Restaurant apps are an entirely new way to deliver food. Several food owners use restaurant apps to help customers quickly order food, make payments, track online, etc., without physically visiting restaurants. According to Statista reports, the number of food delivery app users in the US increased from 36.4 to 45.6 million in 2020, giving restaurant owners a reason to incorporate better marketing strategies to stay ahead of the competition.
Collecting data with a manual process is a tedious task. Whether you are a professional or a novice in the restaurant business, you need innumerable relevant information related to restaurant types, names, services, facilities, etc., to monitor the competitors. Hence, restaurant mobile app scraping provides automated data collection from targeted websites.
TripAdvisor is a well-known travel website. The website comprises information about several hotels and restaurants, details, reviews, and ratings. Over several years, this website has significantly influenced travelers’ minds and decisions. However, scrape TripAdvisor data to get complete details on trip destinations, lodging, restaurants, and travelers’ ratings to maintain an equivalent pace with your competitors.
Why Scrape TripAdvisor Restaurant Data
TripAdvisor is the largest source of hospitality industry data. All these data greatly help business intelligence like market and competitive analysis.
People are primarily interested in scraping its reviews, but it also contains data like restaurant information, pricing, hotels, tours, etc. So, using TripAdvisor mobile app restaurant scraping services, you can collect information about restaurants and public opinions about them too.
The TripAdvisor data scraper can easily collect information about TripAdvisor. Without scrolling through pages of evaluation, the output data will help you evaluate and compare restaurants in a better way
List of Data Fields
The following data fields are collected from TripAdvisor restaurant Mobile App scraping:
- 1 Name of the restaurant
- 2 Price per person.
- 3 TripAdvisor Link
- 4 Phone Number
- 5 Address.
- 6 Location.
Steps Involved in TripAdvisor Mobile App Restaurant Scraping
This guide will show you how to scrape TripAdvisor hotel & restaurant data and export it to a CSV file. Let’s begin.
As you sign in, you are now on the in-app home page. In the main search bar, look for the TripAdvisor extractor. Click on the results that you get. You will see four different extractors for Hotels, Restaurants, Attractions, etc. But, our objective is to use the Restaurants only,
Activation of the Scraper
Click the activate button to proceed, and then add the extractor to your profile.
First, open TripAdvisor.com in a new tab and then select restaurants. Now, add a location, e.g., London. For this keyword search, we will get results for all London restaurants on TripAdvisor.
Now, to get a more precise restaurant search, we will filter the results. After getting a satisfactory search, copy the URL.
Configuring the Extractor
Paste the copied link in the edit starter link box. Click on Update.
Run the Extractor
Start the extracting process by clicking on the ‘Run Now’ option
Wait Until You Get the Data
You will receive a pop-up saying that the extractor is running and the data will be available soon.
Download the Data
After finishing the process, you will receive an email notification. Click the link to download the data in desired format – CSV, XLS, JSON, etc.
Why Choose Food Data Scrape to Scrape Restaurant Data from TripAdvisor?
Food Data Scrape is a well-known provider of TripAdvisor data scraping services. The company offers customized solutions for hotel & restaurant scraping, making it available in several formats. Backed with the latest tools and techniques, the company can quickly extract the latest restaurant data by scheduling TripAdvisor restaurant data scraper. The obtained data helps understand your customers, analyzing the gap between product & consumer demand, unwrapping several market trends, and discovering several new business opportunities.
Scraping travel sites for information, including restaurant data, is essential. It gives detailed insights into restaurants, menus, locations, customer preferences, etc.