A US-based leading energy client with more than 1,000 agents across different call centers was handling around 12 million calls a year at a cost of $200 million. It was facing a number of challenges, including a high repeat-call rate of more than 20 percent, and thanks to fragmented data across ten-plus databases and limited advanced-analytics tools, little understanding of why repeat-call rates were so high.
By implementing a data-driven approach and advanced-analytical model to identify the root causes of repeat calls, as well as building client capabilities allowing them to own and refine the model, we were able to capture a saving of approximately $20 million—a reduced call volume of between 5 and 10 percent.
In addition, we trained a client data scientist, who was able to maintain the momentum of the project, as well as implement 30-plus initiatives around call containment, routing, and customer education.