Bing Maps Scraper

Unlock the potential of location data with our Bing Maps Scraper – your ultimate solution for extracting invaluable geographic insights. Whether you're planning a journey, analyzing market trends, or conducting research, our scraper streamlines the process of gathering location-based data. With just a few simple steps, access a wealth of information, including addresses, landmarks, businesses, and more. Simplify your projects and enrich your analyses with our intuitive Bing Maps Scraper.

Easy to use and Free to try

A few mouse clicks and copy/paste is all that it takes!

* to use you will need to sign up for a  FREE TRIAL account

Steps to use:

Step 1: Click on "Use for Free"

Step 2: Activate the Pre-Defined Extractor by clicking the "Activate button"

Step 3: Enter your starter URLs

Enter a List of search URLs to start the web scraping. It must be a Tripadvisor Restaurants search URL.

Step 4: Click "Run now" 

Using this extractor, you can get:

• address
• locate store url
• main store url
• phone number
• star rating
• store name
• timestamp

Valid Starter Links:

To initiate data extraction with the Bing Maps extractor, users can obtain valid starter links directly from Bing Maps' website.

Obtaining the Starter Link:

Bing Maps and input relevant search criteria such as location names, addresses, or landmarks. Once the desired map view or search results are displayed, users can copy the URL of the page containing the geographic information they wish to extract data from.

Cost

When you use Bing Maps Extractor pre-defined web scraper, the cost will be 10 credits per row which equals to $1 for 100 rows.

Video Tutorial on how to scrape Bing Maps

The output file can be exported as csv, xml, xlsx, json formats.

Below is a screenshot of what data fields we will be web scraping from Bing.com/Maps

You will get your data in following structure in different formats:

{
  'locate_store_url': 'https://piccolinorestaurants.com/locations/heddon-street/',
  'main_Store_url': 'https://piccolinorestaurants.com',
  'store_name': 'Piccolino Heddon Street',
  'address': '21 Heddon Street, Mayfair, London W1B 4BG',
  'phone_number': '020 7287 4029',
  'star_rating': ' 4 out of 5.'
}

What does the output data look like?

*** Data below was extracted on Dec 02, 2024 @01:01