The best platforms for tracking ChatGPT, Gemini, and Perplexity visibility do not treat AI visibility as one score. They track provider, prompt, market, competitor, citation, and answer changes separately.
That matters because local buyers do not ask one generic question in one tool. They ask for the best plumber near them, the best HVAC company for AC repair, the best med spa for a treatment, or the best franchise location in a specific city. Different AI systems can answer those questions with different sources.
For a fast public snapshot, use the Cheers AI Visibility Grader. For ongoing tracking, the platform has to store the run history and turn provider misses into work.
One prompt is not tracking
Typing a query into ChatGPT once is useful for curiosity. It is not enough for a business decision.
The answer can change by provider, geography, date, prompt wording, citation availability, and model behavior. The same brand might appear in Gemini, miss in ChatGPT, and appear as a citation but not a recommendation in Perplexity. That is why the platform should keep the raw run context, instead of the final score alone.
For local businesses, the minimum useful record is a row: prompt, provider, location or market, answer, appearance, citation, competitors, cited sources, and timestamp. Without that row, the team cannot tell whether visibility improved or whether someone happened to test a friendlier prompt.
What the platform should record
A serious provider-tracking platform should capture enough detail for another person to audit the result later.
- Prompt and prompt group.
- Provider and model surface where known.
- Location, service line, brand, and competitor set.
- Whether the business appeared, was cited, or was absent.
- Which competitors appeared and in what role.
- Which source URLs were cited or implied.
- Run time, refresh cadence, and change history.
- Owner and next action when a miss is discovered.
The owner field is not decorative. A citation miss might belong to SEO. A stale profile might belong to a local manager. A weak review pattern might belong to operations. A confusing acquired brand name might belong to leadership before the next rebrand.
Provider differences change the work
ChatGPT, Gemini, Perplexity, and Google AI surfaces do not all expose the same answer or the same source behavior. Some answers cite more sources. Some lean harder on web results. Some blend local profile data, directories, articles, and review evidence differently.
That means the fix depends on the provider. If ChatGPT cites a competitor page, inspect the page. If Perplexity cites a directory, inspect the directory. If Google AI surfaces seem to rely on the Business Profile and the location page, make sure those facts agree.
Each AI Search Engine Trusts Different Sources covers the source differences in more detail. The tracking platform should make those differences visible enough that the team stops arguing from screenshots.
How to evaluate platforms
Use your own priority prompts. A demo prompt about "best pizza in New York" tells a plumbing, HVAC, restoration, or med spa buyer almost nothing.
Run the demo on your own demand instead: the two markets you most need to win, the service lines that drive revenue, the competitor that keeps showing up, and at least one urgent "who do I call right now" question. Ask the platform to show the raw runs, provider differences, cited sources, competitor mentions, and the suggested next action.
The shortlist depends on the job.
Comparison
Provider tracking platforms compared
Tracking ChatGPT, Gemini, and Perplexity is table stakes. The differences show up in what the platform keeps and who acts on it.
| Platform | Multi-provider coverage | Run history and drift | Cited-source capture | Competitor tracking | Owner assignment by market |
|---|---|---|---|---|---|
| CheersThat's us | Core capability | Core capability | Core capability | Core capability | Core capability |
| Profound | Core capability | Core capability | Core capability | Core capability | Not the focus |
| Otterly | Core capability | Core capability | Core capability | Partial or add-on | Not the focus |
| Peec | Core capability | Core capability | Core capability | Core capability | Not the focus |
| Semrush | Core capability | Core capability | Partial or add-on | Core capability | Not the focus |
Pricing: Custom, scoped by locations and execution support
Best for: Service brands that want provider differences turned into managed work across the website, reviews, listings, and local content
Strengths
- Every run keeps prompt, provider, market, competitors, and cited sources
- Misses become managed fixes: website, profile, review, listing, or local content
- Built around local buying prompts, not generic brand checks
Tradeoffs
- Service-brand focus: not aimed at ecommerce or national content brands
- Lighter than enterprise monitors for pure PR use cases
Pricing: Custom plans
Best for: Enterprise AI answer monitoring with deep citation analysis
Strengths
- Strong provider coverage and citation analytics
- Built for large brand and content programs
Tradeoffs
- Operating handoff stays with your team
- Location-level ownership is not the design
Pricing: From $29 per month
Best for: Affordable multi-surface AI search monitoring
Strengths
- Covers major AI search surfaces with prompt-tier pricing
- Fast way to get a recurring snapshot
Tradeoffs
- Prompt budgets limit market-by-market depth
- No execution or ownership layer
Pricing: Prompt and model based
Best for: Prompt and model analytics for marketing teams
Strengths
- Model-level analysis across providers
- Citation and competitor views built for analysis
Tradeoffs
- Analysis tool, not an operating system
- Your team still owns every fix
Pricing: $99 per month per domain
Best for: SEO suites where AI tracking joins rankings and content
Strengths
- AI Visibility Toolkit inside the broader Semrush stack
- Familiar reporting for existing Semrush teams
Tradeoffs
- Per-domain model strains multi-location budgets
- Local operating context is not the focus
The short version
- Enterprise brand monitoring with analyst depth: Profound or Peec
- A budget-friendly recurring snapshot: Otterly
- One more lens inside an existing SEO suite: Semrush
- Provider misses that should become managed local work, not another report: Cheers
Capability reads reflect each vendor's official public positioning as of June 2026, using the sources linked in this article. Pricing appears only where the vendor publishes it. Cheers builds the highlighted platform, so treat this as a vendor-authored map and pressure-test it in your own demos.
If listings, reviews, pages, and location data also need enterprise controls, add a multi-location local marketing platform to the evaluation rather than forcing one tool to do both jobs.
Before the pricing conversation, use How Much Does AI Visibility Software Cost? to separate prompt volume, provider coverage, citations, competitors, locations, and execution support.
The best platforms make the report boring in a good way. A manager should know what happened, where it happened, what source influenced the answer, who owns the fix, and when the team will retest.
When a free check is enough
A free checker is enough when the question is, "Are we visible at all?" It is a diagnostic, not a program.
Ongoing tracking is needed when the business has multiple locations, multiple service lines, seasonal demand, active competitors, acquisitions, franchisees, or a leadership team that expects reporting. In those cases, one score hides too much. Provider-level rows let the team see whether the next fix should happen on the profile, page, review program, citation source, or third-party listing.
The practical standard is this: choose the platform that records enough detail to make the next action obvious.
If provider differences are already showing up in screenshots, book a Cheers demo with the prompts you want to track across ChatGPT, Gemini, Perplexity, and Google AI surfaces.
Sources
- Google Search Central: AI features and your website. Supports the idea that Google AI surfaces are connected to Search eligibility and source visibility.
- Google Search Central: optimizing your website for generative AI features on Google Search. Supports the Search foundation behind AI visibility tracking.
- Profound: how to track AI visibility. Official Profound source used for AI visibility category context.
- Otterly features. Official Otterly source used for AI search monitoring category context.
- Peec AI documentation. Official Peec source used for AI search analytics category context.
- Semrush AI Visibility Toolkit, Yext Listings, Uberall, and SOCi Genius Search. Official sources used for broader platform-category context.
- Cheers first-party visibility sample, May 8-June 12, 2026. Aggregate owned-strategy sample used for directional provider-tracking context.
Dylan Allen-Arnegård is the CEO & Co-Founder of Cheers, the done-for-you platform that manages the website, reviews, listings, structured data, and local content that get service businesses recommended across Google, Maps, ChatGPT, and Perplexity.