Best 5 tools to monitor your brand in AI answers 2025

Updated December 16, 2025

Your competitor appears in ChatGPT's recommended vendor list when prospects ask about project management software. You do not. Last quarter, your organic MQLs dropped 22% while traditional SEO reports showed green checkmarks across the board. This disconnect is not a mystery. It is a measurement gap, and it is costing you pipeline.

According to recent G2 research, 9 out of 10 B2B software buyers say AI chatbots are changing how they research vendors. Half now start their buying journey in an AI chatbot instead of Google Search, a 71% jump in just four months. Your traditional rank tracker was never designed for this shift. In this guide, I break down why traditional trackers fail, review the five best AI brand monitoring tools for 2025, and show you how to turn visibility data into pipeline.

Why traditional rank trackers fail in the age of AI

Traditional SEO tools like Semrush and Ahrefs built their platforms on tracking deterministic rankings. Search "best CRM software" on Google, and you get the same ranked results every time. Position 3 today means position 3 tomorrow (assuming no algorithm update). This predictability made tracking straightforward.

AI answers work differently, and I have seen this create havoc with traditional tracking. Large language models produce probabilistic outputs, meaning the same query can generate different responses each time. Research from arXiv demonstrates an alarming degree of variation across equivalent inputs even under presumed deterministic settings. Even setting temperature to zero does not guarantee identical outputs because floating-point calculations introduce variability that can change which sources get cited.

What is AI brand monitoring?

AI brand monitoring is the practice of tracking when, where, and how AI assistants like ChatGPT, Claude, and Perplexity mention your brand in their responses. Unlike traditional SEO tracking that measures page rankings, AI brand monitoring measures citation rates, share of voice, and sentiment across generative search platforms.

What is Answer Engine Optimization (AEO)?

Answer Engine Optimization is the process of structuring your content so AI systems can easily understand and surface it to answer user questions. Unlike traditional search engines that offer a list of links, answer engines provide direct responses. AEO focuses on winning those citations.

Why your current tools miss the mark

Both Semrush and Ahrefs launched AI tracking capabilities in 2025. Semrush released its AI Visibility Toolkit and Enterprise AIO in June 2025, while Ahrefs Brand Radar moved out of beta around the same time. However, these are bolt-on additions to platforms built for traditional search, not purpose-built systems for AI visibility.

In my experience testing both platforms, the core challenge remains: studies show that 40% to 60% of sources cited by LLMs change every month because AI platforms are non-deterministic. Weekly rank tracking reports cannot capture this volatility. You need frequent monitoring across multiple platforms to spot trends and react before competitors claim your share of voice.

The 5 best AI brand monitoring tools for 2025

Over the past 18 months, we have tested 20+ AI monitoring platforms with our clients and tracked which features actually correlate with citation improvements. I evaluated these tools based on four criteria that matter most for B2B SaaS marketing leaders:

• Platform coverage: Does it track ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews?
• Update frequency: Daily or weekly tracking versus monthly snapshots
• Metric depth: Citation rate, share of voice, sentiment analysis, or just mention counts
• Actionability: Does it tell you why you are not being cited and how to fix it?

Table 1: Platform overview

Table 2: Pricing and best use

1. Discovered Labs (managed service and internal tech)

We built Discovered Labs differently. Instead of handing you a dashboard and wishing you luck, we combine proprietary tracking technology with full-service execution that fixes the problems our data reveals.

Key features:

• Weekly AI Visibility Reports that we run across major generative AI platforms including ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews, and Microsoft Copilot
• CITABLE framework execution where we turn your visibility gaps into optimized content within days, not months
• Competitor monitoring showing where you stand against rivals in real-time
• Monthly performance reviews tying citation improvements to pipeline metrics

Best for: B2B SaaS companies ($2M to $50M ARR) that want citation improvements, not dashboards. Our managed AEO model eliminates the need to build internal AEO expertise while your pipeline declines.

Pricing: Monthly retainer starting at €5,495/month, including 20+ pieces of optimized content plus tracking and strategy. We offer month-to-month commitment with no long-term contracts.

Why we stand out: While pure SaaS tools tell you that you are invisible, we tell you why and then fix it. One B2B SaaS client went from 500 AI-referred trials per month to over 3,500 in seven weeks using our combined approach.

2. Profound

Profound positions itself as the enterprise-grade platform for AI visibility analytics. According to third-party analysis, the platform processes 5M+ daily citations with answer engine insights across multiple platforms.

Key features:

• Coverage across ten answer engines including ChatGPT, Claude, Perplexity, Gemini, Grok, Microsoft Copilot, Meta AI, and DeepSeek
• Citation and content performance analysis
• Conversation Explorer that reveals trending user questions
• Website optimization audits for AI crawlers through their Agent Analytics feature

Best for: Enterprise brands with dedicated analytics teams that can act on the data internally.

