Predicting Customer’s Satisfaction (Dissatisfaction) Using Logistic Regression

Customer satisfaction is a metric of how products and services offered by companies meet customer expectations. This performance indicator assists companies in managing and monitoring their business effectively. Firms thus need reliable and representative measure to know the customer satisfaction. In the present work, we provide a predictive model to identify customer’s satisfaction (dissatisfaction) with the firm’s offerings. For the analysis, “mobile phone” has been used as a product and 11 related decision making variables have been taken as independent variables. Due to the dichotomous (i.e. satisfaction/ dissatisfaction) nature of the dependent variable, a powerful tool among multivariate techniques i.e. Logistic Regression has been applied for the validation. Further, Receiver Operating Characteristic (ROC) curve has been plotted which displays the degree to which the prediction agrees with the data graphically. The analysis has been done on data collected from students of University of Delhi, Delhi. Keywords-customer’s dissatisfaction, customer’s satisfaction, logistic regression, multivariate technique, receiver operating characteristic (ROC) curve.

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