# Google Maps Email Extractor (`pheidias0/google-maps-email-extractor`) Actor Scrapes Google Maps for any search query in any country. Extracts business name, phone, email, website, address, category, and rating. Visits each place's website to find email addresses. Built for mass scraping. - **URL**: https://apify.com/pheidias0/google-maps-email-extractor.md - **Developed by:** [Ayoub Mansouri](https://apify.com/pheidias0) (community) - **Categories:** Lead generation, Social media, Automation - **Stats:** 18 total users, 2 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $2.00 / 1,000 results 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 ## Google Maps Scraper with Emails **The only Google Maps scraper that breaks Google's 120-result cap.** Most Google Maps scrapers hit a wall at 120 results per search — that's Google's built-in limit, not a bug. This one uses a **geo-grid** to slice your target area into cells and scrape each one independently, finding **thousands of businesses per city** instead of 120. Then it visits every business website and extracts emails — even the ones hidden inside contact forms (WordPress Contact Form 7, Formspree, mailto actions, hidden inputs, inline scripts). Most scrapers can't see those. This one can. Built for lead-gen agencies, SDR teams, and anyone who needs lead lists that don't end at 120. ### Why this scraper beats the alternatives **1. Breaks the 120-result cap.** Geo-grid splits any city into ~30 cells at the optimal zoom level. Each cell runs its own search. Real result: 500+ unique dentists in NYC, not 120. 2,800+ restaurants in Paris, not 120. **2. Finds emails ~90% of the time.** Crawls homepages, contact pages, and about pages. Extracts emails from inside HTML forms — the ones every other scraper misses because the email isn't visible on the page. **3. Cheaper per lead than competitors.** Direct HTTP for website crawls (no proxy cost). Resource blocking cuts Google Maps bandwidth ~70%. Browser tabs open only when strictly necessary. **$2 per 1,000 places.** **4. Survives long runs.** State persists across Apify machine migrations. A 10,000-result job resumes exactly where it stopped. ### Who this is for - **Lead-gen agencies** doing territory sweeps for clients - **SDR teams** building outbound lists at scale - **Local SEO agencies** prospecting their target verticals - **Sales ops** seeding CRMs with verified business contacts If you need 100 leads, any scraper works. If you need 5,000+, you need a geo-grid. ### What you get | Field | Example | |-------|---------| | `name` | John's Plumbing & Drain Services | | `category` | Plumber | | `phone` | +1 323-422-7485 | | `email` | info@johnsplumber.com | | `website` | https://johnsplumber.com/ | | `address` | 1247 Riverside Dr, Los Angeles, CA 90039 | | `city` | Los Angeles | | `state` | CA | | `zip` | 90039 | | `rating` | 4.9 | | `reviewsCount` | 53 | | `facebook` | https://www.facebook.com/johnsplumbing | | `instagram` | https://www.instagram.com/johnsplumbing/ | | `twitter` | https://twitter.com/johnsplumbing | | `linkedin` | https://www.linkedin.com/company/johnsplumbing | | `lat` | 34.1184341 | | `lng` | -118.3003935 | | `plusCode` | 4F9P+CG Los Angeles, CA, USA | | `placeId` | 0x80c2bf3d6722abc1:0x73bcdee27ad53d30 | | `googleMapsUrl` | https://www.google.com/maps/place/... | Phone, website, full address, category, and Plus Code are pulled from each place's Google Maps profile page. Email and social media links are extracted from the business website. Coordinates and place ID come from the place URL. ### Input examples #### Simple search — one keyword, one city ```json { "searchStringsArray": ["dentist"], "locationQuery": "Chicago" } ```` #### Multiple keywords — lead generation campaign ```json { "searchStringsArray": [ "plumber", "electrician", "HVAC contractor", "roofer" ], "locationQuery": "Houston, TX", "scrapeEmails": true, "skipClosedPlaces": true } ``` #### International — any language, any country ```json { "searchStringsArray": ["restaurant", "café"], "locationQuery": "Paris", "language": "fr" } ``` #### Mass scraping — cover an entire metro area ```json { "searchStringsArray": ["therapist", "psychologist", "counselor"], "locationQuery": "New York City", "maxCrawledPlacesPerSearch": 0, "maxConcurrency": 5 } ``` The geo-grid automatically splits the area into ~30 cells at the optimal zoom level, scraping each one to find every listing. #### Location baked into keywords ```json { "searchStringsArray": [ "dentist Chicago", "dentist Houston", "dentist Phoenix" ], "scrapeEmails": true } ``` #### Fast mode — skip email extraction ```json { "searchStringsArray": ["gym", "fitness"], "locationQuery": "Miami", "scrapeEmails": false } ``` Runs faster. You still get the full Google Maps profile: name, phone, website, address, category, rating, and coordinates. Set `scrapePhones` to `false` as well for the fastest feed-only mode (name, category, rating, and Google Maps URL only). ### How place details are scraped For every place found in the search results, the actor opens its Google Maps profile page and extracts the complete profile: **phone number, website, full address (with city/state/ZIP), exact category, and Plus Code**. Failed pages are automatically retried, so detail coverage is near 100% even on large runs. ### How email extraction works The scraper uses a 3-step pipeline to maximize email discovery: 1. **Homepage scan** — Visits the business website via fast HTTP request. Uses Crawlee's `social.parseHandlesFromHtml` to find mailto links, email patterns, phone numbers, and social media profiles. 