Scraping Restaurant Location Data
This case study shows how we collected restaurant location data from major cities in the USA for a client based in Hawaii. An established bakery in Hawaii gathers information about restaurants in major cities across the USA using targeted data scraping from websites.
CLIENT:
A popular bakery in Hawaii
Website-specific data extraction and crawling
Challenges
The client needed information on restaurants in major US cities, focusing on specific price ranges. They wanted details like cuisine and demographics to be included in a structured menu.
They needed easy access to complete data on restaurant locations, food menus, and pricing from certain categories.
Importing restaurant data for their business was challenging. They required accurate data in a specific format so it could be easily uploaded to their internal database for comparison and monitoring.
The client gave us a list of resources to scrape, the data points needed, and the frequency for daily updates.
Our team set up restaurant location scraping APIs to gather the necessary data from specific websites.
The client requested the scraped data in CSV format, which was uploaded to S3 servers. The initial setup was completed in a few days, and the crawlers started providing the data right away.
Solution
Setting Up the Crawler: We configured the crawler to automatically collect restaurant location data and other relevant details for specific categories each day.
Data Template: Based on the customer’s requirements, we created a structured template for organizing the data.
Data Delivery: The final data was delivered daily in XML format through our Restaurant Location Data Scraping API, with no manual work needed from either side.
Data Details: Each record included all necessary information: Restaurant Name, Address, City, State, Zip Code, Fax, Latitude & Longitude, Phone Number, Opening Hours, Ingredients Picture, Food Name, Price, Type, Description, Promotion Details, Delivery Price, Category, Website, Working Hours, Star Ratings, and Number of Reviews.
Each record in the dataset contains comprehensive information such as Restaurant Name, Address, City, State, Zip Code, Fax Number, Latitude & Longitude, Phone Number, Opening Hours, Images of Ingredients, Food Name, Price, Food Type, Description, Promotion Details, Delivery Charges, Category, Website, Working Hours, Star Ratings, and Number of Reviews. This ensures you have all the key details you need.
DxMinds Enterprise Crawling Advantages
Complete Solutions for Non-Tech Clients
- We handle all the technical details of the source websites.
- Data is imported quickly, often within a day of placing an order.
- The client doesn’t need to manage any tasks or deal with technical issues.
- We handle any changes on the resource websites, so clients aren’t bothered by these problems.
- Faster data processing has enhanced the client’s market capabilities and services.
- With improved productivity, the data team can work on other projects, allowing the client to expand into new business areas.
