In 2020, my colleague Jonas Juul Jeppesen had a guest in the Subscription Talks studio who introduced us to the possibilities of churn prediction. At that time, we eagerly followed how Mads Gorm Hansen managed to analyze customer churn behavior and thereby predict which subscribers were most likely to churn within the next subscription period.
A lot has happened since then, and today we are going to talk about a B2B subscription that turbocharges the phenomenon that Mads introduced to us almost 3 years ago.
Intelligent churn prediction is the future in any subscription business
The company Blueshift specializes in using machine learning and artificial intelligence to predict which customers exhibit behavior that leads to churn. And not only can the model predict and alert the CRM team, but Blueshift can also tailor personalized content and offers that can re-engage the subscriber before it’s too late.
On the client list, Blueshift has names like BBC, Britbox, Discovery+, and American Skillshare. And it is particularly companies like these that have large amounts of behavioral data on their customers that benefit the most from a tool like this. And perhaps that’s actually the key takeaway here: Do you have enough customer data to implement churn prediction soon? Because if not, you need to get started!
Future opportunities depend on the investments of today
It can be challenging to prioritize proper data structuring and a data warehouse when you are a smaller subscription business focused on growing your customer base. Implementing Churn Prediction may not be at the forefront of your Subscription Modeling phase here at Subscrybe. However, it can still be a good idea to consider it from the beginning.
Tools like Blueshift can integrate with your existing CRM system, and there are plenty of similar tools available that can be customized according to your level of ambition.
Even if your subscription product is not digital and thus harder to collect customer behavioral data, there are still ways to work around it. For example, at Matas, they collect data on purchases and experiences from Club members in their physical stores, which they then use in their CRM activities through the app and email. This is due to a special focus on obtaining as much knowledge as possible about customer engagement and, most importantly, satisfaction. Because that is the path to stronger retention.
So if you haven’t started developing a data strategy and exploring how the new opportunities in artificial intelligence can be used to enhance your retention efforts, I highly recommend getting started!
If you need advice and guidance on how to embark on your journey towards better customer data, feel free to reach out to me or one of my colleagues. It can prove to be a worthwhile investment as customer expectations continue to rise significantly in the near future.
