Executing data-driven marketing strategy: an integrated framework of antecedents, process and consequences

Purpose Today, with the digitalization of businesses and changing customer expectations, we are faced with the increasing importance of data and its analysis. Extracting actionable insights from raw big data, especially in the marketing field, has become a strategic priority for senior marketing managers. Despite the importance of this issue and the increasing investment in data-driven technologies, organizations have not been able to achieve the desired results in these initiatives. Focusing on the technical aspects of implementing these approaches and ignoring the strategic management aspects can be one of the challenges of implementing data-driven initiatives in marketing. However, existing research has not yet provided practical guidance on the successful implementation of data-driven marketing (DDM) strategies. This study, focusing on the implementation of DDM strategies, aims to address this neglected aspect. Through an exploratory approach, it seeks to design an integrated process that identifies key activities and factors affecting the implementation of a successful DDM strategy. Design/methodology/approach To achieve the research objective, a qualitative approach was adopted. First, a comprehensive review of the relevant literature was conducted. Then, 12 semi-structured interviews were carried out to identify and extract key activities and processes involved in executing DDM strategies. The research population included experienced managers in DDM projects, specialists and analysts in marketing analytics and academic experts with hands-on experience in related projects. Participants were selected using a purposive non-random sampling approach. The qualitative data were analyzed using a thematic analysis approach. Findings The results indicate that the proposed integrated methodology comprises three main categories – antecedents, processes and consequences – encompassing 14 key concepts. The antecedents of DDM strategy execution consist of four key concepts, the process execution is structured into five main phases and the outcomes of DDM strategy execution are categorized into four groups. Research limitations/implications The proposed methodology presents a comprehensive picture of data-driven strategy execution, capturing the critical multifaceted aspects of data-driven success. The findings provide actionable insights for marketing managers, helping them adopt effective strategies to leverage their marketing analytics initiatives. Originality/value A review of the literature on DDM reveals that strategic research in this field has been largely overlooked. Despite the growing body of research, no methodology has been developed to assist managers in executing DDM strategies effectively. This study is among the first in the field of DDM to address this gap by designing a methodology for strategy execution. It bridges the theoretical gap by providing an integrated methodology to this stage of strategic management, encompassing antecedents, processes and outcomes of DDM execution.