Pseudo-Social Network Targeting from Consumer Transaction Data

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.