A two-stage customer journey analytical model in single house business

Abstract

The single housing industry is currently experienc-ing a continuous expansion in demand for housing. Addressing the needs of different customer groups is the key to increasing the sales rate. The objec-tive of this research is to propose a single house customer journey analytical model that consists of two stages. The first stage concerns the customer journey between registration and reservation processes. The second one identifies the customer loyalty from the reservation to the transfer stage. We experimented with four classification data mining techniques. The experimental results include comparison of the accuracy and F-Measure. We also performed statistical testing. The Artificial Neural Network was the most accurate model for both stages. This model analyzes the probability of the customer progressing through the stages to the conclusion of purchase by learning the customer’s characteristics and the factors in-volved in the customer’s decision. The model displays the reservation and transfer result for customers who have achieved the respective reservation and transfer-ence steps according to their registration profile. Experiments showed that the proposed two-stage models could predict customer loyalty, thereby enhancing relationship management between customers and or-ganizations. It also confers a competitive advantage within the industry.