Case Study: a large US retailer achieves successful online grocery pickup rollout with Tredence predictive analytics

Provided a Robust Framework to Predict the Roll Out of Online Grocery Pickup Service in Stores, for One of the Largest Retailers in the US

Tredence partnered with a large US retailer that wanted to launch an online grocery pickup service to compete with more expensive delivery options. The challenge was to intelligently determine which of the retailer's many stores were the best candidates for a phased and successful roll-out of this new service.

Tredence implemented a predictive analytics solution using machine learning techniques like GLM, Random Forest, and SVM. This model identified key influencing factors and categorized stores by potential, enabling optimal budget allocation. As a result, the client successfully launched the service in over 600 stores. Online grocery customers proved 27% more profitable than in-store-only shoppers, and 20% of store customers adopted the new service.