Objective: The present study was conducted with the aim of designing and validating a data-driven marketing model in online retailing. To achieve this objective, the literature on data-driven marketing was comprehensively reviewed to identify the antecedents and consequences of data-driven marketing. Based on these findings, the conceptual model of the study was developed and subsequently validated.
Methodology:
This study is quantitative in terms of research methodology. The statistical population consisted of Iranian online retailers operating in various industries, including apparel, cosmetics and personal care products, accessories, and other sectors. A total of 79 marketing managers and experts were selected as representatives of their companies to complete the research questionnaire. Data were collected through both library research and a field survey using a questionnaire comprising 34 items. The collected data were analyzed using Structural Equation Modeling (SEM) and SmartPLS software.
Findings: The results indicate that all antecedents included in the research model—namely data-driven culture, top management support, data and technological infrastructure, and data analytics skills—have a positive effect on data-driven marketing. Furthermore, the effects of data-driven marketing on rational decision-making, marketing innovation, and market performance were confirmed. However, the effect of rational decision-making on market performance was not supported.
Conclusion: Considering the requirements and prerequisites of data-driven marketing, companies can adopt strategies such as investing in technology infrastructure, training and empowering human resources, creating a data-driven culture, using advanced analytics to extract strategic insights, etc. to succeed in data-driven marketing and benefit from its valuable results.