Pseudo-social network targeting from consumer transaction data

Abstract

This design science paper presents a method for targeting consumers based on a 'pseudo-social network' (PSN): consumers are linked if they transfer money to the same entities. A marketer can target those individuals that are strongly connected to key individuals. We present the PSN design and a large-scale empirical study using data from a major bank. For two different product offerings, consumers that are close to existing customers in the PSN have significantly higher take rates than the 'most likely' candidates identified by state-of-the-art socio-demographic (SD) predictive modeling. Interestingly, the PSN targeting only does better for the closest neighbors. However, the different models capture different information: combining the two does significantly better than either alone. The results demonstrate that social targeting can be applied broadly, to settings where the network among consumers is unlikely to be a true social network, but nonetheless captures inherent similarity.