A dynamic capability view of marketing analytics: Evidence from UK firms

Abstract

While marketing analytics plays an important role in generating insights from big data to improve marketing decision-making and firm competitiveness, few academic studies have investigated the mechanisms through which it can be used to achieve sustained competitive advantage. To close this gap, this study draws on the dynamic capability view to posit that a firm can attain sustained competitive advantage from its sensing, seizing and reconfiguring capabilities, which are manifested by the use of marketing analytics, marketing decisionmaking, and product development management. This study also examines the impact of the antecedents of marketing analytics use on marketing related processes. The analysis of a survey of 221 UK firm managers demonstrates: (a) the positive impact of marketing analytics use on both marketing decision-making and product development management; (b) the effect of the latter two on sustained competitive advantage; (c) the indirect effect of data availability on both marketing decision-making and production development management; and (d) the indirect effect of managerial support on marketing decision-making. The research model proposed in this study provides insights into how marketing analytics can be used to achieve sustained competitive advantage.

Identifying the configurational conditions for marketing analytics use in UK SMEs

“…However, no prior research has investigated how the configurations of multiple conditions affect business/marketing analytics use in SMEs. Based on the literature review, the following gaps concerning marketing analytics use are identified and will be addressed in this study: First, although studies have established the link between the use of business analytics and improved firm performance such as innovation (e.g., Duan et al, 2020), decision making effectiveness (e.g., Cao et al, 2015), supply chain performance (e.g., Zhan and Tan, 2020), and competitive advantages (e.g., Cao et al, 2019, WangYeoh et al, 2019, the majority of these studies are based on large companies and their findings should not be applied to SMEs directly without further investigation, as SMEs are not smaller versions of larger firms (O'Regan et al, 2005). Aside from only a few studies (e.g., Ferraris et al, 2019, Maroufkhani et al, 2020, Hansen and Bøgh, 2020, Liu et al, 2020, business/marketing analytics use and its effect on the performance of SMEs are yet to be fully investigated (e.g., Maroufkhani et al, 2020, Liu et al, 2020, Wang et al, 2018.…”

“…Second, managerial support refers to the extent to which the top management team understands, appreciates, and promotes the use of marketing analytics (Cao et al, 2019), which is considered necessary to fully exploit the benefits of IS (e.g., Thong et al, 1996, Ragu-Nathan et al, 2004 and is shown to be associated with IS adoption in SMEs (Grandon and Pearson, 2004). Recently, some analytics studies demonstrate that managerial support is positively associated with big data analytics use (Chen et al, 2015).…”

“…It pertains to the collection, management, and analysis of data to extract useful insights to support marketing decisionmaking (Wedel andKannan, 2016, Cao et al, 2019). Extant empirical research indicates that firms can use marketing analytics to improve marketing decision-making and firm competitiveness significantly, inter alia (e.g., Dremel et al, 2020, Cao et al, 2019. However, although firms are increasingly utilizing analytics for data-driven insights, and there has been a substantial amount of academic research into business analytics and its impact on (Trieu, 2017, Mikalef et al, 2020 and deserves further investigation (Ghasemaghaei, 2019).…”

Creativity Forward: A Framework That Integrates Data Analysis Techniques to Foster Creativity Within the Creative Process in User Experience Contexts

“…Big data are fundamentally big datasets, made up of structured, semi-structured, and unstructured data that can be processed and analysed to reveal patterns and trends (Hazen et al, 2014). Growing levels of digitisation increase the demand for greater data evaluation in terms of velocity, efficiency, and accuracy (Cao et al, 2019;Xu et al, 2016). Moreover, with the evolving status of data and the merge of data sets, it will create more and more options in a variety of contexts and domains (Akhtar et al, 2016;Caputo et al, 2016).…”

Computer Estimation of Customer Similarity With Facebook Lookalikes: Advantages and Disadvantages of Hyper-Targeting

“…Moreover, BI systems should be able to merge multiple data sources into one integrated marketing analysis, since the separate evaluation of each data source may lead to differing results [29]. Research related to marketing business intelligence and analytics may be classified into five main directions that find application in many areas (Figure 1).…”