Challenge

The multi-billion-dollar apparel manufacturer services their customers through multiple channels – both wholesale and direct to consumer (online, apps, brand owned retail outlets). There is an increased focus on enhancing the experience in the direct-to-consumer channels with a view to better margins and brand equity. Several customer activation campaigns are used to reach out to customers on a continuous basis but historically, spend with the brand has been the only metric used to differentiate between customers. The goal of this exercise was to understand customer characteristics and behavior across multiple dimensions to enable them to engage with their customers better.

Approach

Historical transaction data from five years was studied to understand customer behavior and spend patterns across multiple channels. Since a significant portion of the customers had made a purchase only once, K-means clustering was used to produce two different clustering outputs – one focused on repeat purchasers and one for one-time purchasers. Historical spend, frequency of transactions, product categories purchased, channels of engagement etc. were used to create distinct customer segments. Several other dimensions such as campaign response behavior, browsing patterns, holiday shopping behavior, specific products purchased in each category, price points shopped etc. were studied for each segment to create detailed customer personas. The models are scored each month to observe shifts in customers across segments over time.

Outcome

A view of detailed customer profiles helped run focused activation campaigns with significant improvement in customer engagement. A segment with high potential (on par with their most premium segment) but declining revenue patterns over the last 12 months was identified for immediate action. This resulted in increasing revenue for the segment by $5MM over a 6-month period. The segmentation exercise also provided a foundational understanding of the customer base that fed into multiple other strategies - customer retention, product based targeting etc.