# GEO Radar - AI Brand Visibility Monitor (`primevision/geo-radar`) Actor Track whether AI assistants recommend YOUR brand. Checks your prompts against Gemini, Perplexity, ChatGPT and Google AI Overviews; reports mentions, positions, cited sources and share of voice vs competitors. - **URL**: https://apify.com/primevision/geo-radar.md - **Developed by:** [Prime Vision](https://apify.com/primevision) (community) - **Categories:** Marketing - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $30.00 / 1,000 prompt check (with citations)s 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## GEO Radar — AI Brand Visibility Monitor **Does AI recommend your brand — or your competitor?** GEO Radar is a generative engine optimization (GEO) monitor: it checks your customer prompts against **Gemini, Perplexity, ChatGPT (web search) and Google AI Overviews**, and tells you exactly where you stand in AI search — mentions, position, cited sources, and **share of voice vs competitors**. AI assistants are the new search results page. If your brand isn't in the answer, you don't exist. Enterprise GEO platforms run $100–500/month on self-serve tiers (and $30k+/year on enterprise contracts) — GEO Radar gives you the same core data **pay-per-check**, no subscription: 50 prompts × 2 engines weekly is a few dollars a month. ### What you get for every prompt × engine - **Mentioned?** — is your brand in the AI's answer at all - **Position** — are you named first, or after two competitors - **Cited?** — does the AI cite YOUR domain as a source (and at which position) - **Competitor breakdown** — same metrics for every competitor you list - **Cited sources** — the exact pages the AI pulled from (your GEO target list) - **Run summary** — mention rate, citation rate, average position and **share of voice** per engine ### Engines and API keys | Engine | Key needed | Where to get it | |---|---|---| | Google Gemini | none — built-in shared key (fair-use limits) | optional override: [aistudio.google.com](https://aistudio.google.com) | | Perplexity | your key, required | [perplexity.ai/settings/api](https://www.perplexity.ai/settings/api) | | ChatGPT (web search) | your OpenAI key, required | [platform.openai.com](https://platform.openai.com) | | Google AI Overviews | your SerpApi key, required | [serpapi.com](https://serpapi.com) | **Gemini out of the box:** the built-in shared key answers from the model's knowledge (no live Google Search grounding — that quota requires a billed Google key). Such checks are flagged `grounded: false`, carry no citations, and are billed at the cheaper *basic check* rate. Plug in your own billing-enabled Gemini key to get fully grounded answers with cited sources. ### Example output ```json { "engine": "perplexity", "prompt": "best crypto tax software europe", "brand_mentioned": true, "brand_position": 2, "brand_cited": true, "brand_citation_position": 3, "competitors": [ {"name": "Koinly", "mentioned": true, "position": 1, "citation_position": 1} ], "cited_sources": [ {"position": 1, "url": "https://koinly.io/blog/...", "domain": "koinly.io"} ] } ```` Failed checks are recorded in the dataset too (with an `error` column), and the run summary — mention rate, citation rate, share of voice per engine — is saved to the run's OUTPUT record. ### How to use 1. Enter your **brand** (name, aliases, domain — domain enables citation tracking). 2. List **competitors** you want share-of-voice against. 3. Add the **prompts** your buyers actually ask ("best X for Y", "X vs Y", "is X trustworthy") — up to 100 per run. 4. Pick **engines** and run — or put it on a weekly [Schedule](https://docs.apify.com/schedules) to build an AI-visibility trend line. ### Who uses this - **SEO/GEO agencies** — sell AI search optimization audits to clients without enterprise tooling - **SaaS founders** — track whether AI recommends you in your category and which pages get cited - **Content teams** — find which sources AI trusts in your niche, then get cited there - **Brand monitoring** — catch when ChatGPT or Gemini starts recommending a competitor first # Actor input Schema ## `brand` (type: `object`): The brand to track. Example: {"name": "Acme", "aliases": \["Acme Corp"], "domain": "acme.com"} — domain enables citation tracking. ## `competitors` (type: `array`): Competitor brands for share-of-voice. Same shape as brand. ## `prompts` (type: `array`): The questions your customers ask AI assistants (e.g. "best CRM for small business"). Each prompt is checked against each engine. Max 100 prompts per run. ## `engines` (type: `array`): Which AI engines to monitor. Gemini works with the built-in key; Perplexity, ChatGPT and Google AI Overviews need your own API key (fields below). ## `country` (type: `string`): Two-letter country code for Google AI Overviews localization. ## `language` (type: `string`): Two-letter language code for Google AI Overviews localization. ## `geminiApiKey` (type: `string`): Override the built-in shared key with your own (aistudio.google.com). A key with billing enabled unlocks Google-Search-grounded answers with