The Effect of Big Data on Small Firm Marketing Capabilities: An Abstract

Abstract

Researchers have recently started to explore the foundations of marketing capabilities, with the aim of identifying and understanding the mechanisms and resources required by firms to create, develop and organize their marketing capabilities (Massiera et al. 2018). Whilst interest is increasing, a gap still exists regarding how marketing capabilities develop in small firms and their potential antecedents (Qureshi and Kratzer 2011). This study addresses this deficit by exploring the relationship between big data and three types of marketing capabilities in small firms: specialized (marketing mix), architectural (market planning) and dynamic capabilities (market sensing and resource reconfiguration). Marketing capabilities within small firms have long been identified as under-developed, given their lack of resources, time and personnel (Blankson et al. 2006). A small pool of recent research, however, purports that big data can enhance small firm marketing capabilities by providing customer insights that guide them as to which value-adding activities they should undertake, and how they should be implemented (Hutchinson et al. 2015). However, extant literature in this area remains in its infancy and attention from the resource-based theory has generally focused on how large firms deploy big data to outperform competitors (O’Connor and Kelly 2017). Hence, this study offers to broaden understanding of the deployment of big data in small firms and its effect on their marketing capabilities. This research observed seven case firms from the Northern Irish agri-food industry. Using a qualitative, longitudinal approach, the change in their marketing capabilities was explored over three-stages (pre, post and during data provision). The findings show a complementarity between big data absorption and small firm marketing capabilities. In some cases, the uptake of planning processes and resource reconfiguration increased, which directed the deployment of newly informed marketing mix activities. In others, a lack of direction or commitment to learning and a nonchalant attitude portrayed by the owner-manager precipitated an indifference towards engagement with the data, with the effect that their marketing processes remained static. Therefore, a pertinent aspect of this empirical research is the influence of the owner-manager on data application. This is particularly interesting for practitioners as it indicates the potential of big data as a small firm resource, relative to the degree of empathy towards its value. It also represents a significant opportunity for government bodies subsidizing the provision of information resources, as by identifying a classification of owner-manager prior to an engagement, the likely return on public investment can be predicted and justified.