How and when do big data investments pay off? The role of marketing affordances and service innovation

Abstract

Big data technologies and analytics enable new digital services and are often associated with superior performance. However, firms investing in big data often fail to attain those advantages. To answer the questions of how and when big data pay off, marketing scholars need new theoretical approaches and empirical tools that account for the digitized world. Building on affordance theory, the authors develop a novel, conceptually rigorous, and practice-oriented framework of the impact of big data investments on service innovation and performance. Affordances represent action possibilities, namely what individuals or organizations with certain goals and capabilities can do with a technology. The authors conceptualize and operationalize three important big data marketing affordances: customer behavior pattern spotting, real-time market responsiveness, and data-driven market ambidexterity. The empirical analysis establishes construct validity and offers a preliminary nomological test of direct, indirect, and conditional effects of big data marketing affordances on perceived big data performance. Keywords Big data technologies and analytics. Affordance theory. Marketing affordances. Service innovation. Big data performance. Industry digitalization "There is nothing so practical as a good theory (Kurt Lewin)." More and better customer data have long been marketers' holy grail when such information was scarce. Firms are now investing significant resources into big data technologies and analytics (BDTA), following the assumption that they may drive superior performance (Lambrecht and Tucker 2015), enable business transformation (Davenport and Bean 2019), and facilitate disruptive business model innovations (Sorescu 2017). This is particularly evident in the service industry, where BDTA are changing the nature of the customer-firm connection, thereby disrupting existing value propositions (Huang and Rust 2017). Yet, the accelerating rate of big data investments is not always matched by an increased quality and effectiveness of marketing decisions (Shah et al. 2012), and senior managers report mixed perceptions of the extent to which big data contribute to a firm's performance (Bean and Davenport 2019). 1 Hence, developing a better understanding 1 According to a recent survey of senior executives in Fortune 1000 and industry-leading US firms, 91.6% of companies are accelerating the pace of big data investments. However, only 62.2% report measurable results from these investments; 59.5% declare to drive innovation with data, 47.6% claim to be competing on data and analytics, and only 31% perceive themselves as a data-driven organization (Davenport and Bean 2019).

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