A Viral Branching Model for Predicting the Spread of Electronic Word of Mouth

In a viral marketing campaign, an organization develops a marketing message and encourages customers to forward this message to their contacts. Despite its increasing popularity, there are no models yet that help marketers to predict how many customers a viral marketing campaign will reach and how marketers can influence this process through marketing activities. This paper develops such a model using the theory of branching processes. The proposed viral branching model allows customers to participate in a viral marketing campaign by (1) opening a seeding e-mail from the organization, (2) opening a viral e-mail from a friend, and (3) responding to other marketing activities such as banners and offline advertising. The model parameters are estimated using individual-level data that become available in large quantities in the early stages of viral marketing campaigns. The viral branching model is applied to an actual viral marketing campaign in which over 200,000 customers participated during a six-week period. The results show that the model quickly predicts the actual reach of the campaign. In addition, the model proves to be a valuable tool to evaluate alternative what-if scenarios.branching processes, forecasting, Markov processes, online marketing, viral marketing, word of mouth