Table of Contents
Why Choose Data Enrichment for Coordinate Extraction?
The reason we're focusing on the data enrichment method is simple: it's much easier to switch from the second method to the first than from the first to the second. As we'll discover throughout this guide, depending on the quality of our input data, we can achieve more or less accurate results.
Before we dive into the technical details, if you would like to discover the optimal solution for scraping Google Maps, you can visit Scrap.io. We will talk about this powerful tool later in this guide. Additionally, if you have concerns about the legal aspects of coordinate extraction, you can read our comprehensive guide on whether it's allowed to scrape Google Maps to ensure you're following best practices.
Method 1: Using Addresses as Input
The first method we're going to explore involves using addresses as your starting point. You probably have a list of addresses, and the aim is to insert them one by one into the Google Maps input to make a Google Maps search. Ideally, you should end up with a Google Maps detail page, and based on this detailed page, you should be able to extract Google Maps coordinates.
Setting Up Your Scraping Tool
To demonstrate this method, I'm going to use Octoparse. First, I type my URL, which is google.com/maps. Initially, you might see the interface in a different language - in this case, it was in French because my browser settings were in French. But let me change the language settings for you.
I turn on browser mode and change the language settings. Once that's done, I turn off browser mode and select the Google Maps search text input. This is very important - I need to make sure that I'm selecting an input field, which appears as a text box. I enter a text example - let's take the first address as an example.
After entering the address, I adjust the settings and configure the system to press the enter key when finished entering the address. I also enable Ajax loading to ensure the page loads properly. When I click apply, I should be able to reach the detail page.
Extracting Coordinates from the URL
Now comes the crucial part: extracting the coordinate data. The interesting thing about Google Maps is that while coordinates might not be visibly displayed on the page, they are embedded in the Google Maps URL itself. If you look at the detailed page URL, you'll find the latitude and longitude coordinates right there.
To extract this data, I click on custom field options and select page URL data. I actually need to do this twice - once for latitude and once for longitude. To modify the extracted text, I use the "clean data" feature and add a step for regular expression matching.
Regular expressions (regex) might seem complicated, but their purpose is straightforward: they help you identify specific patterns within text. For example, I know that the latitude starts with an "@" symbol and ends with a comma. Using regex, I can generate a match for this pattern and extract my latitude. I apply the same principle for longitude, which is located between two commas in the URL.
After adjusting the settings with a 5-second timeout, there's one more important step. I need to make sure that any popup that appeared at the beginning won't interfere with the process. To handle this, I use cookies from the current page and click apply.
The Limitations of Address-Based Extraction
Once I've set up the basic extraction, I need to customize the script by adding a loop. While we can extract coordinates one by one, it's not very practical for bulk operations.
However, here's where we need to be honest about the limitations. While using addresses as input does work in some cases, it's not an optimal solution. When you enter an address into the Google Maps input, you'll encounter one of two scenarios:
Option 1: You end up with a detail page. In this case, there's no problem - one address equals one specific location, so we can perfectly extract Google Maps coordinates.
Option 2: You end up with multiple locations. When you enter an address and Google Maps shows you a list of two or more locations, your coordinates will be inaccurate because the system doesn't know which specific location you're targeting.
This is why address-based extraction isn't optimal. If you absolutely must use addresses as input, please make sure your addresses are as accurate as possible. You can make your addresses more specific by using concatenation formulas in Excel, combining street address, city, state, and zip code.
Method 2: Using Place IDs for Precision
Rather than relying on addresses as inputs, a much better approach is to focus on Place IDs. The use of Place IDs seems much more relevant because while an address may lead to multiple locations, a Place ID is always related to a single location - a single place.
Setting Up Google Maps API for Geocoding
To find coordinates based on Place IDs, we need to use the Google Maps API, specifically the Geocoding API. Don't worry if you're not a developer - it's not as difficult as it might sound. For a detailed walkthrough of the entire process, you can check out our ultimate guide to getting your Google Maps API key with ease.
The process involves importing the requests library, writing a bit of code, and using a specific URL format. We replace the output format with JSON and add two parameters: our Place ID and our API key.
