Ahrefs for AI Visibility: Brand Radar Review & What It Still Can't Track (2026)

Traffic from AI platforms increased 527% year over year according to AllAboutAI's 2025 visibility statistics, and marketers are scrambling to understand where their brand appears in AI-generated responses. Ahrefs responded with Brand Radar, a product that tracks brand mentions across 6 AI platforms using 260M+ monthly prompts. But after testing Brand Radar against dedicated AI visibility tools and analyzing its structural methodology, a critical question emerges: does tracking what already happened actually help you win AI citations, or do you need tools that predict where AI will retrieve content before searches occur?

This review is an honest assessment. Ahrefs remains one of the most powerful traditional SEO platforms available, and Brand Radar represents a genuine effort to bridge the gap between legacy SEO and AI visibility. But as 60% of searches now end without clicks, understanding precisely what Brand Radar can and cannot do has become essential for any marketing team evaluating their Ahrefs visibility strategy.

What You'll Learn

• What Ahrefs Brand Radar actually tracks across its 6 AI platform indexes, including 2026 pricing ($199/mo per index or $699/mo for all platforms)
• Why Brand Radar's snapshot-based methodology produces documented accuracy gaps (ChatGPT reported 3 mentions vs 123 actual in independent testing)
• How query fan-out creates an 88% "dark query" blindspot that no backward-looking tool can see
• The difference between backward-looking measurement (Ahrefs) and forward-looking citation prediction (Ekamoira's 9 proprietary models)
• How a product-plus-service hybrid model with a 30-day performance guarantee compares to paying $828-$1,148/month for passive tracking
• Head-to-head feature and pricing comparison of Ahrefs Brand Radar vs 8+ dedicated AI tracking tools

Metric	Value	Source
Brand Radar Monthly Prompts	260M+	Ahrefs Brand Radar, Feb 2026
AI Platforms Covered	6 (AI Overviews, AI Mode, ChatGPT, Copilot, Gemini, Perplexity)	Ahrefs Brand Radar, Feb 2026
Brand Radar All-Platform Bundle	$699/month (on top of base plan)	Ahrefs Brand Radar, Feb 2026
Total Minimum Cost (Base + Bundle)	$828-$1,148/month	EWR Digital, Feb 2026
ChatGPT Tracking Accuracy (Writesonic Test)	3 reported vs 123 actual mentions	Writesonic, Jan 2026
Perplexity Tracking Accuracy (Writesonic Test)	6 reported vs 212 actual mentions	Writesonic, Jan 2026
Industry Average AI Tool Cost	$337/month	Rankability, Jan 2026
AI Traffic YoY Growth	527%	AllAboutAI, 2025
AI-Cited Content Freshness Advantage	25.7% fresher than Google SERP results	Ahrefs Study, Jul 2025

What Does Ahrefs Brand Radar Actually Track in 2026?

Ahrefs Brand Radar is an add-on product that monitors brand visibility across 6 AI platforms: Google AI Overviews, Google AI Mode, ChatGPT, Perplexity, Gemini, and Copilot. According to the official Brand Radar landing page, the tool draws from 260M+ monthly prompts to produce brand visibility scores, share of voice percentages, and brand coverage metrics. These prompts are described by Ahrefs as "search-backed prompts, not synthetic ones," meaning they come from real search behavior patterns rather than artificially generated queries.

The core methodology works through timed snapshots. Brand Radar runs its prompt library against each AI platform at scheduled intervals and records which brands appear in the generated responses. For Google AI Overviews, according to Rankability's January 2026 review, "users note its Google AI Overview tracking provides 'a realistic figure' with valuable directional insights." The tool also provides historical data that dedicated AI tracking tools often lack, as confirmed by MRS Digital who noted that "Ahrefs shows historical data" while competitors like Peec and Otterly cannot access historical data.

Brand Radar's genuine strengths lie in its integration with Ahrefs' broader SEO platform. Users who already pay for Ahrefs get the benefit of connecting AI visibility data with backlink analysis, keyword research, and site audit capabilities. For teams already embedded in the Ahrefs ecosystem, Brand Radar provides a single-dashboard view of both traditional and AI visibility. The Ahrefs Help Center confirms that "Any Indexes that are in beta are free to all paid subscribers," which means early adopters can test new platform coverage without additional cost.

