Estimating the effect of word of mouth on churn and cross-buying in the mobile phone market with Markov logic networks

Abstract: Much has been written about word of mouth and customer behavior. Telephone call detail records provide a novel way to understand the strength of the relationship between individuals. In this paper, we predict using call detail records the impact that the behavior of one customer has on another customer’s decisions. We study this in the context of churn (a decision to leave a communication service provider) and cross-buying decisions based on an anonymized data set from a telecommunications provider. Call detail records are represented as a weighted graph and a novel statistical learning technique, Markov Logic Networks, is used in conjunction with logit models based on lagged neighborhood variables to develop the predictive model. In addition, we propose an approach to propositionalization tailored to predictive modeling with social network data. The results show that information on the churn of network neighbors has a significant positive impact on the predictive accuracy ...

• Type: Journal
• Year: 2011
• Where: DSS
• Authors: Torsten Dierkes, Martin Bichler, Ramayya Krishnan
• Keywords: Call Detail Records, Communication Service Provider, DSS 2011, Emerging Technology, Network Neighbors