Consumer behavior is one of the most vital aspects of business, given the need to make an enterprise competitive in the market by improving marketing efforts and the product range. The project goes further into the actual segmentation and analysis of consumer behavior in relation to purchase through data analytics and machine learning for the identification of significant trends and patterns. The most important outcome of this phase is that a mere 1% of customers are able to fairly estimate delivery timings, hence showing the most room for further advancement. The implementation also takes place of an intelligent product recommendation system that personalizes product recommendations for a greatly enhanced customer experience. The paper provides strategic recommendation for optimal promotion, steering clear of purchase slumps, e.g. on Saturdays. The outcome is tangible insight for businesses by which they can fine- tune strategies adopted to elevate customer satisfaction.
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Garg et al. (2024) studied this question.
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