Client's challenge
An application software vendor who developed software for a specific industry had a serious growth issue. The company was losing out to competitors because of service support failures. While sales had grown consistently over a several years, customer complaints about telephone support had grown faster. Rapid growth was negatively impacting the company's ability to provide adequate levels of customer service.
Management had previously agreed to fund development of a customer support dispatching system to help diagnose and route customer support calls, and ultimately improve customer service. However, the artificial intelligence (AI) technology needed for the system to function was still unavailable after a full year's development and an investment of approximately $1 million.
PricewaterhouseCoopers Advisory solution
We began by evaluating the efficacy of the AI technology, first reviewing the status of the system development effort and then working with client support technicians to understand the nature and volume of customer support calls. The PricewaterhouseCoopers Advisory team determined that the client's AI technology was not only far behind schedule and over budget, but also that the system failed to address fundamental business issues driving customer support call difficulties.
Our analysis compared support fees paid with calls made to the support hotline, revealing that customers who paid very little in support fees generated well over half of all calls. This tied up support capacity and prevented higher-paying customers from accessing support technicians. In addition, an analysis by call type showed that many calls resulted from customers who had upgraded to new versions of the software. This software had not been adequately tested, nor had users received adequate training, compounding the number of calls technicians had to address.
Finally, the analysis demonstrated that customers were using multiple versions of the software, which made it harder for the technicians to accurately diagnose and fix problems. Once the real issues were understood, it became apparent that a far simpler system that more effectively addressed core business issues could be put in place. Development of the AI system was immediately halted.
Impact on client's business
Based on these findings, the company made several important changes to improve its customer relationships. Customers were required to periodically update software to minimize the number of versions used in the field. Product testing was bolstered and customer training expanded—thereby growing a source of revenue.
The company initiated a tracking system for customer calls so that high users of the support desk could be better monitored and managed. All of these measures helped improve response time and reduce the overall volume of calls. A high quality of service support was restored, enabling the company to better maximize its growth potential.
