A Systematic Literature Review and Research Agenda of Data-Driven Marketing

Introduction

The rapid proliferation of information derived from customer activities, driven by Information and Communication Technologies (ICT) and the Internet, has led to exponential growth in fields such as Big Data (BD), Customer Relationship Management (CRM), Artificial Intelligence (AI) and Machine Learning (ML) (De Luca et al., 2021). The growth of these technologies has shaped the practice of marketing, which until recently was limited to obtaining consumer data. However, today, the challenge is not obtaining information but learning how to use it effectively (Aguirre et al., 2015). In this context, Data-Driven Marketing (DDM) has become an innovative marketing strategy that is a fundamental pillar for companies and organizations worldwide, allowing them to adapt and thrive in a changing environment (Grandhi et al., 2020). DDM is a set of innovative marketing strategies to promote products or services differently from traditional marketing methods. DDM activities involve thinking outside the box and leveraging new technologies and trends in consumer behaviours to capture the attention and interest of the target audience (Choe et al., 2021).

Although there are studies on DDM, few have addressed its evolution in depth. Therefore, this study explores the evolution of DDM and its impact on marketing activities, companies and customers, covering 40 years (1980 - 2023). To this end, a systematic literature review was conducted to map the development of DDM over time, to provide an overview of the state of knowledge on DDM, identify research gaps and create a future research agenda. This study will provide value to those researchers and practitioners interested in marketing and information technology. The research questions that this study answers are as follows:

RQ1: What has been the growth of DDM publications?

RQ2: What are the main topics, journals and authors on DDM?

RQ3: What methodological approaches and theoretical models have been used in DDM research?

RQ4: What has been the evolution of DDM, and what drivers and outcomes have been observed given the adoption of DDM?

RQ5: What impact has DDM left on customers and marketing personnel?

RQ6: What lines of research open up from this analysis?

The chapter is structured as follows: It begins with the background, explaining the evolution from traditional marketing to data-driven marketing (DDM). Subsequently, the contextual framework is presented, incorporating implications of DDM use in organizations, its social and economic impact, and previous studies on its evolution. The following section explains the methodology for conducting the systematic literature review. Later, the main results are presented, followed by an analysis of trend topics, the most cited documents, and the sources of publication, as well as an examination of co-citation among sources. Subsequently, authors were examined, and co-citation between them was observed. Additionally, methodological approaches, theoretical lenses, the evolution of DDM by decades, drivers, and outcomes of DDM adoption were analysed. Towards the end of the chapter, the obtained results and conclusions are discussed, emphasizing their implications. Finally, future lines of research are described.

Background

Throughout history, marketing has evolved from promotion in ancient civilizations to the mass production of the Industrial Revolution, where marketing emerged as a recognized profession and industry. Among the activities of Marketing, it is essential to highlight that in the 1990s, branding became a widespread strategy. At the end of that decade, companies began to explore the digital world, creating websites and using search engine optimization (Botezatu, 2019). These developments led to the birth of digital marketing. This modality has evolved from a specific strategy of marketing products and services through digital channels to a comprehensive term, encompassing the use of digital technologies to attract and retain customers, promote brands and increase sales (Kannan et al., 2016).