A social network analysis of customer-level revenue distribution

Social network analysis has been a topic of regular interest in the marketing discipline. Previous studies have largely focused on similarities in product/brand choice decisions within the same social network, often in the context of product innovation adoption. Not much is known, however, about the importance of social network effects once customers have been acquired. Using the customer base of a telecommunications company, our study analyzes network autocorrelation in the distribution of customer-level revenue within a social network. Our results indicate a significant and substantial degree of positive network autocorrelation in customer-level revenue. High (low) revenue customers therefore tend to be primarily related to other high (low) revenue clients. Furthermore, we show that approximating communicative proximity by spatial proximity leads to a substantial underestimation of these effects.