Designing and Explaining the Purchase Journey Map of Moviegoers Based on Contact Points

The purpose of the present study is to design and explain the purchase journey map of moviegoers based on contact points. In the first step, using the content analysis method, 29 indicators were extracted as the contact points of moviegoers in the three stages of the shopping trip, and based on that, a research questionnaire was designed. In the second step, quantitative approaches were used to investigate the statistical population. To describe the research population, 419 adult moviegoers were clustered and analyzed in two separate clusters using the Davis-Bouldin index. The results showed that in the first cluster, the pre-purchase stage (actresses and director's brand), during the purchase (sanitary facilities), and post-purchase (advice, silence, and bad-mouthing) contact points were most significant. In the second cluster, the pre-purchase stage (previous experience), during purchase (store quality), and post-purchase (information on upcoming movies) contact points were most significant. Naive Bayes was used to design the model predicting the audience return rate. The application of Naive Bayes showed that by using contact points, it is possible to predict the return rate of moviegoers in the first and second clusters with an accuracy of 0.910 and 0.814, respectively. The sensitivity analysis results showed that in the first cluster, the pre-purchase stage (cinema brand), during the purchase (personnel encounter), and post-purchase (discount for the next visit) were the best predictors of consumer behavior. In the second cluster, the pre-purchase stage (word-of-mouth advertising), during purchase (store quality), and post-purchase (handling complaints) were the best predictors of consumer behavior.