Web Scraping Food Delivery Data

The online food delivery segment is projected to reach around $127 billion by the end of 2021. With revenue expected to grow to a market size of $192 billion by 2025. These platforms and apps have thousands of restaurant listings and are used by millions of customers. 

Restaurants and food chains are leveraging big data and analytics to understand consumer preferences and tastes. You can now use web scraping services to collect data from food delivery platforms to adjust prices, improve marketing strategies, and more. If you are trying to improve your restaurant or food delivery business, web scraping is a solution that can help you get closer to your goals. 

Why Scrape Food Delivery Data?

Web scraping is the process of extracting vast amounts of data from target websites or apps. As the competition among food delivery platforms, restaurants, and related businesses is consistently rising, food delivery businesses will need to quickly capitalize on their data. Data such as delivery routes, food preparation time, and more can optimize services and help you gain a competitive advantage.

The data scraped from these platforms can be used in several different ways. Some of the top reasons why you should consider scraping food delivery data are as follows:

Increased Use Among Customers

Food delivery platforms are now the go-to solution for customers who want to order food online. However, due to COVID-19 restrictions, at-home dining has gained prominence. The trend will continue well into the future, with people not wanting to risk the spread of the virus even when restaurants will be allowed to offer dine-in services. 

Discover Latest Restaurant Types and Menus

Scraping restaurant data on food delivery apps is also one of the most effective ways to discover the latest food options offered across the various restaurant types, including bakeries, multi-cuisine, fast food, and health foods. Data scraping can help you figure out the types of cuisines and inventive dishes offered in your area. Then, if you are running a restaurant, you can add those cuisines to your menu to attract more customers. 

Improve Pricing and Marketing Strategy

Menu pricing is another critical aspect of running a successful restaurant business. While you can now find customers ordering food across price points, your pricing strategy should at least be in line with others in the surrounding area. Similarly, a key incentive for customers to order food from delivery apps is the discounts and rewards they offer. 

Scraping food delivery data can help you discover the pricing strategy of your competitors. It can also provide an instant overview of their marketing strategies. 

Analyze Customer Ratings and Reviews

Customers get to review and rate the restaurants from where they order their food through the delivery platform. Reviews often have vital information about a restaurant’s food and service quality, which can be very useful for competitors. They can target the weaknesses of other restaurants to try and improve their offerings and provide better quality and service to the customers. 

Detailed Overview of the Local Restaurant Industry

If you are about to open a new restaurant, a detailed overview of the local restaurants can help you create a better business plan. Even if you are planning to expand your business and open a new outlet at another location, the scraped data can offer valuable insights into the operations of restaurants already existing in the locality. 

What Can You Scrape from Food Delivery Websites?

Many different data fields can be extracted from popular food delivery platforms. Some of the most popular data points are as follows-

• Restaurant Name
• Restaurant Type
• City
• Address
• Contact Details
• Food Menu
• Discounts and Offers
• Menu Image
• Ratings
• Reviews
• Working Hours

Once the data is collected, it can be cleaned and delivered in a structured format. 

What can you do with scraped Food Delivery Data?

These are a few ways in which web scraped data can be utilized to optimize your business strategy.

Restaurant Data

Monitor upcoming restaurants in your locality and monitor their brand presence using data such as restaurant name, restaurant type, menu image, and more.

Pricing and Discount Data

Beat the pricing of competition by extracting data related to discounts and offers. Then, you can work on a pricing strategy to make sure your offerings are competitive.

Reviews and Ratings

If you are a multi-location brand, you can understand the service quality gaps in each location and decide on your local branding strategy using data related to reviews and ratings.

Opening Times

Find out which services and chains offer early breakfast or late-night delivery options by understanding the areas where competition has limited working hours and take advantage of the market.

Update Marketing Strategy

Optimize your marketing campaigns and tie-up with micro-influencers based on insights from competitive pricing and delivery fee data.

Gather Food Delivery Data using ScrapeHero

The whole process of building websites and apps has evolved by leaps and bounds over the years. There is no particular rule or structure that modern websites or mobile applications follow. Even the objective behind data extraction could significantly vary between businesses. As a result, a one-size-fits-all approach is seldom practical when selecting a data scraping solution.

The food delivery industry is ever-changing with competitive pricing and features. A customized web scraping solution like ScrapeHero can help you monitor data according to your requirements. Using a web scraping API can also ensure that you get data from websites in real-time. ScrapeHero builds custom web scraping APIs for platforms that do not have a web scraping API to help you achieve this.

ScrapeHero can gather publically available data from anywhere on the internet and is one of the top web scraping providers in the world. The pre-built scrapers and easy-to-follow web scraping tutorials provided by ScrapeHero allow small businesses, students, and analysts to gather data from popular websites in a simple and cost-effective manner.