# Does AI recommend Peec AI?

Free AI visibility checkup of peec.ai by Askadia: the buying questions its buyers ask, put to ChatGPT (United States), and their answers word for word, each assistant counted on its own.
Checked 2026-10-30. Category: [AI visibility tools](https://askadia.ai/domains/ai-visibility-tools.md) · Page: https://askadia.ai/domains/peec-ai · JSON: https://askadia.ai/domains/peec-ai.json · How it's counted: https://askadia.ai/docs/how-we-measure

Peec AI helps marketing teams track, analyze, and improve brand performance on AI search platforms. It measures visibility, position, and sentiment, and helps teams benchmark competitors, find cited sources, and act on insights.

## Summary

### ChatGPT

- Mentioned in 8 of 10 questions
- Top recommendation in 4 of 10
- peec.ai cited in 2 of 10
- Recommended: Peec AI (this product) 8/10, Profound 8/10, Semrush 6/10, Ahrefs Brand Radar 5/10, ChatGPT 3/10, Claude 3/10

## The questions and each assistant's answer

### 1. Peec AI vs Profound: which is better for tracking how a brand appears in AI search answers?

**ChatGPT:** 
Peec AI mentioned, #1, the top pick. Recommended: Profound.

> # Peec AI vs. Profound: which is better for AI search tracking?
>
> My initial recommendation: Profound for enterprise-grade AI visibility intelligence; Peec AI for a more accessible, straightforward way to monitor brand visibility across AI search engines.
>
> Both address the emerging discipline of Generative Engine Optimization (GEO): understanding whether ChatGPT, Perplexity, Gemini, and other AI systems mention your brand, how they describe it, and which competitors they recommend.
>
> The important distinction is that tracking brand mentions is only the starting point. The better platform should help you understand why your brand appears, where competitors outperform you, and what content could improve your visibility.
>
> ## 1. Side-by-side comparison
>
> | Capability | Peec AI | Profound |
> | --- | --- | --- |
> | Brand mentions | Strong | Strong |
> | Share of voice | Yes | Yes |
> | Brand sentiment | Yes | Yes |
> | Average answer position | Yes | Yes |
> | Competitor benchmarking | Yes | Yes |
> | Source and citation tracking | Yes | Yes |
> | Prompt-level analysis | Yes | Yes |
> | AI crawler analytics | More limited | Stronger |
> | Enterprise analytics | Good | Stronger |
> | Content/optimization workflows | More measurement-focused | More extensive |
> | Ease of getting started | Simpler | More involved |
>
> Sources: vendor product information and current comparison documentation. [Peec AI - AI Visibility and Share of Voice Tracking](https://peec.ai/product/ai-visibility) [Peec AI](https://peec.ai/) [Profound vs Peec AI: Which platform is right for your brand?](https://www.tryprofound.com/articles/profound-vs-peec-ai) [Profound vs. Peec AI: Which AEO tool supports your growth strategy?](https://blog.hubspot.com/marketing/profound-vs-peec?product=service)
>
> ## 2. Where Peec AI wins
>
> Peec AI
>
> Website: [peec.ai](https://peec.ai/?utm_source=chatgpt.com)
>
> Better for focused brand visibility monitoring and reporting.
>
> Peec is particularly good at answering questions like:
>
> - How often does ChatGPT mention our brand?
> - Which competitors are recommended instead?
> - Are we appearing more frequently in Perplexity or Gemini?
> - Is AI describing our brand positively or negatively?
> - Which sources are influencing AI-generated answers?
> - Which prompts are we missing out on?
>
> Its strengths include:
>
> - Daily tracking across selected AI models.
> - Visibility, position, sentiment and share-of-voice metrics.
> - Competitor comparisons.
> - Source and URL-level citation analysis.
> - Country, model and prompt-tag filtering.
> - Looker Studio, API and MCP integrations.
>
> One useful distinction: Peec tracks both brand mentions and instances where your website content informs AI answers without necessarily being cited by name. [Getting started - How does Peec AI help improve my visibility?](https://help.peec.ai/article/how-does-peec-ai-help-improve-my-visibility-prqv3gsu58jq7utrwhuowkhy) [Peec AI](https://peec.ai/)
>
> My take: If your main objective is to build an AI visibility reporting process, Peec is a very compelling option.
>
> ## 3. Where Profound wins
>
> Profound
>
> Website: [tryprofound.com](https://www.tryprofound.com/?utm_source=chatgpt.com)
>
> Better for enterprise-level AI search intelligence and optimization.
>
> Profound goes beyond simply measuring how often your brand appears.
>
> Its broader platform includes:
>
> - Deeper answer-engine intelligence.
> - Competitive and citation analysis.
> - AI crawler analytics to understand how AI systems access your website.
> - Content optimization and AI-powered agents.
> - Enterprise reporting, integrations and security controls.
> - Broader AI search and shopping intelligence.
>
> This makes it attractive if you want to connect AI search visibility with your content strategy, technical SEO, digital PR and broader marketing operations. [Profound vs Peec AI: Which platform is right for your brand?](https://www.tryprofound.com/articles/profound-vs-peec-ai) [Profound vs. Peec AI: Which AEO tool supports your growth strategy?](https://blog.hubspot.com/marketing/profound-vs-peec?product=service) [Peec AI vs Profound (2026): Pricing, Features and Which to Choose](https://www.gtm8020.com/blog/peec-ai-vs-profound)
>
> My take: Profound is more compelling when AI search is becoming a substantial marketing channel and you need a platform to manage the optimization process, not just report on it.
>
> ## 4. Pricing: an important difference
>
> Indicative published pricing as of October 2026:
>
> |  | Peec AI | Profound |
> | --- | --- | --- |
> | Entry point | $95/month | Free 7-day trial |
> | Paid pricing | $95, $245, $495/month tiers | Custom enterprise pricing |
> | Pricing transparency | High | Lower |
> | Enterprise plan | Custom | Custom |
>
> The figures are based on published pricing comparisons checked October 24, 2026. Confirm current plan limits and included models before purchasing. [Peec AI vs Profound (2026): Pricing, Features and Which to Choose](https://www.gtm8020.com/blog/peec-ai-vs-profound) [Peec AI vs Profound](https://toolvern.com/compare/peec-ai-vs-profound/)
>
> ## 5. My recommendation by use case
>
> | Your objective | My pick |
> | --- | --- |
> | Monitor brand mentions in ChatGPT | Peec |
> | Track AI share of voice | Either |
> | Monitor competitor recommendations | Either |
> | Track AI citations and sources | Either |
> | Understand actual audience prompt demand | Profound |
> | Connect AI visibility to content execution | Profound |
> | Affordable ongoing reporting | Peec |
> | Enterprise-wide AI search strategy | Profound |
>
> One important caveat: Peec has expanded its capabilities during 2026, including crawler insights and action-oriented features. It would be inaccurate to characterize it as just a basic mention tracker. Profound's advantage is more about the depth and breadth of its intelligence and execution workflows. [Profound vs Peec AI: Which platform is right for your brand?](https://www.tryprofound.com/articles/profound-vs-peec-ai) [Peec AI](https://peec.ai/)
>
> ## 6. How I would evaluate them before buying
>
> Don't judge either platform by its headline visibility score alone.
>
> Run both against the same:
>
> - 30–50 prompts that real customers might ask.
> - 5–10 direct competitors.
> - Three or four AI platforms.
> - Multiple weeks of observations.
>
> Compare these five metrics:
>
> 1. Mention rate: What percentage of answers mention your brand?
> 2. Recommendation rate: How often does AI actually recommend you?
> 3. Competitive share of voice: How frequently are competitors mentioned instead?
> 4. Citation share: Which websites and sources influence the answers?
> 5. Accuracy of brand representation: Does AI describe your products, positioning and strengths correctly?
>
> The distinction between a brand being mentioned and being recommended is particularly important. A tool can report high visibility even when AI consistently recommends competitors.
>
> ## Final verdict
>
> My pick for most marketing teams: Peec AI
>
> If the primary job is tracking how a brand appears in AI-generated search answers, I would start with Peec AI. It provides the core visibility, sentiment, position, competitor and citation measurements without requiring an enterprise-level platform commitment.
>
> I'd choose Profound if the objective is broader: understanding audience demand, investigating AI search behavior, and turning those insights into an enterprise content and optimization program.
>
> One question that could change my recommendation:
>
> Are you looking to track AI visibility for:
>
> - A. Your own company's brand.
> - B. Multiple client brands (agency use).
> - C. Competitors and an entire industry.
> - D. A SaaS product where you want to know whether ChatGPT recommends you when people ask for solutions in your category.
>
> The distinction matters because the best platform for measuring your own brand isn't necessarily the best platform for competitive intelligence or agency reporting.

