Big Data Analytics in Undergraduate Advertising Curricula: A Global Survey of Higher Education Institutions

Big Data Analytics in Undergraduate Advertising Curricula: A Global Survey of Higher Education Institutions

Kenneth C. C. Yang (Department of Communication, The University of Texas at El Paso, El Paso, USA) and Yowei Kang (Department of Oceanic Cultural Creative Design Industries, National Taiwan Ocean University, Keelung, Taiwan)
Copyright: © 2018 |Pages: 14
DOI: 10.4018/IJTEM.2018010103

Abstract

The rapid ascent of data-driven advertising practices has allowed advertising professionals to develop highly-targeted and personalized advertising campaigns. The success of data-driven advertising relies on if future professionals are proficient with basics of Big Data analytics. However, past research of undergraduate advertising curricula around the world has shown that higher education institutions tend to fall behind in offering the most up-to-dated training for advertising students. Findings have shown that undergraduate advertising programs have slowly taken advantage of the potential of the data analytics tools and techniques. This trend is observed among higher education institutions around the world. Practical, research, and pedagogical implications are discussed.
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Introduction

Agency’s abilities to manage audience’s data effectively to identify and target the key market segment is critical to the success of advertising campaigns (Aitken, 2017). However, many advertising professionals are often found to be lacking in maximizing the capability of audience data (cited in Aitken, 2017). According to a 2017 survey by AdAge and Neustar, only 23% of its respondents indicate that they are presently making the best use of their data management platform (cited in Aitken, 2017). In a recent 2018 CES panel, organized by Deloitte Consulting, to discuss the future of advertising, several panelists have mentioned the importance of delivering relevant advertising to consumers after taking advantage of massive amount of data from consumers’ connected devices (Deloitte Development LLC, 2018). New connected technologies (through Internet-of-Things, Over-the-Top, or Artificial Intelligence) have enabled a large amount of consumer data collection (Andrew & Brynjolfsson, 2012; Deloitte Development LLC, 2018). Organizations now are able to increase their performance by using their information flow to its full capacity (Andrew & Brynjolfsson, 2012). As a result, clients would expect more accountability of advertising agencies to deliver more effective advertising campaigns in the future.

The rapid ascent of data-driven advertising has also led some industry pundits to claim it will be “the next frontier” (Rothental, 2017). Data is “[a]dvertising’s North Star” (Salesforce, 2018). The advertising industry has displayed “a big crush” on Big Data (Marshall, 2013) that has produced a dedicated topic session (“Big Data”) in AdWeek.com as well as several professional conferences on related topics such as Big Data, data-driven marketing and advertising, or data analytics (Kaye, 2014; Yang & Kang, 2016). Ranging from brand preference to previous contact and online transaction information, CRM data is employed by 94% of the advertisers to track campaign effectiveness (Columbus, 2018). According to Digital Advertising 2020 Report by Salesforce Research (2018), 47% of advertisers in North America plan to increase their use of 3rd party data to help them create personalized advertising messages to better target their market segments. The same survey of 900 global advertising leaders also reports that 91% of them have adopted or plan to adopt data management platforms (Salesforce Research, 2018).

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