Are you looking to identify B2B leads to promote your business, product, or service? Outscraper Google Maps Scraper might just be the tool you've been searching for. This powerful software enables you to extract business data directly from Google's extensive database, which spans millions of businesses across countless industries worldwide.

Outscraper Google Maps Scraper is a tool built with advanced technology that lets you scrape a myriad of valuable information about businesses from Google's database. This information includes but is not limited to, business names, addresses, contact information, website URLs, reviews, ratings, and operational hours.

Whether you are a small business trying to make a mark or a large enterprise exploring new territories, the data obtained from the Outscraper Google Maps Scraper can be a treasure trove. This tool provides a cost-effective, efficient, and accurate method to generate leads and gather market insights.

By using Outscraper, you'll gain a significant competitive edge as it allows you to analyze your market and find potential B2B leads with precision. You can use this data to understand your competitors' landscape, discover new markets, or enhance your customer database. The tool offers the flexibility to extract data based on specific parameters like business category or geographic location, helping you to target the most relevant leads for your business.

In a world that's growing increasingly data-driven, utilizing a tool like Outscraper Google Maps Scraper could be instrumental to your business' success. If you're looking to get ahead in your market and find B2B leads in a more efficient and precise manner, Outscraper is worth considering. It streamlines the data collection process, allowing you to focus on what truly matters – using the data to grow your business.

https://outscraper.com/google-maps-scraper/

As a result of the Google Maps scraping, your data file will contain the following details:

Query Name Site Type Subtypes Category Phone Full Address Borough Street City Postal Code State Us State Country Country Code Latitude Longitude Time Zone Plus Code Rating Reviews Reviews Link Reviews Per Scores Photos Count Photo Street View Working Hours Working Hours Old Format Popular Times Business Status About Range Posts Verified Owner ID Owner Title Owner Link Reservation Links Booking Appointment Link Menu Link Order Links Location Link Place ID Google ID Reviews ID

If you want to enrich your datasets with social media accounts and many more details you could combine Google Maps Scraper with Domain Contact Scraper.

Domain Contact Scraper can scrape these details:

Email Facebook Github Instagram Linkedin Phone Twitter Youtube

Scrape business and place information from Google Maps in real time. Get addresses, phone numbers, websites, ratings, reviews, photos, business hours, and location coordinates. Useful for business directories, store locators, review analytics, and local search tools.

Explore APISCRAPY, your AI-powered Google Map Data Scraper. Easily extract Business Location Data from Google Maps and other platforms. Seamlessly access and utilize publicly available map data for your business needs. Scrape All Publicly Available Data From Google Maps & Other Platforms.

Outscraper's Location Intelligence Service is a powerful and innovative tool that harnesses the rich data available from Google Maps to provide valuable Point of Interest (POI) data for businesses. This service is an excellent solution for local intelligence needs, using advanced technology to efficiently gather and analyze data from Google Maps, creating precise and relevant POI datasets​.

This Location Intelligence Service is backed by reliable and up-to-date data, thanks to Outscraper's advanced web scraping technology. This ensures that the data extracted from Google Maps is both accurate and fresh, providing a dependable source of data for your business operations and strategic planning​.

A key feature of Outscraper's Location Intelligence Service is its advanced filtering capabilities, enabling you to retrieve only the POI data you require. This means you can target specific categories, locations, and other criteria to get the most relevant and valuable data for your business needs, eliminating the need to sift through irrelevant records​.

With Outscraper, you also get worldwide coverage for your POI data needs. The service's advanced data scraping technology allows you to collect data from any country and city without limitations, making it an invaluable tool for businesses with global operations or those seeking to expand internationally​.

Outscraper provides a vast amount of data, offering the largest number of fields available to compile and enrich your POI data. With more than 40 data fields, you can create comprehensive and detailed datasets that provide deep insights into your areas of interest​.

