# AI Brand Visibility Tracker — ChatGPT, Perplexity & Gemini (`cooki/ai-brand-visibility-tracker`) Actor Check if AI assistants mention and cite your brand. Runs your buyers' questions through ChatGPT, Perplexity, and Gemini with live web search and returns mentions, citations, share of voice, and competitor comparison as clean JSON. - **URL**: https://apify.com/cooki/ai-brand-visibility-tracker.md - **Developed by:** [Isaiah Duncan](https://apify.com/cooki) (community) - **Categories:** SEO tools, AI, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $50.00 / 1,000 visibility checks This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## AI Brand Visibility Tracker — ChatGPT, Perplexity & Gemini Find out whether AI assistants **mention and cite your brand** when buyers ask for recommendations. This Actor runs realistic buyer questions through **ChatGPT, Perplexity, and Gemini with live web search** and returns structured JSON: mentions, citation status, position, share of voice vs. competitors, and a per-engine summary. AI answers are the new search results page. If ChatGPT recommends your competitor and not you, you're invisible where buying decisions increasingly happen. That's what GEO/AEO (generative engine optimization) tracking measures. ### What you get per check ```json { "engine": "perplexity/sonar", "query": "What is the best note taking app in 2026?", "brandMentioned": true, "mentionCount": 3, "positionScore": 9, "brandCited": true, "shareOfVoice": 0.6, "competitorMentions": { "Evernote": 1, "Obsidian": 1 }, "citedDomains": ["notion.com", "techradar.com"], "answerExcerpt": "For most people the best note taking app in 2026 is..." } ```` Plus a **summary item**: visibility rate, citation rate, and average share of voice per engine. ### Use cases - **GEO / AEO tracking**: measure your brand's visibility in AI answers over time (schedule weekly runs). - **Agency reporting**: deliver AI-visibility reports to clients; export CSV or feed dashboards via API. - **Competitor benchmarking**: share of voice against any number of competitors. - **Content strategy**: see which domains AI engines cite for your category, and win those citations. ### Quick start 1. Enter your **brand name** (and domain, for citation detection). 2. Add **topics** your buyers ask about (e.g. "note taking app") and realistic buyer questions are generated for you. Or write exact custom queries. 3. Add your **OpenRouter API key** (one key = all engines; get it at openrouter.ai in 2 minutes). 4. Run. Schedule it weekly to track movement. Works with any OpenRouter model ID, so you can swap in Claude, Llama, or new engines by editing the `engines` list. Append `:online` to give any model live web search. ### Works inside AI agents (MCP) This Actor is available as an **MCP tool** through the [Apify MCP server](https://mcp.apify.com). Connect it to Claude, Cursor, or any MCP client and run visibility checks from inside your agent. ### More tools by this developer - [Bluesky Mentions Scraper](https://apify.com/cooki/bluesky-mentions-scraper): track brand & keyword mentions on Bluesky with sentiment analysis. - [Bluesky Profile Scraper](https://apify.com/cooki/bluesky-profile-scraper): bulk profiles, followers & following lists. ### FAQ **Why OpenRouter?** One key covers every AI engine through official APIs. No scraping, no fragile browser automation, stable results. **Which engines are checked by default?** Perplexity Sonar (native web search), ChatGPT (gpt-4o-search-preview), and Gemini 2.5 Flash with web search. **How is "position score" computed?** 10 = your brand appears at the very start of the answer; 1 = at the very end; 0 = not mentioned. **Can I run it on a schedule?** Yes. Use Apify Schedules for weekly/daily tracking, and integrations (Slack, email, webhooks, Make, n8n) for alerts. # Actor input Schema ## `brandName` (type: `string`): The brand or product to track in AI answers. ## `brandDomain` (type: `string`): Your website domain (e.g. notion.com). Used to detect when AI engines cite you as a source. ## `competitors` (type: `array`): Competitor brands to compare against (share of voice). ## `topics` (type: `array`): What your buyers search for (e.g. "note taking app"). Used to auto-generate realistic buyer questions. ## `queries` (type: `array`): Exact questions to ask the AI engines. When set, topics are ignored. ## `maxQueries` (type: `integer`): Cap on the number of questions asked per engine. ## `engines` (type: `array`): Which