This case study highlights how iWeb Data Scraping helped a mid-sized restaurant chain optimize its pricing strategy using real-time Swiggy and Zomato scraped data. In today’s hyper-competitive food delivery space, pricing is a critical factor influencing conversions, repeat orders, and profit margins. By leveraging Food Delivery Data Intelligence Services, iWeb Data Scraping enabled a mid-sized restaurant chain to fine-tune their pricing model across five cities by leveraging real-time data scraped from Swiggy and Zomato.
A Multi-City Restaurant Group with Outlets in Bengaluru, Hyderabad, Pune, Mumbai, and Delhi.
iWeb Data Scraping Offerings: Use data crawling services to Extract Real-Time Restaurant Pricing and Promotion Data from Zomato & Swiggy.
Background
The client, a multi-city restaurant group with outlets in Bengaluru, Hyderabad, Pune, Mumbai, and Delhi, was struggling to determine the right pricing strategy for each location. While centralized pricing was convenient, it led to loss of customers in price-sensitive zones and missed margins in premium neighborhoods. They lacked access to localized insights, which is where Food Delivery Data Extraction Services, including Zomato Food Data Scraping Services and solutions to Extract Swiggy Food Delivery Data, played a crucial role in uncovering regional pricing dynamics.
Challenge
The Solution
iWeb Data Scraping deployed a city-wise scraping API that aggregated:
Sample Data Output (Pune vs Mumbai)
| Item | Pune Price | Mumbai Price | Promotion |
|---|---|---|---|
| Butter Chicken | ₹220 | ₹260 | Mumbai: ₹50 off above ₹499 |
| Veg Biryani | ₹170 | ₹180 | Pune: 10% OFF |
| Cold Coffee | ₹90 | ₹110 | None |
Results Achieved
Menu pricing was revised based on localized competitor data, improving order completion rates.
By identifying where they were overpricing (Mumbai) or underpricing (Hyderabad), margins improved without losing customers.
City-level data revealed what kinds of promotions resonated with customers — enabling smarter campaign deployment.
Integrated API data into their POS system to update prices and offers every 24 hours.
Why iWeb Data Scraping?
Cities Tracked
Compatible Users
"iWeb Data Scraping’s Swiggy and Zomato scraping API helped this restaurant chain take a data-driven approach to menu pricing, tuned to each city’s market conditions. This case study illustrates the real value of hyperlocal intelligence in food delivery economics."
— Chief Operating Officer, Multi-City Restaurant Group
We start by signing a Non-Disclosure Agreement (NDA) to protect your ideas.
Our team will analyze your needs to understand what you want.
You'll get a clear and detailed project outline showing how we'll work together.
We'll take care of the project, allowing you to focus on growing your business.