Contact Center Analytics:
Driving Costs Down and Revenue Up
Bruce Ratner, Ph.D.
An essential component of a contact strategy is determining which key-drivers affect higher revenue while lowering costs. In other words, how can a manager optimize the two-dimensional cost-revenue factor of contact performance? Identifying the best predictors of optimal contact performance requires the intelligence of the next-generation of a “smart” analytic system. The purpose of this article is to introduce the latest smart (based on a genetic paradigm) contact performance optimization system – the Genetic Cost-Revenue (GCR) Model. The GCR Model simultaneously addresses the two important objectives facing database contact manager: minimizing cost and maximizing revenue. The GCR Model, which is based on the data-driven genetic programming inspired by Darwin’s Principle of Survival of the Fittest, balances the two objectives yielding a single score that identifies the best predictors of successful contacts – lower cost to contact, and higher revenue per contact. The GCR Model is theoretically optimal, and easy to build and validate. I discuss two real CRM case studies to highlight the features of the new model.
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