Let me walk you through creating an API key. First, go to console.cloud.google.com and create a new project. Select "New Project," give your project a name, and click create. This process takes just a few seconds.
Once your project is created, you need to set up your API. Go to "APIs & Services" and then "Library." Search for "Geocoding API," click on the result, and click "Enable."
Important note: You'll also need to create a billing account because the Google Maps API is a paid service. After enabling the API, you'll get your API key. Save this key somewhere secure - you'll need it for your requests.
If you need to find your API key later, go to "Credentials" and you'll see it listed there.
Writing the Code
Now let's write the actual code. First, I import the necessary libraries - requests and json. Then I structure my request:
import requests
import json
response = requests.get(url_with_parameters)I change the output format to JSON and add parameters for Place ID and API key. When everything is set up correctly, you should get a status code of 200, which means the request was successful.
To access the coordinate data from the JSON response, I create a variable and navigate through the data structure:
data = response.json()
latitude = data['results'][0]['geometry']['location']['lat']
longitude = data['results'][0]['geometry']['location']['lng']The good news is that this method actually works very well. If we insert multiple Place IDs, we can achieve much more accurate results than with the address method.
The Place ID Challenge
However, our script isn't complete yet. While we can extract data into a JSON file, we might want to save results into a CSV or Excel file. For that, we'd need to use additional libraries like pandas and create loops to handle multiple Place IDs simultaneously.
But there's a bigger challenge: Place IDs are really difficult to scrape in the first place. While we can find techniques to locate Place IDs one at a time, let's be honest - it's not really a scalable solution.
Method 3: The Optimal Solution - Data Enrichment
So what choices do we have? We can use addresses, which are easy to scrape but not very accurate. We can use Place IDs, which are very accurate but difficult to scrape.
But there's a third option - and it's probably the best one. We can use data such as website URLs, phone numbers, or email addresses as our input. Actually, we can use four different types of fields: the website URL, domain name, phone numbers, and email addresses.
Why This Method Works Best
The purpose of this approach is data enrichment. Based on these easily obtainable data points, we can retrieve every Google Maps data field, including coordinates, as long as there's a corresponding Google Maps business listing.
The challenge here is that we cannot use the standard Google Maps API for this type of enrichment. This is where specialized tools come into play.
Introducing Scrap.io for Coordinate Extraction
Scrap.io is the ultimate solution for Google Maps scraping and coordinate extraction. As a powerful lead generation platform, Scrap.io allows you to extract comprehensive Google Maps data, including precise latitude and longitude coordinates, from over 200 million indexed businesses worldwide.
What makes Scrap.io particularly effective for coordinate extraction:
- Real-time data extraction directly from Google Maps (no outdated databases)
- Advanced filtering capabilities to target only businesses with specific data points
- Bulk coordinate extraction for thousands of locations simultaneously
- Data enrichment features that combine Google Maps data with website information
- API access for automated coordinate extraction workflows
By specifying a category and a location, you can gather thousands of leads with their exact coordinates within just a couple of clicks. The system provides you with comprehensive data exports in CSV or Excel format.
If you're interested in extracting additional data points beyond coordinates, you might find our guide on how to find email addresses from Google Maps particularly useful, as it demonstrates the full data enrichment capabilities of the platform.
When I say you can get all this data within a couple of clicks, I mean it literally. By visiting the platform and creating your account, you can get your first 100 leads free of charge. The good news is that by subscribing to Scrap.io, you can also make use of their powerful API for automated coordinate extraction.
For those evaluating different tools in the market, Scrap.io stands out as a superior alternative to other popular platforms. You can read our detailed comparison in OutScraper Alternative: Why Scrap.io is the Best Google Maps Scraping Tool to understand the key differentiators.
Using the Scrap.io API
Let me show you how to use the Scrap.io API for coordinate extraction. After importing requests and json libraries, I need to check the API documentation. In the documentation, I click on "gmaps" and "enrich" and make sure I'm looking at the Python tab.
I copy the provided code and customize it for my needs. The URL remains the same, but I modify the parameters. Instead of using "domain," I change it to "url" and insert a specific website URL.