Key Finding: Brand Radar covers the broadest range of AI platforms (6 indexes) among legacy SEO tools. Its integration with Ahrefs' backlink and keyword databases provides context that standalone AI tools lack.

How Much Does Ahrefs Brand Radar Actually Cost in 2026?

Ahrefs Brand Radar pricing in 2026 follows a layered model that significantly increases the total cost beyond what many marketers initially expect. According to the official Ahrefs pricing, Brand Radar AI Indexes are available at $199/month per individual AI platform index or $699/month for access to all 6 platforms bundled together. However, Brand Radar is an add-on that requires an active Ahrefs base subscription.

According to EWR Digital's February 2026 pricing analysis, the base Ahrefs plan starts at $129/month. This means the total minimum cost to access Brand Radar with all 6 AI platform indexes is $828/month ($129 base + $699 bundle), scaling up to $1,148/month or more on higher-tier Ahrefs plans. As EWR Digital concluded, the "main limitation is prohibitive cost for most businesses and agencies, coupled with documented accuracy issues."

Additionally, as MRS Digital documented, "you have to pay more money to track prompts on an already paid-for add-on." This means that if you want to monitor specific custom prompts beyond Brand Radar's default prompt library, there are additional costs on top of the base plan and the Brand Radar add-on fee.

For context, the industry average cost for a dedicated AI visibility tracking tool is $337/month according to Rankability's January 2026 survey. That means Ahrefs Brand Radar at full deployment costs roughly 2.5 times the industry average for AI tracking alone, before factoring in the value of the broader Ahrefs SEO toolkit.

Tool / Configuration	Monthly Cost	AI Platforms Covered	Custom Prompt Tracking
Ahrefs Base Only	$129/mo	0 (beta indexes only)	No
Ahrefs + 1 AI Index	$328/mo	1	Additional cost
Ahrefs + All 6 Indexes	$828-$1,148/mo	6	Additional cost
Peec AI (Professional)	~$199/mo (€199)	Multi-platform	Included (100 prompts)
Otterly AI (Growth)	$189/mo	Multi-platform	Included (100 prompts)
Ekamoira (Lifetime)	$79 one-time	3 (Google AI, ChatGPT, Perplexity)	Included
Ekamoira (Pro)	$49/mo	3	Included (50 prompts)
Profound	Mid-four figures/mo	Multi-platform	Included

Pro Tip: If you are already paying for Ahrefs and need directional AI visibility data, start by testing the free beta indexes before committing to the $699/month bundle. According to the Ahrefs Help Center, beta indexes are available to all paid subscribers at no additional cost.

Why Does Brand Radar's Snapshot Methodology Create Accuracy Problems?

The most widely documented issue with Ahrefs Brand Radar is the accuracy gap between what it reports and what actually happens across AI platforms. According to TryAnalyze.ai's January 2026 review, "the cause lies in how the tool captures AI data: instead of monitoring live queries, it uses a static prompt library and timed snapshots." The same review confirmed that "the same prompt can produce different AI outputs every few hours," meaning any single snapshot represents only one possible version of reality.

Independent testing from Writesonic's January 2026 Brand Radar review revealed the scale of this accuracy problem. When Writesonic tested Brand Radar's ChatGPT tracking module against their own known brand presence, Brand Radar reported only 3 mentions while manual verification found 123 actual mentions. Perplexity tracking showed a similar discrepancy: Brand Radar reported 6 mentions globally while the actual count was 212 mentions. Writesonic's review documented that Brand Radar offers "no per-query context visibility" and "no sentiment or quality scoring for brand references."

This is not a minor calibration issue. A tool that reports 3 mentions when 123 exist is capturing roughly 2.4% of actual ChatGPT brand visibility. For teams making strategic content decisions based on this data, the gap between reported and actual visibility could lead to misallocated budgets and missed opportunities.

