Case study: Improving Cross-sell for Consumer Electronics through Personalized Recommendation

About the Client

The client is a global technology company specializing in hardware and software products for consumers as well as enterprises. The company is also a global leader in the PC market.

Business Context

The client wanted the ability to identify specific products to target for cross-sell campaigns aimed at the existing customer base. The critical success factors were defining preference based on evolving customer needs, and improving conversion rates through better accuracy of recommendations.

BRIDGEi2i Solution

BRIDGEi2i partnered with the client to create an enhanced customer experience by providing relevant cross-sell product recommendations through campaigns. The insights provided by BRIDGEi2i’s Recommender helped the client’s marketing team personalize campaigns by determining the right segments for targeting based on the browsing and purchase behaviour of customers and prospects.

BRIDGEi2i’s data engineering team created a data mashup of Product Hierarchy, Customer Transactions & third-party demographics data in the data base.

BRIDGEi2i’s AI Labs automated the Customer Segmentation based on demography and also built an algorithm for Item-to-Item similarity based on innovative definition of preference. The result was the most logical product recommendation.

BRIDGEi2i’s AI Lab developed and implemented a Personalized recommender to help clients execute close-looped campaigns (close-looping here was to improve accuracy and fine-tune over time)

Business Impact

0
%
of products recommended were purchased within a 3 month period
0
%
strategic improvement in campaign effectiveness