Kiwi Wealth needed to reduce customer churn by identifying customers at risk of leaving and understanding the factors driving this behavior.

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DOT created a churn model that included media spend and press release data to predict which customers were at risk of churning. The segmentation tool and churn model were combined to assign each customer a probability of churning and insights into what factors were driving their behavior. DOT separately developed a segmentation algorithm that incorporated Kiwi Wealth’s customer data and additional data from DOT’s Dynamic Deprivation and US Segmentation products to understand each customer’s unique circumstances. 

Kiwi Wealth was able to identify customers at risk of leaving and personalize offerings to retain them. The segmentation algorithm and churn model led to an immediate uplift in open rates to messages, and Kiwi Wealth used a champion challenger approach to refine messaging for each segment. The performance of campaigns and offerings in each segment could be tracked, allowing Kiwi Wealth to evaluate their effectiveness and make data-driven decisions to reduce customer churn.

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