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Google Maps Scraper - Extract Business Data
A powerful open-source tool built in Go for scraping comprehensive data from Google Maps, including business details, contact information, reviews, and location data.
Go
Added on 2025年5月8日1,838
Stars217
ForksGo
LanguageProject Introduction
Summary
This project is a command-line tool and library designed to programmatically scrape business data from Google Maps. It allows users to extract detailed information for numerous businesses based on search queries or location.
Problem Solved
Manually gathering extensive business data from Google Maps is time-consuming and impractical for large datasets. While official APIs exist, they can be costly and have usage limitations. This tool provides an efficient and open-source alternative for bulk data collection.
Core Features
Comprehensive Data Extraction
Efficiently extracts key business information such as name, address, phone, website, and more.
Reviews and Ratings Scraping
Gathers ratings, total number of reviews, and detailed review texts for listed businesses.
Location Data Retrieval
Obtains precise geographic coordinates (latitude and longitude) for each location.
Tech Stack
Go
HTTP/2
Concurrency
Use Cases
The Google Maps Scraper can be utilized in numerous scenarios where aggregated business information is required:
Lead Generation and Sales Prospecting
Details
Gather contact details and location information for businesses in specific industries or geographic areas to build targeted sales lists.
User Value
Efficiently build comprehensive lists of potential customers or partners.
Market Research and Competitor Analysis
Details
Collect competitor information, including services offered, reviews, and locations, to analyze market positioning.
User Value
Gain insights into the competitive landscape and identify market trends.
Sentiment Analysis of Customer Reviews
Details
Extract review data to perform sentiment analysis or identify common feedback themes across multiple businesses.
User Value
Understand customer perceptions at scale without manual data collection.
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