound is built specifically for prompt monitoring

Profound is designed specifically as a prompt monitoring platform, allowing organizations to track how their brand appears for specific AI queries over time.

Users typically create projects that monitor prompts related to their brand, competitors or product categories. These prompts are then executed regularly across supported AI systems, allowing teams to track how AI-generated responses evolve.

Because the same prompts are repeatedly tracked, organizations can monitor metrics easily over time. These include:

Prompts can also be grouped into broader themes — for example product attributes, brand perception or industry topics — allowing teams to monitor performance across categories of AI queries rather than individual prompts alone.

Ahrefs’ Brand Radar also provides prompt tracking capabilities, allowing users to create custom prompts and analyze the responses generated by AI platforms.

However, prompt tracking works rather differently in Ahrefs. When you click on a tracked prompt in Ahrefs, you’re essentially given a ‘snapshot’ of what’s being cited — but with Profound, the data you get is more like rank tracking in SEO. You immediately get an idea of whether your brand is being mentioned, and can track its performance over time.

In addition, custom prompt monitoring in Ahrefs requires a separate add-on, which sits on top of the base Brand Radar subscription.

As a result, organizations that want to build structured monitoring around a defined set of queries may find Profound’s prompt-centric architecture better suited to that task.

6. Profound analyzes brand narratives and sentiment in AI answers

Profound provides tools designed to analyze how AI systems describe and evaluate brands, helping organizations understand not just where AI tools are mentioning brands, but what they think of them.

Themes relating to product quality, innovation, pricing or durability can all be identified by Profound, and classified as positive or negative sentiment signals.

These themes are displayed alongside example AI responses (see my screenshot below for an example).

For companies concerned with brand reputation within AI answers, this type of analysis can provide useful insight.

Brand Radar primarily measures visibility and citation patterns; this lets you see how often brands appear and which sources AI systems cite — but doesn’t give insights into how your brand is being perceived and presented by these systems.

Ahrefs vs Profound: pricing

Pricing for Ahrefs and Profound is structured quite differently, reflecting the different roles the tools are designed to play.

Profound operates as a dedicated AI visibility monitoring platform, while Ahrefs provides AI monitoring through its Brand Radar feature (a tool that can be used within, or outside of, the general Ahrefs SEO platform).

Profound currently offers three main plans.

Its Starter plan costs $99 per month and allows monitoring in ChatGPT only. It facilitates tracking for 50 prompts and up to 1,500 AI responses per month.

Its Growth plan, priced at $399 per month, expands coverage to three AI platforms — ChatGPT, Perplexity and Google AI Overviews — and increases monitoring limits to 100 prompts and 9,000 monthly responses.

For access to the platform’s full capabilities, however — including monitoring across a wider range of AI systems and tracking larger prompt sets — users need to move to Enterprise plans, which come with custom, negotiated pricing.

Ahrefs’ Brand Radar can be accessed in two ways.

First, it can be used as an add-on to a standard Ahrefs subscription (starting at $129 per month), giving users access to Brand Radar alongside Ahrefs’ wider SEO toolkit.

Alternatively, Brand Radar can be purchased as a standalone product.

Pricing for Brand Radar starts at $199 per month per AI platform, or $699 per month for access across all supported platforms. This full plan includes 2,500 prompt checks per month. If additional prompt monitoring is required, Ahrefs offers custom prompt check packages, starting at:

Each time a prompt is executed on a specific platform, it counts as one check.

Profound’s pricing is based primarily on fixed limits around prompt monitoring, response volume and platform coverage, with the lower tiers supporting relatively small monitoring limits.

Ahrefs’ model is somewhat more modular. While there are core subscription tiers, the check-based system allows teams to increase or decrease monitoring volume more flexibly depending on how intensively they want to track prompts.

For some organizations — particularly agencies or teams running multiple campaigns — that flexibility may make it easier to scale monitoring activity up or down over time.

Ahrefs vs Profound: the verdict

Both Ahrefs and Profound bring valuable capabilities to the emerging category of AI visibility tools.

Profound stands out in situations where structured prompt monitoring is the main priority: it does a better job of this than Ahrefs. Unlike Brand Radar, its prompt-tracking model makes it straightforward to track specific queries over time, and features such as prompt demand estimates, AI shopping analysis and crawler analytics offer unique insights into how AI systems surface brands and products.

Profound also wins when it comes to brand sentiment analysis — unlike Ahrefs, it gives you considerable data on how AI tools perceive and present brands.

The key reason to use Ahrefs probably boils down to the fact that it doesn’t just give you AI visibility data — it is a long-established SEO platform that gives you a host of data and tools that help you optimize your site for search results too. And because SEO remains at the heart of AI visibility — authoritative, well-linked sites crop up far more often in AI-generated responses — these SEO features are incredibly important.

So in other words, it’s best to consider Ahrefs as a ‘best of both worlds’ option: it gives you the data you need to get a good sense of how you’re performing in AI tools, and the features you need to get your content performing in the first place. It also gives you access to more data — its prompt library is considerably bigger than Profound’s, and it facilitates tracking in more countries too.

Profound has a much more narrow focus — prompt tracking over time — and it’s currently better at that than Ahrefs.

If you have any questions about Ahrefs or Profound — or you’d like to share your own thoughts on either platform — feel free to leave a comment below.

Alternatives to Ahrefs and Profound

If neither Ahrefs nor Profound feels like the right fit for your needs, there are several other platforms beginning to offer tools for monitoring AI visibility and conversational search performance. Three notable options are Semrush, SE Ranking and Similarweb.

Semrush

Semrush has also begun expanding into AI visibility analysis through its Semrush One platform. This product combines traditional SEO datasets with tools designed to monitor how brands appear in AI-generated answers.

Because Semrush sits on top of a large SEO data infrastructure — including keyword research, backlink analysis, rank tracking and site auditing tools — it offers a similar “AI visibility plus SEO toolkit” model to Ahrefs.

You can learn much more about Semrush in our full ‘Semrush review,’ our ‘Ahrefs vs Semrush’ comparison, and our ‘Semrush pricing’ post.

SE Ranking

SE Ranking recently introduced an AI Visibility Tracker designed to monitor how brands appear in AI-powered search environments. The tool tracks visibility across AI-generated answers and Google’s AI Overviews, helping teams understand how their content surfaces in conversational search results.

Compared with enterprise-focused platforms like Profound, SE Ranking is generally positioned as a more affordable option for smaller SEO teams and agencies.

You can learn more about SE Ranking in our ‘SE Ranking vs Semrush’ and ‘SE Ranking vs Moz’ comparisons.

Similarweb

Similarweb has also begun expanding its analytics platform to include insights into AI-driven traffic sources. Its tools can identify visits originating from AI platforms and help organizations understand how generative search environments contribute to website traffic.

While Similarweb focuses primarily on digital market intelligence rather than prompt monitoring, its data can still provide useful insight into how AI platforms influence online discovery and referral patterns.

You can learn more about Similarweb in our full Similarweb review and our Similarweb vs Semrush comparison.