How to Effectively Scrape Google Maps Data?

Google Maps contains millions of business listings: addresses, phone numbers, emails, customer reviews, hours, photos. It is a free and public database. But how can you extract the data efficiently without investing months in development?

This article explains three approaches to scrape Google Maps — from Python code to no-code tools — along with their advantages, limitations, and actual costs.

Why Scrape Google Maps?

Google Maps is not just a navigation app. It is a comprehensive business directory. Each listing contains:

Address and GPS coordinates — exact location
Phone — direct contact
Email — enriched from the website
Google Rating — real-time reputation
Customer Reviews — full text, date, author
Opening Hours — days and times
Photos — visuals of the place
Website — link to the digital
Social Media — online presence

Use cases are concrete: sales prospecting, market analysis, competitive study, detection of hot leads (poorly rated, newly opened), CRM data enrichment.

A real estate agency can find 500 competing agencies in a region in 2 minutes. An SEO consultant can identify small businesses without a website. An ABM manager can target companies with a bad Google reputation.

The problem: Google Maps limits results to 120 per search. And the interface does not allow exporting to CSV. Hence the need for scraping.

Three Approaches to Scrape Google Maps

Approach 1: Free Chrome Extensions (quick, limited)

Chrome extensions like "Maps Data Exporter" or "Google Maps Extractor" allow you to scrape directly from the browser.

How it works: 1. Install the extension 2. Search on Google Maps (e.g., "plumbers Paris") 3. The extension reads the visible results 4. You download in CSV/Excel

Advantages: - Free - No code to write - Results in 30 seconds - No technical setup

Limitations (critical): - Limits to 120 results — Google Maps only displays 120 listings per search - Limited data — name, address, phone only. No reviews, no enriched emails, no technology detection - No advanced filters — impossible to search by Google rating, number of reviews, or claimed listing - Unstable — extensions break with every Google Maps update - No API — impossible to automate or integrate into a workflow

Real use case: A plumber wants 50 potential clients in Paris. The extension is sufficient. But an agency that wants 5,000 prospects? No.

Approach 2: Python Code with Selenium + Beautiful Soup (powerful, complex)

This is the "developer" approach. You write a Python script that automates the browser, scrolls through Google Maps, scrapes the HTML, and exports the data.

Script architecture:

from selenium import webdriver
from selenium.webdriver.common.keys import Keys
from bs4 import BeautifulSoup
import csv
import time

# 1. Open the browser
driver = webdriver.Chrome()
driver.get("https://www.google.com/maps")

# 2. Search
search_box = driver.find_element("name", "q")
search_box.send_keys("restaurants Paris")
search_box.send_keys(Keys.RETURN)

# 3. Wait for loading
time.sleep(3)

# 4. Scrape visible results
html = driver.page_source
soup = BeautifulSoup(html, "html.parser")
results = soup.find_all("div", class_="Nv2PK")

# 5. Extract data
data = []
for result in results:
    name = result.find("span", class_="qBF1Pd").text
    address = result.find("span", class_="UaQhf").text
    phone = result.find("span", class_="UsdlK").text
    data.append({"name": name, "address": address, "phone": phone})

# 6. Export
with open("results.csv", "w", newline="") as f:
    writer = csv.DictWriter(f, fieldnames=["name", "address", "phone"])
    writer.writerows(data)

driver.quit()

Advantages: - Free (Python is open source) - No volume limits (in theory) - Customizable data - Possible to add filters (rating > 4 stars, etc.) - Automatable (run every night)

Limitations (very real): - Detection and blocking — Google detects Selenium scrapers. Your IP will be blocked after 50-100 requests - Ongoing maintenance — Google changes its HTML every month. Your script breaks with every update - No reviews or emails — Selenium can read visible HTML, but not reviews (loaded in JavaScript) or emails from the website (needs an enrichment API) - Development time — 40-80 hours for a robust script - Infrastructure — requires a server, proxies, error management - Legal gray area — Google Maps ToS prohibits scraping. You risk a permanent IP block

Real use case: An SEO agency with an in-house developer who wants to scrape 1,000 leads per month and can accept occasional IP blocking. Not for SMEs.

