Impact of Big Data Analytics in Marketing on Firm Bottom Line: An Abstract

Big Data is defined as high-volume, high-velocity, high-variety (and more recently, high-veracity) information assets that demand cost-effective, innovative forms of capturing, storing, distributing, managing and analyzing that information (Gartner IT Glossary, n.d.; TechAmerica Foundation’s Federal Big Data Commission 2012). Big Data Analytics (BDA) refers therefore to the “application of statistical processing, and analytics techniques to big data for advancing business” (Grover et al. 2018, p. 360). In marketing, despite much interest to the concept of Big Data and analytics, there is a lack of empirical evidence of the benefits associated with BDA. More surprisingly, little attention has been paid to the empirical investigation of the impact of BDA for market purposes on financial performance, despite the critical importance of such a relationship to reach strategic objectives.

Using the resource-based theory (RBT) framework (Barney 1991; Lee and Grewal 2014), this study fills that void in the literature by adopting an inter-disciplinary perspective to assess the impacts of BDA for marketing purposes on firm financial performance. More specifically, the research involves a large-scale study of organizations that are part of the S&P 500 (Standard & Poors 500) in the USA, and of the S&P/TSX 60 (Standard & Poors/Toronto Stock Exchange 60), in Canada, to identify to what extent the implementation of BDA, in the marketing function, forms a competitive advantage that materializes through financial performance.

Overall, the findings suggest that BDA has a significant and extensive impact on corporate performance. Second, while descriptive analytics contribute positively to profit-related performance indicators (i.e., share price), prescriptive analysis load more significantly on revenue and profit-related performance indicators. Furthermore, the contribution of BDA to the revenue performance of the manufacturing industry is greater than in other industries.

This study contributes uniquely to past research and professional practice by providing an exploratory research on the impact of particular big data analytics (i.e., descriptive, predictive, and prescriptive) on the financial performance of 560 large capitalization companies (i.e., S&P500 and S&P/TSX60 stock indices).