Travis Perkins Re-engages lapsing customers to increase retention by 8.8% using RedEye's Predictive Modeller
The Problem Faced
Losing customers has the most significant impact on the revenue of any business, but what if you could find out your customer was likely to churn before they even knew themselves? This knowledge could mean the difference between a customer lost forever and a customer re-engaged and spending money with your brand again.
Keeping customers and ensuring they stay loyal to your brand is imperative. Travis Perkins were looking to identify those customers that were most likely to lapse from their online journey.
RedEye’s Predictive Modeller, part of their Marketing Automation solution, Contour, empowers businesses by predicting if a customer is likely to churn. With this knowledge, the marketer is able to create multi-channel communications specifically designed to reduce the likelihood of this happening.
The Predictive Model
Using the Predictive Churn model Travis Perkins were able to identify whether or not a customer was likely to churn. The model takes into consideration transactional, behavioural and multi-channel engagement data, using this wealth of information to create two segments of data, those with a high or a low propensity to lapse.
The customers that were identified as likely to lapse were sent a dedicated campaign, with the aim of engaging these customers to prevent them from leaving the brand, with the control segment being sent the business-as-usual email campaign. The model gave Travis Perkins the power to act, not react, resulting in a strategy that could be put in place to stop a customer leaving, rather than sending a ‘please come back’ email.
The Results Achieved
The information that Travis Perkins now has access to about their customer, equipped them to deliver a much more relevant, targeted campaign. This campaign led to an 8.8% increase in retention of customers, compared with the control segment.
With RedEye’s support, Travis Perkins were able to transform customers that were disengaging, into customers that were engaged and making purchases. This transformation led to increased revenue, with Travis Perkins seeing a massive 909.6% increase in transactions amongst the ‘likely to lapse’ segment. Ultimately the model provides a much greater customer lifetime value.
To find out what the client said, read the full case study here.