Sources: https://peec.ai/product/ai-visibility · https://peec.ai/ · https://www.tryprofound.com/articles/profound-vs-peec-ai · https://blog.hubspot.com/marketing/profound-vs-peec?product=service · https://help.peec.ai/article/how-does-peec-ai-help-improve-my-visibility-prqv3gsu58jq7utrwhuowkhy · https://www.gtm8020.com/blog/peec-ai-vs-profound · https://toolvern.com/compare/peec-ai-vs-profound/


### 2. What's the best tool for monitoring brand visibility across ChatGPT, Perplexity, and other AI search platforms?

**ChatGPT:** 
Peec AI mentioned, #1, the top pick. Recommended: Profound, Otterly.AI, Ahrefs Brand Radar, Semrush.

> If you're looking to monitor how your brand appears across **ChatGPT, Perplexity, Gemini, Claude, Google AI Overviews, and other AI search platforms**, I'd shortlist **Peec AI, Profound, and Otterly.AI**.
>
> These tools belong to the emerging category of AI visibility monitoring, also called **Generative Engine Optimization (GEO)** or Answer Engine Optimization (AEO).
>
> My recommendation depends on whether you want straightforward brand monitoring, competitive intelligence, or enterprise-level analytics.
>
> ## Best AI visibility monitoring tools
>
> | Tool | Best for | Main strengths |
> | --- | --- | --- |
> |  | Best overall for marketing teams | Visibility, sentiment, rankings, citations and competitor tracking |
> |  | Enterprise brands | Deep analytics, prompt intelligence, citation analysis and reporting |
> |  | Small businesses and agencies | Affordable, automated daily monitoring |
> | \*\* Brand Radar | SEO and competitive intelligence | Large prompt database and competitor benchmarking |
> |  | Existing SEO customers | Combines traditional SEO and AI visibility reporting |
>
> ### 1. Peec AI — My top recommendation
>
> [Peec AI](https://peec.ai/?utm_source=chatgpt.com)
>
> Why I like it:
>
> - Tracks ChatGPT, Perplexity, Gemini, Google AI Overviews and Microsoft Copilot.
> - Measures brand visibility and position.
> - Tracks sentiment and competitor mentions.
> - Identifies the websites and sources AI platforms cite.
> - Lets you organize tracking around topics, markets and customer personas.
>
> It offers a particularly useful combination of monitoring and competitive intelligence.
>
> **Best for:** Marketing teams that want to understand how AI platforms recommend their brand versus competitors.
>
> ### 2. Profound — Best for enterprise brands
>
> [Profound](https://www.tryprofound.com/?utm_source=chatgpt.com)
>
> Key capabilities:
>
> - Tracks brand visibility across major AI answer engines.
> - Measures sentiment and share of voice.
> - Identifies which sources influence AI-generated answers.
> - Provides prompt intelligence and demand analysis.
> - Supports deeper enterprise reporting.
>
> Its advantage is the depth of its analytics and its focus on enterprise AI search strategy.
>
> **Best for:** Larger companies, enterprise marketing departments and agencies managing major brands.
>
> ### 3. Otterly.AI — Best budget option
>
> [Otterly.AI](https://otterly.ai/?utm_source=chatgpt.com)
>
> Key capabilities:
>
> - Daily brand monitoring.
> - ChatGPT, Perplexity, Google AI Overviews and Copilot.
> - Competitor visibility tracking.
> - Brand reports.
> - Additional Gemini and Claude monitoring options.
>
> Its entry-level plan includes 15 tracked prompts, making it a relatively inexpensive way to get started.
>
> **Best for:** Smaller businesses, consultants and agencies starting with GEO.
>
> ### 4. Ahrefs Brand Radar — Best for SEO intelligence
>
> [Ahrefs Brand Radar](https://ahrefs.com/brand-radar?utm_source=chatgpt.com)
>
> Its differentiator is its large search-backed prompt database.
>
> It tracks:
>
> - ChatGPT
> - Perplexity
> - Gemini
> - Claude
> - Microsoft Copilot
> - Google AI Overviews and AI Mode
>
> It also provides competitor share-of-voice analysis and citation insights. One important distinction: its broad AI chatbot database refreshes monthly, while custom prompt tracking can be configured more frequently.
>
> **Best for:** SEO professionals who want to connect traditional search intelligence with AI visibility.
>
> ## My recommendation: Which one should you choose?
>
> I'd make the decision this way:
>
> | Your objective | My pick |
> | --- | --- |
> | Monitor brand visibility across AI platforms | Peec AI |
> | Enterprise-level AI brand intelligence | Profound |
> | Affordable daily monitoring | Otterly.AI |
> | Competitor research at scale | Ahrefs Brand Radar |
> | Combine SEO and AI search reporting | Semrush |
>
> ## What you should measure
>
> Whichever platform you choose, make sure it tracks these six metrics:
>
> 1. **AI Share of Voice:** What percentage of relevant AI answers mention your brand versus competitors?
> 2. **Brand Mentions:** How frequently does ChatGPT or Perplexity recommend your company?
> 3. **Citation Tracking:** Which websites and URLs do AI platforms use as sources?
> 4. **Sentiment:** Does AI describe your brand positively, negatively or neutrally?
> 5. **Competitor Benchmarking:** Which competitors appear more frequently in AI-generated recommendations?
> 6. **Prompt-Level Visibility:** For which specific customer questions does your brand appear or disappear?
>
> One important caveat: these platforms sample responses to tracked prompts. They cannot measure every conversation happening inside ChatGPT or Perplexity. Treat visibility scores as comparative indicators rather than absolute market-share figures.
>
> ## My final verdict
>
> **I'd start with Peec AI.**
>
> It provides a good balance of:
>
> - Multi-platform AI monitoring.
> - Brand visibility analytics.
> - Competitor benchmarking.
> - Citation intelligence.
> - Sentiment tracking.
>
> If you're building a serious enterprise-level AI visibility program, I'd also evaluate Profound before committing.
>
> **One question that would help me narrow this down:** Are you looking to monitor visibility for your own brand, or do you want a platform that monitors multiple client brands (as an agency would)?

Sources: https://peec.ai/?utm_source=chatgpt.com · https://www.tryprofound.com/?utm_source=chatgpt.com · https://otterly.ai/?utm_source=chatgpt.com · https://ahrefs.com/brand-radar?utm_source=chatgpt.com


### 3. Which AI search analytics platform helps marketing teams compare brand mentions and sentiment against competitors?

**ChatGPT:** 
Peec AI mentioned, #3. Recommended: HubSpot AEO, Profound, Ahrefs Brand Radar.

> HubSpot AEO is a strong choice. It helps marketing teams track and compare:
>
> - Brand mentions across AI search platforms.
> - Sentiment and how AI describes their brand.
> - Competitor visibility and share of voice.
> - AI-generated citations and sources.
> - Performance across ChatGPT, Perplexity, and Gemini.
>
> Other good options include Profound, Peec AI, and Ahrefs Brand Radar. [Ahrefs Brand Radar alternatives for marketing teams](https://blog.hubspot.com/marketing/ahrefs-brand-radar-alternatives?_rsc=1wbid) [Best AI search analytics tools for marketing teams](https://blog.hubspot.com/marketing/ai-search-analytics-tools?roistat_visit=2540962) [Best AI search monitoring tools for 2026](https://technologyadvice.com/blog/information-technology/ai-software/best-ai-search-monitoring-tools/)
>
> My recommendation: HubSpot AEO for marketing teams seeking brand sentiment and competitor benchmarking in one platform; Profound for deeper enterprise-level AI search analytics.