Outscraper's Location Intelligence Service is designed to be user-friendly, even for those without coding skills. Creating a Google Maps scraping task is quick and simple with the Outscraper App Dashboard, where you select a few parameters like category, location, limits, language, and file extension to scrape data from Google Maps​.

Outscraper also offers API support, providing a fast and easy way to fetch Google Maps results in real-time. This feature is ideal for businesses that need to access location data quickly and efficiently​.

Outscraper's Global Location Data service is an advanced solution for harnessing location-based data from Google Maps. Equipped with features such as worldwide coverage, precise filtering, and a plethora of data fields, Outscraper is your reliable source of fresh and accurate data.

Outscraper's Global Location Data Service leverages the extensive data accessible via Google Maps to deliver critical location data on a global scale. This service offers a robust solution for your global intelligence needs, utilizing cutting-edge technology to collect and analyze data from Google Maps and create accurate and relevant location datasets. The service is supported by a constant stream of reliable and current data, powered by Outscraper's advanced web scraping technology, guaranteeing that the data pulled from Google Maps is both fresh and accurate.

One of the key features of Outscraper's Global Location Data Service is its advanced filtering capabilities, allowing you to extract only the location data you need. This means you can specify particular categories, locations, and other criteria to obtain the most pertinent and valuable data for your business requirements, eliminating the need to sort through irrelevant records.

With Outscraper, you gain worldwide coverage for your location data needs. The service's advanced data scraping technology lets you collect data from any country and city without restrictions, making it an indispensable tool for businesses operating on a global scale or those looking to expand internationally. Outscraper provides a wealth of data, offering an unmatched number of fields to compile and enrich your location data. With over 40 data fields, you can generate comprehensive and detailed datasets that offer deep insights into your areas of interest.

The global reach of this service spans across Africa, Asia, and Europe, covering over 150 countries, including but not limited to Zimbabwe in Africa, Yemen in Asia, and Slovenia in Europe. This broad coverage ensures that no matter where your business operations or interests lie, you will have access to the location data you need.

Experience the Outscraper difference today and elevate your location data analysis to the next level.

Dataset

This dataset was created by Yohana Sri Rejeki

Contents

The Easiest Way to Collect Data from the Internet Download anything you see on the internet into spreadsheets within a few clicks using our ready-made web crawlers or a few lines of code using our APIs

We have made it as simple as possible to collect data from websites

Easy to Use Crawlers Amazon Product Details and Pricing Scraper Amazon Product Details and Pricing Scraper Get product information, pricing, FBA, best seller rank, and much more from Amazon.

Google Maps Search Results Google Maps Search Results Get details like place name, phone number, address, website, ratings, and open hours from Google Maps or Google Places search results.

Twitter Scraper Twitter Scraper Get tweets, Twitter handle, content, number of replies, number of retweets, and more. All you need to provide is a URL to a profile, hashtag, or an advance search URL from Twitter.

Amazon Product Reviews and Ratings Amazon Product Reviews and Ratings Get customer reviews for any product on Amazon and get details like product name, brand, reviews and ratings, and more from Amazon.

Google Reviews Scraper Google Reviews Scraper Scrape Google reviews and get details like business or location name, address, review, ratings, and more for business and places.

Walmart Product Details & Pricing Walmart Product Details & Pricing Get the product name, pricing, number of ratings, reviews, product images, URL other product-related data from Walmart.

Amazon Search Results Scraper Amazon Search Results Scraper Get product search rank, pricing, availability, best seller rank, and much more from Amazon.

Amazon Best Sellers Amazon Best Sellers Get the bestseller rank, product name, pricing, number of ratings, rating, product images, and more from any Amazon Bestseller List.

Google Search Scraper Google Search Scraper Scrape Google search results and get details like search rank, paid and organic results, knowledge graph, related search results, and more.

Walmart Product Reviews & Ratings Walmart Product Reviews & Ratings Get customer reviews for any product on Walmart.com and get details like product name, brand, reviews, and ratings.

Scrape Emails and Contact Details Scrape Emails and Contact Details Get emails, addresses, contact numbers, social media links from any website.

