How to Scrape Google Maps: A Step-by-Step Guide

Automating Local Intelligence: A Guide to scraping Google Maps that is readable by humans

We are all guilty of it. You have a list of local businesses – maybe to generate leads or do competitor analysis – and you can find yourself clicking through Google Maps profiles and copy-pasting the phone numbers into Excel and correcting the typing errors. It is tiresome, error prone and quite honestly, wastes precious engineering hours.

How to Scrape Google Maps A Step-by-Step Guide

Google Maps scraping is the answer as it automates retrieval of the publicly available data. In this tutorial, we are going to deconstruct the technical process of scraping Google Maps in order to effectively use Public Scraper Ultimate Edition as the reference tool.

What is Google Maps Scraping?

Scraping is technically defined as the process of extracting structured data of a webpage in a programmed manner. When using Google Maps, you are not hacking anything you are just using a bot to access publicly available business listing and converting the visible information to an accessible format (CSV, JSON or XML).

Common examples of such data include:

Business Name
Category (e.g., “HVAC” or Sushi Restaurant)
Address and Geolocation
Phone Number
Website URL
Review Count and aggregate rating

The Tooling Stack

Although you can write your own Python scripts using tools like Selenium or Puppeteer, it is a full-time job to maintain them against the ever-evolving Google UI This suite takes care of the DOM parsing, request management, and detection of anti-bots. It also brings together other scrapers (Bing, Yahoo, Yellow Pages, and XML sitemaps) into one interface which is good when you want to cross-reference data sources in the future, or leave your IP block listed.

1. Define Your Query Logic

Output can only be as good as your input. A scraper only automates a search query.

Bad Query: “restaurants” (Too broad, irrelevant results).
Good Query: “Italian restaurant” + “Chicago, IL 60614” List Build a list of pairs of Keyword + Location.

In case you are covering a wide area, divide it into zip code or neighborhood to get the best coverage.

2. The Google Maps Scraper has been opened

Enter your pairs of keyword-location.

Pro Tip on Fields: Only pick in the data fields you need. When you are making cold-calling list, you have to have Name, Phone, and Website. Ratings and Reviews are what you require in case you are conducting research in the field of SEO. One can remove needless DOM elements, which makes the scraping faster and consumes less memory.

3. Handle Reliability (Proxies)

When scraping 50 businesses, the local IP address should be okay. When you are scraping 5,000 you require rotating proxies.

Google keeps a record on request frequency. In case an IP requests 1,000 maps in a minute, it is flagged. Public Scraper allows integration of proxies. Allow this to redirect your traffic on varied IPs, it touches organic traffic and avoids timeouts or CAPTCHas.

4. Canary Test

Do not scrape in full at once. Test with one location pair.

Check the output: Have the phone numbers been formatted properly?
review the columns: Does the CSV export look as expected?
Check the data: Is it actually the business URL or is it the Google redirect URL?

Execute and Export

When it is tested, run the entire batch.

CSV/Excel: Ideal where the end user is non-technical or direct import to CRM ( Salesforce, HubSpot ).
JSON: Ideal when what you need is a list of single attributes (e.g., a list of URLs only).
TXT: Useful when you just require a simple list of single attributes (e.g., a list of URLs only).

Post-Processing (Data Hygiene)

Raw data is not always clean.

De-duplication: You have duplicates in case you scraped “Coffee Shops NYC” and “Cafes NYC”
De-dupe Your Spreadsheet: Tagging Add a column to your spreadsheet (e.g., ScrapeBatch001) to identify the source of your lead.

Nevertheless, you should comply with the functionality of the platform (do not DDoS the site) and privacy regulations on the use of personal data.

To explore the compliance aspect of the process in details, use the following primer: [Is Scraping Google Maps Legal?]

Scaling Up

Google Maps is the best model, although the data validation process may involve cross-checking. Public Scraper Ultimate Edition enables you to scale this process by executing the same queries on either Bing Maps or Yellow Pages to either confirm or discover other contact details of the business or to receive more time back.

Summary

Scraping is not about theft; it is about reclaiming time. With the automation of the process of collecting public business information, you no longer require data entry but rather data analysis.

Ready to construct your pipeline?

[Google Maps Scraper] – The toolkit of this workflow.