Optimizing Pricing with Glovo Food Delivery Datasets

Introduction

In today's hyper-competitive food delivery ecosystem, pricing can make or break a restaurant’s profitability. A leading European restaurant chain partnered with Arc Technolabs to leverage Glovo Food Delivery Datasets and extract granular, city-specific menu intelligence. By analyzing item-level pricing, order patterns, and regional competition, the brand aimed to tailor its pricing for maximum revenue and market fit. With Arc Technolabs' advanced Web Scraping Services, the client accessed structured Food Delivery Datasets across multiple cities to improve their pricing model. This project marked a turning point in their data-driven pricing strategy and customer satisfaction.

The Client

The client is a fast-growing restaurant chain with operations in eight countries across Europe. Known for its diverse offerings and consistent quality, the brand had recently expanded into three new cities. They wanted to gain a data-driven understanding of local preferences and pricing benchmarks. By using Glovo Food Delivery Datasets, they aimed to ensure competitive yet profitable pricing for every menu item. They chose Arc Technolabs for its domain expertise and scalable Mobile App Scraping Services that allowed them to extract menu and pricing data accurately and consistently from the Glovo platform.

Key Challenges

The client faced several challenges while entering new markets. Each city had different customer expectations, competitor pricing strategies, and purchasing power. Without reliable data, they struggled to price their menu items appropriately. Additionally, the Glovo platform uses dynamic loading and custom content structures, making it hard to scrape Glovo food delivery data using off-the-shelf tools. The client’s internal teams lacked a robust web scraper for Glovo menus that could handle multilingual content, item variants, and promotional pricing. On top of that, competitor offerings and pricing changed frequently, requiring a real-time Glovo order data pipeline. Data inconsistency, item duplication, and mapping issues further complicated their pricing optimization model. Without a clean, centralized Glovo delivery dataset for analysis, decisions were delayed or based on assumptions. The need for accurate, city-level benchmarking was growing urgent, especially as they launched seasonal campaigns.

Key Solution

Arc Technolabs implemented a custom scraping engine to scrape Glovo food items, categorize competitors' menus, and normalize prices city-by-city. Using our proprietary framework, we built a location-aware Glovo pricing intelligence dataset updated daily. The scraper could parse dynamic content, capture bundled deals, and even identify promotional timings. Our team used multi-layered data pipelines to provide the client with clean, ready-to-analyze Glovo Food Delivery Datasets, integrated with their pricing dashboard. Custom alerts flagged price changes and new menu items from competitors. The entire solution was built using our scalable Web Scraping Services , backed by proxy rotation and smart scheduling to avoid IP blocks. For app-specific insights, we extended capabilities with our Mobile App Scraping Service , ensuring they didn’t miss app-only discounts. In just three weeks, the client had a full view of competitive pricing across all target cities.

Client Testimonial

"Arc Technolabs transformed how we approach pricing. Their structured Glovo Food Delivery Datasets gave us the competitive edge we needed in new markets. The data accuracy, delivery speed, and customization exceeded our expectations. We now make localized pricing decisions with confidence and speed."

— Director of Pricing Strategy

Conclusion

By leveraging Glovo Food Delivery Datasets, the client drastically improved their market responsiveness, pricing accuracy, and profit margins. Arc Technolabs' expertise in scrape Glovo food delivery data and real-time pricing analysis enabled faster, smarter decisions based on actual competitor behavior. The result: better menu performance, improved customer satisfaction, and scalable market entry strategies. This case study highlights the power of specialized web scraping solutions in transforming operational efficiency in the food delivery industry.