Abstract:

Machine learning (ML)is important in data analysis and decision-making for any business.ML algorithms are used to analyze complex data sets and to extract useful insights from a large collection of data. It enhances the efficiency of decision-makers to arrive at better solutions for complex business problems. Two major glitches faced by all businesses are customer acquisition and preservation. The very first thing the companies can do to reduce the attrition rate is to understand their customers. Even if some customers have churned, the companies should analyze the reasons for their attrition, so that they can make use of this information to reduce the future attrition rate. In this paper, different algorithms are used for identifying the key customers who are making up their minds to switch their mobile network service provider. Predictive modeling with KNN, SVC, logistic regression, decision tree, and random forest with its performance evaluation for prediction of customer attrition. If the service providers use such efficient tools, they can reduce the attrition rate of customers and can focus on targeted promotion and retention strategies.

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