Enhancing E-commerce Experiences
How we used AI to transform customer experiences for
a leading U.S. Grocery Retailer
Our client is one of United States’ largest grocery retailers, serving more than 11 million customers daily in stores and online. With 2,800 stores in 35 states, our client operates two dozen grocery retail brands, 34 manufacturing locations, and 44 distribution facilities, totaling over $140 billion in annual revenue.
Our client observed a common issue among customers: difficulty finding products matching their preferences. Consequently, customer interaction and interest decreased, resulting in reduced engagement, lower loyalty, and a decline in repeat business. This inadequate search experience led to customer frustration, dissatisfaction, and potential loss of sales. Additionally, they faced the challenge of fully grasping the vast amounts of data they possessed, like customer, transaction, and behavioral data, to generate better insights and enhance convenience for each customer across all channels.
Within a span of four weeks, we were able to design data cleaning operations as well as a machine learning engine that delivered real-time recommendations and personalized upsell and cross-sell suggestions to millions of customers utilizing the client's web or mobile apps. Each time a customer interacted with the client's products, it sent feedback to the engine, continuously improving the performance and accuracy of the recommendations and shopping experience.
After cleaning and analyzing petabytes of data, like order history and purchasing behavior, Rapidops employed advanced algorithms like collaborative and content-based filtering to develop a personalized recommendations engine that met customers’ unique preferences and needs.