citations. ## `geminiModel` (type: `string`): Pin a specific Gemini model id (default: gemini-flash-latest). ## `perplexityApiKey` (type: `string`): Required for the Perplexity engine (perplexity.ai/settings/api). ## `openaiApiKey` (type: `string`): Required for the ChatGPT (web search) engine (platform.openai.com). ## `serpapiKey` (type: `string`): Required for the Google AI Overviews engine (serpapi.com). ## Actor input object example ```json { "brand": { "name": "Acme", "aliases": [], "domain": "acme.com" }, "competitors": [ { "name": "Globex", "domain": "globex.com" } ], "prompts": [ "best widget software for startups" ], "engines": [ "gemini" ], "country": "us", "language": "en" } ``` # 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 = { "brand": { "name": "Acme", "aliases": [], "domain": "acme.com" }, "competitors": [ { "name": "Globex", "domain": "globex.com" } ], "prompts": [ "best widget software for startups" ] }; // Run the Actor and wait for it to finish const run = await client.actor("primevision/geo-radar").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 = { "brand": { "name": "Acme", "aliases": [], "domain": "acme.com", }, "competitors": [{ "name": "Globex", "domain": "globex.com", }], "prompts": ["best widget software for startups"], } # Run the Actor and wait for it to finish run = client.actor("primevision/geo-radar").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 '{ "brand": { "name": "Acme", "aliases": [], "domain": "acme.com" }, "competitors": [ { "name": "Globex", "domain": "globex.com" } ], "prompts": [ "best widget software for startups" ] }' | apify call primevision/geo-radar --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=primevision/geo-radar", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "GEO Radar - AI Brand Visibility Monitor", "description": "Track whether AI assistants recommend YOUR brand. Checks your prompts against Gemini, Perplexity, ChatGPT and Google AI Overviews; reports mentions, positions, cited sources and share of voice vs competitors.", "version": "0.1", "x-build-id": "HYUgS27uabsLZjBei" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/primevision~geo-radar/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-primevision-geo-radar", "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/primevision~geo-radar/runs": { "post": { "operationId": "runs-sync-primevision-geo-radar", "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/primevision~geo-radar/run-sync": { "post": { "operationId": "run-sync-primevision-geo-radar", "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": [ "brand", "prompts" ], "properties": { "brand": { "title": "Your brand", "type": "object", "description": "The brand to track. Example: {\"name\": \"Acme\", \"aliases\": [\"Acme Corp\"], \"domain\": \"acme.com\"} — domain enables citation tracking." }, "competitors": { "title": "Competitors", "type": "array", "description": "Competitor brands for share-of-voice. Same shape as brand.", "default": [] }, "prompts": { "title": "Prompts to check", "maxItems": 100, "type": "array", "description": "The questions your customers ask AI assistants (e.g. \"best CRM for small business\"). Each prompt is checked against each engine. Max 100 prompts per run.", "items": { "type": "string" } }, "engines": { "title": "AI engines", "uniqueItems": true, "type": "array", "description": "Which AI engines to monitor. Gemini works with the built-in key; Perplexity, ChatGPT and Google AI Overviews need your own API key (fields below).", "items": { "type": "string", "enum": [ "gemini", "perplexity", "chatgpt", "google_ai_overview" ], "enumTitles": [ "Google Gemini (built-in key)", "Perplexity (your API key)", "ChatGPT web search (your API key)", "Google AI Overviews (your SerpApi key)" ] }, "default": [ "gemini" ] }, "country": { "title": "Country (AI Overviews)", "type": "string", "description": "Two-letter country code for Google AI Overviews localization.", "default": "us" }, "language": { "title": "Language (AI Overviews)", "type": "string", "description": "Two-letter language code for Google AI Overviews localization.", "default": "en" }, "geminiApiKey": { "title": "Your Gemini API key (optional)", "type": "string", "description": "Override the built-in shared key with your own (aistudio.google.com). A key with billing enabled unlocks Google-Search-grounded answers with citations." }, "geminiModel": { "title": "Gemini model (optional)", "type": "string", "description": "Pin a specific Gemini model id (default: gemini-flash-latest)." }, "perplexityApiKey": { "title": "Your Perplexity API key", "type": "string", "description": "Required for the Perplexity engine (perplexity.ai/settings/api)." }, "openaiApiKey": { "title": "Your OpenAI API key", "type": "string", "description": "Required for the ChatGPT (web search) engine (platform.openai.com)." }, "serpapiKey": { "title": "Your SerpApi key", "type": "string", "description": "Required for the Google AI Overviews engine (serpapi.com)." } } }, "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 } } } } } } } } } } ```