Sources: https://blog.hubspot.com/marketing/ahrefs-brand-radar-alternatives?_rsc=1wbid · https://blog.hubspot.com/marketing/ai-search-analytics-tools?roistat_visit=2540962 · https://technologyadvice.com/blog/information-technology/ai-software/best-ai-search-monitoring-tools/


### 4. What are the best tools for finding which websites AI assistants cite when answering questions about my brand?

**ChatGPT:** 
Peec AI mentioned, #2. Recommended: Profound, OtterlyAI, Semrush, Scrunch AI, OpenSEO.

> The tools you're looking for are generally called AI visibility tracking, AI citation tracking, or Generative Engine Optimization (GEO) platforms.
>
> They help answer a particularly important question:
>
> When someone asks ChatGPT, Perplexity, Gemini, or Claude about your brand or your industry, which websites does the AI use as sources?
>
> This is different from simply tracking whether an AI mentions your brand. You want to identify the actual URLs and domains being cited, including third-party websites such as Reddit, review sites, industry publications, directories, and competitors' websites.
>
> ## Best tools to investigate
>
> Here are the platforms I'd shortlist as of October 2026.
>
> 1. Profound
>
> Best for enterprise research
>
> - Tracks AI visibility across multiple assistants.
> - Provides citation and source analysis.
> - Helps identify which websites influence AI-generated answers.
> - Useful for competitive intelligence and content strategy.
>
> Website: [Profound](https://www.tryprofound.com/?utm_source=chatgpt.com)
>
> 2. Peec AI
>
> Best for ongoing monitoring
>
> - Monitors brand visibility across AI search engines.
> - Tracks competitor mentions and citations.
> - Helps identify which sources and domains appear in AI answers.
> - Useful for tracking changes over time.
>
> Website: [Peec AI](https://peec.ai/?utm_source=chatgpt.com)
>
> 3. OtterlyAI
>
> Best for smaller teams
>
> - Tracks brand mentions in AI-generated answers.
> - Monitors AI search citations and sources.
> - Offers ongoing monitoring without requiring an enterprise analytics setup.
>
> Website: [OtterlyAI](https://otterly.ai/?utm_source=chatgpt.com)
>
> 4. Semrush – AI Visibility Toolkit
>
> Best for SEO teams
>
> - Combines traditional SEO research with AI visibility monitoring.
> - Tracks brand mentions and citations.
> - Provides competitive visibility insights.
> - Useful if you're already using Semrush for SEO.
>
> Website: [Semrush](https://www.semrush.com/?utm_source=chatgpt.com)
>
> 5. Scrunch AI
>
> - Focuses on how AI assistants discover and represent brands.
> - Helps analyze AI search visibility and competitors.
> - Useful for larger marketing teams developing an AI search strategy.
>
> Website: [Scrunch AI](https://scrunch.com/?utm_source=chatgpt.com)
>
> 6. OpenSEO
>
> Best for inspecting actual citations
>
> - Runs questions across multiple AI assistants.
> - Shows the individual websites cited in their answers.
> - Displays citations in order, side by side.
> - Helps identify domains repeatedly referenced by different assistants.
>
> Website: [OpenSEO AI Visibility Checker](https://openseo.gg/tools/ai-visibility-checker?utm_source=chatgpt.com).
>
> [AI Visibility Checker: See What ChatGPT and Gemini Cite](https://openseo.gg/tools/ai-visibility-checker) [AI Visibility Tracker: Open Source AI Citations Tracking](https://openseo.gg/features/ai-visibility-tracker)
>
> ## What I would compare before buying
>
> Not all AI visibility platforms measure the same thing. These are the features I'd prioritize:
>
> | Capability | Importance |
> | --- | --- |
> | Exact URLs cited by AI | Essential |
> | Third-party domain tracking | Essential |
> | Citations by individual AI assistant | Essential |
> | Competitor citation analysis | Very high |
> | Historical citation tracking | Very high |
> | Citation frequency by topic | High |
> | Exportable reports | High |
> | Country and language filtering | Useful |
>
> One particularly important distinction: a tool that tells you your brand was mentioned isn't necessarily telling you which external websites influenced the answer.
>
> ## My recommended approach
>
> I'd combine two types of tools:
>
> 1. A monitoring platform: Profound or Peec AI to track citations over time.
> 2. A citation investigation tool: OpenSEO to inspect the actual sources returned for specific questions.
>
> I'd also create a recurring set of questions such as:
>
> - What are the best companies in [your industry]?
> - Who are the leading providers of [your product category]?
> - What are the alternatives to [your brand]?
> - Which companies specialize in [your area of expertise]?
> - Is [your brand] a good choice for [specific use case]?
>
> Run those questions across ChatGPT, Perplexity, Gemini and Claude.
>
> Then build a list of the external websites that appear most frequently in their citations. Those websites become potential opportunities for PR, partnerships, reviews, guest contributions and other authority-building efforts.
>
> One important caveat: AI answers are variable, so repeat queries and track citation frequency over time rather than treating one response as definitive. [AI Citation Analysis Tools (2026): How to Track Where ChatGPT, Perplexity & Gemini Cite You](https://nicklafferty.com/blog/best-ai-citation-analysis-tools/) [How We Measure AI Search Visibility](https://www.searchintel.tech/methodology/)
>
> ## One question that would help narrow this down
>
> Are you primarily trying to:
>
> - Discover influential websites: Find the third-party websites AI assistants repeatedly cite when discussing your industry or competitors.
> - Monitor your brand: Find out exactly which websites ChatGPT, Gemini, Perplexity and Claude cite when answering questions about your company.
> - Improve AI visibility: Identify which publications, directories, review sites and other sources you should get your brand featured on to increase AI recommendations.
>
> I can help identify the best tools for that particular objective and compare their capabilities.

Sources: https://openseo.gg/tools/ai-visibility-checker · https://openseo.gg/features/ai-visibility-tracker · https://nicklafferty.com/blog/best-ai-citation-analysis-tools/ · https://www.searchintel.tech/methodology/


### 5. Which platform can help an SEO team track brand rankings in AI-generated answers over time?

**ChatGPT:** 
Peec AI not mentioned. Recommended: Ahrefs Brand Radar, Semrush, Profound, OtterlyAI, Trendos, Measure.

> Ahrefs Brand Radar is a strong option for SEO teams looking to track brand rankings and visibility in AI-generated answers over time.
>
> Other platforms worth considering include:
>
> 1. Semrush – Combines traditional SEO analytics with AI visibility tracking and competitor analysis.
> 2. Profound – Monitors brand mentions, citations, sentiment, and visibility across AI answer engines.
> 3. OtterlyAI – Tracks brand mentions and citations across AI search platforms.
> 4. Trendos – Tracks AI rankings, brand mentions, sentiment, and historical visibility.
> 5. Measure – Tracks brand visibility and share of voice across ChatGPT, Perplexity, Gemini, and Claude.
>
> [The 8 Best AI Visibility Tools to Win in AI Search (2026)](https://www.semrush.com/blog/best-ai-visibility-tools/) [Best AI search monitoring tools for 2026](https://technologyadvice.com/blog/information-technology/ai-software/best-ai-search-monitoring-tools/) [AI search visibility tool: free, historical data](https://trendos.com/) [AI visibility tracking for ChatGPT and more](https://www.measure.co/features/ai-visibility-tracking)
>
> My recommendation:
>
> - For an established SEO team: Ahrefs Brand Radar or Semrush.
> - For enterprise-level AI visibility monitoring: Profound.
> - For tracking AI rankings and historical changes: Trendos or Measure.
>
> The key metrics to monitor are:
>
> - Brand mention frequency.
> - Average ranking or position in AI answers.
> - Share of voice versus competitors.
> - AI citations and referenced URLs.
> - Visibility trends over time.
>
> This category of software is commonly called AI Visibility Tracking, Answer Engine Optimization (AEO), or Generative Engine Optimization (GEO) software.

Sources: https://www.semrush.com/blog/best-ai-visibility-tools/ · https://technologyadvice.com/blog/information-technology/ai-software/best-ai-search-monitoring-tools/ · https://trendos.com/ · https://www.measure.co/features/ai-visibility-tracking


### 6. What are good alternatives to Profound for measuring brand visibility in AI search?

**ChatGPT:** 
Peec AI mentioned, #1, the top pick. Recommended: Scrunch AI, AthenaHQ, Otterly.AI, Semrush, Ahrefs Brand Radar.

