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Abstract
While social media spending continues to increase, measuring its impact remains a challenge for most organisations, with surprisingly few able to access the quantitative impact on business outcomes. With an understanding of these measurement issues, this paper examines an assessment of the social media performance model (SMPM) — an analysis procedure that enables improved return on investment using data science. In the context of a business-to-consumer nonprofit organisation, executed across social media, sales promotions, e-mail campaigns and Facebook news feed ads, the use of the model to provide predictive insights will be explored. As new insights are derived from the findings, the SMPM enables data-driven strategy that can be used to influence business outcomes achieved not only through organic social media but also other forms of marketing communication efforts.
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Author's Biography
Gary B. Wilcox is the John A. Beck Centennial Professor in Communication at the Stan Richards School of Advertising & Public Relations. He is also an associated faculty in the Department of Statistics & Data Sciences and the Center for Health Communication at UT Austin. Dr Wilcox holds a PhD from Michigan State University and two degrees from UT Austin. His recent research interests include unstructured data analysis, social media analytic models and advertising’s effects on alcohol products and brands.