The Ahrefs Help Center confirms that People Also Ask questions within Brand Radar are "prompted once per month," which means prompt-level data refreshes on a monthly cycle. For a landscape where AI responses can shift within hours, monthly refresh rates create significant blind spots. As Search Engine Land reported in October 2025, "LLM interactions are conversational and variable" and "people rephrase questions in different ways within single session," making static prompt libraries inherently limited.

Watch Out: Brand Radar's ChatGPT module reported only 3 mentions for a brand that actually had 123 mentions across ChatGPT responses. That is a 97.6% underreporting rate. Before making strategic decisions based on Brand Radar data, verify a sample of results manually.

For a deeper understanding of how ChatGPT actually selects which sources to cite, see our complete guide to ChatGPT SEO ranking factors. If you need better Perplexity-specific tracking, explore our guide to dedicated Perplexity rank tracking tools.

What Are Dark Queries and Why Can't Brand Radar See Them?

Dark queries represent the single largest blindspot in Ahrefs Brand Radar's methodology, and they explain why backward-looking AI tracking tools structurally cannot capture the full AI retrieval surface. When a user submits a query to an AI search platform like Google AI Mode, ChatGPT, or Perplexity, the AI system does not simply look up that exact query. As iPullRank documented in their December 2025 research, "rather than searching for a single exact match to a user's question, modern large language models (LLMs) decompose complex queries into multiple smaller, interconnected sub-queries."

This process, known as query fan-out, means that a single user query generates multiple simultaneous retrieval sub-queries. These sub-queries are routed to different data sources, and the AI system synthesizes the results into a single response. The critical insight is that the vast majority of these sub-queries have zero Google search volume. No human types them into a search bar. They exist only within the AI system's internal retrieval pipeline. These are dark queries: invisible to every traditional keyword research tool including Ahrefs' keyword database.

Ekamoira's internal analysis of query fan-out patterns across Google AI Mode, ChatGPT, and Perplexity reveals that approximately 88% of the AI retrieval surface consists of dark queries with zero Google search volume. This means that even if Brand Radar's 260M+ prompt database perfectly captured every human-typed query, it would still miss the vast majority of retrieval events that determine which brands get cited.

According to WordLift's research on query fan-out, content optimized for conversational queries achieves 40% higher coverage in fan-out simulations compared to content optimized only for traditional keyword targets. This finding directly explains why brands that perform well in traditional SEO metrics can still be invisible in AI responses: their content addresses the queries humans type, but not the sub-queries AI systems generate.

For the complete research behind these findings, see our query fan-out research reveals 88% of brands miss AI citations.

Key Finding: 88% of the AI retrieval surface consists of "dark queries" with zero Google search volume. These sub-queries are generated by AI platforms during query fan-out and are invisible to traditional keyword tools, including Ahrefs' 260M+ prompt database.

How Does the Query Fan-Out Framework Predict AI Citations Before They Happen?

The fundamental distinction between Ahrefs Brand Radar and Ekamoira's approach is the difference between backward-looking measurement and forward-looking prediction. Brand Radar tells you which prompts mentioned your brand after the fact. Ekamoira's Query Fan-Out Estimator simulates where AI platforms will retrieve content before searches occur, then generates a citability-scored content roadmap to capture those retrieval opportunities.

The Query Fan-Out Estimator works by simulating query decomposition across all three major AI search platforms: Google AI Mode, ChatGPT, and Perplexity. Each platform decomposes queries differently, routes sub-queries to different data sources, and applies different citation selection criteria. The estimator runs this simulation using 9 proprietary models:

1. CASO (Composite AI Search Opportunity, 0-100) scores overall opportunity by weighting volume, growth trajectory, coverage breadth, and commercial value.
2. TASS/FME (Total AI Search Surface / Fan-Out Multiplier Effect) estimates the total retrieval volume by multiplying core queries by the fan-out factor and query stability coefficient.
3. DQV (Dark Query Volume) quantifies the hidden volume from zero-volume sub-queries using median core volume, intent weighting, and a 0.15 coefficient.
4. ROI (Retrieval Opportunity Index) calculates the expansion ratio between core queries and total retrievable surface.
5. CPFI (Cross-Platform Fan-Out Index) measures opportunity breadth across Google AI Mode, ChatGPT, and Perplexity with platform-specific weights.
6. ICI (Intent Concentration Index) uses Shannon entropy to measure query intent diversity across commercial, informational, navigational, and transactional categories.
7. CPM (Citation Probability Model) predicts the likelihood of earning a citation using fan-out coverage ratio and a 1.61 multiplier.
8. FDC (Fan-Out Data Coverage) measures what percentage of the retrieval surface has measurable data behind it.
9. TCG (Topical Coverage Gap) identifies remaining content gaps by calculating the inverse of existing coverage weighted by query stability.

