# LLM Brand Mentions Monitor - DataForSEO AI Visibility API (`changeable_peddler/llm-brand-mentions-monitor`) Actor Track brand and competitor mentions in DataForSEO LLM Mentions results for Google AI Overview and ChatGPT. - **URL**: https://apify.com/changeable\_peddler/llm-brand-mentions-monitor.md - **Developed by:** [Sean J](https://apify.com/changeable_peddler) (community) - **Categories:** SEO tools, Marketing, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $350.00 / 1,000 llm mention queries This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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 ## LLM Brand Mentions Monitor - DataForSEO AI Visibility API Track whether a brand or domain appears in LLM/AI-search answers for target topics. Use it for GEO reporting, AI visibility baselines, competitor comparison, and source/citation discovery. This Actor uses DataForSEO LLM Mentions Search and returns one report per topic/platform query for Google AI Overview and optional ChatGPT data. ### Related workflow Use this alongside [AI SERP Visibility Monitor](https://apify.com/changeable_peddler/ai-serp-visibility-monitor) when you need LLM mention and citation evidence beyond standard Google SERP/AI Overview checks. Feed winning topics from [Keyword ROI Scorer](https://apify.com/changeable_peddler/keyword-roi-scorer) into this Actor to build an AI visibility baseline. Public examples and tutorials: https://github.com/shamusj-create/seo-dataforseo-apify ### Pricing Recommended pay-per-event pricing: - Event: `llm-mention-query` - Price: `$0.35` - Unit: one topic/platform LLM mention query The Actor charges before each DataForSEO LLM Mentions request so Apify spending limits are respected. ### Demo input ```json { "brandName": "Apify", "targetDomain": "apify.com", "topics": [ "web scraping api", "google ai overview tracker" ], "competitorDomains": [ "zyte.com", "brightdata.com" ], "platforms": [ "google" ], "locationCode": 2840, "languageCode": "en", "limit": 10 } ```` ### What you get back Each dataset row includes target visibility, competitor visibility, source domains, top mention rows, recommendations, metrics, raw DataForSEO evidence, and timestamp. DataForSEO credentials are configured as encrypted Apify Actor environment variables, not user input. # Actor input Schema ## `brandName` (type: `string`): Brand name to detect in LLM answers and brand entities. ## `targetDomain` (type: `string`): Domain to detect in cited sources and search results. ## `topics` (type: `array`): Topics or commercial prompts to monitor. Up to 3 are accepted. ## `competitorDomains` (type: `array`): Competitor domains to detect in answers and citations. Up to 5 are accepted. ## `platforms` (type: `array`): LLM mention platforms to query. ChatGPT is available for United States and English only. ## `locationCode` (type: `integer`): DataForSEO LLM Mentions location code. 2840 is United States. ## `languageCode` (type: `string`): Language code. ChatGPT data is currently limited to en. ## `limit` (type: `integer`): Maximum LLM mention rows to return for each topic/platform query. ## Actor input object example ```json { "brandName": "Apify", "targetDomain": "apify.com", "topics": [ "web scraping api", "google ai overview tracker" ], "competitorDomains": [ "zyte.com", "brightdata.com" ], "platforms": [ "google" ], "locationCode": 2840, "languageCode": "en", "limit": 10 } ``` # Actor output Schema ## `results` (type: `string`): Structured report rows. # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("changeable_peddler/llm-brand-mentions-monitor").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 = {} # Run the Actor and wait for it to finish run = client.actor("changeable_peddler/llm-brand-mentions-monitor").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 '{}' | apify call changeable_peddler/llm-brand-mentions-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=changeable_peddler/llm-brand-mentions-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LLM Brand Mentions Monitor - DataForSEO AI Visibility API", "description": "Track brand and competitor mentions in DataForSEO LLM Mentions results for Google AI Overview and ChatGPT.", "version": "0.0", "x-build-id": "uBx9ybknqsaxufYhW" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/changeable_peddler~llm-brand-mentions-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-changeable_peddler-llm-brand-mentions-monitor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/changeable_peddler~llm-brand-mentions-monitor/runs": { "post": { "operationId": "runs-sync-changeable_peddler-llm-brand-mentions-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/changeable_peddler~llm-brand-mentions-monitor/run-sync": { "post": { "operationId": "run-sync-changeable_peddler-llm-brand-mentions-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "targetDomain", "topics" ], "properties": { "brandName": { "title": "Brand Name", "type": "string", "description": "Brand name to detect in LLM answers and brand entities.", "default": "Apify" }, "targetDomain": { "title": "Target Domain", "type": "string", "description": "Domain to detect in cited sources and search results.", "default": "apify.com" }, "topics": { "title": "Topics", "minItems": 1, "maxItems": 3, "type": "array", "description": "Topics or commercial prompts to monitor. Up to 3 are accepted.", "items": { "type": "string" }, "default": [ "web scraping api", "google ai overview tracker" ] }, "competitorDomains": { "title": "Competitor Domains", "maxItems": 5, "type": "array", "description": "Competitor domains to detect in answers and citations. Up to 5 are accepted.", "items": { "type": "string" }, "default": [ "zyte.com", "brightdata.com" ] }, "platforms": { "title": "Platforms", "maxItems": 2, "type": "array", "description": "LLM mention platforms to query. ChatGPT is available for United States and English only.", "items": { "type": "string" }, "default": [ "google" ] }, "locationCode": { "title": "Location Code", "minimum": 1, "maximum": 100000000, "type": "integer", "description": "DataForSEO LLM Mentions location code. 2840 is United States.", "default": 2840 }, "languageCode": { "title": "Language Code", "type": "string", "description": "Language code. ChatGPT data is currently limited to en.", "default": "en" }, "limit": { "title": "Result Limit", "minimum": 1, "maximum": 25, "type": "integer", "description": "Maximum LLM mention rows to return for each topic/platform query.", "default": 10 } } }, "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 } } } } } } } } } } ```