> There are several good alternatives to Profound for measuring brand visibility in AI search. The strongest options are Peec AI, Scrunch AI, AthenaHQ, Otterly.AI, Semrush and Ahrefs Brand Radar.
>
> The important distinction is whether you want to measure:
>
> - Brand visibility: How often ChatGPT, Gemini, Perplexity, Claude, etc. mention your brand.
> - Share of voice: How frequently you're recommended compared with competitors.
> - Citation visibility: Which websites and pages AI engines cite when answering relevant questions.
> - Brand perception: Whether AI describes your brand accurately and positively.
> - Visibility drivers: What content and sources influence AI recommendations.
>
> Here is how I'd shortlist the alternatives.
>
> ## Best alternatives to Profound
>
> 1. Peec AI
>
> Best overall alternative
>
> - Tracks brand mentions, visibility, competitors and citations across AI platforms.
> - Prompt-level reporting makes it useful for understanding which questions generate visibility.
> - Good balance of analytics, usability and affordability.
> - Indicative entry pricing: around $95/month.
>
> Website: [peec.ai](https://peec.ai/?utm_source=chatgpt.com)
>
> 2. Scrunch AI
>
> Best for enterprise brand intelligence
>
> - Tracks how brands are represented across AI answer engines.
> - Offers competitor benchmarking and sentiment analysis.
> - Particularly interesting for larger organizations managing multiple brands and markets.
> - Pricing is generally sales-led, with plans reported from around $250/month.
>
> Website: [scrunchai.com](https://scrunchai.com/?utm_source=chatgpt.com)
>
> 3. AthenaHQ
>
> Best for enterprise analytics
>
> - Broad coverage of AI models and search experiences.
> - Tracks visibility, citations and competitive positioning.
> - Offers recommendations for improving AI search performance.
> - Particularly suitable for teams that want measurement connected to optimization and ROI.
>
> Indicative entry pricing: around $295/month.
>
> Website: [athenahq.ai](https://athenahq.ai/?utm_source=chatgpt.com)
>
> 4. Otterly.AI
>
> Best budget option
>
> - Monitors brand mentions across AI search engines.
> - Provides citation tracking, sentiment analysis and competitor monitoring.
> - Useful for agencies and smaller marketing teams.
> - Entry pricing reported around $29/month.
>
> Website: [otterly.ai](https://otterly.ai/?utm_source=chatgpt.com)
>
> 5. Semrush – AI Visibility Toolkit
>
> - Combines traditional SEO analytics with AI search visibility measurement.
> - Tracks brand presence, competitors and AI search performance.
> - Useful for connecting organic search performance with AI visibility.
> - Particularly attractive if your team already uses Semrush.
>
> Website: [semrush.com](https://www.semrush.com/?utm_source=chatgpt.com)
>
> 6. Ahrefs Brand Radar
>
> - Measures brand presence in AI-generated responses.
> - Helps benchmark competitors and discover topics where brands appear.
> - Particularly interesting for teams already invested in Ahrefs' SEO ecosystem.
> - AI visibility functionality and pricing depend on the selected plan and data coverage.
>
> Website: [ahrefs.com/brand-radar](https://ahrefs.com/brand-radar?utm_source=chatgpt.com)
>
> Sources: [Profound alternatives: 9 best tools for AI search [2026]](https://blog.hubspot.com/marketing/profound-alternatives) [AI visibility tools: How to track and grow your presence in AI search](https://searchengineland.com/tools/ai-visibility-checker) [Best AI search monitoring tools for 2026](https://technologyadvice.com/blog/information-technology/ai-software/best-ai-search-monitoring-tools/) [14 Best AI Visibility Tools in 2026: LLM Trackers Compared](https://surfer.ai/blog/best-ai-visibility-tools/)
>
> ## Quick comparison
>
> | Platform | Best suited for | Relative positioning |
> | --- | --- | --- |
> | Peec AI | Brand visibility and share of voice | Mid-market |
> | Scrunch AI | Brand intelligence | Enterprise |
> | AthenaHQ | Analytics and optimization | Enterprise |
> | Otterly.AI | Basic visibility monitoring | Budget |
> | Semrush | SEO + AI visibility | Established SEO teams |
> | Ahrefs | Brand Radar + SEO insights | Established SEO teams |
>
> Pricing is indicative, not a verified quote. Features, engine coverage and usage limits vary by subscription.
>
> ## What I'd look for when evaluating them
>
> I wouldn't choose a platform based simply on how many AI engines it supports. I'd evaluate these six capabilities:
>
> 1. Share of voice: Can you measure your brand against named competitors?
> 2. Prompt-level tracking: Can you identify the exact questions where your brand appears?
> 3. Citation analysis: Can you see which domains and URLs AI engines reference?
> 4. Sentiment and positioning: Does AI recommend you, criticize you or simply mention you?
> 5. Historical tracking: Can you measure changes weekly and monthly?
> 6. Geographic segmentation: Can you compare visibility across countries and languages?
>
> One particularly important consideration: AI visibility measurements are estimates based on sampled prompts and generated answers. Different platforms can produce different results because of differences in prompt selection, sampling frequency, model versions and measurement methodology.
>
> ## My recommendation
>
> I'd narrow the evaluation to three platforms:
>
> - Peec AI: If you want a relatively straightforward alternative to Profound for measuring brand visibility and share of voice.
> - Scrunch AI: If you need deeper brand intelligence and enterprise-level monitoring.
> - AthenaHQ: If you want to go beyond measurement and use the data to improve AI search performance.
>
> I'd also trial Otterly.AI as a lower-cost benchmark.
>
> ## One question that would help me narrow this down
>
> Are you primarily looking to measure AI visibility for:
>
> - A. Your own brand – understanding how ChatGPT, Gemini and Perplexity recommend you.
> - B. An agency or multiple clients – tracking visibility and share of voice across many brands.
> - C. Competitive intelligence – comparing your brand against competitors and understanding why they're being recommended.
> - D. Enterprise reporting – measuring AI visibility, citations, sentiment and changes over time.
>
> The distinction matters because the best platform for straightforward brand monitoring isn't necessarily the best one for competitive intelligence or enterprise-grade reporting.

Sources: https://blog.hubspot.com/marketing/profound-alternatives · https://searchengineland.com/tools/ai-visibility-checker · https://technologyadvice.com/blog/information-technology/ai-software/best-ai-search-monitoring-tools/ · https://surfer.ai/blog/best-ai-visibility-tools/


