Empirical Analysis of Customer Repeat Purchase Forecast on O2O platform

Abstract

On the O2O platform, accurate forecasting of customer repeat purchase is critical to the management of these businesses. Based on the NBD model and SMC model, and taking nearly thousands of different categories of businesses on the O2O platform "koubei" as study object, we implement empirical research on customer repeat purchase forecast. The main contents include: (1) the introductions about NBD and SMC model; (2) forecasting the customer repeat purchase of different categories of businesses based on the models and analyzing the models fitting; (3) analyzing the models applicability based the results. The results shows that, in addition to the hot pot category, predicted results of the SMC model in each category of business is better than the NBD model, while the NBD model is more excellent in the forecast of the hot pot category.

An Effective Approach to Promote Air Traveler Repurchasing Using the Random Forest Algorithm: Predictive Model Design and Utility Evaluation

“…Repeated purchase intention refers to the subjective probability/implied promise that an air traveler will continue to purchase a product from the same seller [1]. Traveler repeat purchase behavior has been a topic of interest in many contexts [22], such as in B2C e-commerce [1,10,23], on O2O platforms [24], in direct marketing [18,20], and in mobile commerce [8,25]. In our work, we focused on an airlines' direct marketing context, especially the low-cost carriers.…”

“…(3) SVM models represent a specific type of learning algorithm characterized by the capacity control of the decision function, the use of the kernel functions, and the sparsity of solutions [24]. Prior work has shown that SVMs [51] are excellent tools for predictive tasks.…”