Case studies

Kenneth Cole + Custora

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I N Q U I R I E S info@custora.com R E Q U E S T A D E M O Schedule a demo at get.custora.com/demo-request C U S T O R A U A great place for marketing teams to learn about e-commerce analytics custora.com/university "Creating a connection for shoppers who purchase our products is critical to inspire loyalty and ultimately drive success in the digital retail landscape. Custora has been a valuable partner in helping us deepen our customer analytics capabilities as we look to create a superior experience for today's shoppers." In working with the Custora team, the marketing team at Kenneth Cole identified three strategic priorities for better customer-obsessed engagement: identifying and cultivating VIPs, acquiring high-value customers and reducing churn to drive retention—all with the ultimate goal of increasing revenue by 1.5%. The Results Satisfied customers, incremental revenue Using Custora's predictive analytics and machine learning solutions, the Kenneth Cole marketing team was empowered to identify their high- value customers, as well as customers likely to have an affinity for certain categories and products. They began by testing the affinity segment for men's suits with an email marketing campaign in which Custora's predictive algorithms identified the customers most likely to purchase a men's suit. The Kenneth Cole marketing team was able to then frictionlessly build this audience using Custora's natural language segment builder, learn who comprised the segment, then push these contacts into their email service provider (ESP). During this first test, Kenneth Cole sold more suits in one day than they had in the entire previous week. Kenneth Cole's marketing team is just getting started. They plan to continue using predictive affinities to better learn about and communicate with their customers. Next up on the team's roadmap: launching a predictive churn prevention program, a VIP program, and a high-value customer acquisition program. K E N N E T H C O L E + C U S T O R A

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