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Online commerce websites often request users to register in the online shopping process. Recognizing the challenges of user registration, many websites opt to delay their registration request until the end of the conversion funnel (i.e., ex post registration request). Our study explores an alternative approach by asking users to register with the website at the beginning of their shopping journey (i.e., ex ante registration request). Guided by a stylized analytical model, we conducted a large-scale randomized field experiment in partnership with an online retailer in the United States to examine how the ex ante request affects users’ registration decisions, short-term customer conversions, and long-term purchase behaviors. Specifically, we randomly assigned the new users in the website’s incoming traffic to one of two experimental groups: one with an ex ante registration request preceding the ex post request (treatment) and the other with only an ex post registration request (control). Our results show that the ex ante request leads to an increased probability of user registration; that is, the users in the treatment group, on average, are 58.08% relatively more likely to register with the website than those in the control group. Furthermore, the ex ante request leads to significant increases in customer purchases in the long run. Based on our estimation of the local average treatment effects, the ex ante registered users are 10.89% relatively more likely to make a purchase, place a 16.76% relatively greater number of orders, and generate 13.22% relatively higher total revenue for the firm in the long run. Finally, the ex ante request also does not impact customer conversion in the short-term. Further investigation into the long-term and short-term effects provides suggestive evidence on several potential mechanisms, such as firm-initiated interaction and screening of low-interest users. Our study provides managerial implications to the e-commerce websites on customer acquisition and contributes to the research on IT artifact design.
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Modeling Sequential Online Interactive Behaviors with Temporal Point Process
The massively available data about user engagement with online information service systems provides a gold mine about users' latent intents. It calls for quantitative user behavior modeling. In this paper, we study the problem by looking into users' sequential interactive behaviors. Inspired by the concepts of episodic memory and semantic memory in cognitive psychology, which describe how users' behaviors are differently influenced by past experience, we propose a Long- and Short-term Hawkes Process model. It models the short-term dependency between users' actions within a period of time via a multi-dimensional Hawkes process and the long-term dependency between actions across different periods of time via a one dimensional Hawkes process. Experiments on two real-world user activity log datasets (one from an e-commerce website and one from a MOOC website) demonstrate the effectiveness of our model in capturing the temporal dependency between actions in a sequence of user behaviors. It directly leads to improved accuracy in predicting the type and the time of the next action. Interestingly, the inferred dependency between actions in a sequence sheds light on the underlying user intent behind direct observations and provides insights for downstream applications.
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- PAR ID:
- 10106909
- Date Published:
- Journal Name:
- Proceedings of the 27th ACM International Conference on Information and Knowledge Management
- Page Range / eLocation ID:
- 873 to 882
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3269206.3271782
