It's About Time! Modeling Customer Behaviors as the Secretary Problem in Daily Deal Websites
2017 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN)(2017)
摘要
Daily deal websites, such as Groupon and Living-Social, are now becoming increasingly popular current shopping trends worth multi-billion dollars. Understanding customers' purchase behaviors in daily deal websites is important to provide accurate and precise personalized recommendations in order for companies to gain more revenue. However, different from traditional online shopping sites, such as Amazon and Target, in which consumers can evaluate and purchase multiple items at the same time, customer's behaviors in daily deal websites have their unique characteristics and thus pose several challenges for modeling these behaviors: (1) daily deals are not available all the time and customers have to decide whether to purchase today's deal or forgo the opportunity and wait for future deals; (2) daily deals are made sequentially available to the consumers and the future quality of the deals are uncertain. Despite recent advances in user modeling and item recommendation, modeling users' purchase behaviors in daily deal websites is still not well resolved. In this paper, we present a large-scale study of customers' behaviors based on Groupon data with the following contributions: (1) By conducting empirical analysis on customers' complete clickstream data, we first demonstrate that customers are active but prudent for the purchase behaviors, then we show customers have their criteria for the purchase decision and the criteria changes with the waiting time since their last purchase; (2) Based on these observations, we formulate users' behaviors in daily deal websites as the Secretary Problem and propose a structure model based on consumer behavior theories to investigate how individual and deal characteristics would affect the purchase behavior on daily deal website; (3) We model customers' purchase criteria as reservation value and propose the use of copula modeling for reservation value estimation. We demonstrate the performance of the proposed model for purchase behavior modeling and discuss how this model can be used to reveal the behavior mechanism and provide reliable solutions to target the right people at the right time using the product with the right features even in the long run.
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关键词
customer behavior modeling,secretary problem,daily deal Websites,Living-Social,shopping trends,customer purchase behavior understanding,personalized recommendation,online shopping sites,Amazon,Target,deal quality,user modeling,item recommendation,Groupon data,customer complete clickstream data analysis,purchase decision,structure model,copula modeling,reservation value estimation
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