The output is a citability-scored content roadmap where every content angle is ranked by citation probability with specific platform assignments (Google AI Mode, ChatGPT, or Perplexity). Content angles are clustered by 60%+ word overlap, then prioritized into three tiers based on citability score.

This approach fundamentally differs from what Ahrefs Brand Radar can deliver. Brand Radar watches prompts and records mentions. The Query Fan-Out Estimator identifies the sub-queries AI platforms will generate, scores each one for citation probability, and tells you exactly what content to create before your competitors appear in those retrieval results. For a practical implementation guide, see our walkthrough on building a query fan-out strategy from GSC data to AI rankings in 30 days.

TL;DR:

• Ahrefs Brand Radar = backward-looking (measures what happened in past AI responses)
• Query Fan-Out Estimator = forward-looking (predicts where AI will retrieve content before it happens)
• 9 proprietary models simulate cross-platform query decomposition and score content opportunities by citation probability
• Output: citability-scored content roadmap with platform-specific assignments

How Does Ahrefs Brand Radar Compare to Dedicated AI Tracking Tools?

When evaluating Ahrefs visibility products for marketers, the critical question is whether Brand Radar competes with dedicated AI visibility tools or occupies a different category entirely. Based on independent reviews from MRS Digital (January 2026), Writesonic (January 2026), and TryAnalyze.ai (January 2026), the best AI search ranking trackers compared to legacy SEO tools like Ahrefs or Semrush show consistent patterns.

MRS Digital's January 2026 comparison tested Ahrefs Brand Radar against Peec AI and Otterly AI directly. Their conclusion: while "Ahrefs Brand Radar has made significant improvements since first tested," Peec AI "pipped into first position with breadth of features" and "Otterly came in close second." Brand Radar was ranked third among the three tools tested.

Feature	Ahrefs Brand Radar	Peec AI	Otterly AI	Ekamoira
AI Platform Coverage	6 platforms	Multi-platform	Multi-platform	3 platforms (Google AI, ChatGPT, Perplexity)
Custom Prompt Tracking	Additional cost	Included	Included	Included
Per-Query Context	No	Yes	Yes	Yes
Sentiment Analysis	No	Yes	Limited	Limited
Dark Query Detection	No	No	No	Yes (fan-out simulation)
Forward-Looking Prediction	No	No	No	Yes (9 proprietary models)
Historical Data	Yes	No	No	Yes
Backlink Integration	Yes (Ahrefs ecosystem)	No	No	No
Done-For-You Service Layer	No	No	No	Yes (Query Intelligence Service)
Content Roadmap Generation	No	No	No	Yes (citability-scored)
Performance Guarantee	No	No	No	Yes (30-day cycles)
Minimum Monthly Cost	$828+ (base + bundle)	~$89 (€89)	$29	$49 (Pro) or $79 lifetime

The comparison reveals a fundamental architectural difference. Tools like Ahrefs Brand Radar, Peec AI, and Otterly AI all track AI mentions after they happen, differing primarily in accuracy, granularity, and pricing. Ekamoira operates in a different category: it combines tracking with forward-looking prediction and an execution service layer. This distinction matters for teams who want to evaluate Ahrefs on model coverage versus platforms that actively predict and create citation opportunities.

For readers wanting a broader comparison across all available tools, see our complete comparison of 12+ AI visibility tools. For teams specifically comparing Ahrefs to Semrush's AI capabilities, read what Semrush doesn't track in AI visibility.

Why Does the Product-Plus-Service Model Change the AI Visibility Equation?