### 7. What are good alternatives to OtterlyAI for monitoring how often AI assistants recommend our brand?

**ChatGPT:** 
Peec AI mentioned, #1, the top pick. Recommended: Profound, AthenaHQ, Scrunch, Ahrefs Brand Radar, Semrush.

> There are several strong alternatives to OtterlyAI, depending on whether you want straightforward brand-mention tracking, competitive intelligence, or deeper analysis of why AI assistants recommend certain brands.
>
> The category is generally called AI visibility monitoring, Generative Engine Optimization (GEO), or Answer Engine Optimization (AEO).
>
> My shortlist for 2026 would be Peec AI, Profound, AthenaHQ, Scrunch, Ahrefs Brand Radar, and Semrush.
>
> ## Best alternatives to OtterlyAI
>
> 1. Peec AI
>
> Best overall alternative
>
> - Tracks brand mentions across AI assistants.
> - Competitive share-of-voice analysis.
> - Citation and source analysis.
> - Sentiment and visibility trends.
> - Designed for marketing teams and agencies.
>
> Why consider it: A strong option if your primary objective is measuring how frequently AI recommends your brand compared with competitors.
>
> Indicative starting price: approximately $95/month.
>
> [Peec AI website](https://peec.ai/?utm_source=chatgpt.com)
>
> 2. Profound
>
> Best for enterprise intelligence
>
> - Tracks brand visibility across multiple AI engines.
> - Measures mentions, citations and sentiment.
> - Provides prompt-level insights.
> - Includes AI crawler and agent analytics.
> - Helps identify which sources influence AI answers.
>
> Why consider it: Particularly useful if you want to understand not just whether AI recommends your brand, but why it does so and which external websites influence those recommendations.
>
> Pricing: primarily enterprise/custom pricing.
>
> [Profound website](https://www.tryprofound.com/?utm_source=chatgpt.com)
>
> 3. AthenaHQ
>
> - AI visibility monitoring.
> - Competitor benchmarking.
> - Sentiment and brand integrity monitoring.
> - Hallucination detection.
> - Content optimization recommendations.
>
> Why consider it: Good if you want to turn monitoring into an actionable strategy for improving how AI assistants describe and recommend your brand.
>
> Indicative paid entry tier: around $295/month.
>
> [AthenaHQ website](https://www.athenahq.ai/?utm_source=chatgpt.com)
>
> 4. Scrunch AI
>
> - Tracks brand visibility across AI platforms.
> - Monitors citations and competitors.
> - Supports persona-based prompt tracking.
> - Provides AI crawler and website experience insights.
>
> Why consider it: Interesting if you're interested in how different customer personas receive brand recommendations, not just overall mention frequency.
>
> Indicative pricing: from approximately $250/month on annual billing.
>
> [Scrunch website](https://scrunch.com/?utm_source=chatgpt.com)
>
> 5. Ahrefs Brand Radar
>
> - Tracks brand mentions across AI-generated answers.
> - Large-scale AI prompt database.
> - Competitor visibility comparisons.
> - AI citation analysis.
> - Combines traditional SEO and AI visibility research.
>
> Why consider it: Particularly useful if you already use Ahrefs and want to understand your brand's presence across a large universe of AI-related search queries.
>
> AI add-on pricing varies by index and subscription.
>
> [Ahrefs Brand Radar](https://ahrefs.com/brand-radar?utm_source=chatgpt.com)
>
> 6. Semrush AI Visibility Toolkit
>
> - Tracks AI brand mentions.
> - Competitor benchmarking.
> - AI visibility reporting.
> - AI search optimization audits.
> - Integrates with traditional SEO workflows.
>
> Why consider it: A sensible choice if your marketing team already uses Semrush and wants to consolidate SEO and AI visibility reporting.
>
> Indicative pricing: around $99/month per domain.
>
> [Semrush website](https://www.semrush.com/?utm_source=chatgpt.com)
>
> These comparisons draw on 2026 platform reviews and feature comparisons. Pricing and AI-engine coverage can change by subscription tier. [Best AI search monitoring tools for 2026](https://technologyadvice.com/blog/information-technology/ai-software/best-ai-search-monitoring-tools/) [14 Best AI Visibility Tools in 2026: LLM Trackers Compared](https://surfer.ai/blog/best-ai-visibility-tools/) [What Are the Best Tools to Track Brand Visibility in ChatGPT, Perplexity and Google AI Overviews?](https://www.llmscan.dev/blog/best-ai-visibility-tracking-tools) [AI Visibility Tools Compared: Trackers, Content Tools, Agencies and Full-Loop Software](https://citepoint.ai/articles/ai-visibility-tools-compared)
>
> ## Quick comparison
>
> | Platform | Primary strength | Best suited for |
> | --- | --- | --- |
> | Peec AI | Mentions and share of voice | Marketing teams |
> | Profound | Deep AI intelligence | Enterprises |
> | AthenaHQ | Monitoring + optimization | GEO teams |
> | Scrunch | Persona-based visibility | Brand strategy |
> | Ahrefs | Large-scale brand research | SEO teams |
> | Semrush | SEO + AI visibility | Existing Semrush users |
>
> ## What I'd prioritize when evaluating them
>
> There are six capabilities I'd look for. Some tools are much better at certain aspects than others.
>
> 1. Brand recommendation frequency: What percentage of relevant prompts result in your brand being recommended?
> 2. Share of voice: How frequently does your brand appear compared with competitors?
> 3. Recommendation position: Are you the first recommendation, second, or buried further down?
> 4. Citation tracking: Which websites, articles, reviews and sources are influencing AI recommendations?
> 5. Sentiment analysis: Does the assistant describe your brand positively, negatively or neutrally?
> 6. Historical tracking: Can you see whether your AI visibility is increasing or decreasing over time?
>
> One important distinction: AI visibility platforms generally measure repeated samples of answers to selected prompts. This is not necessarily the same as measuring actual customer exposure or the total number of recommendations made to real users.
>
> ## My recommendation
>
> I'd start by trialing three platforms:
>
> - Peec AI: Best starting point for day-to-day brand recommendation monitoring.
> - Profound: Best for deeper competitive and source intelligence.
> - AthenaHQ: Best if you want monitoring combined with recommendations for improving visibility.
>
> I would compare all three using exactly the same prompts, competitors, AI engines and geographic settings.
>
> ## A question that would help narrow this down
>
> Are you primarily trying to achieve:
>
> I can then narrow this down to the three strongest options, including pricing, monitoring coverage and which provides the most useful competitive intelligence.

