AI Brand Visibility Tracker — ChatGPT, Perplexity, Gemini & Claude

Find out if AI recommends you — or your competitor.

Run real buyer-intent queries across ChatGPT, Perplexity, Gemini, and Claude. Get mention rates, position scores, share of voice vs. competitors, cited sources, and automatic week-over-week trend deltas in a single run. No API keys needed.

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What it does

For each combination of brand × query × engine, the actor:

1. Sends the query to the AI engine (using its real web-search mode)
2. Detects whether your brand is mentioned, how early, and how often
3. Measures your share of voice vs. every competitor you list
4. Collects the URLs the AI cited as sources
5. Compares results to your previous run and reports the delta

All checks run in one batch — track a whole client roster or your brand + every competitor in a single run.

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Why this tracker

Feature	This actor	Most trackers
Multi-brand batches	✅ unlimited	❌ one brand per run
Built-in trend deltas	✅ automatic	❌ manual export
4 engines (incl. web-search)	✅	❌ 1–2 engines
No API keys needed	✅	❌ requires your keys
Pay only for what you run	✅ per-check pricing	❌ flat subscription

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Who uses it

• SEO / GEO agencies building AI visibility reports for clients
• Brand & comms teams monitoring how LLMs describe them vs. the competition
• Founders checking whether AI search recommends them or their rival
• Product marketers tracking share of voice across AI channels

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Input

The default input works out of the box — just swap in your brand name:

{
  "brands": [
    {
      "name": "Asana",
      "aliases": [],
      "competitors": ["Trello", "Monday.com", "ClickUp"]
    }
  ],
  "queries": [
    "best project management tool for small teams",
    "what project management software should a startup use"
  ],
  "engines": ["chatgpt", "perplexity", "gemini"],
  "trackTrends": true
}

Input fields:

Field	Required	Description
brands	✅	List of brands. Each has name, optional aliases, optional competitors.
queries	✅	Buyer-intent questions your customers ask AI assistants.
engines	—	chatgpt, perplexity, gemini, claude. Default: first three (search-backed).
trackTrends	—	Save this run's summary and report deltas vs. the previous run. Default: true.
trendKey	—	Label to keep separate trend series (e.g. one per client).

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Output

Dataset — one row per (brand × query × engine) check

{
  "brand": "Asana",
  "engine": "chatgpt",
  "query": "best project management tool for small teams",
  "brand_mentioned": true,
  "mention_count": 2,
  "position_score": 9,
  "share_of_voice": 0.4,
  "competitor_mentions": { "Trello": 2, "Monday.com": 1, "ClickUp": 0 },
  "cited_domains": ["g2.com", "blog.asana.com"],
  "response_snippet": "For small teams, Asana offers a generous free tier...",
  "response_truncated": false
}

Key fields:

• position_score — 1–10; 10 = brand named first, 1 = named last, 0 = not mentioned
• share_of_voice — brand mentions ÷ (brand + all competitor mentions)
• cited_domains — domains the AI cited as sources for its answer
• response_truncated — true if the AI hit its token limit (treat that row as inconclusive)

SUMMARY key-value — per-brand rollup + trend deltas

{
  "summary": {
    "Asana": {
      "mention_rate": 0.67,
      "avg_position_score": 7.5,
      "avg_share_of_voice": 0.42,
      "engines": {
        "chatgpt":    { "mention_rate": 1.0, "responses": 2 },
        "perplexity": { "mention_rate": 0.5, "responses": 2 }
      }
    }
  },
  "trends": {
    "Asana": {
      "mention_rate":       { "current": 0.67, "previous": 0.5,  "delta":  0.17 },
      "avg_position_score": { "current": 7.5,  "previous": 6.0,  "delta":  1.5  },
      "avg_share_of_voice": { "current": 0.42, "previous": 0.38, "delta":  0.04 }
    }
  }
}

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Pricing

Pay per event — a small flat fee per visibility check (brand × query × engine). All upstream AI API costs are included; you don't need your own keys.

Example: 1 brand × 3 queries × 3 engines = 9 checks.

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Scheduling for weekly trend reports

1. Set up a Schedule in Apify (Actors → Schedules → New schedule)
2. Point it at this actor with your saved input
3. Keep trackTrends: true (the default)
4. Every run automatically compares to the previous one and writes deltas to SUMMARY

Use trendKey to maintain separate trend series per client — e.g. "trendKey": "client-acme".

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Use as an MCP tool

Add this actor to Claude Desktop, Cursor, or any MCP-compatible client via Apify's MCP server and let your agent check AI brand visibility on demand.

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FAQ

Do I need OpenAI / Anthropic / Google API keys? No. All API calls are made server-side and the cost is bundled into the per-check price.

Which engine uses real web search? All four: chatgpt uses gpt-4o-search-preview, perplexity uses sonar (always web-backed), gemini uses gemini-2.5-flash, and claude uses claude-sonnet-5 via OpenRouter.

What if a response is truncated? The actor flags response_truncated: true on that row. A brand absent from a truncated response may simply not have been reached yet — treat it as inconclusive rather than a true "not mentioned."

Can I track multiple clients without their data mixing? Yes — set a unique trendKey per client (e.g. "client-acme", "client-beta"). Each series is stored separately.

What's the difference between mention_count and position_score? mention_count is how many times the brand appeared in the response. position_score (1–10) measures where it first appeared — being named first scores 10, being buried at the end scores 1.

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