This study investigates the impact of big data on online consumer satisfaction and purchasing behavior within the Moroccan context, addressing the gap in understanding its effects on consumer satisfaction in specific markets. Through a quantitative analysis, the authors explore how big data's application in personalized marketing strategies influences consumer behaviors and satisfaction. The research reveals the critical role of product quality and personalized recommendations in enhancing online consumer satisfaction, despite the general assumption of price as a primary factor. These findings suggest that big data, while potent in tailoring marketing efforts, shows varied significance in directly influencing consumer satisfaction levels in Morocco. The study contributes to the digital marketing literature by providing insights into the strategic application of big data in enhancing consumer engagement and satisfaction, offering managerial implications for leveraging technology in marketing strategies.
Top1. Introduction
In the current digital era, Big Data has become a fundamental accelerator of transformation across many fields, notably in marketing (Brewis et al., 2023a; Cadden et al., 2023) and understanding online consumer behavior (Chou et al., 2022; Liu, 2021). The ability to collect, analyze, and decipher vast data sets has provided organizations with deep insights into consumption habits trends (Kauffmann et al., 2020; Wang et al., 2020), expectations, and strategic purchasing decisions (Akram et al., 2022), allowing them to adjust their marketing strategies more effectively (Chou et al., 2022). However, despite numerous studies on Big Data in marketing (Brewis et al., 2023a; Chou et al., 2022), several questions remain unanswered, particularly regarding its impact on satisfaction and online purchasing behavior under specific circumstances, such as the technologically evolving Moroccan market.
Morocco, with its progressive integration of digital and technological tools and an increasingly interconnected population, becomes a conducive environment to study how Big Data can impact online satisfaction and purchasing behavior. Previous studies (Roy et al., 2020; Salonen et al., 2024) highlight that Big Data, by adjusting and personalizing marketing strategies, has the potential to significantly improve consumer behavior and satisfaction. Yet, the extent of these effects in the Moroccan context remains largely unanalyzed.
This observation highlights the importance of examining the impact of Big Data on online satisfaction and purchasing behavior in the Moroccan context. The existing literature broadly addresses the technical aspects and benefits of Big Data for businesses, but there is a lack of in-depth research on consumer perceptions, their reaction to personalized recommendations, and how these elements influence their online purchasing decision. Consequently, a quantitative study will be undertaken to provide an updated status on the influence of Big Data on online purchasing behaviors, with a focus on the Moroccan market. This study aims to elucidate the impact of Big Data analytics on customer satisfaction within the rapidly digitizing market of Morocco, a context that remains underexplored despite its potential insights into consumer behavior. By focusing on this specific geographical and digital milieu, the research seeks to bridge the gap between the extensive capabilities of Big Data and the actual enhancement of consumer satisfaction, forming a coherent narrative that examines both the benefits and challenges posed by Big Data in a uniquely evolving market. This study will also aim to analyze how Big Data can enhance marketing personalization and, consequently, positively influence consumer behaviors and satisfaction. Moreover, it will identify sectors requiring future research for a deeper understanding of these mechanisms.
Our article will begin with a literature review addressing the general concepts of Big Data. Next, we will examine the correlation between Big Data, satisfaction, and consumer behaviors. In the second part, we will present the adopted methodology, specifying the study context as well as the data collection and analysis processes. Thirdly, we will discuss the results and discussions of previous studies, highlighting the findings obtained. Finally, we will conclude by synthesizing the results of our study, the theoretical and managerial contributions, encountered limitations, and future research directions.