Most top AI visibility tracking platforms vs Semrush and Ahrefs share a common trait: they are pure software products. Users pay a subscription, get access to dashboards, and then must figure out what to do with the data themselves. Ahrefs Brand Radar fits this model. So do Peec AI, Otterly AI, and Profound. The user pays to observe, then either hires an agency to act on the findings or assigns internal resources to execute.

Ekamoira operates as a SaaS platform plus Done-for-You Query Intelligence Service. The platform provides AI visibility tracking, content generation, and Google Search Console integration. The service layer provides strategic execution through the Query Intelligence Service, which takes brands from zero AI visibility to a citability-scored content roadmap within 30 days.

The practical difference becomes clear when you consider the typical workflow. With a tool-only approach, a marketing team pays $828+/month for Ahrefs Brand Radar, reviews the dashboard, identifies that their brand appears in 3% of relevant AI prompts, and then needs to determine which content to create, which platforms to target, and how to optimize for citation. That strategy development and execution either requires in-house expertise or a traditional SEO agency.

According to Abstrakt MG's January 2026 pricing guide, monthly SEO retainers range from $1,000 to $10,000+, with small businesses typically paying $1,000-$3,000/month. And as the same guide confirms, "it takes 6-12 months to see real results." So the true cost of a tool-only approach is the tool subscription plus the agency retainer, with a 6-12 month timeline before results appear.

The Ekamoira alternative costs $79 for lifetime platform access or $49/month for Pro-tier access, with the Query Intelligence Service operating on 30-day performance cycles. The total investment is a fraction of the $828/month Brand Radar subscription alone, before factoring in the agency retainer that Brand Radar's data inevitably requires.

Pro Tip: When calculating the true cost of AI visibility tracking, add the tool subscription cost to the cost of acting on the data. A $699/month dashboard that generates no action is more expensive than a $79 platform paired with a 30-day execution service.

What Is the 30-Day Performance Guarantee and How Does It Work?

Traditional SEO engagements operate on 6-12 month retainers where results are expected gradually over time. The Ekamoira Query Intelligence Service operates on a fundamentally different model: 30-day cycles with a performance guarantee. If AI rankings do not materialize within a cycle, there is no payment for that cycle.

The 30-day pipeline follows 5 stages:

Days 1-2: GSC Seed Extraction. The service connects to the client's Google Search Console data to identify existing ranking signals, content assets, and keyword patterns that can seed the query fan-out analysis.

Days 3-5: Volume Qualification. Extracted seeds are run through DataForSEO volume validation, PAA analysis, and related keyword expansion to identify the addressable search surface.

Days 6-8: Cluster Strategy. Keywords and content angles are clustered by topical relevance, intent alignment, and platform-specific citation patterns. The 9 proprietary models (CASO through TCG) score each cluster.

Days 9-15: Query Fan-Out Analysis. The Query Fan-Out Estimator simulates decomposition across Google AI Mode, ChatGPT, and Perplexity. Dark queries are identified, citability scores are calculated, and content angles are prioritized.

Days 16-30: Citability-Scored Content Roadmap. The final deliverable is a complete content roadmap where every piece is ranked by citation probability with specific platform assignments, priority tiers, and execution guidance.

This contrasts sharply with the tool-only model. Ahrefs Brand Radar provides data that you must interpret and act on yourself. The Query Intelligence Service provides both the analysis and the strategic roadmap, with accountability tied to 30-day performance cycles rather than open-ended retainers.

For teams already using Google Search Console data, see our guide on free and paid methods to track Google AI Mode as a starting point before scaling to a full query intelligence engagement.

What Does Ahrefs Brand Radar Do Well That Dedicated Tools Cannot?

An honest Ahrefs Brand Radar review must acknowledge what the tool does better than its standalone competitors. The most significant advantage is ecosystem integration. Ahrefs Brand Radar is not an isolated product. It connects directly to Ahrefs' backlink index, keyword explorer, site audit, and content explorer tools. No dedicated AI visibility tool offers this level of traditional SEO context alongside AI tracking.

