Building an Application to Predict Customer Churn

Website : https://blog.cloudera.com/building-an-application-to-predict-customer-churn/
Blog #2

Student name : Vanessa 黃妮莎
Student ID : D0726551


Building an Application to Predict Customer Churn

            The term customer churn refers to the loss of existing customers. It is very often that companies find out after their customer stopped using their product or service, without enough notice to have done anything to keep them. Tracing customer churn is a key business metric for many companies because studies have showed that existing customers are more profitable than acquiring new customers. 
            One argument with customer churn is that companies don’t know who is at chance of leaving. Although companies have enough notice, it is still difficult to keep them when it’s not sure what to offer these “at-risk” customers. 
            Of course if a company are going to collect data to address customer churn it will be very challenging. Collecting the data itself requires them to pull in data from various systems, such as their CRM, call center, ERP, etc. These systems will help them gather the full information they need about the demand of consumers and they can identify better the customers most at risk of going away. The next issue is to keep the data as close to real-time as possible. If the data is a few days or weeks old, customers might changed their mind in between that time. More recent the data, the more likely the prediction of customer churning will be accurate. Then the next issue is identifying the data using machine learning model to find which data identifies at risk customers and deciding what is the next step to keep that customer like a special promotion or discount. Last issue is that companies need to be able to understand the machine learning model. This will ensure that they are making the right business decisions, understanding all the factors and significance of each, which affected a model into making a specific endorsement.

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