Google Maps Scraper: How to Get Business Data the Allowed Way

Can you scrape Google Maps?

Google’s terms prohibit scraping or exporting Maps content outside its products and APIs, and tools that do it can get blocked and expose you to legal risk. The supported route is the Google Maps Platform, specifically the Places API. It returns business names, addresses, phone numbers, websites and ratings as structured data, and it is meant for this kind of lookup. Google also sets rules on how long you can store results and how they must be shown, so read the Maps Platform terms for your use.

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Step 1: set up the Places API

1. Create a Google Cloud project and enable billing.
2. Enable Places API (New).
3. Create an API key and restrict it to that API.
4. Check current pricing and free usage on the Google Maps Platform pricing page before you run big searches. Costs depend on which fields you request, so ask only for what you need.

Step 2: the Python script

Install requests with pip install requests, add your key, and run. It searches by text, follows result pages and writes a CSV.

import csv
import requests

API_KEY = "YOUR_API_KEY"
URL = "https://places.googleapis.com/v1/places:searchText"
FIELDS = "places.displayName,places.formattedAddress,places.nationalPhoneNumber,places.websiteUri,places.rating,nextPageToken"

def parse(data):
    rows = []
    for p in data.get("places", []):
        rows.append({
            "name": p.get("displayName", {}).get("text", ""),
            "address": p.get("formattedAddress", ""),
            "phone": p.get("nationalPhoneNumber", ""),
            "website": p.get("websiteUri", ""),
            "rating": p.get("rating", ""),
        })
    return rows

def search(query, max_pages=3):
    headers = {"X-Goog-Api-Key": API_KEY, "X-Goog-FieldMask": FIELDS}
    body = {"textQuery": query, "pageSize": 20}
    rows = []
    for _ in range(max_pages):
        r = requests.post(URL, json=body, headers=headers, timeout=30)
        r.raise_for_status()
        data = r.json()
        rows += parse(data)
        token = data.get("nextPageToken")
        if not token:
            break
        body["pageToken"] = token
    return rows

if __name__ == "__main__":
    rows = search("plumbers in Austin TX")
    with open("places.csv", "w", newline="", encoding="utf-8") as f:
        w = csv.DictWriter(f, fieldnames=["name", "address", "phone", "website", "rating"])
        w.writeheader()
        w.writerows(rows)
    print(len(rows), "places saved")

The field mask tells Google which fields to return, which keeps cost down. The parsing function was tested on sample responses, including places with missing phone or website fields, which come back as empty cells instead of errors. The live request needs your own key, so test with a small search first.

Turn the list into leads

• Open places.csv in Excel and remove duplicates.
• Rate each lead and add notes in a simple tracker. Our project tracker template works for outreach lists.
• Follow marketing laws such as CAN-SPAM and GDPR when you contact people, and use only contact details you are allowed to use.

For learning the general technique on a site that allows it, see our web scraping with Python tutorial.

Frequently asked questions

More free tools: All free tools · Web scraping with Python · Email extractor · Project tracker template