Ahrefs Brand Radar Tutorial: Track Your Brand Visibility Across AI Search Engines
Why AI search visibility is hard to measure without a tool
With traditional SEO, visibility is legible: you have a keyword, you have a rank position, you have a traffic estimate. AI search strips that structure away. When a user asks ChatGPT for waterproof hiking boot recommendations, your brand either appears in the answer or it does not. There is no position 4.
That makes competitive benchmarking genuinely difficult. You can manually ask AI platforms questions and note whether you appear, but that is not scalable and gives you no data on how often your competitors are recommended, which platforms mention them, or whether the trend is moving in your favor.
Ahrefs Brand Radar is the tool Ahrefs built to make this measurable. It launched January 21, 2026, added Grok as a seventh platform on April 24, 2026, and now pulls from a database of 260 million monthly prompts to tell you where your brand appears in AI-generated answers and where your competitors appear instead.
What the tool covers
Brand Radar currently tracks seven AI platforms: ChatGPT, Gemini, Perplexity, Copilot, AI Overviews, AI Mode, and Grok. It also covers YouTube, TikTok, and Reddit, which increasingly appear in AI-powered search results as cited sources.
The database of 260 million prompts comes from real user queries collected by Ahrefs across various channels. The tool matches your brand name against the AI-generated responses to those prompts and reports how often you appear. Competitor data uses the same methodology, so the comparison is apples-to-apples.
Access requires the Standard plan at $249/month or higher. Individual AI platform indexes are $199/month each; a bundle of the original six costs $699/month, with Grok priced separately as the seventh addition. Most brands start with one or two platforms rather than buying the full bundle.
For e-commerce, Perplexity and ChatGPT are typically the highest priority; they handle more product and purchase-intent queries than the others. If your primary markets are in Europe, Copilot’s share is worth including.
Setting up custom prompt tracking
The default Brand Radar setup is passive: you enter your brand name and the tool searches the existing 260 million prompt database for mentions. That is useful as a baseline, but it only tells you how often your brand appeared in queries that real users happened to ask.
Custom prompt tracking flips this. You define the specific queries you want to monitor — questions that are relevant to your product category and target customer — and Ahrefs actively queries the AI platforms with those prompts on a recurring basis, recording whether your brand appears in the responses.
To set it up:
- Open Brand Radar and select the AI platform you want to track (for example, ChatGPT)
- Navigate to the Custom Prompts or Prompt Sets section
- Create a prompt group named after the category or market you’re targeting (for example, “US waterproof hiking boots”)
- Enter the actual queries you want tracked. Write them the way a real customer would ask: “best waterproof hiking boots under $200,” “hiking boots that don’t leak,” “hiking boots for wide feet waterproof”
- Save the group. Ahrefs will run these prompts periodically and record your brand’s appearance rate
The phrasing matters more than you’d expect. “Waterproof hiking boots” as a two-word keyword phrase behaves very differently in an AI context from “what are the best waterproof hiking boots for someone who hikes in the Pacific Northwest.” Write queries as natural questions, not SEO keyword strings.
You can build separate prompt groups for different markets (US, UK, EU) with phrasing adapted to local vocabulary and price points. This lets you see whether your AI visibility differs by geography even when you’re selling the same products.
Reading the AI Share of Voice report
The core output from Brand Radar is an AI Share of Voice figure: within your defined set of prompts, what percentage of all brand mentions in AI responses belongs to your brand versus competitors?
If your 50 custom prompts generated 120 total brand mentions across ChatGPT responses, and your brand appeared 18 times, your Share of Voice is 15%. The report shows the same breakdown for competitor brands in the same query set.
A few ways to work with this data:
Track your own trend. The most useful signal is month-over-month movement in your Share of Voice. If it rose from 12% to 15% after you published a cluster of comparison articles, that’s evidence your GEO content strategy is working on that platform. If it dropped, check which competitor’s numbers went up.
Find prompts where competitors appear and you do not. Brand Radar shows individual prompt-level data: you can see exactly which queries are generating competitor recommendations while you’re absent. Each of those is a concrete content gap: a topic where you need to publish something substantive enough for AI systems to cite.
Compare across platforms. If your Share of Voice on ChatGPT is 15% but only 6% on Perplexity, that tells you something specific about the information sources Perplexity is drawing from. Perplexity heavily cites news coverage, user reviews, and Reddit discussions; a low score there often means insufficient third-party coverage rather than a content problem on your own site.
Look at mention position. Being mentioned first in an AI response and being mentioned sixth as an “also consider” are not equivalent. If you’re frequently appearing late in responses, the signal is that you have some visibility but not enough authority — which usually points to thin backlink profiles from authoritative sources rather than a content volume problem.
Acting on what you find
Brand Radar is a measurement tool. It shows you the gap; closing the gap is your job.
The most direct use of the data is content gap identification. When a competitor gets recommended for “hiking boots for plantar fasciitis” and you do not appear at all, look at what the AI is actually citing when it recommends them. Perplexity typically shows sources inline; for ChatGPT you may need to run the query manually and inspect the response. The content types that AI systems cite most often in product recommendation contexts are independent comparison articles, detailed product reviews from niche publications, and high-vote Reddit threads. If your brand lacks coverage in those formats for specific queries, that’s where to focus content investment.
For brands doing paid PR or media outreach, Brand Radar provides a feedback loop that was previously unavailable. You can test whether a coverage campaign in outdoor media publications actually moves your Perplexity Share of Voice over the following two months.
One limitation worth knowing: Brand Radar is not real-time. There is a lag between when content is published and when it registers in the AI indexes that Ahrefs tracks. It works well for monthly or quarterly trend analysis, but you cannot use it to measure the impact of a single article published last week.
Integrating Brand Radar into a regular workflow
The practical workflow for most e-commerce brands is a monthly review: pull the Share of Voice report, compare to the prior month, note which prompt groups moved and which didn’t, identify two or three content gaps to address in the next publishing cycle.
Quarterly, revisit the prompt groups themselves. The questions your customers ask change over time, and prompts that were relevant six months ago may no longer reflect how people are actually searching. Add new questions that reflect emerging product concerns or use cases; retire prompts that generate no data.
If you’re managing multiple brands or markets, the custom prompt group structure lets you keep each one separate while reporting on all of them from the same account. That’s particularly useful for agencies running GEO programs for e-commerce clients who want to show AI visibility improvements alongside traditional SEO metrics.
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