AI engines to check. Any OpenRouter model ID works; append :online to force web search on models without native search. ## `openrouterApiKey` (type: `string`): Your OpenRouter key (sk-or-...). If the actor is deployed with a server-side key, leave empty — checks are then included in the per-result price. ## `maxAnswerChars` (type: `integer`): How many characters of each AI answer to keep in the output. ## Actor input object example ```json { "brandName": "Notion", "brandDomain": "notion.com", "competitors": [ "Evernote", "Obsidian" ], "topics": [ "note taking app" ], "maxQueries": 5, "engines": [ "perplexity/sonar", "openai/gpt-4o-search-preview", "google/gemini-2.5-flash:online" ], "maxAnswerChars": 600 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "brandName": "Notion", "brandDomain": "notion.com", "competitors": [ "Evernote", "Obsidian" ], "topics": [ "note taking app" ] }; // Run the Actor and wait for it to finish const run = await client.actor("cooki/ai-brand-visibility-tracker").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "brandName": "Notion", "brandDomain": "notion.com", "competitors": [ "Evernote", "Obsidian", ], "topics": ["note taking app"], } # Run the Actor and wait for it to finish run = client.actor("cooki/ai-brand-visibility-tracker").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "brandName": "Notion", "brandDomain": "notion.com", "competitors": [ "Evernote", "Obsidian" ], "topics": [ "note taking app" ] }' | apify call cooki/ai-brand-visibility-tracker --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=cooki/ai-brand-visibility-tracker", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "AI Brand Visibility Tracker — ChatGPT, Perplexity & Gemini", "description": "Check if AI assistants mention and cite your brand. Runs your buyers' questions through ChatGPT, Perplexity, and Gemini with live web search and returns mentions, citations, share of voice, and competitor comparison as clean JSON.", "version": "0.1", "x-build-id": "Lz9BWNjWmG9DlLtKy" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/cooki~ai-brand-visibility-tracker/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-cooki-ai-brand-visibility-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/cooki~ai-brand-visibility-tracker/runs": { "post": { "operationId": "runs-sync-cooki-ai-brand-visibility-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/cooki~ai-brand-visibility-tracker/run-sync": { "post": { "operationId": "run-sync-cooki-ai-brand-visibility-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "brandName" ], "properties": { "brandName": { "title": "Brand name", "type": "string", "description": "The brand or product to track in AI answers." }, "brandDomain": { "title": "Brand domain", "type": "string", "description": "Your website domain (e.g. notion.com). Used to detect when AI engines cite you as a source." }, "competitors": { "title": "Competitor names", "type": "array", "description": "Competitor brands to compare against (share of voice).", "items": { "type": "string" } }, "topics": { "title": "Topics / product category", "type": "array", "description": "What your buyers search for (e.g. \"note taking app\"). Used to auto-generate realistic buyer questions.", "items": { "type": "string" } }, "queries": { "title": "Custom queries (optional)", "type": "array", "description": "Exact questions to ask the AI engines. When set, topics are ignored.", "items": { "type": "string" } }, "maxQueries": { "title": "Max queries", "minimum": 1, "maximum": 50, "type": "integer", "description": "Cap on the number of questions asked per engine.", "default": 5 }, "engines": { "title": "AI engines (OpenRouter model IDs)", "type": "array", "description": "Which AI engines to check. Any OpenRouter model ID works; append :online to force web search on models without native search.", "default": [ "perplexity/sonar", "openai/gpt-4o-search-preview", "google/gemini-2.5-flash:online" ], "items": { "type": "string" } }, "openrouterApiKey": { "title": "OpenRouter API key (optional)", "type": "string", "description": "Your OpenRouter key (sk-or-...). If the actor is deployed with a server-side key, leave empty — checks are then included in the per-result price." }, "maxAnswerChars": { "title": "Answer excerpt length", "minimum": 0, "maximum": 20000, "type": "integer", "description": "How many characters of each AI answer to keep in the output.", "default": 600 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```