خریدهای مشتریان در بازار آنلاین به آفلاین
Abstract
1. Introduction
2. Literature review
3. The model
4. Empirical illustration
5. Simulation study
6. Conclusions and discussions
Acknowledgements
Appendix.
References
Abstract
In the Online-to-Offline (O2O) ecommerce model, one challenge facing the online business is to predict customers’ future purchases towards each product or subcategory of products, and consequently, coordinate the large amount of offline businesses involved. The main obstacle in doing that originates from the highly diversified services and thus the customer base which offline businesses bring in. The heterogeneity of customers, geographic or demographic, needs to be accurately accounted for. However, although the previous transactions for each customer are well documented, his/her demographic data is difficult or costly to acquire. Traditional wisdom relies on fitting customers into some specific statistical distribution to arrive at a satisfactory stochastic model, which may be accurate, to some extent, at a higher level. This is the case for the classic BetaBinomial/Negative Binomial Distribution (BB/NBD) model on customers’ repeat purchasing in offline context. Nevertheless, to deal with the complex level in customers’ heterogeneity at an O2O business, using specific distribution is inadequate, let alone the mathematical challenges. We propose a new model to deal with the diversity of customers. Using BB/NBD as a starting point, we relax the Beta assumption in the model to include a generalized distribution. The generalization is made possible through using the Gaussian quadrature. The results retain the elegance of stochastic model while at the same time it captures customers’ heterogeneity at a better, granular level. We use a dataset from Ctrip.com, a leading O2O provider in China, to show that the proposed method outperforms the BB/NBD model in both in-sample and out-of-sample predictive performance. Our approach provides a practical solution for O2O practitioners to forecast their future demands.
Introduction
In a typical Online-to-Offline (O2O) business, customers purchase some service online (e.g., order a meal, book a hotel room or a trip through APPs using their cell phones), and consume the service offline through a third party. O2O has several differences with the traditional Business-to-Customer (B2C) model. First, in O2O model, the online business coordinates with the third party to provide service offline. A B2C business, however, provides products to its customers directly. On the other hand, an O2O business is more than an agent or match maker. The online business and the offline service providers take separate roles in the value chain, with online business providing website store front, advertising, order processing and customer support (like hosting online reviews, resolving customers’ issues etc.). The service provider focuses on its core business. In this way, O2O model lowers the bar for offline businesses to enter the online market. Second, the scope of products provided in O2O market is different or wider than the B2C. A B2C business usually deals with physical products. In O2O model, however, offline providers could sell not only products but also their services (e.g., a meal in a restaurant or a stay at a hotel). After smartphones penetrated the world, service products are now “just one touch away”, which leads to the tremendous growth of O2O market.