Most ChatGPT tracking tools tell you how often you show up. None of them tell you why the model picked the story it’s telling about your category, which is the part that actually decides who gets recommended.
The Tracking Tool Trap: Why ‘Mentions’ Isn’t Strategy
Type “best project management software” into ChatGPT ten times and you’ll get roughly the same three or four names, in different orders, with different phrasing. A tracking tool will happily tell you that you appeared in 6 of those 10 answers, and your competitor appeared in 9. That’s a real number. It’s also almost useless on its own.
Here’s what it doesn’t tell you: why the model keeps reaching for your competitor first. Whether it’s pulling from a G2 category page, a Reddit thread from 2023, or a comparison article your competitor’s agency planted eighteen months ago. Whether the story ChatGPT tells about your category even matches how you’d describe your own product. Counting mentions treats AI search like a scoreboard. But AI search doesn’t rank you, it recommends you, based on a narrative it’s learned about your category. Mentions are the output. The narrative is the cause.
Most of the market right now is built to measure the output.
What Popular ChatGPT Tracking Tools Actually Do (And Don’t)
| Tool | Pricing | Rating | Best for |
|---|---|---|---|
| Profound | ~$399/mo (Growth), enterprise $2k-5k+/mo, demo-gated | G2 4.6/5, ~845 reviews | Enterprise brands needing deep AEO feature set |
| Peec AI | $95-495/mo, 7-day trial | G2 4.9/5, ~12 reviews | European SMBs/agencies wanting UI-accurate scraping |
| Semrush AI Toolkit | $99/mo add-on + base plan | No dedicated listing | Teams already living in Semrush |
| Otterly.AI | $29-489/mo, free trial | G2 ~4.8/5 cited | Solo marketers/small agencies on a budget |
| AthenaHQ | $295-499/mo, credit-based | G2 4.9/5, ~32 reviews | Startups wanting recommendation tooling, not just tracking |
| Scrunch AI | $250-1,000+/mo, 7-day trial | G2 ~4.6-4.7/5, ~50-59 reviews | Mid-market teams bringing their own execution plan |
| Ahrefs Brand Radar | $328-1,148/mo realistic all-in | No dedicated listing | Enterprises already deep in Ahrefs |
| HubSpot AEO Grader | Free | No listing (free tool) | A quick one-time diagnostic |
| Brandlight | Sales-gated, ~$199-750+/mo | G2 4.7/5, 19 reviews | Enterprise teams wanting white-glove support |
| Evertune | ~$3,000+/mo, demo-led | Gartner Representative Vendor | Large brands needing rigorous API-scale measurement |
| Goodie AI | $399/mo self-serve | G2 ~4.9 cited, thin base | Mid-market wanting monitoring plus content execution |
| Gauge | $99-599/mo | Product Hunt 5.0/5 (3 reviews) | Agencies wanting affordable citation tracking |
| Mavel | €89-499/mo, free GEO report to start | No public review base yet (new entrant) | Teams wanting the narrative layer, not just mention counts |
Look at the pattern. Profound gives you enterprise-grade prompt volume data and competitor benchmarking, and one G2 reviewer says it’s “like having an assistant always keeping me in the loop on our AEO and LLM visibility performance.” That’s genuinely useful if you’re an enterprise team with budget. Peec AI scrapes the real assistant UI so what you see matches what your customers see, but as one buyer put it, it “tells me the score but not how to improve it.” Ahrefs Brand Radar has a huge data engine behind it, but an independent test found it reported 3 ChatGPT mentions where 123 actually existed. Otterly.AI is a great $29 entry point if you’re just starting a GEO program. AthenaHQ is one of the few that ships actual recommendations, not just monitoring.
Every one of these tools, at every price point, is answering the same question: are you showing up? None of them answer why the model is telling the story it’s telling.
Mentions ≠ Narrative: A Real Example
Picture two project management tools. One gets mentioned in ChatGPT answers 47 times a month. The other gets mentioned 12 times. On a mentions dashboard, the first one is winning by a mile.
But look closer. The brand with 47 mentions shows up buried in listicles, “here are 10 tools to consider,” rarely first, rarely with a clear reason attached. The brand with 12 mentions shows up less often, but when it does, ChatGPT says something specific: “best for distributed teams that need async approvals.” That’s a frame. That’s a story the model has learned to associate with that brand from somewhere, a review site, a comparison post, a category report, that’s built enough consensus for the model to repeat it as fact.
Twelve confident, specific mentions built on a clear frame will move more buyers than 47 generic ones. A mentions dashboard can’t see that difference. It just counts.
What You Actually Need to Track: Sources, Frames, and Consensus
If mentions are the symptom, the real diagnostic questions are upstream:
- What frame has the model adopted about your category? Is it telling a story where you’re the budget option, the enterprise pick, the outdated one? You may not agree with that story, but if it’s what the model repeats, it’s the story that’s shaping recommendations.
- Which sources is it actually drawing from? A citation to a stale 2022 roundup carries different weight than a citation to a current, detailed comparison. Most tracking tools show that a citation exists. Few show which sources are doing the real work of building consensus.
- Where is the gap between how you want to be seen and how the model actually describes you? That gap is often the highest-leverage thing to fix, and it’s invisible if you’re only counting appearances.
This is closer to reading a market than running a dashboard. It takes some human judgment: automated tools are good at detecting that something changed, less good at explaining what story is winning and why.
From Visibility to Narrative Share: A Better Approach
This is the gap Mavel is built for. Instead of just counting whether you show up, Mavel reads the upstream narrative: whose frame the model has adopted about your category, what sources built that consensus, and where the gap sits between how you want to be seen and how AI actually describes you. The output isn’t another score to interpret. It’s a prioritized list of what to ship to change the story, not just chase the number.
Mavel is newer and doesn’t have the review history Profound or Peec have built up. That’s an honest tradeoff. If you need enterprise-grade prompt volume data today, Profound is the safer bet. If you want the narrative layer, the whose-frame-and-why behind the mentions, at self-serve pricing starting at €89/mo, Mavel is built specifically for that gap.
Start by asking ChatGPT what it says about your category, and notice whether it’s just naming names or actually telling a story. If it’s a story, you need to know whose it is. That’s what we help you figure out, and what to do about it.
