Companies usually have a greater focus on customer acquisition and keep retention as a secondary priority. However, it can cost five times more to attract a new customer than it does to retain an existing one. Increasing customer retention rates by 5% can increase profits by 25% to 95%, according to research done by Bain & Company.
Churn is a metric that shows** customers who stop doing business** with a company or a particular service, also known as customer attrition. By following this metric, what most businesses could do was try to understand the reason behind churn numbers and tackle those factors, with reactive action plans.
But what if you could know in advance that a specific customer is likely to leave your business, and have a chance to take proper actions in time to prevent it from happening?
The reasons that lead customers to the cancellation decision can be numerous, coming from poor service quality, delay on customer support, prices, new competitors entering the market, and so on. Usually, there is no single reason, but a combination of events that somehow culminated in customer displeasure.
If your company were not capable to identify these signals and take actions prior to the cancel button click, there is no turning back, your customer is already gone. But you still have something valuable: the data. Your customer left very good clues about where you left to be desired. It can be a valuable source for meaningful insights and to train customer churn models. Learn from the past, and have strategic information at hand to improve future experiences, it’s all about machine learning.
#telecommunication #machine-learning #churn-prediction #data-science #churn #deep learning