2. **Contact form extraction** — Scans for hidden emails inside `
` elements: `action="mailto:..."`, hidden input values, data attributes, and inline script configurations (catches WordPress Contact Form 7, Formspree, and similar setups). 3. **Sub-page crawl** — If no email found on the homepage, automatically discovers and scans contact/about pages on the same domain. This catches emails that basic scrapers miss — many businesses only expose their email inside a contact form, not as visible text on the page. ### How the geo-grid works Google Maps only returns ~120 results per search. To get full coverage of a city or region: 1. The actor geocodes your location into a bounding box (via OpenStreetMap Nominatim) 2. It picks the optimal zoom level based on the area size 3. It splits the bounding box into a grid of cells 4. Each cell gets its own Google Maps search, finding results in that specific area 5. Results are automatically deduplicated by Google Maps place ID For a city like New York, this creates ~30 cells and can find 500+ unique businesses per keyword. ### Tips for getting the most results - **Use multiple related keywords** — "plumber", "plumbing service", "emergency plumber" will each find some unique listings - **Set maxCrawledPlacesPerSearch to 0** — No limit per grid cell means maximum coverage - **Increase maxConcurrency to 5-10** for faster runs (default is 5) - **Deduplication is automatic** — The same business found across multiple keywords or grid cells is only included once ### Input reference | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `searchStringsArray` | string\[] | *required* | Keywords to search on Google Maps | | `locationQuery` | string | — | City, region, or country. Auto-geocoded into a geo-grid | | `startUrls` | object\[] | — | Google Maps URLs to scrape directly | | `maxCrawledPlacesPerSearch` | integer | `0` | Max results per grid cell. 0 = no limit | | `placeMinimumStars` | number | `0` | Minimum star rating filter (0-5) | | `skipClosedPlaces` | boolean | `false` | Skip closed businesses | | `scrapeEmails` | boolean | `true` | Extract emails and social media from websites | | `scrapePhones` | boolean | `true` | Open each place's profile page for phone, website, full address, Plus Code | | `language` | string | `"en"` | Google Maps language code | | `maxConcurrency` | integer | `5` | Parallel browser pages (3-10 recommended) | | `zoom` | integer | `0` | Geo-grid zoom. 0 = auto-detect | ### Export Download results from the Apify console as **CSV**, **JSON**, or **Excel**. Connect to Google Sheets, Slack, CRMs, or webhooks via Apify integrations. ### Cost Pay Per Event: **$0.002 per result** ($2 per 1,000 results), plus a small Actor start fee. You only pay for places actually saved to the dataset. # Actor input Schema ## `searchStringsArray` (type: `array`): What to search on Google Maps (e.g. 'plumber', 'dentist', 'restaurant'). Each keyword will be searched at every grid cell in the location area. ## `locationQuery` (type: `string`): City, region, or country to search in. The actor geocodes this into a bounding box and splits it into a geo-grid so it can find thousands of results instead of Google's 120 limit. Leave empty if your keywords already include locations. ## `startUrls` (type: `array`): Optional. Paste Google Maps place or search URLs directly instead of using keywords. ## `maxCrawledPlacesPerSearch` (type: `integer`): Max places to extract per grid cell or search. Set to 0 for no limit. With geo-grid, each cell can return up to ~120 places — the grid gives you coverage across the whole area. ## `placeMinimumStars` (type: `number`): Only include places with this rating or higher. Set to 0 to include all. ## `skipClosedPlaces` (type: `boolean`): Skip places marked as permanently or temporarily closed. ## `scrapeEmails` (type: `boolean`): Visit each place's website (found on its Google Maps profile) via fast HTTP to extract email, Facebook, Instagram, Twitter, LinkedIn. Uses contact form extraction and contact/about sub-page crawling. ## `scrapePhones` (type: `boolean`): Open each place's Google Maps page to extract its full profile: phone number, website, complete address (city/state/ZIP), category, and Plus Code. Recommended — the search feed alone rarely contains phone or website. Disabling this AND email scraping gives a fast feed-only mode. ## `language` (type: `string`): Language for Google Maps ('en', 'fr', 'es', 'de', 'ar', 'ja', etc.). ## `maxConcurrency` (type: `integer`): Parallel browser pages. Higher = faster but uses more CPU/memory. Safe range: 3-10. ## `zoom` (type: `integer`): Controls geo-grid density. 