Walmart Search Results Scraper Walmart Search Results Scraper Get Product details such as pricing, availability, reviews, ratings, and more from Walmart search results and categories.

Glassdoor Job Listings Glassdoor Job Listings Scrape job details such as job title, salary, job description, location, company name, number of reviews, and ratings from Glassdoor.

Indeed Job Listings Indeed Job Listings Scrape job details such as job title, salary, job description, location, company name, number of reviews, and ratings from Indeed.

LinkedIn Jobs Scraper Premium LinkedIn Jobs Scraper Scrape job listings on LinkedIn and extract job details such as job title, job description, location, company name, number of reviews, and more.

Redfin Scraper Premium Redfin Scraper Scrape real estate listings from Redfin. Extract property details such as address, price, mortgage, redfin estimate, broker name and more.

Yelp Business Details Scraper Yelp Business Details Scraper Scrape business details from Yelp such as phone number, address, website, and more from Yelp search and business details page.

Zillow Scraper Premium Zillow Scraper Scrape real estate listings from Zillow. Extract property details such as address, price, Broker, broker name and more.

Amazon product offers and third party sellers Amazon product offers and third party sellers Get product pricing, delivery details, FBA, seller details, and much more from the Amazon offer listing page.

Realtor Scraper Premium Realtor Scraper Scrape real estate listings from Realtor.com. Extract property details such as Address, Price, Area, Broker and more.

Target Product Details & Pricing Target Product Details & Pricing Get product details from search results and category pages such as pricing, availability, rating, reviews, and 20+ data points from Target.

Trulia Scraper Premium Trulia Scraper Scrape real estate listings from Trulia. Extract property details such as Address, Price, Area, Mortgage and more.

Amazon Customer FAQs Amazon Customer FAQs Get FAQs for any product on Amazon and get details like the question, answer, answered user name, and more.

Yellow Pages Scraper Yellow Pages Scraper Get details like business name, phone number, address, website, ratings, and more from Yellow Pages search results.

Dataset is taken from the scraping results using the Instant Data Scraper extension on the Google Maps website for the largest printing company in Central Sulawesi, Palu City. This dataset still needs thorough ETL processing to obtain clean and informative data.

All the reviews from Google Maps. Select the businesses and get the reviews.

Overall, scraping a restaurant list of Dhaka can provide valuable insights into the food and beverage industry in the city and help individuals and businesses make informed decisions about where to eat and what to order.

This study aims to examine Google users’ evaluations and the spatial attributes of services. Geographical and attribute data from Google Maps were collected using Apify, a data scraping tool, and analyzed statistically and spatially in R programming.

This dataset contains anonymised data of accounts and reviews, labelled as fake/real collected through scraping of Google Maps. It is a part of the research described under this link.

Please cite the article describing this dataset as: P. Gryka and A. Janicki, “Detecting Fake Reviews in Google Maps—A Case Study,” Applied Sciences, vol. 13, no. 10, p. 6331, May 2023, doi: 10.3390/app13106331.

Este dataset contiene hasta 1000 reseñas de usuarios extraídas de Google Maps, enfocadas en los POI correspondientes a las cuatro universidades del Consorcio de Universidades del Perú hasta la fecha que figura en la última versión del archivo. Cada reseña incluye texto, calificación, fecha y algunos metadatos del usuario y del lugar reseñado.

La información puede ser usada para tareas como:

• Análisis de sentimiento
• Clasificación de opiniones
• Detección de problemas en servicios
• Estudios sobre experiencia de cliente y reputación online

Para conocer mejor la metodología de extracción puedes revisar el código aquí. Las preguntas y sugerencias son más que bienvenidas.

Unlock insights into Moroccan banking customer experiences! 🇲🇦

This dataset contains scraped and cleaned Google Maps reviews for banks across all cities in Morocco. Collected as part of a collaborative student/freelancer project, it’s perfect for sentiment analysis, market research, or academic projects.

What’s Inside?

