📩📍 Google Maps Email Extractor

What is Google Maps Email Extractor?

Google Maps Email Extractor is a web scraping tool that enables you to quickly extract emails, social media, and other contact details from places on Google Maps.

• Find contact details by URL, placeID, category, keyword, location, or coordinates
• Get information like emails, but also social media accounts, phone numbers, website, and physical address
• Social media includes LinkedIn, Twitter, YouTube, TikTok, Facebook, Instagram, Pinterest, and Discord
• Show results in tables or in map view
• Get over the limitation of Google Maps of displaying (and scraping) no more than 120 places per area
• Pre-filter Google Maps places by rating, for example scrape only places that are 3 stars and higher
• Choose to skip places that are temporarily or permanently closed
• Get a visualized map of scraped places
• Set up the language of Google Maps scraping, so you could get Spanish-language Google Maps results, for example
• Use API in Python and Node.js, API Endpoints, integrations with other apps, and webhooks
• Export Google Maps data in Excel, CSV, JSON, and HTML

We recommend trying out Google Maps Scraper, as well, since it extracts even more than Google Maps Email Extractor can. It’s also faster, while costing less.

What data can this Google Maps Email Extractor extract?

To scrape all data from Google places, including images, reviews, and web results, try the original Google Maps Scraper.

How much does Google places email scraping cost?

This scraper uses a pay-per-result (PPR) pricing model. It costs $10 to scrape 1,000 search results, so $0.01 per item. On the free plan you get $5 in credit, meaning you can scrape 500 places on Google Maps without it costing anything.

Subscribing to one of our paid plans adds more credit to your account and reduces the cost of scraping. Our Starter plan reduces the price to $9 per 1,000 search results, allowing you to scrape around 4,300 Google Maps Places monthly.

Google Maps Scraper is even cheaper, costing just $0.004 per result on the free and Starter plans (though with a tiny fee to start the Actor). It offers the option to decide which paid add-ons to use, giving it more flexible pricing than Google Maps Email Extractor.

How do I use Google Maps Email Extractor?

This Google Maps Email Extractor was designed for an easy start even if you've never extracted contact detail data from the web before. If you want more guidance on how to use Google Maps Email Extractor, this video tutorial shows you how to do it in just a few minutes.

⬇️ Input

The input for Google Maps Email Extractor should be either a Google Maps URL or a location in combination with a search term. You can provide keywords, URLs, and categories either one by one or in bulk. You can provide the location as a simple city name, a full postal address, or as a polygon consisting of multiple coordinates.

Here's a simple input example of scraping email addresses from 50 bars in Boston:

{
    "language": "en",
    "locationQuery": "Boston, USA",
    "maxCrawledPlacesPerSearch": 50,
    "searchStringsArray": [
        "bar"
    ],
    "skipClosedPlaces": false
}

Click on the input tab for a full explanation of input in JSON.

Search terms

Using multiple similar search terms can increase the number of scraped places, but also increases the time a run takes. We recommend using a combination of search terms that are distinct or overlap only slightly in meaning. Using a long list of duplicate search terms will just increase the time of a run without providing more results.

Example of a good list of search terms: [restaurant, bar, pub, cafe, buffet, ice cream, tea house]

Example of a bad list of search terms: [restaurant, restaurants, chinese restaurant, cafe, coffee, coffee shop, takeout]

While Google search results often include categories adjacent to your search, e.g. restaurant might also capture some cafe or bar places, but you will get better results if you use them as separate search terms, as well.

Categories

Using categories can be dangerous!

Search terms can introduce false positives, extracting some irrelevant places. Categories can be used to narrow down the results to just the ones you select.

Categories can also be dangerous because they can cause false negatives, excluding places you might want in the results. Google has thousands of categories, and many are synonymous. You must list all the categories you want to match, including all synonyms; for example, Divorce lawyer, Divorce service, and Divorce attorney are three distinct categories. Some places might be classified as only one of them, meaning you should input all of them. For this reason, we recommend going through the categories list carefully. For some use cases, you might want to select as many as 100 categories to ensure you don't miss any relevant places.

To help with this, Google Maps Email Extractor tries to increase the chance of a match by doing the following:

• If any category of a place (each can have several categories) matches any category from your input, it will be included.
• If all words from your input are contained in a category name, it will be included. E.g. restaurant will match Chinese restaurant and Pan Asian restaurant.

⚠️ If categories are used without search terms, they will be used both as search terms and as category filters. However, for the above reasons, using categories without search terms is not recommended. We generally recommend using fewer search terms and more categories.