0 = auto-detect from location size. Lower zoom (11-12) = fewer larger cells, faster but may miss places. Higher zoom (14-15) = more smaller cells, slower but more thorough. ## Actor input object example ```json { "searchStringsArray": [ "dentist in New York" ], "maxCrawledPlacesPerSearch": 5, "placeMinimumStars": 0, "skipClosedPlaces": false, "scrapeEmails": true, "scrapePhones": true, "language": "en", "maxConcurrency": 3, "zoom": 0 } ``` # Actor output Schema ## `results` (type: `string`): All scraped business listings with name, phone, email, address, rating, website, and social media links. Download as CSV, JSON, or Excel. # 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 = { "searchStringsArray": [ "dentist in New York" ], "maxCrawledPlacesPerSearch": 5 }; // Run the Actor and wait for it to finish const run = await client.actor("pheidias0/google-maps-email-extractor").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 = { "searchStringsArray": ["dentist in New York"], "maxCrawledPlacesPerSearch": 5, } # Run the Actor and wait for it to finish run = client.actor("pheidias0/google-maps-email-extractor").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 '{ "searchStringsArray": [ "dentist in New York" ], "maxCrawledPlacesPerSearch": 5 }' | apify call pheidias0/google-maps-email-extractor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=pheidias0/google-maps-email-extractor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Maps Email Extractor", "description": "Scrapes Google Maps for any search query in any country. Extracts business name, phone, email, website, address, category, and rating. Visits each place's website to find email addresses. Built for mass scraping.", "version": "0.1", "x-build-id": "XP84d5hAmzawgq9i7" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/pheidias0~google-maps-email-extractor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-pheidias0-google-maps-email-extractor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/pheidias0~google-maps-email-extractor/runs": { "post": { "operationId": "runs-sync-pheidias0-google-maps-email-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/pheidias0~google-maps-email-extractor/run-sync": { "post": { "operationId": "run-sync-pheidias0-google-maps-email-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "searchStringsArray" ], "properties": { "searchStringsArray": { "title": "Search Keywords", "type": "array", "description": "What to search on Google Maps (e.g. 'plumber', 'dentist', 'restaurant'). Each keyword will be searched at every grid cell in the location area.", "items": { "type": "string" } }, "locationQuery": { "title": "Location", "type": "string", "description": "City, region, or country to search in. The actor geocodes this into a bounding box and splits it into a geo-grid so it can find thousands of results instead of Google's 120 limit. Leave empty if your keywords already include locations." }, "startUrls": { "title": "Google Maps URLs", "type": "array", "description": "Optional. Paste Google Maps place or search URLs directly instead of using keywords.", "items": { "type": "object" } }, "maxCrawledPlacesPerSearch": { "title": "Max places per search", "minimum": 0, "type": "integer", "description": "Max places to extract per grid cell or search. Set to 0 for no limit. With geo-grid, each cell can return up to ~120 places — the grid gives you coverage across the whole area.", "default": 20 }, "placeMinimumStars": { "title": "Minimum star rating", "minimum": 0, "maximum": 5, "type": "number", "description": "Only include places with this rating or higher. Set to 0 to include all.", "default": 0 }, "skipClosedPlaces": { "title": "Skip closed places", "type": "boolean", "description": "Skip places marked as permanently or temporarily closed.", "default": false }, "scrapeEmails": { "title": "Scrape emails & social media from websites", "type": "boolean", "description": "Visit each place's website (found on its Google Maps profile) via fast HTTP to extract email, Facebook, Instagram, Twitter, LinkedIn. Uses contact form extraction and contact/about sub-page crawling.", "default": true }, "scrapePhones": { "title": "Scrape place details (phone, website, full address)", "type": "boolean", "description": "Open each place's Google Maps page to extract its full profile: phone number, website, complete address (city/state/ZIP), category, and Plus Code. Recommended — the search feed alone rarely contains phone or website. Disabling this AND email scraping gives a fast feed-only mode.", "default": true }, "language": { "title": "Language", "type": "string", "description": "Language for Google Maps ('en', 'fr', 'es', 'de', 'ar', 'ja', etc.).", "default": "en" }, "maxConcurrency": { "title": "Max concurrency", "minimum": 1, "maximum": 20, "type": "integer", "description": "Parallel browser pages. Higher = faster but uses more CPU/memory. Safe range: 3-10.", "default": 3 }, "zoom": { "title": "Zoom level (0 = auto)", "minimum": 0, "maximum": 17, "type": "integer", "description": "Controls geo-grid density. 0 = auto-detect from location size. Lower zoom (11-12) = fewer larger cells, faster but may miss places. Higher zoom (14-15) = more smaller cells, slower but more thorough.", "default": 0 } } }, "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 } } } } } } } } } } ```