Published Paper Details:

This study aims to explore the definition and properties of big data as well as analyze consumer behavior features in the context of big data research. The findings indicate that while big data influences customer perception through external factors, external factors and internal perception are the main determinants of consumer decision making. Because of the sheer volume of data, standard database management system techniques are unable to handle and analyze it(Latvia_ESRD_43_2016, n.d.) .this article examines the features of the big data phenomena and how analytics may be used as a tool to help marketers understand consumer behavior and provide their companies a competitive edge. When service users receive technical and business training in a controlled context, data is collected from them. In addition to discussing technical details such environment building, theory, logic, framework, infrastructure, and architecture, this study will address consumer behavior modeling(Big Data Analytics, 2016) The first section of the literature review looks at ideas of consumer behavior that are connected to trust. It explores the psychological underpinnings of consumer trust and how perceptions of risk, confidence, and trust impact the process of making decisions. Moreover, it contradicts the notion of empowered firms by emphasizing the effect of legitimacy on consumer trust, trust, and brand integrity. On the other hand, it examines customer mistrust of unlicensed services and talks about issues and causes for that mistrust.(Anshari et al., 2019) In essence, the recommendation engine makes many product recommendations depending on a range of variables, such as age and past purchases made by the user. It is a type of data filtering technology that suggests the most pertinent products to a specific client based on machine learning algorithms. This study aims to develop a product recommendation system by analyzing user sentiment and segmentation related product reviews.(Ertemel, 2015).