John Greed reduces email unsubscribes by 31% using our Predictive Modeller

The Problem Faced

Every brand loses money when a customer unsubscribes from their emails. But what if you could predict that one of your customers was about to opt out before it happened? What if you could take proactive steps to shape the future the way you want, keeping the customer engaged and the integrity of your database secure?

Like many organisations, John Greed’s email communications are a crucial tool in engaging customers and driving all-important sales. John Greed were looking for a way to optimise their contactable database and identify customers who were at risk of unsubscribing from their emails.

RedEye’s Predictive Modeller, part of their Marketing Automation solution, Contour, made the idea of predicting the likelihood of a customer to unsubscribe, a reality. This allowed John Greed to identify those customers at risk and act on that information proactively.

The Predictive Model

RedEye implemented their unique Unsubscribe Predictive Model to John Greed’s business-as-usual email campaigns. The model predicts the likelihood that a customer will unsubscribe, using a number of key factors, including behaviour.

To fully showcase the success of the model, RedEye split John Greed’s contactable data 50/50. One segment received emails at the usual frequency with the usual content, while the other half had the unique model applied and received a bespoke journey designed specifically to prevent unsubscribes.

The beauty of the model meant that John Greed was able to automatically exclude recipients from certain emails where the model had indicated a high propensity to unsubscribe and create specific communication strategies aimed at retaining these customers.

The Results Achieved

With the Unsubscribe Predictive Model applied John Greed saw an impressive decrease in unsubscribes of 31.05%. What’s more, where the model was applied John Greed saw an increase in revenue of 103.83%, as the model gave John Greed the ability to identify segments that were potentially undervalued. Armed with this new information, John Greed was able to target this segment with new, engaging emails.

Essentially John Greed lost fewer customers. They saw higher conversion rates. Higher revenue. Ultimately, an increased customer lifetime value.

While the cost of sending an email is negligible, the cost of a customer lost due to an unsubscribe can be very large. The RedEye predictive solution takes the guesswork out of choosing the optimal segment for campaigns. Predictive Modeller allows the marketer to choose the recipients least likely to unsubscribe allowing danger zone recipients to receive only selective, important messages. The John Greed scenario is a prime example of how selective messaging can not only improve database opt in retention, but also have a positive impact on conversion.

Vasudha Khandeparkar

RedEye

104%

Increase in revenue

£85

Industry average value of an email address in your database

31%

Reduction in unsubscribes

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