Optimizing Food Menus at Scale with Data Scraping
Unlocking Efficiency: Optimizing Food Menus at Scale with Data Scraping
This case study illustrates how our superior services supported a precedent food delivery aggregator in Optimizing Food Menus at Scale with Data Scraping. In this case, the client was having difficulty with menus with inconsistent formats spread out over thousands of restaurants. This inconsistency impacted their customer experience through messy formats, ultimately lowering conversion rates. We implemented our automated scraping solutions to obtain and structure menu data (item names, item prices, ingredients, and add-ons) from several disparate platforms. This allowed them to analyze their menu data in one central location, grouping by cuisine and geography. The centralized insights allowed the client to standardize menu presentation styles, realize high-performing items, and determine which items were relevant in policy searches. Ultimately, they saw increased order accuracy and higher customer satisfaction. With the ability to Scrape Data For Menu Structuring at Scale, our solution also allowed the client to support real-time updates and localized versions of the menus. The project gave the client a significant, scalable, competitive advantage in the food delivery vertical.
