Few well-documented studies have explained the importance of researching firms' marketing analytics capability (FMAC). In spite of its significance, there is scant attention to conceptualising and empirically investigating FMAC and its consequences in a data-driven business context. Thus, this study aims to develop and test a conceptual model that relates FMAC and its repercussions in the data-rich business environment.
This study analysed the data from 250 managers amongst large and medium-sized manufacturing and service-intensive firms. Furthermore, this research performed an empirical study by using operationalised questionnaire survey method to verify the hypotheses and reach its theoretical and managerial implications. Structural equation modelling with maximum-likelihood estimation method was applied to verify the validity of the proposed research model.
Multivariate analysis results show that FMAC significantly influences firms' competitive marketing performance (FCMP) with the presence of holistic marketing decision-making (HMDM) as a mediator. Moreover, adoption of artificial intelligence (AAI) enhances the relationship of FMAC-HMDM and FMAC-FCMP linkages.
This study analyses how FMAC can enhance FCMP and contributes to resource-based views and technological capability theories. From a managerial perspective, guidelines are provided for marketers to adopt advance technologies, such as AI, to optimise FMAC and HMDM to achieve competitive marketing performance.
Believing that “how to be competitive in marketing performance under data-rich-environment”, this research is the first to use the data of a firm manager to facilitate the understanding of FMAC, which provides a new direction for improving marketing performance. In addition, HMDM and AAI are also proposed for firms to optimise FCMP.