Approach 3: Dedicated SaaS Tools (optimal balance)

Tools like IBLead, IBLead, or Apify offer a pre-indexed database of Google Maps. You do not scrape in real-time — you query a pre-built database.

How it works: 1. Log in to the app 2. Search by city, region, category 3. Apply filters (rating, number of reviews, detected technologies) 4. Export to CSV in 2 clicks

Concrete example with IBLead:

You want to find all restaurants in Lyon with a rating < 3 stars (potential clients for a reputation agency).

Go to app.iblead.com
Select "France" → "Auvergne-Rhône-Alpes" → "Lyon"
Category: "Restaurants"
Filters: Google Rating < 3 stars
Export: 247 restaurants in CSV
Columns: name, address, phone, email, rating, full reviews

Total time: 90 seconds. No code, no IP blocking, no maintenance.

Advantages: - No IP blocking — data is pre-indexed, no real-time scraping - Advanced filters — Google rating, number of reviews, detected technologies (WordPress, Shopify, etc.), claimed listing, SIRET (France) - Enriched data — complete Google reviews (EXCLUSIVE at IBLead), emails from the website, detection of 160+ technologies - Zero maintenance — the database updates automatically every month - Legal — no ToS violation, no risk - API and integrations — connect to HubSpot, Salesforce, Zapier, Lemlist

Limitations: - Not free (but €44/month minimum for 10,000 exports/month) - Data updated monthly (not in real-time, but sufficient for 99% of cases)

Real use case: A prospecting agency that wants 2,000 leads/month in 2 hours. IBLead costs €89/month (20,000 exports). IBLead costs €179/month for the same thing. IBLead is 44% cheaper.

Comparison of the Three Approaches

Criteria	Chrome Extension	Python + Selenium	SaaS (IBLead)
Cost	€0	€0 (internal dev)	€44-250/month
Max volume/month	500	1,000	10,000-100,000
Setup time	5 min	40-80h	5 min
Risk of IP blocking	Low	Very high	Zero
Advanced filters	No	Yes (complex)	Yes (simple)
Google Reviews	No	No	Yes (EXCLUSIVE)
Enriched Emails	No	No	Yes
Tech Detection	No	No	Yes (160+)
Maintenance	Medium	Very high	Zero
Use Case	Small volume	Tech-savvy	Professional

Data You Can Extract

Here’s what each approach allows you to retrieve:

Chrome Extension + Python Selenium

Business name
Address (street, city, postal code)
Phone
Website (URL)
Categories (e.g., Restaurant, Pizzeria)
GPS coordinates (latitude, longitude)
Number of reviews
Average Google rating
Opening hours

SaaS (IBLead)

Everything above +: - Complete Google reviews — text, rating (1-5), date, author - Enriched email — extracted from the business's website - Detected technologies — WordPress, Shopify, WooCommerce, React, Google Analytics, HubSpot, Mailchimp, etc. (160+ total) - Social media — Facebook, Instagram, LinkedIn links - Claimed listing — yes/no (listing optimized by the owner) - Number of photos — count of visuals - SIRET/SIREN (France only) — legal identification number - Manager (France) — name of the responsible person - APE code (France) — activity classification - Legal form (France) — SARL, SAS, EIRL, etc.

Legal Limits of Scraping Google Maps

Google Maps ToS (Terms of Service) explicitly prohibits automated scraping.

Article 3.2.1: "You must not... access, search, or create databases from the Services without Google's written permission."

Possible consequences: - Temporary IP blocking (24-48h) - Permanent IP blocking - Legal request (rare, but possible)

Practical reality: - Chrome extensions are tolerated (low volume, no detected scrapers) - Selenium scripts are quickly blocked (Google detects the automated user-agent) - SaaS tools that use proxies and random delays survive longer but still risk blocking

The legal solution: Use a pre-indexed database (like IBLead) that has already done the scraping. You are no longer responsible for scraping — you simply access organized public data.