I also add another parameter: "per_page = 1" because I expect to get one specific result, not 10 or 25 results.
For authorization, I simply replace the placeholder with my actual API key. To create an API key, I go back to Scrap.io, click on my dashboard, then profile and security, and finally API keys. I create my API key and copy it into my code.
Extracting Coordinates from API Response
Once I run the request, I can access the coordinates from the response. The coordinates are located under "location_latitude" and "location_longitude" in the returned data:
data = response.json()
latitude = data[0]['location_latitude']
longitude = data[0]['location_longitude']This third method is probably the best approach because it combines the best of both worlds. On one hand, website URLs and phone numbers are relatively easy to scrape (email addresses require additional steps but can be found through website analysis). At the same time, these data fields are accurate - each URL, phone number, and email address is typically related to a single location and a single company.
Frequently Asked Questions
Q: What's the difference between using addresses vs Place IDs for coordinate extraction?
A: Addresses can lead to multiple locations on Google Maps, making your coordinates inaccurate. When you search for an address, you might get a list of similar locations rather than a specific business page. Place IDs, however, are always related to a single, specific location, making them much more accurate for coordinate extraction.
Q: Why is the data enrichment method better than direct Google Maps scraping?
A: Data enrichment using website URLs, phone numbers, or email addresses offers the best balance of accuracy and scalability. These data points are easier to obtain than Place IDs but more accurate than addresses. Plus, it's easier to transition from data enrichment to direct scraping than the other way around.
Q: Can I extract coordinates from Google Maps URLs directly?
A: Yes! Google Maps coordinates are actually embedded in the URL after the "@" symbol. For example, in a URL like @37.7749,-122.4194, the numbers represent latitude and longitude. You can extract these using regular expressions (regex) to identify the pattern.
Q: What tools do I need for bulk coordinate extraction?
A: For bulk extraction, you'll need specialized tools like Scrap.io, Octoparse, or similar Google Maps scrapers. These tools can handle thousands of locations simultaneously and provide coordinates along with other business data. Manual extraction is only practical for small numbers of locations.
Q: Is it legal to scrape coordinates from Google Maps?
A: Extracting publicly available data like coordinates falls under acceptable use when done for legitimate business purposes. However, always respect rate limits and terms of service. Tools like Scrap.io ensure compliance with legal requirements while providing comprehensive data extraction capabilities.
Q: How accurate are coordinates extracted through different methods?
A: Place IDs provide the highest accuracy, followed by data enrichment using website URLs/phone numbers, and finally addresses. The quality of your input data significantly impacts the accuracy of results - more specific and complete information leads to better coordinate extraction.
Q: What's the Google Maps Geocoding API and when should I use it?
A: The Geocoding API converts addresses into latitude/longitude coordinates and vice versa. It's perfect when you have Place IDs and want to get precise coordinates programmatically. However, it requires an API key, billing setup, and is best for applications with predefined, static addresses rather than dynamic user input.
Q: Can I automate coordinate extraction for ongoing projects?
A: Absolutely! Using APIs like Scrap.io's or Google's Geocoding API, you can set up automated workflows. This is particularly useful for maintaining up-to-date location databases or integrating coordinate extraction into larger data processing pipelines.
Conclusion and Next Steps
Now all we need to do is improve our script by creating a loop structure. This will allow us to insert as many website URLs as possible to efficiently extract Google Maps coordinates for multiple locations.
The key takeaway from this guide is understanding which method works best for your specific use case:
- Addresses: Easy to obtain but potentially inaccurate
- Place IDs: Highly accurate but difficult to scrape
- Website URLs/Phone Numbers/Emails: The sweet spot of accessibility and accuracy
For most practical applications, the data enrichment approach using website URLs, phone numbers, or email addresses provides the best balance of accuracy and scalability.
If you're serious about Google Maps coordinate extraction and data enrichment, I highly recommend exploring Scrap.io's capabilities. The platform makes it incredibly easy to extract comprehensive location data, including precise coordinates, from Google Maps listings.
The combination of proper technique and the right tools can make Google Maps coordinate extraction both accurate and efficient.