According to MRS Digital's testing, Ahrefs provides historical data for AI visibility trends, which is something Peec AI and Otterly AI cannot currently offer. For teams conducting an Ahrefs content audit alongside AI visibility analysis, the ability to see how brand mentions in AI responses correlate with backlink growth, domain authority changes, and keyword ranking shifts provides analytical depth that standalone tools lack.

The Ahrefs freshness study published in July 2025 is itself evidence of the company's research capabilities. That study analyzed 17 million citations across 7 AI platforms and found that AI-cited content is 25.7% fresher than Google SERP results, with an average age of 1,064 days for AI-cited URLs versus 1,432 days for organic results. ChatGPT showed the strongest preference for new content, citing URLs 393-458 days newer than Google results. The study also found that Google AI Overviews cites content 16 days older on average, making it an exception to the freshness trend.

These research capabilities demonstrate Ahrefs' analytical depth. The same study found that "all AI assistants show a clear preference for fresher content -- except Google's AI Overviews," and "ChatGPT shows the strongest preference for new content." This kind of platform-level insight helps marketers understand the underlying dynamics of AI citation, even if Brand Radar's tracking module has accuracy limitations.

For teams that need Ahrefs share of voice metrics alongside traditional SEO, Brand Radar provides directional value. The Google AI Overview tracking module, in particular, has received more positive reviews than the ChatGPT and Perplexity modules. As Rankability noted, "during its beta phase, Brand Radar is included across all Ahrefs subscription tiers at no additional cost," making it a zero-risk addition for existing Ahrefs customers who want to test AI visibility tracking before committing to the full add-on pricing.

Key Finding: Ahrefs Brand Radar's strongest advantage is ecosystem integration. For teams already using Ahrefs for backlink analysis, site audits, and keyword research, Brand Radar adds AI visibility data without requiring a separate tool. Its Google AI Overview tracking provides "a realistic figure" according to independent testing, and historical trend data is unavailable in most standalone competitors.

What Should You Consider Before Choosing Between Ahrefs and Dedicated AI Tools?

The decision between Ahrefs Brand Radar and a dedicated AI visibility platform depends on where your organization sits in the AI visibility maturity curve. Consider these evaluation criteria when you test Ahrefs visibility against alternatives:

If you already pay for Ahrefs and want directional AI data: Brand Radar's free beta indexes provide a low-risk starting point. You can monitor Google AI Overview coverage and get a general sense of AI visibility without additional spending. This approach makes sense for teams in the early stages of AI visibility strategy who need baseline data before investing in dedicated tools.

If you need accurate ChatGPT or Perplexity tracking: Brand Radar's documented accuracy gaps (3 reported vs 123 actual ChatGPT mentions in the Writesonic test) make it unreliable for these platforms. Dedicated tools like Peec AI and Otterly AI provide more granular, prompt-level tracking with higher accuracy for ChatGPT and Perplexity specifically.

If you need to identify dark queries and predict citation opportunities: No backward-looking tool, including Brand Radar, Peec AI, or Otterly AI, can identify dark queries. Forward-looking query fan-out analysis requires simulation of AI query decomposition, which is structurally different from monitoring prompt responses. Ekamoira's Query Fan-Out Estimator is currently the only platform that simulates cross-platform query decomposition using proprietary models.

If you need both tracking and execution: Pure SaaS tools (Ahrefs, Peec, Otterly) provide dashboards without execution. Ekamoira's hybrid model combines platform access with the Query Intelligence Service, where the 30-day performance guarantee eliminates the risk of paying for data without action.

If budget is the primary constraint: Ahrefs Brand Radar at $828-$1,148/month for full coverage is the most expensive option. Enterprise-grade tools like Profound cost mid-four figures per month according to Rankability's January 2026 review. Mid-market options like Peec AI (~$199/month for 100 prompts) and Otterly AI ($189/month for 100 prompts) according to Writesonic's comparison offer better price-to-feature ratios. Ekamoira's $79 lifetime option provides entry-level AI tracking at the lowest total cost of ownership.

