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E-commerce, Purchase Frequency, Consumer Behaviour, Predictive Analytics, Amazon.

In the evolving digital marketplace, understanding the mechanisms that drive frequent purchases is pivotal for both researchers and practitioners. This study investigates the determinants of repeat purchasing on Amazon, aiming to uncover the key factors that motivate consumers to engage in multiple transactions within a short time frame. Utilizing a robust dataset of 602 responses collected through an online survey, we employed quantitative analysis and advanced visualization techniques via Power BI to examine the interaction between consumer characteristics, product attributes, and platform specific features. Our findings indicate that the product category plays a critical role in influencing purchase frequency, with segments such as groceries, gourmet food, and fashion emerging as significant predictors of repeat buying behaviour. Additionally, the analysis reveals that the strategic use of customer reviews, advanced product search filters, and features like “save for later” markedly enhance the likelihood of frequent purchases. Moreover, increased browsing frequency correlates with heightened consumer engagement, suggesting that repeated exposure to tailored digital content fosters a stronger propensity for recurring transactions. The insights derived from this study are particularly important for Amazon marketplace sellers, digital marketing strategists, and e-commerce platform developers. By leveraging these findings, stakeholders can design more effective customer engagement strategies, optimize marketing efforts, and ultimately cultivate greater customer loyalty. This research contributes to the broader discourse on online consumer behaviour by providing a detailed, data-driven exploration of the factors influencing purchase frequency on one of the world’s leading e-commerce platforms.