Fourth International Conference on Communication & Media Studies

Abstract

The Internet and social media have resulted in an increasing shift from traditional marketing – TV, radio, print – to viral marketing (Jurvetson and Draper 1997) - a phenomenon likened to the infection cycle witnessed in major epidemics (Kaplan and Haenlein 2011). One challenge facing marketers is how to use data from past scenarios to predict expectations of marketing campaigns and thus know how much money they will need to spend in order to attain the necessary effectiveness. A number of virality prediction models exist in the literature; however, many of them fail to use the standard industry measure of viral growth – the viral coefficient, and to use detailed formulas that include factors relevant to the viral diffusion process. We develop a model based on Jarvis (2017) to address this gap. In addition, we outline steps for researchers and practitioners detailing model development challenges and solution steps.