Two Decades of Research on Consumer Behaviour and Analytics: Reviewing the Past to Prepare for the Future

Two Decades of Research on Consumer Behaviour and Analytics: Reviewing the Past to Prepare for the Future

Nirma Sadamali Jayawardena, Abhishek Behl, Mitchell Ross, Sara Quach, Park Thaichon, Vijay Pereira, Achint Nigam, Thanh Tiep Le
Copyright: © 2022 |Pages: 38
DOI: 10.4018/JGIM.313381
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Abstract

The present study is a systematic literature review that identifies the context of consumer behaviour and analytics in business to forecast the future of consumer behaviour with changing business trends through TCCM (theory, context, characteristics, method) guidelines. The authors identified that prior research used theories in different disciplines to explain the phenomenon in customer behaviour and analytics literature. When considering the theory, these phenomena often can be segregated based on the industry (e.g., marketing, advertising, sales, healthcare, human resource management, tourism), focusing on status-based mechanisms (e.g., cross-gaming predictive models), inertia-based mechanisms (e.g., theory of rational expectations and adaptive learning), or relationship-based mechanisms (e.g., theory of consumer engagement behaviour).
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Introduction

Data is the brand new oil, and the ever-developing need and use of statistics has converted business operations into a new era. Entrepreneurs have additionally adopted the lens of information analytics to revisit client behaviors. Data opened a new methodological paradigm and gave a sparkling dimension to revisit theoretical arguments inside advertising and marketing. Several researchers offer a systematic evaluation of literature to deal with a gap in knowledge on the function of analytics in customer behaviors. This paper presents an efficient audit of studies distributed between 2001 to 2021 (twenty years of exploration) in consumer behaviors and analytics. It is critical to comprehend the consolidated ideas of purchaser conduct and examination, as organizations utilize big data and customer analytics tools to discover consumer behaviors (Cruz-Cárdenas et al., 2015; Balica et al., 2022; Kral et al., 2022).

Further, companies can settle on information-driven choices utilizing consumer behaviors analytics examination as they have an individual-level perspective on their customers (Cruz-Cárdenas et al., 2015; Erevelles et al., 2016). Data can be considered an important aspect, and the increasing demand for and application of data has changed how organizations work. Marketers have often re-examined customer/consumer actions through the prism of knowledge analytics. It created a brand new analytical framework and offered a replacement dimension for revisiting theoretical debates within the field of selling. Consumer marketing is becoming increasingly data-driven providing proper consumer-related predictions for business growth (Smith, 2019). Consumer behaviors and analytics can be considered a creative area that introduces new methods and ideas to suit the new reality of analytics-driven marketing (Maheshwari et al., 2020; Smith, 2019). When buying products and services for personal use, people's behaviors and decision-making processes are referred to as consumer behaviors (Maheshwari et al., 2020; Smith, 2019). When considering marketing aligned with consumer behaviors, it can be viewed as a subdivision of economics using scarce resources, consumer psychology, and covert behaviors. Marketing was traditionally described as an application area for its main disciplines (Foxall, 2015; Gambhir, et al., 2022; Gandhi & Kar, 2022).

Today's business theory is focused on how an organization can maximize sales by meeting current and potential customer needs (Kehinde et al., 2016). In marketing management, this involves the use of behavioral science. Consumer theories are most often taken from one of the fundamental disciplines (e.g., psychology and economy) and applied to a particular marketing subject (Alboukaey et al., 2020; Barnes et al., 2020). However, if the laws and principles of marketers' and consumers' behaviors were established, analyzed, and clearly stated, it would benefit marketing and its application (Larsen et al., 2017). The quest for economic and understandable definitions of behavioral classes in marketing is focused on comparing different theories, approaches, and implementations to describe, predict, and control behaviors (Guha & Kumar, 2018; Hofacker et al., 2016; Larsen et al., 2017). Marketing management has ideally shifted from production to market orientation where “information on all important buying influences permeate all business functions” (Zimmerman & Blythe, 2017).

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