Time analysis of online consumer behavior by decision trees, GUHA association rules, and formal concept analysis

Tomáš Pitka (), Jozef Bucko (), Stanislav Krajči (), Ondrej Krídlo (), Ján Guniš (), Ľubomír Šnajder (), Ľubomír Antoni () and Peter Eliaš ()
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Tomáš Pitka: Technical University of Košice
Jozef Bucko: Technical University of Košice
Stanislav Krajči: Pavol Jozef Šafárik University in Košice
Ondrej Krídlo: Pavol Jozef Šafárik University in Košice
Ján Guniš: Pavol Jozef Šafárik University in Košice
Ľubomír Šnajder: Pavol Jozef Šafárik University in Košice
Ľubomír Antoni: Pavol Jozef Šafárik University in Košice
Peter Eliaš: Slovak Academy of Sciences

Journal of Marketing Analytics, 2025, vol. 13, issue 1, No 4, 29-52

Abstract: Abstract Data analytics plays a significant role within the context of the digital business landscape, particularly concerning online sales, aiming to enhance understanding of customer behaviors in the online realm. We review the recent perspectives and empirical findings from several years of scholarly investigation. Furthermore, we propose combining computational methods to scrutinize online customer behavior. We apply the decision tree construction, GUHA (General Unary Hypotheses Automaton) association rules, and Formal concept analysis for the input dataset of 9123 orders (transactions) of sports nutrition, healthy foods, fitness clothing, and accessories. Data from 2014 to 2021, covering eight years, are employed. We present the empirical discoveries, engage in a critical discourse concerning these findings, and delineate the constraints inherent in the research process. The decision tree for classification of the year’s fourth quarter implies that the most important attributes are country, gross profit category, and delivery. The classification of the morning time implies that the most important attributes are gender and country. Thus, the potential marketing strategies can include heterogeneous conditions for men and women based on these findings. Analyzing the identified groups of customers by concept lattices and GUHA association rules can be valuable for targeted marketing, personalized recommendations, or understanding customer preferences.

Keywords: Formal concept analysis; Decision trees; GUHA association rules; Consumers; Marketing (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1057/s41270-023-00274-y

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