# Google Maps Email Scraper Unlimited (`scraperoka/google-maps-email-scraper-unlimited`) Actor 📧 Google Maps Email Scraper Unlimited extracts verified business emails from Google Maps—fast and accurate. Perfect for lead gen, outreach, sales & marketing research. 🚀 Start building targeted B2B lists today! - **URL**: https://apify.com/scraperoka/google-maps-email-scraper-unlimited.md - **Developed by:** [Scraperoka](https://apify.com/scraperoka) (community) - **Categories:** Lead generation, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.01 / 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 Email Scraper Unlimited 🚀 Manually visiting business listings and copying contact details wastes hours you don’t have. **Google Maps Email Scraper Unlimited** finds businesses in your target area and extracts their contact information (including emails) at scale. This Google Maps email scraper, and its unlimited Google Maps leads extractor variant, is ideal for marketers, recruiters, and growth teams looking for thousands of records in minutes. ### What You Get: Sample Output Here's a sample record from a single run: ```json { "street_address": "123 Market St", "city": "Miami", "zip": "33101", "state": "FL", "country_code": "US", "full_address": "123 Market St Miami FL 33101 US", "website": "https://example.com", "avg_rating": 4.6, "total_reviews": 320, "name": "Example Coffee Roasters", "place_id": "ChIJN1t_tDeuEmsRUsoyG83frY4", "phone": "+1 305-555-0123", "lat": 25.7617, "long": -80.1918, "scraped_emails": [ { "email": "hello@example.com", "confidence_score": 92.5, "validation_status": "valid", "source_url": "https://example.com/contact", "source_type": "contact_page" } ], "scraped_phones": [ "+1-305-555-0199" ], "scraped_social_media": [ "https://www.linkedin.com/company/example/" ], "emails_found": 1, "pages_scraped": 5, "scrape_status": "success" } ```` | Field | Type | What It Tells You | |---|---|---| | `name` | string | The business name you can use directly in outreach | | `website` | string | The website URL used to extract emails, phones, and social links | | `phone` | string | The phone number associated with the listing (before website scraping) | | `full_address` | string | One consolidated address string for CRM/import readiness | | `city` | string | City name for filtering and segmentation | | `state` | string | State/region for regional lead lists | | `zip` | string | ZIP/postal code for targeting and sorting | | `country_code` | string | Country code for multi-region lead generation | | `scraped_emails` | array | Email objects the actor scraped from the business website | | `scraped_phones` | array | Additional phone numbers found on the website | | `scraped_social_media` | array | Social profile links discovered on the website | | `emails_found` | number | Quick count of extracted emails for prioritizing leads | | `pages_scraped` | number | How many URLs/pages were processed for a website scrape | | `avg_rating` | number | Listing rating (useful for lead quality scoring) | | `total_reviews` | number | Listing reviews count (another quality signal) | | `scrape_status` | string | Tells you whether scraping succeeded, failed, had no website, or errored | Export your dataset as JSON, CSV, or Excel — straight from the Apify dashboard. ### Why Google Maps Email Scraper Unlimited? There are a lot of ways to pull data from business directories — here’s what sets Google Maps Email Scraper Unlimited apart. #### Targeted discovery for lead generation You define a business type (`query`) and a geographic area (`location`), and the actor builds a batch of businesses to process. This makes unlimited Google Maps leads extractor workflows practical for outreach list building. #### Email-first output (with optional email-only mode) It scrapes business contact data and then visits the business website to extract contact emails, phone numbers, and social media profiles. If you enable “Show Businesses with Email Only,” the output focuses on results where emails were successfully extracted from websites—perfect for building a business email extractor list. #### Deduplicated, business-level results The actor keeps results unique based on `place_id`, so you don’t waste time cleaning duplicates. That’s especially helpful when you’re building a bulk Google Maps email scraper workflow. #### Resilient website scraping with error states Website scraping includes completed/failed/error handling and writes a clear `scrape_status` into your dataset. This helps you understand what worked and what didn’t without guessing. ### Configuring Your Run Drop this into your `input.json` to get started: ```json { "query": "dentists", "location": "Miami, Florida", "maxBusinesses": 50, "emailOnlyResults": false, "proxyConfiguration": { "useApifyProxy": true } } ``` | Parameter | Required | What It Does | |---|---|---| | `query` | ✅ | Type of business to search for (for example, “coffee shops”, “dentists”, or “restaurants”) | | `location` | ✅ | Geographic location to search (for example, “Miami, Florida” or “Los Angeles, CA”) | | `maxBusinesses` | ⬜ | Target number of businesses to find (1–1000). The scraper stops when this target is reached | | `emailOnlyResults` | ⬜ | Only include businesses where emails were successfully extracted from their websites | | `proxyConfiguration` | ⬜ | Proxy settings for scraping. Recommended for large-scale scraping | | ↳ `proxy support` | ⬜ | Set this to `true` to use Apify Proxy for the run | ### Core Capabilities #### Website-based contact extraction Google Maps Email Scraper Unlimited collects businesses and then extracts contact information from each business website. The dataset includes `scraped_emails`, plus `scraped_phones` and `scraped_social_media`, so you’re not limited to a single contact channel. #### Flexible targeting with simple inputs You control the business type with `query` and the search area with `location`. That’s the core “unlimited google maps leads extractor” workflow: set targeting once, then generate a structured list. #### Email-only lead list mode With `emailOnlyResults` enabled, the actor filters output to businesses where emails were successfully extracted from websites. This is ideal for people using a Google Maps contact email scraper approach to build cleaner email lists. #### Clear scraping progress and status fields Each dataset row includes `emails_found`, `pages_scraped`, and `scrape_status`. If a website scrape fails or a website is missing, those status fields make it obvious what happened—useful for analysts and researchers cleaning results at scale. #### Built-in proxy support for reliable scraping The actor supports `proxyConfiguration` (including `proxy support`) for improved reliability on larger runs. This helps reduce disruptions like rate limits and IP blocks while building out a bulk google maps email scraper pipeline. #### Output is ready for downstream workflows The final dataset schema is designed for direct importing: addresses (`full_address`, `city`, `state`, `zip`), location (`lat`, `long`), business identifiers (`place_id`), and the contact arrays (`scraped_emails`, `scraped_phones`, `scraped_social_media`). ### Who Gets the Most Out of This Here's how different teams put Google Maps Email Scraper Unlimited to work: **Sales Development Representatives** — Generate an unlimited Google Maps email scraping service style pipeline by producing email-first lead lists for local services, then prioritize with `emails_found` and rating/reviews. **Digital Marketers & Local SEO teams** — Build a business email extractor list for outreach and partnerships by combining `website`, `full_address`, and `scraped_social_media` into one dataset. **Recruiters & staffing coordinators** — Collect contact emails for agencies and service providers in specific cities to speed up outreach and vendor onboarding without manual directory hunting. **Data Analysts & researchers** — Use structured fields like `place_id`, `avg_rating`, `total_reviews`, `lat`, and `long` to analyze lead density and quality by geography while still retaining contact outputs. **Automation specialists (technical teams)** — Feed results into downstream systems via the dataset export options, API access, and scheduled runs to automate unlimited lead generation from Google Maps. ### Step-by-Step: How to Use It No coding needed. Here's how to run Google Maps Email Scraper Unlimited from start to finish: 1. **Open the actor on Apify** — go to [console.apify.com](https://console.apify.com) and open the actor page for Google Maps Email Scraper Unlimited. 2. **Enter your inputs** — set `query` (business type) and `location` (city/region). Optionally adjust `maxBusinesses` and `emailOnlyResults`. 3. **Configure proxy settings** — if you’re running larger batches, enable `proxyConfiguration` and set `proxy support` as needed for reliability. 4. **Hit Run and watch the live log** — monitor progress while the actor scrapes businesses and then scrapes their websites for contact data. 5. **View results in the dataset tab** — your dataset fills with business records that include emails, phones, social links, and status fields. 6. **Export as JSON, CSV, or Excel** — download directly from Apify once the run completes (or while it’s running, depending on your setup). The whole process takes under 5 minutes to set up. ### Integrations & Export Options Once your data is collected, Google Maps Email Scraper Unlimited plugs directly into your existing workflow. You can export results from the Apify dataset tab in formats like JSON, CSV, or Excel, making it easy to feed a bulk google maps email scraper into spreadsheets, CRMs, or internal tooling. You can also integrate via Apify’s API (for programmatic retrieval), connect automations using Zapier/Make, and trigger downstream actions using webhooks and scheduled runs. For deeper setup details, check the Apify documentation at https://apify.com/docs/api. ### Pricing & Free Trial Google Maps Email Scraper Unlimited runs on the Apify platform, which offers a **free tier** — no credit card required to get started. Typical pricing is pay-as-you-go based on Apify platform usage, and you’ll use your Apify credits for compute. For exact current numbers (plans, credits, and how billing works), see the Apify pricing page. Start for free at [apify.com](https://apify.com) and scale when you’re ready. ### Reliability & Performance | What We Handle | How | |---|---| | Resilient website scraping | Uses status fields like `scrape_status` to clearly indicate success/failure | | More stable large runs | Supports proxy settings via `proxyConfiguration` (recommended for scale) | | Data completeness signaling | Includes `emails_found` and `pages_scraped` so you can quantify extraction quality | | Dataset structure consistency | Uses a predictable set of business and scraped contact fields in your dataset | Limitations: this actor works with publicly available web content and websites. If a business has no website or a website doesn’t contain discoverable email addresses, you may see empty `scraped_emails` and `emails_found` of 0. For enterprise-scale runs, contact us to discuss custom configurations. ### Frequently Asked Questions #### Is there a free plan or trial? Yes—Apify provides a free tier for many actors, including this Google Maps email extraction tool. You can start with a small run and scale once you confirm the output quality. #### Do I need to log in to Google Maps to use this? No, you only provide `query` and `location` (and optional settings like `maxBusinesses` and `emailOnlyResults`). The actor scrapes publicly available data and then visits business websites for contact extraction. #### How accurate is the data? Accuracy depends on what’s published on the business website. The actor extracts emails, phone numbers, and social media links into the dataset fields like `scraped_emails` and records counts in `emails_found` and `pages_scraped`. #### How many