There is a huge demand to extract data from Google Maps, including the names of the places, ratings, addresses, phone numbers, etc. A very common scenario is when a businessman wants to open up a new restaurant in a particular region. He can extract restaurant information from Google Maps, and then analyze the results to develop a strategy for his business. Here, I would like to introduce 5 free Google Maps data extractors.
Some websites provide APIs for their users to access part of their data, such as Facebook, Instagram, Twitter, Amazon, etc. Google Maps is one of these sites, it provides Place API for its users.
To use the Google Maps Place API, you need to set up an account first and create your API key. The Place API returns information about places using HTTP requests. The available requests include place search, place details, place photos, place autocomplete, and query auto-complete.
This method charges you with a pay-as-you-go pricing model. Though it’s not free and lots of data restrictions come with it, it’s the safest way to get fresh place data from Google Maps.
You may be thinking: what is a “web scraping template”? Actually, this is an advanced feature of the industry-leading free data extractor Octoparse. They built dozens of templates covering all popular websites, which are ready to use preformatted crawlers. This is so far the easiest solution in the data extraction industry.
You can extract the name of the places (not necessarily restaurants), ratings, addresses, websites, phone numbers and open time with this Google Maps template. Simply enter the keyword you want to search and the bot will get the data for you within minutes. The best part is that this template is completely free to everyone.
If you think the template doesn’t meet your needs, you can build your own crawler to extract other information. For example, if you want to extract place coordinates from google maps, you may check out this video.
Web Scraper is a popular choice for people who want to scrape websites. Add it to your chrome browser and you can start watching their tutorials and learn how to use it.
Similar to Octoparse, Web Scraper also supports Cloud service, API integration, IP rotation, and extraction project scheduling. It is very flexible in terms of customized data extraction. However, it might take you a few weeks to learn how to use the scraper. Even if you get the data, it can only be stored for one or two months. Also, it is a rather expensive option for those with a limited budget.
To extract Google Maps data with the above 3 methods, users don’t need to know how to code. If you are a non-coder, they would be great solutions for you. However, if you’ve got some coding experience and you are confident with your programming ability, here are more options you can consider.
Every programmer knows Github, which is the world’s leading software development platform. On this platform, there are numerous open-source projects shared by developers worldwide and you can make good use of them. Since the projects were created by other developers before, you don’t need to build a scraper from scratch, which saves you a lot of time and energy. A great example is this Google Maps project written in Node.js.
The disadvantage of this solution is that even though most of the code has already been written, you still need to know the rudiments and write some codes to run the project successfully. Sometimes, Google Maps changes the structure of its website but the codes lack maintenance, which may also be an obstacle in your extraction process.
What’s more, the final result of extraction highly depends on the quality of the original open-source project. Sometimes the data output could be only a .txt file. In this case, it’s not feasible to extract data on a large scale.
Take Advantage of Python Framework/Library
Some Python frameworks/libraries like Scrapy and Beautiful Soup can also help build crawlers and extract the Google Maps data. For experienced programmers with years of practice in data extraction, this is a good solution since they can build highly customized crawlers with these frameworks/libraries. Nevertheless, it is not practical for coders who are in their early programming career and lack profound knowledge on web crawling.
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