An Empirical Analysis on “Choice of Characteristics in Identifying and Classifying Prospective Customer at Real Estate Firm”

Abstract

This Research work deals with Classifying the prospective customers into two categories, Buyers and Non-Buyers, based on various variables that actually impact the decision making for buying a House. The variables considered in this research are Demographics, Family Income, Type of Employment, Does the Customer own a House, Type of Property, Sources through which the Customers look for Houses, Number of Bedrooms the Customers are looking for, Budget for Purchasing the House, Number of Family Members, Radius that the Customer are willing to settle from the preferred location. Classification Technique used to achieve this Research Project is Logistic Regression. The Data has been collected from 50 respondents who were customers at a Real Estate Firm. The Data of whether the Customers purchased the House through the Firm is also noted. Logistic Regression helps in predicting whether the future customers by knowing the values of the variables mentioned above will be a Buyer or Non-Buyer of the property. By following this method, the Firm will know which Customer will really close the deal and concentrate more on such customers. It is helpful in providing adequate services to the Customers.