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

APISCRAPY, your premier provider of Map Data solutions. Map Data encompasses various information related to geographic locations, including Google Map Data, Location Data, Address Data, and Business Location Data. Our advanced Google Map Data Scraper sets us apart by extracting comprehensive and accurate data from Google Maps and other platforms.

What sets APISCRAPY's Map Data apart are its key benefits:

1. Accuracy: Our scraping technology ensures the highest level of accuracy, providing reliable data for informed decision-making. We employ advanced algorithms to filter out irrelevant or outdated information, ensuring that you receive only the most relevant and up-to-date data.

2. Accessibility: With our data readily available through APIs, integration into existing systems is seamless, saving time and resources. Our APIs are easy to use and well-documented, allowing for quick implementation into your workflows. Whether you're a developer building a custom application or a business analyst conducting market research, our APIs provide the flexibility and accessibility you need.

3. Customization: We understand that every business has unique needs and requirements. That's why we offer tailored solutions to meet specific business needs. Whether you need data for a one-time project or ongoing monitoring, we can customize our services to suit your needs. Our team of experts is always available to provide support and guidance, ensuring that you get the most out of our Map Data solutions.

Our Map Data solutions cater to various use cases:

1. B2B Marketing: Gain insights into customer demographics and behavior for targeted advertising and personalized messaging. Identify potential customers based on their geographic location, interests, and purchasing behavior.

2. Logistics Optimization: Utilize Location Data to optimize delivery routes and improve operational efficiency. Identify the most efficient routes based on factors such as traffic patterns, weather conditions, and delivery deadlines.

3. Real Estate Development: Identify prime locations for new ventures using Business Location Data for market analysis. Analyze factors such as population density, income levels, and competition to identify opportunities for growth and expansion.

4. Geospatial Analysis: Leverage Map Data for spatial analysis, urban planning, and environmental monitoring. Identify trends and patterns in geographic data to inform decision-making in areas such as land use planning, resource management, and disaster response.

5. Retail Expansion: Determine optimal locations for new stores or franchises using Location Data and Address Data. Analyze factors such as foot traffic, proximity to competitors, and demographic characteristics to identify locations with the highest potential for success.

6. Competitive Analysis: Analyze competitors' business locations and market presence for strategic planning. Identify areas of opportunity and potential threats to your business by analyzing competitors' geographic footprint, market share, and customer demographics.

Experience the power of APISCRAPY's Map Data solutions today and unlock new opportunities for your business. With our accurate and accessible data, you can make informed decisions, drive growth, and stay ahead of the competition.

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The Google Maps dataset is ideal for getting extensive information on businesses anywhere in the world. Easily filter by location, business type, and other factors to get the exact data you need. The Google Maps dataset includes all major data points: timestamp, name, category, address, description, open website, phone number, open_hours, open_hours_updated, reviews_count, rating, main_image, reviews, url, lat, lon, place_id, country, and more.

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.

Todas las reseñas de Google Maps. Selecciona los negocios y obtén las reseñas.

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.

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.

This dataset contains anonymised data of accounts and reviews, meticulously collected through scraping Google Maps. Its primary purpose is to support research and development in the field of fake review detection, specifically for Google Maps. The data is carefully labelled as either fake or real, providing a clear basis for classification tasks. It forms a crucial part of academic research focused on detecting deceptive online behaviour.

Columns

• _id: A unique identifier for each record.
• is_deleted: A boolean value indicating if the account or review has been deleted.
• is_private: A boolean value indicating if the account is private.
• is_real: A boolean value, the core label, indicating if the account/review is considered real or fake.
• local_guide_level: An integer representing the level of a Google Maps Local Guide associated with the account.
• name_score: An integer score indicating the commonness of the account's name within the Polish language context. Further details are available in the related academic article.
• number_of_reviews: An integer representing the total number of reviews posted by the account.

Distribution

The dataset is structured for ease of use, typically provided in a CSV format. It comprises 605 individual records, each representing anonymised account and review data. While the exact file size is not specified, its structure is designed for straightforward integration into data analysis and machine learning workflows.

Usage

This dataset is ideally suited for data science and analytics professionals, especially those focused on: * Developing and testing machine learning models for binary classification of fake versus real reviews. * Natural Language Processing (NLP) research related to review authenticity. * Investigating patterns of deceptive accounts and reviews on online platforms. * Applications in fraud detection and digital trust initiatives. * Academic research in areas such as applied sciences and artificial intelligence.

Coverage

The data collection period predates May 2023, the publication date of the associated research. While the dataset is classified with a global region coverage, it includes a name_score column that specifically reflects the commonness of names in the Polish language, indicating a potential focus or origin from Polish-speaking contexts. The dataset encompasses anonymised attributes of Google Maps accounts and their review behaviour.

License

CC By 4.0

Who Can Use It

This dataset is primarily intended for: * Researchers and academics studying online fraud, social media analysis, and machine learning applications in authenticity detection. * Data scientists and AI/ML engineers looking to build or refine models for identifying fake reviews. * Organisations interested in protecting brand reputation or improving trust on their platforms. * Students undertaking projects in data analysis, classification, or NLP related to online reviews.

Dataset Name Suggestions

• GMR-PL Fake Reviews Dataset
• Google Maps Account Authenticity Data
• Google Maps Review Classification Data
• Polish Google Maps Fake Reviews
• Online Review Authenticity Dataset

Attributes

Original Data Source: GMR-PL Fake reviews dataset

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?