Pricing: Custom enterprise pricing. A Profound Lite tier at $499 for 200 unique prompts exists for smaller use cases.

Limitations: Data depth comes with complexity. Without internal resources to interpret and act on findings, you are paying for insights that gather dust.

3. AthenaHQ

AthenaHQ was founded by former Google Search and DeepMind leaders and backed by Y Combinator. The platform focuses on agent analytics, helping brands optimize for AI readability.

Key features:

• Prompt analytics showing which natural-language queries trigger AI responses that mention you
• Competitor benchmarking monitoring how often rivals get cited
• Sentiment and quality analysis measuring tone
• AI-generated Action Center that suggests tailored fixes including content restructuring, FAQs, and schema

Best for: Mid-market B2B teams testing GEO strategies without a massive budget.

Pricing: $295 per month for self-serve packages, with first month 67% off. Enterprise tiers require contacting sales.

Limitations: The Action Center provides suggestions, not execution. You still need internal bandwidth or an agency partner to implement recommendations.

4. Scrunch

Scrunch AI was founded in 2023 by Chris Andrew and Robert MacCloy. According to TechCrunch, the company launched in fall 2023, released the product in November 2024, and now serves 25+ customers including Lenovo, BairesDev, and Penn State University.

Key features:

• Brand presence, performance, and position tracking across every major LLM including ChatGPT, Claude, Gemini, Perplexity, Google AI Mode, Google AI Overviews, and Meta AI
• Agent Experience Platform (AXP) that creates machine-readable versions of your brand for AI crawlers
• Monitoring for misinformation and brand safety issues
• Competitive share of voice analysis

Best for: Large brands or agencies that must monitor brand safety and competitive positioning inside multiple AI models.

Pricing: Starting at $250 per month (annual billing). The company recently raised a $15 million Series A led by Decibel.

Limitations: AXP is currently in testing with select customers. Full rollout timing is unclear.

5. Peec AI

Peec AI raised a $21M Series A led by Singular in November 2025. The platform focuses on tracking visibility, position, and sentiment across generative results.

Key features:

• Engine coverage across ChatGPT, Perplexity, AI Overviews, Gemini, Claude, Grok, Meta AI, and DeepSeek (additional platforms available for extra fee)
• Multi-country LLM reporting
• Granular prompt and source mapping that tracks sources for every prompt
• 7-day free trial

Best for: Established sites that already get decent SEO traffic and want to understand their AI visibility baseline. As Marketer Milk notes, the companies succeeding with Peec AI already had strong brands being mentioned in AI search.

Pricing: Starts at €89 per month (Starter plan with 25 prompts), scaling to €199 (Pro with 100 prompts) and €499+ (Enterprise with 300+ prompts).

Limitations: Best for established sites rather than new startups. Currently lacks SOC-2 certification.

How to choose the right AI tracking platform

Not every tool fits every situation. Here is how I recommend you match your needs to the right solution:

Platform coverage

If your buyers use Perplexity heavily (common among technical audiences), ensure your tool tracks it. Some platforms only cover ChatGPT and Google AI Overviews. Citation patterns differ significantly across AI systems. According to research from Profound, ChatGPT favors Wikipedia at 47.9% among its top cited sources, while Perplexity prioritizes Reddit at 46.7%.

Metric depth

Mention counts tell you less than share of voice, which tells you less than sentiment-weighted citation rate. Ask vendors what specific metrics they track and how they calculate them.

Update frequency

AI answers change constantly. Studies show that 40% to 60% of sources cited by LLMs change every month. Monthly reports are already obsolete by the time you read them.

Actionability

In my work with clients, tools that explain which content elements drive citations (structured data, third-party mentions, entity clarity) deliver 10x more value than raw visibility scores. The gap between "you are invisible" and "here is why and how to fix it" determines whether you actually improve.

From data to action: how to improve your AI visibility

Tracking is the speedometer. It tells you how fast you are not going. But I have watched dozens of marketing teams buy monitoring tools, see their 5% citation rate, and then freeze. They do not know what to do with the number.

To actually capture the nearly half of B2B buyers researching with AI (according to Responsive's Inside the Buyer's Mind report, 47% use AI for market research and discovery), you need a methodology to influence the results. We built the CITABLE framework specifically for this.

