GetXEO vs Ahrefs Brand Radar

Brand Radar has the biggest measurement surface in this comparison, and the suite around it audits your site and grades your drafts. It also sits inside a toolset most search teams already pay for, which makes it the cheapest way to start. Two links in the citation chain stay open. Nothing decides the shape of the set you publish, and nothing writes the pages. Those two are the comparison.

Arjun Shenoy

Co-Founder and CPO at GetXEO

Evaluates AI visibility tooling as part of the product role, and has run this category comparison across ten platforms.

31 August 2026 · 11 min read · 2,312 words · 10 cited sources

About the teamLinkedIn

Read the bottom two rows first, because this rival is stronger there than anything else in the category. The suite runs its own site crawler and its own bot logs, so the delivery row is close to a draw, and the measurement row is not close at all. The argument sits in the middle of the table.

Brand Radar tracks visibility two ways. The index maps how brands appear across a pool of prompts already collected, so there is no setup and you can look up any brand or category on the first day. Custom prompts do the opposite: you define the buyer questions and data accumulates from the moment tracking starts.

The index is the headline. Ahrefs takes real queries from its keyword database, expands them into natural questions, then runs the result through each platform and stores every response. That is 473 million monthly prompts across AI Overviews, AI Mode, ChatGPT, Perplexity, Gemini and Copilot, re tested monthly on a ninety day reporting window. Custom prompts add Claude and run as often as daily.

Four AI visibility metrics come out: mentions, citations, share of voice within your topic set, and estimated impressions weighted by the real search volume behind each prompt. Alongside them the suite reports which pages AI sends traffic to, and which crawlers visited and when.

Custom prompts are included in every paid plan with a daily quota, from five tracked prompts on the entry plan to twenty on the top self serve plan, with larger packages sold separately. Every prompt is checked daily on each selected platform.

GetXEO reads the brand first, crawling the domain and building a profile every downstream writer reads. It then derives the question universe and curates twenty five queries for each of the three pillars, mapped back to the keyword or question each came from.

Those queries produce one composite score. The dashboard carries AEO, GEO and SEO sub scores, model citation rates and the change since the last scan. AEO polls answer engines, GEO covers AI summarized search and weights paragraph position, and SEO tracks the classic result page alongside AI Overviews.

Three technical audits follow, one per pillar. The GEO audit checks entity declarations, Organization schema, semantic HTML and knowledge graph signals, and all three roll into a composite score with a page by page heat map, with fixes as a checklist a developer can work through.

Then the part the suite does not do. Fifty blogs a month on the single workspace plan, produced as one interconnected mesh and sequenced on a twelve week calendar that also carries refreshes and technical fixes.

This is the most useful disagreement between the two products, and Ahrefs states its own side of it plainly.

The index is built by taking real search queries and expanding them into questions. That is a sound method and it produces enormous coverage, because search demand is measurable and prompts are not. It also inherits what search demand knows. Ahrefs writes that the index works best for established brands or topics with meaningful search demand, and may have limited coverage where there is little or none.

That limit lands hardest exactly where a new entrant needs help. A category nobody searches by name yet is a category the index sees thinly, and those are the buyers describing a problem to an engine rather than typing a term into Google.

Ahrefs answers this with custom prompts, which is the right answer. The constraint is how many you get: five on the entry plan and twenty on the top self serve plan before buying more. GetXEO tracks a hundred and fifty questions per workspace as the standard inclusion, derived from modeling buyer behavior rather than from volume. Neither approach measures AI visibility without judgment. They just put the judgment in different places.

• Scale nothing here can match. 473 million monthly prompts across six AI surfaces, with responses stored back to 2025 and no domain cap, so you can look up a competitor or a whole category before you have set anything up
• It is already in the toolset. Custom prompts come built in with every paid plan, sitting beside rank tracking and Search Console data, so AI visibility arrives as another tab rather than another contract
• Delivery is genuinely covered. A site audit checking more than a hundred and seventy issues, plus bot analytics showing which AI crawlers read which pages and when. That audit predates AI search by years, which is why it is deeper than the crawler checks most of this category ships
• It is honest about its own method. Ahrefs publishes how the index is built, what the reporting window is, and where coverage thins out. That is rarer in this category than it should be

Three operational rows separate the two products, and they run in both directions.

GetXEO runs no prompt index and does not claim one. Ahrefs sells a content editor with a monthly document allowance, so the last row is not a gap on its side, it is a different unit: one grades a draft you wrote, the other hands you the article. Larger prompt packages are sold on top of every plan.

• The whole chain in one place. Question set, mesh design, extraction craft, technical audit and measurement together, so no step falls to a second product or to nobody in particular
• One composite across three layers. AEO, GEO and SEO roll into a single figure with model citation rates and the change since the last scan, rather than an AI tab beside a ranking tab
• Questions that do not need search volume. A hundred and fifty tracked questions per workspace, derived from modeling how a buyer researches, which is the case a thin search footprint cannot answer
• Output that connects. A designed mesh on a sequenced calendar, so authority accumulates across the whole set instead of starting again at every URL

One limit is worth knowing before committing. Nothing GetXEO publishes approaches the breadth of a category wide prompt index.

The edge here is not measurement, and claiming otherwise would be silly. It is the two links between knowing and shipping.

The structure. Brand Radar tells you which topics and pages engines pull from. It does not decide what set of pages you build next, or how they relate. A designed mesh compounds because each post supports the others, and a report cannot supply that shape however good the report is.

The craft. This is the closest of the three, and worth stating carefully. Ahrefs ships an editor that colors sentences by the subtopics they cover to lift AI visibility, and grades a draft against the pages already ranking. That is real craft work on the page in front of you. The difference is where it starts: it improves a draft somebody already wrote, measured against what already ranks. Pages carrying figures, citations and quotes get named far more often, and pages get their highest citation rates in their first week live, so the specification has to exist before the draft does. It matters because almost all buyers who research with AI check what it tells them before trusting it, and the cited page has to survive a human reading it next.

And the questions, which decide both. A set built from search volume is the best available proxy, and it is a proxy. A set built from modeling behavior is a judgment, and we say so. The difference is that one of them thins out precisely where a brand has no search footprint yet.

One thing we will not argue is that the measurement is worse. about half of B2B buyers now start vendor research inside AI tools, and a 473 million prompt index is a real answer to that. It is simply not the whole chain.

GetXEO fits a marketing team that needs the pages built, not only the gap named. It starts at one thousand dollars a month list, half that with the discount on the page, and nothing free underneath. The suite charges a paying team nothing extra for its audit, its bot report or its custom prompts. Brand Radar fits a search team that already owns the suite and wants its AI visibility number sitting next to its ranking number. Each AI operator crawls under its own user agent, and OpenAI picks up a robots change in about a day. If crawler access is the open question, the suite answers it today, with the note that its bot analytics is in beta and reads through a Cloudflare integration.

All were published or last updated within the past twelve months. A competitor page appears only as a record of that vendor’s own published terms.

1. Machine Relations, AI search citation factors research
2. MarketScale, on where B2B software discovery starts in 2026
3. MarketScale, on the TrustRadius finding that buyers fact check AI
4. OpenAI, the crawler and user agent documentation
5. Cloudflare, the AI crawler bot reference naming each operator, category and user agent
6. Ahrefs, the published Brand Radar page, read 27 August 2026
7. Ahrefs, the published Custom Prompts page and plan quotas, read 27 August 2026
8. Ahrefs, the published Bot Analytics page
9. Ahrefs, the published Site Audit page
10. Ahrefs, the published AI Content Helper page, read 27 August 2026

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