Decision Factor	Best Choice	Why
Already an Ahrefs customer	Brand Radar (free beta)	Zero additional cost for directional data
Accurate ChatGPT/Perplexity tracking	Peec AI or Otterly AI	Higher granularity, prompt-level context
Dark query identification	Ekamoira	Only platform with fan-out simulation
Tracking + execution in one	Ekamoira	Hybrid product + service model
Enterprise-grade depth	Profound	Feature-rich at enterprise cost
Budget-constrained teams	Ekamoira Lifetime ($79)	Lowest total cost of ownership
Historical AI trend data	Ahrefs Brand Radar	Only tool with historical data access

Frequently Asked Questions

Is Ahrefs Brand Radar worth the cost in 2026?

Ahrefs Brand Radar provides the broadest AI platform coverage (6 indexes) and the advantage of ecosystem integration with Ahrefs' backlink, keyword, and site audit tools. However, at $828-$1,148/month for full coverage according to EWR Digital, it is significantly above the $337/month industry average for AI tracking tools reported by Rankability. The value depends entirely on whether you already use Ahrefs and whether directional AI data is sufficient for your needs.

How accurate is Brand Radar's ChatGPT tracking?

Independent testing by Writesonic (January 2026) found that Brand Radar's ChatGPT module reported only 3 mentions for a brand that actually had 123 mentions across ChatGPT responses. The Perplexity module showed a similar pattern: 6 reported versus 212 actual mentions. These accuracy gaps mean ChatGPT and Perplexity data from Brand Radar should be treated as directional indicators rather than precise measurements.

What are dark queries in AI search?

Dark queries are the sub-queries that AI search platforms generate internally during query fan-out. When a user asks a question, AI systems decompose it into multiple simultaneous retrieval sub-queries, each searching different aspects of the topic. These sub-queries have zero Google search volume because no human types them into a search bar. They represent approximately 88% of the total AI retrieval surface and are invisible to every traditional keyword tool, including Ahrefs' keyword database.

Can Ahrefs Brand Radar track query fan-out?

No. Brand Radar uses a static prompt library and runs it against AI platforms at scheduled intervals. It tracks which prompts produce brand mentions, but it cannot simulate the query decomposition process that AI platforms use internally. The sub-queries generated during fan-out are not in Brand Radar's prompt library because they have zero search volume and are generated dynamically by AI systems.

How does Brand Radar compare to Semrush's AI tools?

Both Ahrefs Brand Radar and Semrush's AI Toolkit represent legacy SEO platforms adding AI visibility features. Ahrefs covers 6 AI platforms with 260M+ prompts, while Semrush approaches AI visibility through its existing keyword and domain analytics framework. Neither platform tracks dark queries or simulates query fan-out. For a detailed analysis, see what Semrush doesn't track in AI visibility.

What is the cheapest way to start tracking AI visibility?

Ekamoira's Lifetime tier at $79 (one-time payment) provides AI visibility tracking across Google AI Mode, ChatGPT, and Perplexity with 750 credits. For teams already paying for Ahrefs, Brand Radar's free beta indexes offer zero-cost directional data. Otterly AI starts at $29/month for 10 prompts. The right entry point depends on which AI platforms matter most to your business and whether you need prompt-level granularity or directional trends.

How often does Brand Radar update its AI visibility data?

According to the Ahrefs Help Center, People Also Ask questions within Brand Radar are prompted once per month. As TryAnalyze.ai documented, Brand Radar uses a static prompt library with timed snapshots, and the same prompt can produce different AI outputs every few hours. This means the data represents a snapshot of AI behavior at a specific moment rather than a continuous measurement.

Does fresher content actually get more AI citations?

Yes. An Ahrefs study analyzing 17 million citations across 7 AI platforms found that AI-cited content is 25.7% fresher than Google SERP results. The average age of AI-cited URLs is 1,064 days versus 1,432 days for organic results. ChatGPT shows the strongest preference for fresh content, citing URLs 393-458 days newer than Google results. The exception is Google AI Overviews, which cites content approximately 16 days older on average.

What is Ekamoira's Query Intelligence Service?

The Query Intelligence Service is a Done-for-You engagement that operates on 30-day cycles with a performance guarantee: no AI rankings equal no payment for that cycle. The 5-stage pipeline runs from GSC seed extraction through volume qualification, cluster strategy, and query fan-out analysis to deliver a citability-scored content roadmap within 30 days. It combines Ekamoira's SaaS platform with strategic execution, eliminating the gap between observing AI visibility data and acting on it.

