Intelligent Decision Making and Planning for Call Center

Abstract

There are two types of call centers, Inbound and Outbound Call centers. In inbound call centers, focus is always on multiple factors like customer satisfaction, customer retention etc. In outbound call centers, only focus in on revenue generation whether it is by making sales, selling products, successful surveys etc. The main challenge in all outbound call centers is to increase the revenue without increasing the expenses. Different techniques have been used, by call center management, to make their customer service representatives (CSRs) perfect sellers. Similarly, different systems have been developed to increase the productivity of CSRs. Different dialer system solutions have been developed for this purpose. Automatic Call Distributor (ACD) and Interactive Voice Response (IVR) systems are examples of such systems. These systems utilize techniques like skill based routing, predictive dialing and profile based dialing to execute call center operation in a smart way. All such techniques are studied, implemented and critically reviewed for inbound call centers. For outbound call centers, we do not find the same level of research done and systems developed. Intelligent systems have been developed for inbound call centers. These systems operates on the basis of the history of their customers, maintained in their data repository. CSR's performance has also been analyzed and utilized in few systems like IBM's RAMP (Real Time Analytics Matching Platform). All such systems lack one thing and that is the Analysis of Dialing Data. Our idea is to use dialing data (in addition to CSR's performance), in an intelligent manner, after analyzing it statistically and by using different data mining techniques. Our aim is to increase the number of sales (revenue) and decrease the expenses, by smart utilization of data and work force.