Search without geolocation

Rather than using the standard search term and location inputs, you may also opt to use only the search term (e.g. "restaurants in berlin") or a direct Google Maps search URL (e.g. https://www.google.com/maps/search/restaurants/@52.5190603,13.388574,13z/) without the location input field. However, this approach will limit the number of results to a maximum of 120 because it only opens a single map screen on Google with a finite scroll. We only recommend skipping location input if you don't need more than 120 results, you need the lowest possible latency, or you want to get the results in the same order as Google would provide.

⬆️ Output example

The results will be wrapped into a dataset found in the Output or Storage tab. Note that the output is organized in tables and tabs for your convenience. You can view results as a table, JSON, or as a map.

Once the run is finished, you can also download the dataset in various data formats (JSON, CSV, Excel, XML, HTML). Before exporting, you can pick or omit specific output fields; alternatively, you can also choose to download the whole view, which includes thematically connected data.

Table view

The table view can be manipulated in different ways. There is a general overview, but you can also sort the table by contact info, location rating, reviews, or other fields.

Here's what it looks like to scrape over 1,000 bars in Boston:

JSON file

Here's the amount of data you'd get for a single scraped place:

Contact Details

[
  {
    "emails": [
      "development_sites@dunkinbrands.com"
    ],
    "phones": [
      "+18138841600"
    ],
    "phonesUncertain": [
      "(813) 884-1600",
      "800-777-9983",
      "800-447-0013",
      "(800) 447-0013",
      "800-859-5339",
      "781-737-3000",
      "678-514-4100",
      "4941715"
    ],
    "linkedIns": [
      "https://www.linkedin.com/company/dunkin"
    ],
    "twitters": [
      "https://twitter.com/dunkindonuts"
    ],
    "instagrams": [
      "https://www.instagram.com/dunkin/"
    ],
    "facebooks": [
      "https://www.facebook.com/DunkinUS/"
    ],
    "youtubes": [
      "https://www.youtube.com/user/dunkindonuts"
    ],
    "tiktoks": [],
    "pinterests": [
      "https://www.pinterest.com/DunkinDonuts/"
    ],
    "discords": [],
  }
]

Place Details

"rank": 7,
    "title": "Dunkin'",
    "description": "Long-running chain serving signature breakfast items & a variety of coffee drinks.",
    "price": "$1\u201310",
    "categoryName": "Coffee shop",
    "address": "4325 W Hillsborough Ave, Tampa, FL 33614",
    "neighborhood": "Pinecrest West Park",
    "street": "4325 W Hillsborough Ave",
    "city": "Tampa",
    "postalCode": "33614",
    "state": "Florida",
    "countryCode": "US",
    "website": "https://locations.dunkindonuts.com/en/fl/tampa/4325-hillsborough-plz/337999?utm_source=google&utm_medium=local&utm_campaign=localmaps&utm_content=337999&y_source=1_MTIxMDcxODQtNzE1LWxvY2F0aW9uLndlYnNpdGU%3D",
    "phone": "(813) 884-1600",
    "phoneUnformatted": "+18138841600",
    "claimThisBusiness": false,
    "location": {
      "lat": 27.9966569,
      "lng": -82.5165572
    },
    "totalScore": 3.3,
    "permanentlyClosed": false,
    "temporarilyClosed": false,
    "placeId": "ChIJj0uggtTDwogRV0Q_FH8LfxQ",
    "categories": [
      "Coffee shop",
      "Bagel shop",
      "Bakery",
      "Breakfast restaurant",
      "Donut shop",
      "Fast food restaurant",
      "Takeout Restaurant"

Opening Hours

"openingHours": [
      {
        "day": "Monday",
        "hours": "4\u202fAM to 7\u202fPM"
      },
      {
        "day": "Tuesday",
        "hours": "4\u202fAM to 7\u202fPM"
      },
      {
        "day": "Wednesday",
        "hours": "4\u202fAM to 7\u202fPM"
      },
      {
        "day": "Thursday",
        "hours": "4\u202fAM to 7\u202fPM"
      },
      {
        "day": "Friday",
        "hours": "4\u202fAM to 7\u202fPM"
      },
      {
        "day": "Saturday",
        "hours": "4\u202fAM to 7\u202fPM"
      },
      {
        "day": "Sunday",
        "hours": "4\u202fAM to 7\u202fPM"
      }
    ],
    "additionalOpeningHours": {
      "Delivery": [
        {
          "day": "Monday",
          "hours": "4\u202fAM\u20137\u202fPM"
        },
        {
          "day": "Tuesday",
          "hours": "4\u202fAM\u20137\u202fPM"
        },
        {
          "day": "Wednesday",
          "hours": "4\u202fAM\u20137\u202fPM"
        },
        {
          "day": "Thursday",
          "hours": "4\u202fAM\u20137\u202fPM"
        },
        {
          "day": "Friday",
          "hours": "4\u202fAM\u20137\u202fPM"
        },
        {
          "day": "Saturday",
          "hours": "4\u202fAM\u20137\u202fPM"
        },
        {
          "day": "Sunday",
          "hours": "4\u202fAM\u20137\u202fPM"
        }
      ]
    },