Should I use Ahrefs Brand Radar alongside a dedicated AI tool?

For teams serious about AI visibility, combining Ahrefs' traditional SEO infrastructure (backlinks, site audit, keyword research) with a dedicated AI tracking tool is a viable strategy. Brand Radar's ecosystem integration provides context that standalone tools lack, while dedicated tools provide the accuracy and granularity that Brand Radar currently misses. The key is recognizing that Brand Radar measures backward (what happened) while forward-looking tools like Ekamoira predict where to invest next.

Sources

1. Ahrefs (2026). "Ahrefs Brand Radar: Win brand visibility in AI search & beyond." https://ahrefs.com/brand-radar
2. Ahrefs Help Center (2026). "About Brand Radar." https://help.ahrefs.com/en/articles/11064852-about-brand-radar
3. EWR Digital (2026). "Ahrefs Brand Radar Review & Pricing Comparisons (2026)." https://www.ewrdigital.com/blog/ahrefs-brand-radar-review-alternatives-pricing-comparison
4. Rankability (2026). "Ahrefs Brand Radar Review 2026: Is It Worth the Investment?" https://www.rankability.com/blog/ahrefs-brand-radar-review/
5. TryAnalyze.ai (2026). "Ahrefs Brand Radar Review 2026: Is It Worth It?" https://www.tryanalyze.ai/blog/ahrefs-brand-radar-review
6. Writesonic (2026). "Ahrefs Brand Radar Review: Does It Meet Expectations? [2026]." https://writesonic.com/blog/ahrefs-brand-radar-review
7. iPullRank (2025). "How AI Search Platforms Expand Queries with Fan-Out and Why It Skews Intent." https://ipullrank.com/expanding-queries-with-fanout
8. WordLift (2025). "Query Fan-Out: A Data-Driven Approach to AI Search Visibility." https://wordlift.io/blog/en/query-fan-out-ai-search/
9. AllAboutAI (2026). "AI Visibility Statistics 2026." https://www.allaboutai.com/resources/ai-statistics/ai-visibility/
10. Rankability (2026). "22 Best AI Search Rank Tracking & Visibility Tools (2026)." https://www.rankability.com/blog/best-ai-search-visibility-tracking-tools/
11. Writesonic (2025). "PEEC AI vs Otterly AI: A Comprehensive Comparison." https://writesonic.com/blog/peec-ai-vs-otterly-ai
12. Rankability (2026). "Peec AI Review 2026." https://www.rankability.com/blog/peec-ai-review/
13. Abstrakt MG (2026). "2026 SEO Pricing Guide: Costs & Expectations." https://www.abstraktmg.com/how-much-does-seo-cost/
14. Ahrefs (2025). "New Study: AI Assistants Prefer to Cite 'Fresher' Content (17 Million Citations Analyzed)." https://ahrefs.com/blog/do-ai-assistants-prefer-to-cite-fresh-content/
15. Search Engine Land (2025). "LLM optimization in 2026: Tracking, visibility, and what's next for AI discovery." https://searchengineland.com/llm-optimization-tracking-visibility-ai-discovery-463860
16. MRS Digital (2026). "The Best Tools for AI Search 2026 | Ahrefs vs Otterly & Peec AI." https://mrs.digital/blog/best-ai-seo-tools/
17. AI Peekaboo (2025). "The Best 8 Alternatives to Ahrefs Brand Radar in 2026." https://www.aipeekaboo.com/blog/best-affordable-alternatives-to-ahrefs-brand-radar

---

Ready to Track Your AI Visibility?

Ahrefs Brand Radar shows you where your brand appeared yesterday. Ekamoira's Query Fan-Out Estimator shows you where AI will retrieve content tomorrow, using 9 proprietary models that simulate query decomposition across Google AI Mode, ChatGPT, and Perplexity. Start with a $79 Lifetime plan for AI visibility tracking, or explore the 30-day Query Intelligence Service for a citability-scored content roadmap with a performance guarantee.

Start Free