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Ai's Contribution to Predicting Consumer Behavior in Retail Stores
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Author(s): Brahim Boutaleb (University of Boumerdes, Algeria)and Maher Toukabri (Northern Border University, Saudi Arabia & University of Jendouba, Tunisia & Laboratory ARBRE, University of Tunis, Tunisia)
Copyright: 2026
Pages: 22
Source title:
Harnessing AI for Point-of-Sale Optimization
Source Author(s)/Editor(s): Nozha Erragcha (University of Jendouba, Tunisia)and Maher Toukabri (Northern Border University, Saudi Arabia & University of Jendouba, Tunisia & Laboratory ARBRE, University of Tunis, Tunisia)
DOI: 10.4018/979-8-3373-4392-1.ch004
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Abstract
A key component of retail marketing is the study of consumer behavior, which helps with decision-making about the layout of the product mix that is presented. In the past, retailers found it challenging to forecast customer behavior because the process was expensive and time-consuming due to the large amount of data that needed to be analyzed. However, access to consumer data has become less expensive and time-consuming due to the substantial developments in information and communications technology. Processing this data and turning it into marketing decisions that support customer requirements and aspirations has been made easier by artificial intelligence. Technologies such as machine learning, deep learning, robotics, facial recognition, and augmented reality have been used at retail points of sale by well-known brands like Adidas, Sephora, IKEA, and Amazon Go to understand and meet customer needs.
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