• 2 Versions:
  • Raw Data: As scraped from Google Maps.
  • Cleaned Data: Filtered to exclude non-bank businesses (e.g., cash services, unrelated entries).
• Columns:
  City, Business Name, Address, Phone Number, Website, Google Map ID, Review Text, Timestamp, Stars.
• Cities Sourced from data.gov.ma: Ensured comprehensive coverage of Moroccan regions.

Methodology:

1. City Identification: Used official data from data.gov.ma to target cities with banks.
2. Search Strategy: Queried “bank in [city name]” on Google Maps to compile business links.
3. Scraping: Extracted business details (name, address, etc.) and latest reviews using Python + Playwright (automation) and BeautifulSoup (parsing).
4. Cleaning: Removed duplicates and non-bank entries for accuracy.

Potential Use Cases:

• 📈 Sentiment Analysis: Analyze customer satisfaction trends.
• 🗺️ Geospatial Visualization: Map bank ratings by city/region.
• 🔍 Competitor Analysis: Compare bank reputations.
• 🎓 Academic Projects: Practice NLP, data cleaning, or visualization.

Tech Stack:

• Python 🐍
• Playwright (for browser automation)
• BeautifulSoup (HTML parsing)
• Pandas (data cleaning)

Why This Dataset?

• First-of-its-kind: Focused on Moroccan banks.
• Ready-to-use: Cleaned version requires minimal preprocessing.
• Transparent: Raw data included for reproducibility.

License: CC0: Public Domain (Free to use, modify, and share).

Bali Tourist Attractions Dataset from Google Maps

Dataset Description

This dataset contains information about tourist attractions in Bali collected through automated scraping from Google Maps. It covers 761 tourist spots spread across 9 regencies/cities in Bali Island. The dataset aims to provide a comprehensive overview of the locations, categories, and popularity of Bali’s tourist destinations.

Data Source

• Data collected via automated scraping from Google Maps.
• Rating and links are obtained directly from each attraction’s Google Maps page.
• Dataset includes various popular tourist categories in Bali, ranging from natural parks, beaches, cultural sites, to general tourist attractions.

Column Descriptors

Dataset Purpose

• Support research and analysis related to Bali tourism.
• Facilitate development of map-based and recommendation tourism applications using real data.
• Assist in mapping and promoting tourist destinations more effectively.
• Provide comprehensive data for local governments and tourism industry stakeholders.

Sample Data

How to Use the Dataset

• The dataset can be imported and used in various data analysis tools such as Python (pandas), R, or GIS software.
• The latitude and longitude columns can be used to visualize tourist spots on a map.
• The rating column can be used for popularity and quality analysis of tourist destinations.
• The kategori and preferensi columns can assist in segmenting tourism types.

License

This dataset is provided for research and application development purposes. Use of this dataset must comply with Google Maps’ data usage policies and respect intellectual property rights.

Contact

For questions or further discussion regarding this dataset, please contact:

• Name: Bertnardo Mario Uskono
• Email: bertnardouskono@gmail.com

Dataset ini berisi ulasan dari Google Maps yang terkait dengan kampus BUMN. Data dikumpulkan untuk keperluan penelitian dan edukasi, dengan fokus pada pengalaman dan umpan balik pengguna. Dataset ini dapat digunakan untuk analisis data eksploratif, analisis sentimen, dan penelitian lainnya.

Deskripsi Dataset
File: CyberU_reviews.csv
Format: CSV
Jumlah Baris: 78
Jumlah Kolom: 9

Context

This dataset contains 12.7k entries of restaurants and cafes from all over Bangladesh

Content

This dataset was collected from Google Maps using google places API. To know about the scraping process kindly visit my github repository. The dataset has 8 columns containing information about restaurants. - place id : A unique identifier of a place on Google Maps - name : Name of the Restaurant - latitude - longitude - rating : Rating of the Restaurant (0 - 5.0) - number of reviews : Total number of reviews given - affluence : Prices level of the Restaurant (1.0 -> Cheap, 2.0 -> Moderate, 3.0 -> Expensive, 4.0 -> Very Expensive) - address : Address of the Restaurant

Inspiration

• How many Restaurants are around Bangladesh?
• What are the Most Popular/Highly Rated Restaurants?
• Is there any relationship between the price level and popularity of a restaurant?