Practical Guide: Scrape Effectively in 5 Steps

Step 1: Define Your Need

Ask yourself these questions: - Volume: How many leads per month? (100? 5,000? 50,000?) - Frequency: Once or regularly? - Filters: Do you need to filter by Google rating, reviews, technologies? - Data: Do you need full reviews? Enriched emails? Tech detection? - Skills: Do you have an in-house developer?

Example: "I want 500 plumbers from Paris every month, with their phone and email, without worrying about IP blocks."

→ Answer: SaaS (IBLead).

Example 2: "I want to test with 50 restaurants, just to see."

→ Answer: Chrome extension.

Step 2: Choose the Tool

For a quick test: Chrome extension For a developer: Python + Selenium (and accept the risks) For professional use: SaaS (IBLead)

Step 3: Set Up Filters

If you are using a SaaS: - Geography: Country, region, city - Category: Restaurants, plumbers, hotels, etc. - Google Rating: > 4 stars? < 3 stars? - Number of reviews: Minimum 10 reviews (avoids fake listings) - Technologies: If you sell a CRM, target companies without a CRM - Claimed listing: Yes (engaged owner) or no (abandoned)

Step 4: Export and Clean

Raw data always contains noise: - Duplicates (same business, two addresses) - Missing data (empty phone) - Invalid numbers (incorrect format) - Invalid emails

Simple cleaning in Excel: - Remove empty rows - Deduplicate by name + address - Validate numbers (must start with +33 or 0) - Validate emails (regex: ^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$)

Result: 80-90% of the data is usable.

Step 5: Integrate into Your Workflow

Options: - CRM: Import in CSV to HubSpot, Salesforce, Pipedrive - Email: Send the list to Lemlist, Instantly, or another cold email tool - Analysis: Load in Excel/Google Sheets to analyze by region, rating, etc. - Automation: Via Zapier or n8n, trigger an action (create a deal, add a tag)

Concrete Use Cases

Case 1: Reputation Agency (e-reputation)

Objective: Find businesses with a bad Google rating.

Approach: 1. Search by category (restaurants, hotels, services) 2. Filter Google rating < 3 stars 3. Retrieve full reviews (text, date, author) 4. Identify recurring issues (slow service, cleanliness) 5. Contact the business: "We saw your reviews. We can help you."

Tool: IBLead (€89/month) — exclusive review scraping.

Result: 500 hot prospects/month, conversion rate 15-20%.

Case 2: Web Agency

Objective: Find small businesses without a website (or with an outdated WordPress site).

Approach: 1. Search by region (e.g., Île-de-France) 2. Filter by category (plumbers, electricians, hairdressers) 3. Technology detection: target sites without modern CMS 4. Export emails 5. Prospecting email: "We saw that your site is not mobile-friendly. Here’s how we can improve it."

Tool: IBLead (detection of 160+ technologies).

Result: 1,000 prospects/month, acquisition cost €5.50/prospect.

Case 3: SEO Consultant

Objective: Analyze local competition.

Approach: 1. Search "SEO Paris" on Google Maps 2. Export the 200 SEO agencies found 3. Analyze: who has the most reviews? What is the average rating? What social media? 4. Identify leaders (rating > 4.8, > 50 reviews) 5. Propose an audit: "We saw that your competitors have X reviews. You have Y. Here’s how to catch up."

Tool: IBLead.

Result: Personalized sales pitch, response rate +30%.

Frequently Asked Questions

Q1: Is it legal to scrape Google Maps?

Short answer: Legally gray. Google prohibits it in its ToS, but rarely pursues action. SaaS tools use techniques (proxies, random delays) to minimize risk. Pre-indexed databases (like IBLead) eliminate the risk.