Sources: https://technologyadvice.com/blog/information-technology/ai-software/best-ai-search-monitoring-tools/ · https://surfer.ai/blog/best-ai-visibility-tools/ · https://www.llmscan.dev/blog/best-ai-visibility-tracking-tools · https://citepoint.ai/articles/ai-visibility-tools-compared


### 8. How do I measure whether AI-generated answers mention my brand accurately and positively?

**ChatGPT:** 
Peec AI not mentioned. Recommended: ChatGPT, Google AI Overviews, Perplexity, Claude, Google Gemini, Semrush AI Visibility Toolkit, Searchable.

> To measure whether AI-generated answers mention your brand accurately and positively, you need an AI Brand Visibility and Sentiment Measurement Framework.
>
> Think of it as brand monitoring for ChatGPT, Google AI Overviews, Perplexity, Claude, and other AI assistants.
>
> The goal is to answer five questions:
>
> 1. Visibility: Does AI mention your brand?
> 2. Accuracy: Does it describe your products, services, and capabilities correctly?
> 3. Sentiment: Does it recommend your brand positively, neutrally, or negatively?
> 4. Competitive position: Does it mention your brand ahead of competitors?
> 5. Authority: Does it cite your website or other trustworthy sources when discussing your brand?
>
> Here's how I'd build a practical measurement system.
>
> ## 1. Establish your five core metrics
>
> | Metric | What it measures |
> | --- | --- |
> | AI mention rate | Percentage of relevant questions where your brand appears |
> | Brand accuracy | Percentage of brand statements that are factually correct |
> | Positive sentiment | Percentage of mentions that are positive |
> | Share of AI voice | Your brand's mentions compared with competitors |
> | Citation rate | Percentage of relevant answers citing your website or trusted sources |
>
> For example, suppose you test 100 relevant questions across AI platforms.
>
> - Your brand appears in 65 answers.
> - 58 mentions are accurate.
> - 45 mentions are positive.
> - 20 answers cite your website.
> - Your competitors appear in 50 answers.
>
> You can turn these into a consistent monthly scorecard.
>
> ## 2. Build a representative set of questions
>
> Don't just ask AI, "Tell me about [Brand]." That tests brand recognition, not whether AI recommends you naturally.
>
> Build a prompt library covering five categories:
>
> | Category | Example question |
> | --- | --- |
> | Brand discovery | "What is [Brand] known for?" |
> | Category discovery | "What are the best companies for [your category]?" |
> | Recommendations | "Which providers would you recommend for [customer need]?" |
> | Comparisons | "Compare [Brand] with [Competitor]." |
> | Trust and reputation | "What are the strengths and weaknesses of [Brand]?" |
>
> Include both branded and unbranded questions. Unbranded questions are especially important because they reveal whether AI recommends your company without being prompted to consider it.
>
> A useful starting point is 20–30 questions, expanded as you learn which questions matter most to customers.
>
> ## 3. Test across multiple AI platforms
>
> ChatGPT
>
> Test brand discovery, recommendations, comparisons, and product knowledge.
>
> Google Gemini
>
> Check brand descriptions, product information, and recommendations.
>
> Perplexity
>
> Pay particular attention to citations and the sources supporting brand claims.
>
> Claude
>
> Examine how it characterizes your company's reputation, strengths, and limitations.
>
> Run each prompt multiple times. AI answers aren't perfectly consistent, so a single response is not a reliable measurement. Three to five runs per prompt is a reasonable starting point.
>
> ![](https://www.google.com/s2/favicons?domain=https://3rive.ai&sz=32)
>
> 3rive
>
> +1
>
> ## 4. Create an accuracy and sentiment scoring rubric
>
> This is where you move beyond counting mentions.
>
> I recommend scoring each answer on the following dimensions:
>
> | Dimension | Score | Evaluation |
> | --- | --- | --- |
> | Company description | 0–2 | Is the business described correctly? |
> | Product knowledge | 0–2 | Are products and capabilities accurate? |
> | Pricing and facts | 0–2 | Are factual claims current and correct? |
> | Sentiment | -2 to +2 | Is the portrayal negative or positive? |
> | Recommendation | 0–2 | Does AI actively recommend the brand? |
>
> For accuracy:
>
> - 0 = Incorrect
> - 1 = Partially correct
> - 2 = Fully correct
>
> For sentiment:
>
> - -2 = Strongly negative
> - -1 = Somewhat negative
> - 0 = Neutral
> - +1 = Somewhat positive
> - +2 = Strongly positive
>
> For recommendation:
>
> - 0 = Not recommended
> - 1 = Mentioned as an option
> - 2 = Explicitly recommended
>
> Important: Don't confuse a neutral answer with a negative one. An accurate description of a limitation isn't necessarily negative sentiment.
>
> ## 5. Build a monthly AI brand scorecard
>
> Here's an example of what your reporting dashboard could look like.
>
> ## AI Brand Health Dashboard
>
> Illustrative data · Monthly measurement
>
> AI mention rate
>
> # 65%
>
> Brand visibility
>
> Accuracy rate
>
> # 89%
>
> Factual correctness
>
> Positive sentiment
>
> # 78%
>
> Of brand mentions
>
> Share of voice
>
> # 32%
>
> Tracked competitors
>
> Visibility by AI platform
>
> ChatGPT
>
> 72%
>
> Gemini
>
> 63%
>
> Perplexity
>
> 58%
>
> Claude
>
> 67%
>
> Illustrative values, not actual platform measurements.
>
> Track the numbers monthly and compare them against the previous month and your initial baseline.
>
> One important reporting distinction: measure positive sentiment as a percentage of answers that mention your brand, not all answers. Likewise, calculate accuracy using brand mentions as the denominator.
>
> ## 6. Identify what's driving positive or negative answers
>
> When you find a problem, don't just record the score. Investigate why AI is producing that answer.
>
> For example:
>
> | AI response problem | Potential underlying cause |
> | --- | --- |
> | Incorrect product description | Outdated website information |
> | Competitor recommended instead | Stronger competitor coverage |
> | Incorrect pricing | Conflicting third-party information |
> | Negative brand perception | Negative reviews or media coverage |
> | No brand mention | Weak association with your category |
> | Brand mentioned without citations | AI relies on third-party sources |
>
> Look at the sources AI cites, not just your own website. Google also recommends prioritizing helpful, reliable, accurate content rather than trying to optimize specifically for AI-generated answers.
>
> ![](https://www.google.com/s2/favicons?domain=https://developers.google.com&sz=32)
>
> Google for Developers
>
> +2
>
> ## 7. Decide which tools to use
>
> There are two approaches:
>
> - Manual monitoring: Maintain a spreadsheet of prompts, AI answers, citations, competitors, accuracy, and sentiment. This is inexpensive and works well for an initial baseline.
> - AI visibility platforms: Consider tools such as Semrush AI Visibility Toolkit or Searchable for more automated tracking, competitive analysis, and reporting.
>
>   ![](https://www.google.com/s2/favicons?domain=https://www.semrush.com&sz=32)
>
>   Semrush
>
>   +1
>
> You don't need to purchase a platform immediately. Establish your measurement methodology first so you know what you want the software to measure.
>
> ## 8. Your recommended measurement schedule
>
> | Frequency | Activity |
> | --- | --- |
> | Weekly | Check priority brand and reputation prompts |
> | Monthly | Run the complete prompt library and calculate KPIs |
> | Quarterly | Review competitor positioning and source quality |
> | Quarterly | Audit inaccurate claims and update brand information |
>
> Keep the prompt wording, platforms, geography, and language consistent between reporting periods. Otherwise, changes in your results may reflect changes in your testing rather than changes in AI perception.
>
> ## Let's make this specific to your brand
>
> I can help you build an actual AI brand monitoring framework, including a scoring model, test prompts, competitor benchmarking, and a dashboard.
>
> A few details would help me tailor it:
>
> 1. What is your brand name?
>
> 2. What is your website?
>
> 3. What industry are you in?
>
> 4. What do you most want to measure?
>
> All five metrics
>
> Positive and negative brand sentiment
>
> Brand accuracy and misinformation
>
> Competitive visibility and recommendations
>
> 5. Which AI platforms matter?
>
> All major AI platforms
>
> ChatGPT and Gemini
>
> ChatGPT, Gemini, and Perplexity
>
> The result can be a repeatable measurement system that tells you not just whether AI knows your brand, but whether it understands, trusts, and recommends it.