Dataset Tempat Wisata Bali dari Google Maps

Deskripsi Dataset

Dataset ini berisi informasi mengenai tempat-tempat wisata di Bali yang dikumpulkan melalui proses scraping dari Google Maps. Dataset mencakup 761 tempat wisata yang tersebar di 9 kabupaten/kota di Pulau Bali. Data ini bertujuan untuk menyediakan gambaran komprehensif mengenai lokasi, kategori, dan popularitas destinasi wisata di Bali.

Struktur Dataset

Sumber Data

• Data dikumpulkan melalui scraping otomatis dari Google Maps.
• Informasi rating dan link diperoleh langsung dari halaman Google Maps tempat wisata tersebut.
• Data mencakup berbagai kategori tempat wisata populer di Bali, mulai dari taman alam, pantai, situs budaya, hingga objek wisata umum.

Tujuan Dataset

• Membantu penelitian dan analisis terkait pariwisata Bali.
• Mendukung pengembangan aplikasi peta dan rekomendasi wisata berbasis data nyata.
• Memfasilitasi pemetaan dan promosi destinasi wisata secara lebih efektif.
• Memberikan data komprehensif bagi pemerintah daerah dan pelaku industri pariwisata.

Contoh Data

Cara Menggunakan Dataset

• Dataset ini dapat diimpor dan digunakan dalam berbagai tools analisis data seperti Python (pandas), R, atau software GIS.
• Kolom latitude dan longitude dapat dipakai untuk memvisualisasikan titik-titik wisata di peta.
• Kolom rating dapat digunakan untuk analisis popularitas dan kualitas tempat wisata.
• Kategori dan preferensi dapat membantu dalam segmentasi jenis wisata.

Lisensi

Dataset ini disediakan untuk tujuan penelitian dan pengembangan aplikasi. Penggunaan dataset harus mengikuti ketentuan penggunaan data dari Google Maps dan menghormati hak kekayaan intelektual.

Kontak

Jika ada pertanyaan atau ingin berdiskusi lebih lanjut mengenai dataset ini, silakan hubungi:

• Nama: [Bertnardo Mario Uskono]
• Email: [bertnardouskono@gmail.com]

The Entertainment_KSA.csv dataset contains data on various entertainment spots in Saudi Arabia. With over 500 rows of data, this dataset provides information on the name, rating, review count, genre, location, and best comment for each entertainment spot. This dataset can be used to analyze the entertainment industry in Saudi Arabia and understand the types of entertainment spots available in the country.

The way of creating datasets like Entertainment_KSA.csv is by web scraping information from public sources such as Google Maps or Yelp. Web scraping is the process of automatically extracting data from websites using software tools. In this case, a web scraper would be programmed to visit the relevant pages on Google Maps or Yelp and extract information on entertainment spots such as name, rating, review count, genre, location, and best comment.

The scraped data can then be saved in a CSV file, like the Entertainment_KSA.csv dataset. Once the data is collected, it can be cleaned and processed to remove any errors or duplicates and then analyzed to gain insights into the entertainment industry in Saudi Arabia.

As for inspiration, datasets like Entertainment_KSA.csv can be used for a variety of purposes, including market research, trend analysis, and predictive modeling. Researchers and data analysts can use this dataset to explore the types of entertainment spots available in Saudi Arabia, identify popular spots, and understand the factors that influence customer reviews and ratings.

For example, this dataset could be used to predict which new entertainment spots are likely to be successful based on their genre, location, and other factors. It could also be used to identify trends in the entertainment industry in Saudi Arabia, such as the increasing popularity of certain genres or the growth of entertainment spots in specific regions.