In the modern business world, customer churn has become a major concern for companies across all industries. Customer churn is the process of losing customers over time due to various factors such as poor customer experience, inadequate product offerings, or stiff competition. Churn can be detrimental to the sustainability of a business as it affects the revenue stream and can damage the company’s reputation. To ensure sustainability, companies have started leveraging churn prediction to identify and proactively address customer attrition, optimise retention strategies, and drive long-term profitability.
What is churn prediction?
Churn prediction is the process of identifying maternity retouching customers who are at risk of leaving a business before they actually do so. It involves analysing customer behaviour and historical data to predict which customers are likely to churn and the reasons behind it. By leveraging churn prediction, companies can take proactive measures to prevent customer churn and ensure the long-term sustainability of their business.
Designing the churn model
To develop a supervised machine learning model, we require a set of training data that consists of both explanatory variables and target responses. The model is then adjusted using the training data to reveal the correlation between the variables and the responses.
Historical data is typically used for this purpose, where positive targets indicate clients who depart while negative targets indicate those who remained. The features used to determine the likelihood of a client BA Leads leaving include demographic information such as age, gender, occupation, and education, as well as data on customer interactions, feedback, buying habits, and transaction value.
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Steps To Make a Churn Prediction Model
Source: Digital Uncovered
Key benefits of churn prediction
Identify the root causes of customer churn
By analysing customer behaviour and feedback, companies can understand the reasons why customers are leaving and take steps to address these issues. For example, if customers are leaving due to poor customer asia email list service, the company can invest in improving its customer service to reduce churn. This can lead to increased customer satisfaction, loyalty, and retention, which can drive long-term revenue growth.