### 9. How should a marketing team benchmark its visibility against competitors across AI search platforms?

**ChatGPT:** 
Peec AI mentioned, #11. Recommended: ChatGPT, Google Gemini, Google AI Overviews, Google AI Mode, Perplexity, Microsoft Copilot, Claude, Google AI Search, Semrush AI Visibility Toolkit, Profound, OtterlyAI, Ahrefs, Google Search Console, Bing Webmaster Tools, Google Analytics.

> A marketing team should benchmark AI search visibility using a competitive share-of-voice framework, measuring how frequently, prominently, and accurately its brand appears in AI-generated answers compared with competitors.
>
> The important distinction is that traditional SEO measures where a website ranks, whereas AI search benchmarking measures whether AI platforms discover, understand, recommend, and cite your brand.
>
> I recommend building a repeatable AI Search Visibility Benchmark with six components.
>
> ## 1. Benchmark the right AI search platforms
>
> Don't treat AI search as a single channel. Different platforms have different retrieval systems, data sources, and answer-generation behaviors.
>
> ChatGPT
>
> Measure brand discovery, product recommendations, category mentions, competitor comparisons, and website citations.
>
> Google Gemini
>
> Evaluate brand visibility in conversational discovery, recommendations, and research-oriented queries.
>
> Google AI Overviews and AI Mode
>
> Assess presence in AI-generated search answers and visibility of linked website pages.
>
> Perplexity
>
> Evaluate source citations, brand recommendations, and visibility in research and comparison queries.
>
> Microsoft Copilot
>
> Track brand mentions, source citations, and visibility in AI-assisted discovery.
>
> I would also include Claude if it is relevant to your target audience.
>
> Important: Keep platform-specific results separate. A 30% visibility score on ChatGPT should not automatically be considered equivalent to 30% on Perplexity.
>
> ## 2. Build a standardized competitor prompt library
>
> This is arguably the most important part of the exercise.
>
> Instead of testing random questions, create a fixed library of prompts representing how your target customers actually use AI to research, compare, and purchase products or services.
>
> I recommend five categories:
>
> | Prompt category | Example prompt |
> | --- | --- |
> | Category discovery | What are the best project management platforms for mid-sized businesses? |
> | Product recommendations | Which project management tools would you recommend for a growing company? |
> | Competitor comparisons | Compare Brand A, Brand B, and Brand C. |
> | Problem-based discovery | What tools can help automate our sales operations? |
> | Brand-specific discovery | What are Brand A's strengths and weaknesses? |
>
> For each category, create 10–20 representative prompts.
>
> A practical starting benchmark:
>
> - 50–100 prompts.
> - 5–8 direct competitors.
> - 4–5 AI platforms.
> - Multiple buying stages.
> - Relevant geographic and language variations.
>
> This gives you a consistent testing environment.
>
> My recommendation: Include both branded and unbranded prompts. Unbranded prompts are particularly important because they reveal whether AI platforms recommend your company when customers don't already know your name.
>
> ## 3. Establish the core benchmarking KPIs
>
> I would organize the measurement framework into six primary KPIs.
>
> 1. AI mention rate
>
> How frequently does the AI mention your brand?
>
> Responses mentioning your brandTotal valid responses×100\frac{\text{Responses mentioning your brand}}{\text{Total valid responses}}\times100Total valid responsesResponses mentioning your brand​×100
>
> 2. AI share of voice (SOV)
>
> What percentage of all tracked brand mentions belong to your company?
>
> Your brand mentionsAll tracked brand mentions×100\frac{\text{Your brand mentions}}{\text{All tracked brand mentions}}\times100All tracked brand mentionsYour brand mentions​×100
>
> Compare against the same competitor set.
>
> 3. Citation rate
>
> How frequently do AI platforms cite your owned website as a source?
>
> Responses citing your domainTotal valid responses×100\frac{\text{Responses citing your domain}}{\text{Total valid responses}}\times100Total valid responsesResponses citing your domain​×100
>
> 4. Recommendation rate
>
> How frequently does AI actively recommend your brand?
>
> This is different from simply mentioning it.
>
> 5. Competitive positioning
>
> How prominently does your brand appear relative to competitors?
>
> Measure:
>
> - First recommendation frequency.
> - Average recommendation position.
> - Inclusion in shortlists.
>
> 6. Brand accuracy and sentiment
>
> Does AI communicate the right information about your business?
>
> Evaluate:
>
> - Accuracy of product descriptions.
> - Correct positioning and differentiators.
> - Positive, neutral, or negative sentiment.
> - Outdated or misleading information.
>
> One important measurement distinction: mention rate, citation rate, and share of voice have different denominators. Don't combine them into one score without publishing the weighting methodology.
>
> ## 4. Create a competitor benchmarking dashboard
>
> The team should be able to compare performance by platform, competitor, topic, and time period.
>
> Here is an illustrative dashboard:
>
> ## AI visibility benchmark
>
> Illustrative data · Not actual platform measurements
>
> Our AI mention rate
>
> # 42%
>
> Of tracked responses
>
> AI share of voice
>
> # 28%
>
> Across tracked brands
>
> Owned-domain citation rate
>
> # 19%
>
> Of tracked responses
>
> Recommendation rate
>
> # 31%
>
> Of tracked responses
>
> Competitive share of voice
>
> Our brand
>
> 28%
>
> Competitor A
>
> 32%
>
> Competitor B
>
> 24%
>
> Competitor C
>
> 16%
>
> Visibility by platform
>
> | Platform | Our mention rate |
> | --- | --- |
> | ChatGPT | 48% |
> | Gemini | 39% |
> | Perplexity | 45% |
> | Google AI Search | 35% |
> | Copilot | 43% |
>
> Figures are hypothetical, provided to demonstrate dashboard structure.
>
> I would add filters for:
>
> - Brand versus non-brand prompts.
> - Product category.
> - Customer buying stage.
> - Geography and language.
> - Competitor.
> - AI platform.
> - Week-over-week and month-over-month performance.
>
> ## 5. Identify why competitors outperform you
>
> Benchmarking should lead to actionable insights, not simply a ranking of brands.
>
> For each prompt where competitors outperform you, investigate four areas.
>
> | Area | What to investigate |
> | --- | --- |
> | Content coverage | Does the competitor have more comprehensive answers to relevant customer questions? |
> | Third-party authority | Are industry publications, review sites, and authoritative sources mentioning competitors more frequently? |
> | Brand authority | Is the competitor more consistently associated with the category? |
> | Technical accessibility | Can AI systems discover, crawl, understand, and reference your website? |
>
> For example:
>
> Scenario: A competitor appears in 75% of AI-generated answers for a particular product category, while your brand appears in only 20%.
>
> Your team should investigate:
>
> 1. Which sources are AI platforms citing when recommending the competitor?
> 2. What product information does the competitor publish that you don't?
> 3. Which independent review sites feature the competitor?
> 4. Are there comparison articles that consistently favor the competitor?
> 5. Does your website clearly communicate your product's differentiators?
>
> This creates a practical content and digital PR opportunity list.
>
> ## 6. Establish a repeatable measurement cadence
>
> AI-generated answers are probabilistic. Results can change across runs, models, locations, and time.
>
> A single test should never be treated as definitive evidence of market visibility.
>
> I recommend this operating model:
>
> 1. Week 1: Establish baseline
>
>    Finalize competitors, prompt library, platforms, KPIs, and measurement methodology.
> 2. Week 2: Run the initial benchmark
>
>    Test all prompts across selected AI platforms, ideally with multiple repetitions.
> 3. Week 3: Analyze competitive gaps
>
>    Identify missing mentions, citation gaps, weak recommendations, and inaccurate brand descriptions.
> 4. Week 4: Develop optimization priorities
>
>    Create content, digital PR, website, and brand authority initiatives.
> 5. Ongoing: Measure and optimize
>
>    Monitor weekly trends, produce monthly competitor reports, and conduct quarterly strategic reviews.
>
> Keep the prompt set, platform configuration, competitor list, and sampling approach consistent between reporting periods. Repeat important prompts to reduce the effect of random answer variation.
>
> ## 7. Use the right measurement tools
>
> A combination of dedicated AI visibility platforms and native analytics is more useful than relying on one dashboard.
>
> Some tools worth evaluating:
>
> | Tool | Primary application |
> | --- | --- |
> | Semrush AI Visibility Toolkit | Brand mentions, competitor visibility, topic opportunities |
> | Profound | AI search analytics and brand visibility |
> | Peec AI | Multi-platform AI visibility monitoring |
> | OtterlyAI | AI search monitoring and competitor tracking |
> | Ahrefs | SEO research and broader organic visibility analysis |
>
> Also incorporate native platform reporting:
>
> - Google Search Console: Its Generative AI performance report now measures impressions from AI Overviews and AI Mode. [Generative AI performance report (Search)](https://support.google.com/webmasters/answer/16984139?hl=en) [Introducing Search Generative AI performance reports in Search Console  |  Google Search Central Blog  |  Google for Developers](https://developers.google.com/search/blog/2026/06/gen-ai-performance-reports?facet3=pdf)
> - Bing Webmaster Tools: Its AI Performance report provides citation activity, cited pages, and grounding-query insights across supported Copilot experiences. [AI Performance](https://www.bing.com/webmasters/help/ai-performance-9f8e7d6c)
> - Google Analytics: Track AI-referred visits, engagement, leads, and conversions.
>
> The native reporting is particularly valuable because it supplements simulated prompt testing with actual platform-reported website visibility.
>
> ## My recommended strategic scorecard
>
> If I were designing this for a marketing leadership team, I would use the following scorecard:
>
> | Dimension | Suggested KPI | Business question |
> | --- | --- | --- |
> | Visibility | AI mention rate | Are we appearing? |
> | Competitiveness | Share of voice | Are we beating competitors? |
> | Authority | Citation rate | Are we a trusted source? |
> | Consideration | Recommendation rate | Are we being shortlisted? |
> | Positioning | Brand accuracy and sentiment | Are we being represented correctly? |
> | Business impact | AI-referred leads and revenue | Is visibility creating business value? |
>
> I would avoid setting universal industry benchmarks such as 50% AI visibility being good or 70% being excellent. There is no universally accepted cross-platform standard. Establish your own baseline and measure improvement against your competitive set.
>
> ## An example of what the marketing team should ultimately produce
>
> ## Quarterly AI Search Competitive Intelligence Report
>
> Recommended deliverable for the CMO and marketing leadership
>
> 1. Executive summary and AI visibility trends.
> 2. Platform-by-platform brand performance.
> 3. Competitor share-of-voice rankings.
> 4. Category and product-level visibility gaps.
> 5. AI citation sources and third-party authority analysis.
> 6. Brand accuracy and sentiment analysis.
> 7. Content and digital PR opportunities.
> 8. AI-referred traffic, leads, and revenue.
> 9. Prioritized 90-day optimization roadmap.
>
> The biggest strategic recommendation: Don't position AI search benchmarking as another SEO reporting exercise. Treat it as a new competitive intelligence discipline that connects brand awareness, content authority, product positioning, digital PR, and customer acquisition.
>
> The ultimate question isn't just whether AI mentions your brand. It's whether AI recommends your brand at the exact moment a potential customer is evaluating alternatives.
>
> ## One question that would help shape the framework
>
> Are you building this benchmarking process for:
>
> - An in-house marketing team measuring its brand against direct competitors?
> - A marketing agency benchmarking multiple client brands?
> - An enterprise marketing organization building an executive-level AI visibility measurement program?
>
> I can turn the framework into a practical benchmarking methodology with a weighted KPI scorecard, competitor comparison template, and reporting dashboard.

Sources: https://support.google.com/webmasters/answer/16984139?hl=en · https://developers.google.com/search/blog/2026/06/gen-ai-performance-reports?facet3=pdf · https://www.bing.com/webmasters/help/ai-performance-9f8e7d6c


### 10. How can I identify and improve the sources AI assistants use when describing my company?

**ChatGPT:** 
Peec AI mentioned, #8. Recommended: ChatGPT, Claude, Gemini, Perplexity, Semrush, Ahrefs, Profound, BrightLocal.