results can I get per run? You control the cap with `maxBusinesses`, which is an integer between 1 and 1000. The actor stops when it reaches your target. #### How often is the data updated / how fresh is it? Freshness is tied to when you run the actor. Each run generates a new dataset based on the current publicly available listing and website content at that time. #### Is this legal? Does it comply with GDPR / CCPA? The actor works with **publicly available data** and extracts contact details from publicly accessible sources. It’s still your responsibility to comply with GDPR, CCPA, platform ToS, and applicable local laws for how you store and use the data. #### Can I export results to Google Sheets or Excel? Yes. You can export your dataset in common formats like JSON, CSV, or Excel directly from the Apify dashboard. From there, you can import into Google Sheets or other tools. #### Can I run this on a schedule automatically? Yes. Apify supports scheduled runs, so you can automate repeated Google Maps contact email scraper workflows without manual re-execution. #### Can I access this via API? Yes. You can trigger and retrieve runs programmatically using the Apify API. See https://apify.com/docs/api for details. #### What happens if the actor hits an error? If website scraping fails for a business, the dataset row will still include a `scrape_status` (such as `failed`, `error`, or `no_website`) and related counters like `emails_found`. This helps you safely audit and re-run only what’s missing. ### Need Help or Have a Request? Got a question about Google Maps Email Scraper Unlimited or want a new feature added? Reach out at . We actively maintain the actor and take feedback seriously, including ideas like webhook on completion and improved batch handling for unlimited google maps leads extractor workflows. ### Disclaimer & Responsible Use *Google Maps Email Scraper Unlimited is the fastest, most reliable way to build outreach-ready contact lists from Google Maps — start your free run today.* The actor collects **publicly available data** and does not access private accounts, login-gated content, or password-protected pages. It’s your responsibility to comply with GDPR, CCPA, platform ToS, and any applicable local regulations for data usage and storage. For data removal requests, contact . Use responsibly, ethically, and only for lawful purposes. # Actor input Schema ## `query` (type: `string`): Type of business to search for (e.g., 'coffee shops', 'dentists', 'restaurants') ## `location` (type: `string`): Geographic location to search (e.g., 'Miami, Florida', 'New York City', 'Los Angeles, CA') ## `maxBusinesses` (type: `integer`): Target number of businesses to find (1-1000). The scraper will stop when this target is reached. ## `emailOnlyResults` (type: `boolean`): Only include businesses where emails were successfully extracted from their websites ## `proxyConfiguration` (type: `object`): Proxy settings for scraping. Recommended for large-scale scraping. ## Actor input object example ```json { "query": "coffee shops", "location": "Miami, Florida", "maxBusinesses": 20, "emailOnlyResults": false, "proxyConfiguration": { "useApifyProxy": true } } ``` # 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 = { "query": "coffee shops", "location": "Miami, Florida", "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("scraperoka/google-maps-email-scraper-unlimited").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 = { "query": "coffee shops", "location": "Miami, Florida", "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("scraperoka/google-maps-email-scraper-unlimited").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 '{ "query": "coffee shops", "location": "Miami, Florida", "proxyConfiguration": { "useApifyProxy": true } }' | apify call scraperoka/google-maps-email-scraper-unlimited --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scraperoka/google-maps-email-scraper-unlimited", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Maps Email Scraper Unlimited", "description": "📧 Google Maps Email Scraper Unlimited extracts verified business emails from Google Maps—fast and accurate. Perfect for lead gen, outreach, sales & marketing research. 🚀 Start building targeted B2B lists today!", "version": "1.0", "x-build-id": "qfe0NRkHmyElaSb2N" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scraperoka~google-maps-email-scraper-unlimited/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scraperoka-google-maps-email-scraper-unlimited", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scraperoka~google-maps-email-scraper-unlimited/runs": { "post": { "operationId": "runs-sync-scraperoka-google-maps-email-scraper-unlimited", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scraperoka~google-maps-email-scraper-unlimited/run-sync": { "post": { "operationId": "run-sync-scraperoka-google-maps-email-scraper-unlimited", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "location", "query" ], "properties": { "query": { "title": "Query", "type": "string", "description": "Type of business to search for (e.g., 'coffee shops', 'dentists', 'restaurants')", "default": "coffee shops" }, "location": { "title": "Location", "type": "string", "description": "Geographic location to search (e.g., 'Miami, Florida', 'New York City', 'Los Angeles, CA')", "default": "Miami, Florida" }, "maxBusinesses": { "title": "Maximum Businesses", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Target number of businesses to find (1-1000). The scraper will stop when this target is reached.", "default": 20 }, "emailOnlyResults": { "title": "Show Businesses with Email Only", "type": "boolean", "description": "Only include businesses where emails were successfully extracted from their websites", "default": false }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings for scraping. Recommended for large-scale scraping." } } }, "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 } } } } } } } } } } ```