The impact of ambidextrous traditional and contemporary data analytics on marketing innovation

Abstract

Businesses today operate in a digital transformation era which relates to accumulation of internet-based technologies that reshape how companies derive insights that affect innovation. With the spread of technologies, managers face dilemmas how to relate to existing technologies. One prominent contemporary technology is big data (BD). While research articulates its importance, it ignores its combination with existing traditional systems (i.e., small data; SD) and how firms cultivate this development. This study examines the impact of SD, BD that constitute marketing analytics, and their intersected relationship on data-driven insights en route implications on marketing innovation. Based on quantitative and qualitative studies and ambidexterity framework, the study proposes the combination of SD and BD (data ambidexterity) as key driver of marketing insights and innovation. A conceptual model was tested using regressions, path analyses, and robustness checks. Findings show that new data technologies should not overshadow older ones and suggest a hierarchy of analytic effects (SD < BD < SD × BD). While BD has a stronger effect than SD on insights, their combination is more beneficial than each in isolation. Moreover, the effect of this combination on marketing innovation is mediated through data-driven insights. The study addresses the paucity of research on SD and BD, proposes a more holistic approach, extends the potential of marketing analytics, and exhibits theoretical and practical implications of data ambidexterity.