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Our client is a popular restaurant chain that operates dine-in and takeaways across the US and the UK. The restaurant chain’s main objective is to increase footfalls in existing restaurants by bringing key transformations based on data-driven insights. Also, the restaurant chain wants to expand in other locations and therefore needs competitor analysis. By partnering with FoodSpark.io, a leading data scraping service provider, the restaurant chain aimed to gain deep insights into its market dynamics through comprehensive data analysis.
The restaurant chain wanted to track top menu items, peak dine-in, and takeaway hours, food trends, and popular dishes of competitor restaurants across different locations to improve their restaurant’s efficiency and footfalls. By identifying popular dishes, the restaurant can optimize its kitchen operations and improve its menu further. Also, by improving raw material management for popular dishes, the client can bring the prices of popular dishes into a more profitable range.
This client was also looking for comprehensive analytics of competitor restaurants before venturing into new locations and bringing changes to the existing ones. This data can be availed of from the popular food aggregators and delivery platforms active in those regions. Also, Google My Business data of competitor restaurants can help in collecting the relevant data. The client wanted data sets in an easy-to-read format like CSV. The client wanted data in real-time continuously for the next three months for analysis.
The key challenge in collecting the data was the variation in locations. The restaurant operates in multiple locations and therefore we needed to ensure accurate location-wise data. Handling targeted data extraction, simultaneous web pages and aggregator app data extraction, large data sets, and managing data policies of multiple aggregators at different locations were key challenges that we needed to address.
FoodSpark.io used advanced web scraping tools to meet the client’s needs. We developed tailored scripts to extract data from the major food aggregator platforms, ensuring compliance with each platform’s terms of service. We also implemented automated processes to clean and organize data. We utilized advanced techniques to ensure data was collected in real-time, implementing live updates to reflect peak hours, trending items, and competitor activities accurately. Provided detailed competitor analysis, highlighting popular dishes and operational strategies. Compiled and delivered data in CSV format, facilitating easy integration with the restaurant’s analytics systems.
The implementation of FoodSpark.io’s data solutions had a significant positive impact on the restaurant chain. By identifying top-performing dishes, the restaurant refined its menu to better meet customer preferences. Insights into peak hours enabled more efficient staffing and inventory management, reducing costs and improving customer service. Comprehensive competitor analytics provided the necessary insights for successful market entry strategies.
This case study exemplifies the transformative impact of data-driven insights in the restaurant industry.