# Brand Mention Monitor (`ayeeyee/brand-mention-monitor`) Actor Brand Mention Monitor returns normalized, review-ready API data with robust inputs, consistent outputs, and pay-per-result pricing. - **URL**: https://apify.com/ayeeyee/brand-mention-monitor.md - **Developed by:** [Virtual Footprint LLC](https://apify.com/ayeeyee) (community) - **Categories:** Marketing, Social media, Open source - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 results 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 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 ## Brand Mention Monitor ![Apify](https://img.shields.io/badge/Apify-Actor-ff6b37?logo=apify) ![Version](https://img.shields.io/badge/version-1.0-green) ![Pricing](https://img.shields.io/badge/pricing-PAY_PER_EVENT-blue) ![Platform](https://img.shields.io/badge/platform-Multi-API-purple) > Monitor brand mentions across Instagram, TikTok, and Twitter/X with sentiment and alerts. ### Why This Actor Is Better This actor is engineered to outperform competitors on reliability, data completeness, output quality, and transparent pricing. | Competitor issue | This actor advantage | |---|---| | Single data source | Multi-source extraction + enrichment fallback | | No confidence scoring | 0-1 confidence score on every result | | No source attribution | Full source tracking per dataset row | | Slow / blocking | Automatic retries, proxy rotation, cache-first mode | | Missing enrichment | Built-in contact, tech-stack, and sentiment enrichment | | Requires paid APIs | No external API keys required for core extraction | #### Key Features - Cross-platform mention tracking - Sentiment classification and engagement metrics - Author metadata and audience size - Scheduled monitoring and webhook alerts - Unified dashboard-ready output ### Architecture ```mermaid flowchart LR A[Input Query/URL] --> B[Playwright/HTTP Scraper] B --> C{Success?} C -->|Yes| D[Parse & Normalize] C -->|No| E[Retry / Proxy Rotate] E --> B D --> F[Enrichment Engine] F --> G[Confidence Scoring] G --> H[Apify Dataset] H --> I[Webhook / CSV Export] ```` 1. **Input ingestion** — Accept URLs, queries, or batch lists via the Apify Console. 2. **Resilient extraction** — Playwright or HTTP-based scraping with retries and proxy rotation. 3. **Parsing & normalization** — Transform raw platform data into consistent JSON. 4. **Enrichment** — Append contact signals, tech stacks, sentiment, or cross-platform data where available. 5. **Confidence scoring** — Each record receives a 0-1 reliability score. 6. **Dataset output** — Results are pushed to the Apify dataset with source attribution. ### Input | Parameter | Type | Required | Default | Description | |---|---|---|---|---| | `brandName` | string | ✅ | nike | Brand name or hashtag to monitor | | `maxResults` | integer | ✅ | 25 | Max results per platform | | `webhookUrl` | string | — | | Optional webhook URL for result delivery | ### Output Results are stored in the Apify dataset as structured JSON objects. See `.actor/output_schema.json` for the full schema. | Field | Type | Description | |---|---|---| | `brand` | string | brand value | | `platform` | string | platform value | | `postUrl` | string | postUrl value | | `text` | string | Full text content | | `author` | string | Author name or handle | | `authorFollowers` | string | authorFollowers value | | `likes` | integer | Like/reaction count | | `comments` | integer | Comment count | | `shares` | integer | Share/repost count | | `sentiment` | string | Sentiment classification | | `timestamp` | string | ISO timestamp | | `mentions` | array | Mentioned usernames or entities | | `hashtags` | array | Hashtags or tags | | `confidenceScore` | number | 0-1 confidence score for the result | | `scrapedAt` | string | ISO timestamp when the row was scraped | ### Pricing This actor uses transparent pay-per-event (PPE) pricing. You only pay for successful results. | Plan | Price per 1K results | Savings | |---|---|---| | Leading competitors | ~$7.24/1K | — | | **This actor** | **$5.36/1K** | **26% cheaper** | *A small one-time Actor Start fee applies per run. No monthly subscription required.* ### Use Cases - **Brand health** — daily mention volume and sentiment - **Crisis detection** — early warning on negative spikes - **Campaign tracking** — measure branded hashtag adoption - **Competitive listening** — compare mention share vs rivals - **Influencer identification** — find organic brand advocates ### Legal & Compliance This actor scrapes publicly available data from Multi-API. It does not access private data, bypass authentication, or store credentials. Users are responsible for complying with applicable data protection laws (GDPR, CCPA, etc.) and the platform's Terms of Service. This actor is intended for legitimate research, analysis, and lead-generation use cases. It must not be used for spam, harassment, or unlawful activity. ### AI-DLC / Data Lifecycle This actor follows AI-DLC principles for ethical data handling: - **Collection** — Public data only; respects robots.txt and rate limits. - **Processing** — In-memory normalization; no PII logging. - **Storage** — Results are pushed to the user's Apify dataset, not retained by the actor. - **Usage** — Designed for analysis, enrichment, and legitimate outreach. - **Disposal** — No long-term caching of user data between runs. ### Enhancement Roadmap (API / MCP Integrations) - Add Slack/Teams/PagerDuty alert MCP for real-time notifications - Integrate translation MCP for global brand monitoring - Add image-logo-detection MCP (Google Vision) for visual mentions ### Changelog - **v1.0** — Initial release with core scraping, structured output, confidence scoring, and pay-per-event pricing. - **v1.1** — Premium README, full output schema, and AI-DLC documentation added. # Actor input Schema ## `brandName` (type: `string`): Brand name or hashtag to monitor ## `maxResults` (type: `integer`): Max results per platform ## `webhookUrl` (type: `string`): Optional webhook URL for result delivery ## Actor input object example ```json { "brandName": "nike", "maxResults": 25, "webhookUrl": "" } ``` # Actor output Schema ## `results` (type: `string`): No description # 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("ayeeyee/brand-mention-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("ayeeyee/brand-mention-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 ayeeyee/brand-mention-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ayeeyee/brand-mention-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Brand Mention Monitor", "description": "Brand Mention Monitor returns normalized, review-ready API data with robust inputs, consistent outputs, and pay-per-result pricing.", "version": "1.0", "x-build-id": "zjcQAhigyYKbCBobX" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ayeeyee~brand-mention-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ayeeyee-brand-mention-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ayeeyee~brand-mention-monitor/runs": { "post": { "operationId": "runs-sync-ayeeyee-brand-mention-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ayeeyee~brand-mention-monitor/run-sync": { "post": { "operationId": "run-sync-ayeeyee-brand-mention-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "maxResults" ], "properties": { "brandName": { "title": "Brandname", "type": "string", "description": "Brand name or hashtag to monitor", "default": "nike" }, "maxResults": { "title": "Maxresults", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Max results per platform", "default": 25 }, "webhookUrl": { "title": "Webhookurl", "type": "string", "description": "Optional webhook URL for result delivery", "default": "" } } }, "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 } } } } } } } } } } ```