Lead Data Scientist in Virgin Media O2. Petros is an ex astrophysicist who has been modelling solar eruptions as a postdoctoral researcher and Lectures at the University of St Andrews. Following his academic posts, he has applied machine learning in financial documents, genetic data and telecommunications. Petros is passionate about using data science and machine learning to model data, derive insights and productionise solutions.
Large scale call centres are the frontline of customer experience across many industries. Optimizing their operations is crucial for achieving better customer service. We model agent customer pairing as a “talent” allocation problem. In this talk, we discuss how we used uplift modelling to provide real time agent-customer pairings that drive a positive lift in overall interaction score (which can come from any arbitrary scoring function). We discuss the challenges of developing and deploying such models to make real-time interventions in call centres. Similar approaches can be used to drive uplift of any important business KPI with respect to an allocation decision.