Title: Predictive analytics of user cognitive styles in online shopping

Authors: Vijaya Bharathi Jagan; Jyothi M. Rao; Amiya Kumar Tripathy

Addresses: Department of Information Technology, Pillai College of Engineering, New Panvel, Maharashtra, India ' Department of Computer Engineering, K.J. Somaiya College of Engineering, Vidyavihar, Mumbai, Maharashtra, India ' Department of Computer Engineering, Don Bosco Institute of Technology, Kurla, Mumbai, Maharashtra, India

Abstract: Revolution in online retail has led to a paradigm shift in customers' shopping behaviour making customer retention relatively tougher. E-retailers need to understand more in depth about their e-customers to provide right offers to right people. Though click stream analysis has been solving e-business problems, still recommendation systems on e-commerce and digital marketing are far from perfect. Thus, a more perfect consumer behaviour model is the need of hour. This study finds that effective adoption of cognitive science in the click stream analysis can identify customers' thinking patterns for decision-making. The proposed system adopted the conceptual framework of cognitive architecture namely adaptive control of thought rational (ACT-R) to identify various cognitive styles of online users using click stream data. The customer segments based on their cognitive styles provides a deeper insight to the e-retailers, which can be best leveraged to offer better personalised marketing advertisements and thereby increasing customer retention rate.

Keywords: clickstream; cognitive model; decision making styles; web usage mining; customer retention; ACT-R.

DOI: 10.1504/IJCISTUDIES.2022.129016

International Journal of Computational Intelligence Studies, 2022 Vol.11 No.3/4, pp.279 - 297

Received: 30 Dec 2021
Accepted: 26 May 2022
Published online: 14 Feb 2023 *

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