Case StudySears

Sears exceeded the target customer numbers in 50% less time by better segmenting customers to improve loyalty programme and marketing campaign effectiveness with machine learning

Sears, the waning US retail giant was a pioneer in customer analytics and was able to segment customers better and develop effective targeted loyalty programmes using machine learning. They were able to add 80m customers in 17 months against initial target of 36 months. They were able to track customer spending patterns and offer better matching recommendations, offers etc.

Context

Sears, after posting losses for several years wanted to improve sales by applying targeted marketing.

The Project

The program would capture, analyze, and report on customer activity at an individual level, across all 4,000 locations. The ensuing information would enable Sears to provide the differential treatment and personalized attention to best customers.

Results

Sears achieved an active member base in the 8 digits (currently 80 Million), exceeding the projected 36 month membership target in 17 months. Member spend is now identifiable leading to more personalization.

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