Struggling with Customer Retention? The biggest reason traditional churn models fall flat

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Olivia Winterbourne
by Olivia Winterbourne
posted on Thu, 3 March 2022

Customer Retention AI & Machine Learning

We all know customer retention is a huge priority for businesses. Large corporates have entire teams dedicated to keeping customers sticky, and retention rates are a key metric reported and tracked by senior executives. With the current economic climate, customers are increasingly likely to be shopping around for the best offers and switching providers more frequently than ever before – meaning customer retention will continue to be a top priority for businesses. 

Traditional churn propensity models do a great job of identifying customers at risk of churning their product or service, however businesses often fail to realise the true value of these models and struggle to save customers, despite the early warning signs. 

 

So why do churn models fail? 

The single biggest reason churn models fail to deliver value is because they are not actionable. Models do a great job of identifying who is likely to churn, but what they don’t do is explain the reasons why customers are likely to churn

Marketers and account managers are often presented with a list of the most ‘at-risk’ customers, without any context as to why they are at risk. Without an understanding of the reasons why customers may churn, it can be hard to take action to save them.  

Extracting the driving factors behind a model can be challenging – models are intentionally complex (that’s why they do such a good job!), and the resulting outputs are based on a combination of contributing inputs and behaviours. Not to mention, what is predictive of churn, may not be indicative of the real reason driving the customer's behaviour.  

Churn model outputs purely tell you who is most likely to leave, they do not tell you what conversations to have or what levers you can pull in order to save your most at-risk customers – and that is a key reason they often fail to deliver value. 

 

DI Retain – Actionable insights to identify, understand and save your at-risk customers.

Data Insight’s DI Retain uses industry-tailored data models and AI algorithms to identify not only which customers are most at-risk of churn, but also the factors driving that risk. This allows businesses to easily identify, understand and action a plan to save these customers. 

DI Retain is a complete solution to your customer retention woes which allows you to not only identify which customers are at risk, but also understand why and what actions you need to take to save them. 

Retain logo green and grey Click here to find out more about DI Retain.

 


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Olivia Winterbourne
by Olivia Winterbourne
posted on Thu, 3 March 2022
Olivia Winterbourne, Data Insight’s General Manager, has been with DI for nearly 9 years. With a strong background in data analytics across a wide range of industries, Olivia is passionate about transforming data into actionable insights and helping our clients deliver greater value and develop data-driven strategies.

Customer Retention AI & Machine Learning