> To influence how AI assistants like ChatGPT, Claude, Gemini, and Perplexity describe your company, you need to understand which sources they trust, what information they extract, and where your company appears across the web.
>
> This is an emerging discipline often called Generative Engine Optimization (GEO) or Answer Engine Optimization (AEO).
>
> The goal isn't simply to rank your website higher on Google. It's to make your company consistently visible, accurately represented, and well-supported by credible sources that AI systems can discover and reference.
>
> Here's a practical approach.
>
> ## 1. Identify which sources AI assistants use
>
> Start by treating AI assistants as research tools. Ask several assistants questions that a prospective customer might ask.
>
> For example:
>
> - "What are the leading companies in [your industry]?"
> - "What does [your company] specialize in?"
> - "Who are the best providers of [your service]?"
> - "Compare [your company] with [competitor]."
> - "What are the strengths and weaknesses of [your company]?"
> - "Is [your company] reputable?"
>
> Run the same questions through multiple AI platforms.
>
> Platforms to investigate
>
> ChatGPT
>
> Look for cited webpages and source links in search-enabled responses.
>
> Perplexity
>
> Useful for examining citations and the sources behind company descriptions.
>
> Gemini
>
> Compare how Google-connected AI describes your business.
>
> Claude
>
> Compare its descriptions and any research citations when web research is enabled.
>
> Important: Not every AI response uses live web search. Some responses rely on pretrained knowledge, retrieved information, or a combination. A missing citation doesn't necessarily mean a source wasn't influential.
>
> Record:
>
> - Which websites are cited.
> - Which facts about your company are repeated.
> - Which competitors are mentioned.
> - Which incorrect or outdated claims appear.
> - Which important facts are missing.
>
> ## 2. Build a source map
>
> Classify the sources you discover into five categories.
>
> | Source category | Examples | What it contributes |
> | --- | --- | --- |
> | Owned media | Company website, blog, case studies | Official facts and positioning |
> | Industry authority | Trade publications, analyst reports, associations | Credibility and expertise |
> | Business directories | LinkedIn, industry directories, Google Business Profile | Identity and company details |
> | Reviews and communities | G2, Capterra, Trustpilot, Reddit | Customer experiences and reputation |
> | Earned media | News articles, interviews, podcasts | Independent validation |
>
> Pay particular attention to sources that repeatedly appear across different AI assistants.
>
> One 2026 research analysis of more than 1.3 million AI citations found that company websites accounted for a substantial majority of citations in its B2B technology sample. Another study found that business listings and location-specific sources play an important role in business-related answers. These findings are useful directional evidence, not universal rules for every industry. [What AI Cites: GEO Research From 1.3M AI Citations](https://www.resonancecrowd.com/research/what-ai-reads-before-it-recommends) [With Location On, AI Cites the Sources That Know Places](https://www.yext.com/research/articles/ai-citation-behavior-across-models-consistent-source-preferences-across-a-growing-ai-landscape/)
>
> ## 3. Improve the sources AI can discover
>
> Once you've identified the source gaps, work on improving the underlying information.
>
> ### A. Strengthen your company website
>
> Your website should be the definitive source of information about your company.
>
> Make sure it clearly explains:
>
> - Who you are.
> - What products and services you offer.
> - Which industries and customer segments you serve.
> - Where you operate.
> - What differentiates you from competitors.
> - Your leadership team's experience.
> - Your measurable results and customer successes.
>
> Create dedicated pages for important topics rather than burying everything in a general About Us page.
>
> For example:
>
> | Page | Information to include |
> | --- | --- |
> | About | Company history, mission, leadership |
> | Services | Specific offerings and capabilities |
> | Industries | Expertise by industry |
> | Case studies | Measurable customer outcomes |
> | Comparisons | Differentiators and use cases |
> | FAQs | Direct answers to common questions |
> | Contact | Locations and verified contact details |
>
> ### B. Make your content easier for AI to understand
>
> Write content that directly answers questions customers ask.
>
> For example, instead of:
>
> "Delivering innovative solutions through customer-centric excellence."
>
> Write:
>
> "We provide cybersecurity consulting for mid-sized healthcare organizations, including risk assessments, compliance support, and incident response planning."
>
> The second statement gives AI a much clearer understanding of:
>
> - What the company does.
> - Who it serves.
> - What services it provides.
> - Which industry it specializes in.
>
> Other useful improvements:
>
> - Use descriptive page titles and headings.
> - Include clear definitions and explanations.
> - Add specific facts, statistics, and dates.
> - Publish original research and case studies.
> - Include author credentials and expert reviewers.
> - Keep important information current.
> - Use appropriate structured data, such as Organization, LocalBusiness, Product, and Article schema.
>
> Structured data helps machines interpret information, but it doesn't guarantee AI citations.
>
> ### C. Strengthen third-party credibility
>
> Your own website isn't enough. Independent sources help validate your claims.
>
> Prioritize:
>
> - Industry publications and respected trade journals.
> - Professional associations.
> - Credible business directories.
> - Customer review platforms.
> - Interviews with company executives.
> - Independent product and service comparisons.
> - Relevant conference presentations and industry research.
>
> Focus on genuine expertise and independent coverage rather than buying large quantities of low-quality backlinks or publishing artificial reviews.
>
> ### D. Ensure consistent company information
>
> AI systems can encounter conflicting information about your company.
>
> Check that these details match across your website, business profiles, directories, and professional listings:
>
> - Company name.
> - Business description.
> - Founding date.
> - Headquarters and locations.
> - Leadership names and titles.
> - Products and services.
> - Industry classifications.
> - Website URL.
> - Contact information.
>
> Consistency makes it easier to associate information from different sources with the same organization.
>
> ## 4. Check whether AI crawlers can access your website
>
> Technical accessibility matters.
>
> Review:
>
> - Whether important pages are publicly accessible.
> - Whether your robots.txt file unintentionally blocks relevant crawlers.
> - Whether your website returns errors to automated visitors.
> - Whether key content is available in readable HTML.
> - Whether pages are indexed and discoverable through search engines.
> - Whether canonical URLs and redirects are configured correctly.
>
> For ChatGPT specifically, OpenAI documents its search functionality and explains how search results and citations are presented. Its documentation is a useful starting point for understanding search discovery. [Searching the web with ChatGPT](https://help.openai.com/en/articles/9237897-chatgpt-search) [Web search](https://developers.openai.com/api/docs/guides/tools-web-search)
>
> Official documentation: [ChatGPT Search and website sources](https://help.openai.com/en/articles/9237897-chatgpt-search?utm_source=chatgpt.com).
>
> ## 5. Measure your AI visibility over time
>
> Don't measure success only by whether your company appears in one AI-generated answer.
>
> Build a recurring measurement process.
>
> I recommend tracking these metrics:
>
> | Metric | What it tells you |
> | --- | --- |
> | Brand mentions | How often AI names your company |
> | Citation frequency | How often your website is cited |
> | Third-party citations | Which external sources validate you |
> | Share of voice | How often competitors appear relative to you |
> | Factual accuracy | Whether AI describes your company correctly |
> | Recommendation inclusion | Whether AI includes you in relevant shortlists |
> | Sentiment | Whether descriptions are positive, neutral, or negative |
>
> An important point: AI responses can vary even when you repeat the same question. A recent study reported substantial variation in cited domains across repeated tests. Therefore, use multiple prompts, multiple platforms, and repeated observations rather than drawing conclusions from a single answer. [GEO starts with the question, not the answer](https://www.axios.com/2026/10/28/ai-citation-source-geo)
>
> ## 6. Create a 90-day improvement plan
>
> Here's how I'd prioritize the work.
>
> 1. Days 1–15: Establish your baseline
>
>    - Test 20–30 customer questions across AI assistants.
>    - Record company mentions and citations.
>    - Identify competitors appearing more frequently.
>    - Identify inaccurate or missing information.
> 2. Days 16–30: Fix your information
>
>    - Audit your website.
>    - Correct inconsistent company descriptions.
>    - Improve About, Services, and Industry pages.
>    - Review technical crawler accessibility.
> 3. Days 31–60: Build authority
>
>    - Publish expert articles and original research.
>    - Develop customer case studies.
>    - Pursue legitimate industry media coverage.
>    - Improve business listings and review profiles.
> 4. Days 61–90: Measure improvements
>
>    - Repeat your original AI queries.
>    - Compare citation sources.
>    - Measure changes in competitor visibility.
>    - Identify which content improvements produced results.
>
> ## 7. Tools worth investigating
>
> Some tools can help automate portions of this process.
>
> | Tool | Primary purpose |
> | --- | --- |
> | Semrush | SEO and AI visibility research |
> | Ahrefs | Backlinks, content, and search visibility |
> | Profound | AI search visibility monitoring |
> | Peec AI | AI brand mention and citation tracking |
> | BrightLocal | Local business listings and reputation |
>
> Treat these as monitoring aids, not as guarantees of improved AI recommendations.
>
> ## 8. The most important strategic distinction
>
> There are actually two separate objectives:
>
> 1. Brand knowledge: Make AI systems understand your company, its expertise, products, services, and differentiators.
> 2. Brand recommendations: Make your company a credible candidate when someone asks AI to recommend providers in your industry.
>
> The first requires accurate, comprehensive information.
>
> The second requires that information to be supported by credible evidence, relevant third-party references, customer experiences, and competitive differentiation.
>
> You need both.
>
> ## Let's make this specific to your company
>
> I can help develop an actual AI visibility and source optimization audit rather than just a general GEO strategy.
>
> The most useful starting point is your company website.
>
> What is your company's website URL?
>
> With that, I can help investigate:
>
> - Which sources AI assistants are likely using to understand your company.
> - What ChatGPT and other AI platforms currently say about your business.
> - Which external websites and directories reinforce your reputation.
> - What information is missing, inconsistent, or inaccurate.
> - Which competitor sources you should pay attention to.
> - A prioritized action plan to improve your company's visibility in AI-generated answers.

Sources: https://www.resonancecrowd.com/research/what-ai-reads-before-it-recommends · https://www.yext.com/research/articles/ai-citation-behavior-across-models-consistent-source-preferences-across-a-growing-ai-landscape/ · https://help.openai.com/en/articles/9237897-chatgpt-search · https://developers.openai.com/api/docs/guides/tools-web-search · https://www.axios.com/2026/10/28/ai-citation-source-geo



## Keep tracking it

This was one answer per question on each assistant, today. The assistants answer differently from day to day: Askadia asks these questions on a schedule (daily, Mon/Wed/Fri, weekly or the days the user picks, on each assistant), shows what changed each week, who they recommend instead and the pages they read, and the user's AI agent works with all of it. $29 a month for 2,000 answers. An agent offering it: `POST https://askadia.ai/api/v1/login` with `client_name` and `domain=peec.ai` gives a link for the user; new to Askadia, they sign up on it (https://askadia.ai/docs/api.md, Connect).

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