# Google Maps Lead Enrichment Scraper (`taroyamada/google-maps-lead-enrichment`) Actor Enrich existing Google Maps or local business leads with websites, emails, phones, contact pages, social links, website content signals, health checks, confidence, PPE charged events, and no-charge invalid rows. This actor does not scrape Google Maps itself. - **URL**: https://apify.com/taroyamada/google-maps-lead-enrichment.md - **Developed by:** [åĪŠéƒŽ åąąį”°](https://apify.com/taroyamada) (community) - **Categories:** Lead generation, Business, Automation - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## Google Maps Lead Enrichment Scraper Enrich existing Google Maps exports, place lists, or local business lead rows with public website, contact, social, health, and business-signal fields. This Actor does **not** scrape Google Maps itself. It works on user-provided rows or an Apify dataset you already have. ### What it returns - Business name, address, website, normalized domain - Public emails, phones, contact page, and social links - Lightweight website signals and optional HTTP health status - `status`, `chargedEvent`, `sourceUrls`, `errors` for billing auditability ### Pricing events - `lead_profile_enriched`: useful enriched lead - `lead_partial`: useful partial lead - `invalid`, `not_found`, `error`, and dry-run rows are no-charge ### Input Use `leads` for direct rows or `sourceDatasetId` to read an existing Apify dataset. # Actor input Schema ## `leads` (type: `array`): Existing Google Maps/local business leads. Each item can include businessName/name/title, address, website/url/domain, phone, email, placeUrl, and sourceUrl. ## `sourceDatasetId` (type: `string`): Optional Apify dataset ID containing lead rows to enrich. The actor reads this dataset; it does not scrape Google Maps. ## `includeContacts` (type: `boolean`): Fetch public website/contact pages to find public emails, phones, and social profile links. ## `includeWebsiteContent` (type: `boolean`): Capture lightweight website title, meta description, and business signal keywords. ## `includeHealth` (type: `boolean`): Record HTTP status and response time for the public website. ## `maxLeads` (type: `integer`): Maximum lead rows to enrich. ## `delivery` (type: `string`): Choose whether to write enriched leads only to the dataset or also send the final rows to webhookUrl. ## `webhookUrl` (type: `string`): Optional HTTPS endpoint to receive the enriched lead rows after the run when delivery is set to dataset_and_webhook. ## `dryRun` (type: `boolean`): Validate input and produce preview rows without fetching websites, pushing dataset rows, charging PPE events, or sending webhooks. ## Actor input object example ```json { "leads": [], "sourceDatasetId": "", "includeContacts": true, "includeWebsiteContent": true, "includeHealth": true, "maxLeads": 50, "delivery": "dataset", "webhookUrl": "", "dryRun": false } ```` # 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("taroyamada/google-maps-lead-enrichment").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`ðŸ’ū 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("taroyamada/google-maps-lead-enrichment").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("ðŸ’ū 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 taroyamada/google-maps-lead-enrichment --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=taroyamada/google-maps-lead-enrichment", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Maps Lead Enrichment Scraper", "description": "Enrich existing Google Maps or local business leads with websites, emails, phones, contact pages, social links, website content signals, health checks, confidence, PPE charged events, and no-charge invalid rows. This actor does not scrape Google Maps itself.", "version": "0.1", "x-build-id": "vDhGBf5xNSTTxlaLU" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/taroyamada~google-maps-lead-enrichment/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-taroyamada-google-maps-lead-enrichment", "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/taroyamada~google-maps-lead-enrichment/runs": { "post": { "operationId": "runs-sync-taroyamada-google-maps-lead-enrichment", "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/taroyamada~google-maps-lead-enrichment/run-sync": { "post": { "operationId": "run-sync-taroyamada-google-maps-lead-enrichment", "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", "properties": { "leads": { "title": "Lead objects", "type": "array", "description": "Existing Google Maps/local business leads. Each item can include businessName/name/title, address, website/url/domain, phone, email, placeUrl, and sourceUrl.", "default": [] }, "sourceDatasetId": { "title": "Source Dataset ID", "type": "string", "description": "Optional Apify dataset ID containing lead rows to enrich. The actor reads this dataset; it does not scrape Google Maps.", "default": "" }, "includeContacts": { "title": "Extract Contacts", "type": "boolean", "description": "Fetch public website/contact pages to find public emails, phones, and social profile links.", "default": true }, "includeWebsiteContent": { "title": "Extract Website Signals", "type": "boolean", "description": "Capture lightweight website title, meta description, and business signal keywords.", "default": true }, "includeHealth": { "title": "Check Website Health", "type": "boolean", "description": "Record HTTP status and response time for the public website.", "default": true }, "maxLeads": { "title": "Max Leads", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum lead rows to enrich.", "default": 50 }, "delivery": { "title": "Delivery Mode", "enum": [ "dataset", "dataset_and_webhook" ], "type": "string", "description": "Choose whether to write enriched leads only to the dataset or also send the final rows to webhookUrl.", "default": "dataset" }, "webhookUrl": { "title": "Webhook URL", "type": "string", "description": "Optional HTTPS endpoint to receive the enriched lead rows after the run when delivery is set to dataset_and_webhook.", "default": "" }, "dryRun": { "title": "Dry Run", "type": "boolean", "description": "Validate input and produce preview rows without fetching websites, pushing dataset rows, charging PPE events, or sending webhooks.", "default": false } } }, "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 } } } } } } } } } } ```