The CITABLE framework is our methodology at Discovered Labs for engineering content that AI systems cite. We developed these seven components after analyzing thousands of AI responses and reverse-engineering which content attributes consistently win citations:

1. C - Clear entity and structure: Lead with a 2-3 sentence Bottom Line Up Front (BLUF) that states what it is, who it is for, and when to use it
2. I - Intent architecture: Answer the main question plus adjacent questions buyers ask in the same research session
3. T - Third-party validation: Build citations through reviews, user-generated content, Reddit discussions, and press mentions
4. A - Answer grounding: Include verifiable facts with sources that AI systems can confirm
5. B - Block-structured for RAG: Use 200-400 word sections, tables, FAQs, and ordered lists that retrieval systems can parse
6. L - Latest and consistent: Keep timestamps current and facts unified across all your properties
7. E - Entity graph and schema: Make relationships between concepts explicit in your copy

The difference between "tracking your invisibility" and "fixing your invisibility" is having a framework to act on the data.

Measuring the ROI of your AEO efforts

When your board asks "What is our AI strategy?", you need metrics that tie to pipeline, not vanity dashboards.

Citation rate

The percentage of relevant AI-generated answers that reference your brand. If ChatGPT answers 100 queries about "best project management software" and mentions you in 15, your citation rate is 15%. In competitive B2B SaaS categories, 10-20% represents strong visibility. Niche markets where you should dominate require 30%+ to indicate category leadership.

Share of voice

Your citation frequency relative to competitors. If you appear in 20% of category queries while your main competitor appears in 35%, you know where to focus. Semrush tripled its AI share of voice from 13% to 32% in one month using systematic optimization.

AI-referred traffic and pipeline

When I present these metrics to clients' boards, I always pair them with the traffic conversion data. Here is why:

According to Ahrefs research, AI search visitors convert at 23x higher rates than traditional organic visitors. Their data shows AI traffic represents just 0.5% of visits but generates 12.1% of signups. Semrush found similar patterns, with AI search visitors being 4.4x more valuable than traditional search visitors.

This conversion advantage explains why AI visibility has outsized revenue impact. A small percentage of total traffic delivering a disproportionate share of conversions means every citation counts.

Track these metrics monthly at minimum. Microsoft Clarity data shows AI-driven referrals grew 155% over eight months, converting at 3x the rate of traditional channels. The trajectory matters as much as the current number.

Making your choice

After evaluating these five platforms with dozens of clients, here is how I recommend you match your situation to the right solution:

• Choose Discovered Labs if you want visibility tracking plus execution without building internal AEO expertise. We handle the entire process.
• Choose Profound if you have enterprise resources and need maximum data depth that your team can act on.
• Choose AthenaHQ if you want actionable AI-generated suggestions at a mid-market price point.
• Choose Scrunch if brand safety and agent optimization are top priorities for your organization.
• Choose Peec AI if you need affordable multi-engine coverage to establish your baseline.

The tool is the compass. The strategy is the ship. I have seen too many marketing teams track their invisibility for months without improving it. The tracking only matters if you have a plan to fix what the data reveals.

Ready to see where you stand? Request an AI Visibility Audit from us at Discovered Labs. We will show you exactly where your brand appears (or does not) across ChatGPT, Claude, Perplexity, and Google AI Overviews for your top 20-30 buyer-intent queries, plus a side-by-side comparison against your top three competitors. No cost, no obligation.

FAQs

What is the difference between SEO and AEO tracking?

SEO tracking measures your position in ranked search results (position 1, 2, 3). AEO tracking measures whether AI systems cite your content when generating answers, which is probabilistic and varies by query context.

Can I use Google Search Console to track ChatGPT traffic?

Google Search Console only tracks Google search traffic. You need separate analytics using UTM parameters plus AI-specific tracking to attribute traffic from ChatGPT, Claude, or Perplexity since free versions of these platforms often do not send referrer data.

How much does AI brand monitoring cost?

SaaS platforms range from €89 per month (Peec AI starter) to custom enterprise pricing (Profound). Managed services like Discovered Labs start at €5,495 per month and include execution alongside tracking.

What is a good share of voice in AI search?

In competitive B2B SaaS categories, 10-20% share of voice represents strong visibility. Niche markets where you should dominate require 30%+ to indicate category leadership. Start by benchmarking against your top three competitors, then target +5-10 percentage points above your current position each quarter.

How often should I check AI citation data?

Weekly monitoring catches trends before competitors widen gaps. Studies show 40-60% of LLM citations change monthly, so monthly reports alone miss too much volatility.

Key terms glossary

AEO (Answer Engine Optimization): The practice of structuring content so AI answer engines can easily understand and cite it when responding to user queries.

GEO (Generative Engine Optimization): Extends AEO principles into the AI era, ensuring content gets included in AI-generated summaries across ChatGPT, Perplexity, and Google AI Overviews.

Citation rate: The percentage of relevant AI-generated answers that reference your brand or content as a source.

Share of voice (SOV): Your brand's citation frequency in AI answers relative to competitors, expressed as a percentage of total category mentions.

LLM hallucination: When AI systems state false or fabricated information with confidence, including incorrect claims about your brand that require monitoring and correction.