Churn prediction means detecting which customers are likely to leave a service or cancel a subscription to a service. It is a very important prediction for many businesses because acquiring new customers often costs more than the retaining existing customers. Once you can identify the customers who are at risk of quitting, you need to know exactly what marketing action to take for each individual customer to maximise the chances of them staying.
Different customers show different behaviour and have different preferences. Therefore, they may cancel their subscription for different reasons. It is crucial to communicate proactively with each of them to keep them in your customer list. You need to know which marketing action will be most effective for each customer, and when.
Why is churn prediction so important?
Customer turnover is a common problem for companies in many sectors. If you want to grow as a company, you have to invest in acquiring new customers. Every time a customer leaves, it means a significant investment that is lost. Both time and effort must go into replacing the customer. If a company can predict when a customer is likely to leave, and offer him incentives to stay, it can save a lot of money.
Understanding what keeps customers engaged is therefore extremely valuable knowledge, as it can help you develop your retention strategies and roll out operational practices aimed at preventing customers from walking out the door.
Predicting churn is a must for any subscription-based business. Even small fluctuations in churn can have a significant impact on your business. So we need to know clearly: "Will this customer leave us in X months?" Yes or No? It is a binary classification task.
What are the main challenges in churn prediction?
Churn prediction modelling techniques attempt to understand the precise customer behaviours and attributes that indicate the risk and timing of customer departure. It is not a walk-in-the-park task.
To succeed in retaining customers who are ready to leave your business, marketing, sales and customer success must be able to predict in advance which customers are going to churn and put in place a plan of marketing or sales actions that will have the greatest retention impact on each customer. The key here is to be proactive and engage with these customers. While this is simple in theory, achieving this "proactive retention" goal is a huge challenge in practice.
The accuracy of the technique is critical to the success of proactive retention. If the marketer does not know that a customer is about to drop out, no action will be taken to retain that customer.
Special retention offers or incentives may be offered to happy, active customers, resulting in less revenue for no real reason.
Your churn prediction model must rely on (near) real-time data to quantify the risk of churn, not on static data. Although you can identify a certain percentage of risky customers even with static data, your initial predictions will be inaccurate. Adjustment is very important.
Summary churn prediction
In summary, predicting customer churn is vital. Effective action can be taken to retain the customer before it is too late. The ability to predict that a customer is at high risk of dropping out while there is still time to do something about it represents a huge additional potential revenue stream for any business.
Trendskout can help you to increase your churn more predictable. Contact us and tell us about your goals! Feel free to book a personalised demo to get a concrete idea of how Trendskout helps companies with their churn prediction.
