Predict and prevent customer churn to keep your existing customers satisfied and have a steady revenue stream
Customer churn is a scenario wherein your customers stop buying products or services from you. The fact is that customer loyalty is the key to generate a steady revenue stream. Acquiring new customers requires a lot of time, money and resources. However, calculating customer churn is not an easy task; and even among data scientists there is no universally agreed upon methodology on how to measure it. If you want to calculate your churn rate accurately you need to ask yourself these questions –
The right time to address customer churn is when you notice a drop in usage instead of waiting for the customer to cancel his subscription or completely stop visiting your site or store. In order to estimate future churn rates, businesses need to adopt predictive analysis and carry out predictive churn modeling.
Our client, an online retailer, thought it was losing customers when it experienced a considerable amount of drop in sales. Our data science team used predictive models on their data sets and tracked the behavior of its regular users to know if and why its customers are switching over to another online shopping website.
This model also tracks what customers do before they are just about to leave and switch to another website. Along with this, we provided the company the best data visualization tools to help its decision makers understand the journey of their customers so that they could observe and know the common actions associated with customer churn.