Towards early purchase intention prediction in online session based retailing systems
Ramazan Esmeli (),
Mohamed Bader-El-Den () and
Hassana Abdullahi ()
Additional contact information
Ramazan Esmeli: University of Portsmouth
Mohamed Bader-El-Den: University of Portsmouth
Hassana Abdullahi: University of Portsmouth
Electronic Markets, 2021, vol. 31, issue 3, No 15, 697-715
Abstract Purchase prediction has an important role for decision-makers in e-commerce to improve consumer experience, provide personalised recommendations and increase revenue. Many works investigated purchase prediction for session logs by analysing users’ behaviour to predict purchase intention after a session has ended. In most cases, e-shoppers prefer to be anonymous while browsing the websites and after a session has ended, identifying users and offering discounts can be challenging. Therefore, after a session ends, predicting purchase intention may not be useful for the e-commerce strategists. In this work, we propose and develop an early purchase prediction framework using advanced machine learning models to investigate how early purchase intention in an ongoing session can be predicted. Since users could be anonymous, this could help to give real-time offers and discounts before the session ends. We use dynamically created session features after each interaction in a session, and propose a utility scoring method to evaluate how early machine learning models can predict the probability of purchase intention. The proposed framework is validated with a real-world dataset. Computational experiments show machine learning models can identify purchase intention early with good performance in terms of Area Under Curve (AUC) score which shows success rate of machine learning models on early purchase prediction.
Keywords: Early purchase prediction; Session logs; Purchase prediction; Real-time offers; E-commerce; User behaviour analysing (search for similar items in EconPapers)
JEL-codes: M37 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed
Downloads: (external link)
http://link.springer.com/10.1007/s12525-020-00448-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:spr:elmark:v:31:y:2021:i:3:d:10.1007_s12525-020-00448-x
Ordering information: This journal article can be ordered from
http://www.springer. ... ystems/journal/12525
Access Statistics for this article
Electronic Markets is currently edited by Rainer Alt and Hans-Dieter Zimmermann
More articles in Electronic Markets from Springer, IIM University of St. Gallen
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().