APPAREL, RETAIL
Customer Segmentation for a Fashion Retailer
Background
A fashion retailer had a customer loyalty program functioning primarily as a discount card. They wanted to transform the program into a pro-active engagement platform and improve marketing efficiency, customer loyalty, and increase sales.
Analytic Objectives
Perform a segmentation analysis of the customer base so that marketing and offerings can be tailored to different segments of customers.
Manifold’s Approach
After attaching our geo-demographic, CanaCode lifestyle cluster, household spending, product usage, shopping behaviour, and psychographic data to the client’s customer transaction data, we performed a cluster analysis based on major principal components and created seven distinct segments among the customer base, for example:
A: Brand Loyalist
B: Buys a Lot
C: Enjoys Fashion
D: Recent Customers
E: Buys Once a Year
F: Average Shopper
G: Discount Hunter
Benefits of Manifold’s Data and Analytics
Augmenting transaction data with Manifold’s 6-digit postal code level data helped the client understand who their customers are, where they are, what their potential is, and their shopping and media usage behaviours.
Customer segmentation enabled the client to tailor communications and offerings for each customer segment. The lift compared with the control cell in the subsequent campaigns has been systematically over 150%.
Tailored communication resulted in very positive customer feedback.
Benefits of Manifold’s Analytics
Applying customer segmentation to store trade area analysis, we helped the client identify gaps and the potential of each of the 300+ stores; simulated store openings to minimize cannibalization and store closings to minimize attrition of the loyalty program. Post campaign analysis showed significant improvement in transactions at the store and customer segment level.