Additional Place Details

{
          "Quick bite": true
        }
      ],
      "Dining options": [
        {
          "Breakfast": true
        },
        {
          "Brunch": true
        },
        {
          "Lunch": true
        },
        {
          "Dinner": true
        },
        {
          "Dessert": true
        },
        {
          "Seating": true
        }
      ],
      "Amenities": [
        {
          "Restroom": true
        },
        {
          "Wi-Fi": true
        },
        {
          "Free Wi-Fi": true
        }
      ],
      "Atmosphere": [
        {
          "Casual": true
        },
        {
          "Trendy": true
        }
      ],
      "Crowd": [
        {
          "College students": true
        },
        {
          "Family-friendly": true
        },
        {
          "Groups": true
        },
        {
          "Tourists": true
        }
      ],
      "Planning": [
        {
          "Accepts reservations": false
        }
      ],
      "Payments": [
        {
          "Credit cards": true
        },
        {
          "Debit cards": true
        },
        {
          "NFC mobile payments": true
        },
        {
          "Credit cards": true
        }
      ],
      "Children": [
        {
          "Good for kids": true
        },
        {
          "High chairs": true
        }
]

Map view

Google Maps Email Extractor provides a zoomable map that shows all the places scraped. The map is shown in the Live View tab on the actor run page and also stored in the Key-Value Store as results-map.html record.

Want to scrape Google Maps reviews or images?

For more comprehensive Google Maps data, we recommend using Google Maps Scraper. It uses the same input options, but has a lot more options and is able to extract many more different types of data.

For more specific use cases, we recommend the following:

• Google Maps Reviews Scraper, which focuses on Google Maps reviews
• AI Text Analyzer for Google Reviews, which can help you figure out keywords from review batches
• Google Maps Scraper Orchestrator, which lets you run multiple Google Maps Scraper instances concurrently
• Competitive Intelligence AI Agent, which can figure out competitors’ strengths and weaknesses
• Market Expansion AI Agent, which can help you determine where best to expand to

Frequently asked questions

How can I extract Google Maps email addresses by coordinates?

If you want to customize your location for a specific area, you can use this tool's Custom search area option. You’ll have to provide coordinate pairs for an area and the scraper will create start URLs out of them. There are several types of search area geometry that you can use in Google Maps Extractor: Polygon, MultiPolygon and Point (Circle). We’ve found the polygons and circle to be the most useful ones when it comes to extracting data from Google Maps.

Can I integrate Google Maps Email Extractor with other apps?

Yes. The Google Maps Email Extractor can be connected with almost any cloud service or web app thanks to integrations on the Apify platform. You can integrate your Google Maps data with Zapier, Slack, Make, Airbyte, GitHub, Google Sheets, Asana, LangChain and more.

You can also use webhooks to carry out an action whenever an event occurs, for example, get a notification whenever Google Maps Scraper successfully finishes a run.

Can I use Google Maps Email Extractor as its own API?

Yes, you can use the Apify API to access Google Maps Email Extractor programmatically. The API allows you to manage, schedule, and run Apify actors, access datasets, monitor performance, get results, create and update Actor versions, and more.

To access the API using Node.js, you can use the apify-client NPM package. To access the API using Python, you can use the apify-client PyPI package.

For detailed information and code examples, see the API tab or refer to the Apify API documentation.

Is it legal to scrape Google Maps data?

Web scraping is legal if you are extracting publicly available data which is most data on Google Maps. However, you should respect boundaries such as personal data and intellectual property regulations. You should only scrape personal data if you have a legitimate reason to do so, and you should also factor in Google's Terms of Use.

Your feedback

We’re always working on improving the performance of our Actors. So if you’ve got any technical feedback for Google Maps Email Extractor or simply found a bug, please create an issue on the Actor’s Issues tab.