Toward Decision Support for Telecom External Data Monetization: A Study of the Value of Network- and Personality-Based Metrics for Third-Party Businesses.

Abstract

Abstract The big data revolution has led to unprecedented opportunities for data sharing between industries. Telephone companies offer specific data involving rich information not only about the customer's behavior but also regarding his/her relationship with other customers and with third-party businesses. This article addresses the following research question: Might telecom data help to improve the prospective selection of third-party businesses? By answering this question, we expect to offer support for two specific investment decisions: on the one hand, the decision of the telecom operator to invest in the new market of the external data monetization for third-party business; on the other hand, the decision of third-party businesses to buy such customer profiling extracted from telecom call data records (CDRs). Using complex data treatments and more than one million models, the article addresses the challenges and opportunities in collecting and analyzing telecom data from two European telephone companies for improving the prospective selection processes of 36 third-party businesses. This improvement relies on new features extracted from the CDR, among which behavioral variables are considered as Personality Proxy variables and network-based variables. The results highlight that Personality Proxy variables are useful to support smaller niche businesses. For these businesses these variables are predominant and they can be directly implemented. In addition, the study shows that network analysis-based variables have the potential to be more beneficial to large companies since the value of network analysis continuously increases with the number of third-party business clients identified.