Design and Analysis of Marketing Experiments on Social Networks

• Activity Number: 167
• Type: Topic Contributed
• Date/Time: Monday, August 5, 2013 : 10:30 AM to 12:20 PM
• Sponsor: Business and Economic Statistics Section
• Author(s): Michael Finegold*+
• Companies: Carnegie Mellon University
• Keywords: Experimental Design ; Social Networks ; Marketing ; Social Influence

Abstract

Leveraging influence in social networks could potentially lead to effective marketing strategies. Measuring influence and its impact on specific marketing campaigns can not be done with observational data alone, however, and thus some degree of experimentation is required. While randomized experiments on individuals of a network might seem a good way to measure influence, there are a number of issues stemming from network structure that need to be considered, including the likelihood of inclusion in the sample group and the implicit dependence between units due to latent homophily. Naive analysis of these experiments can lead to poor inference and eventually bad business decisions. We demonstrate how to correctly analyze data from a class of marketing experiments and discuss implications for the design of more effective experiments.