Analyst Perspectives

It never ceases to amaze me, when you ask people what their business objectives are and how they are measured, how often the two have little in common. This has been the case consistently in the research I have carried out over the last eight years into customer service and contact center performance. The main objective for contact centers is to improve customer satisfaction, but the key performance metric is average call-handling time. Despite hours of contemplation and discussions with colleagues, I still can’t see how one relates to the other.

Furthermore, most companies don’t pay enough attention to the impact metrics have on behavior; for example, sales people and their managers will bend all the rules they can to hit sales targets so everyone earns their commissions, even though this often produces downstream issues such as customers ringing up to complain about what they have been sold, or not being able to repay the loan they took out to make the purchase.

My research and experience talking to contact center managers show that contact centers focus primarily on efficiency metrics related to people and process. For instance, my recent benchmark research into contact center analytics shows that 65% of companies use four or more metrics, and one-fourth use six or more; these include queue lengths, average handling times, hold times, transfer rates, call volumes, silent time, first-call-resolution rates, agent quality scores, and others. Yet these are not what matter most to executives, whom the results show are more interested in customer satisfaction by customer and communication channel, product or service profitably and customer retention rates. Like the disconnect between average call-handling time and customer satisfaction, these two conflicting objectives indicate that companies need to review their key performance metrics to balance efficiency and effectiveness, and to ensure the metrics they use generate the right behavior.

Where should companies start? How about with the cliche that “the customer is king,” which is back in favor today? If you follow social media it seems not all companies have got the message. Debates continue as to whether customers or profits are more important, and how many complaints customers have to make before companies change policies and processes. You can read more about bad customer experiences online than you can about good ones.

Advocates of “the customer is king” argue that you should adopt customer-focused metrics such as net promoter scores, customer effort scores and customer value. I have nothing against any of these, but in isolation they are not particularly useful; it might be good to know customers say they might recommend your company, but do they actually do it? And if they do, can you measure the impact? Metrics become useful only if they produce change.

This is why I favor first-contact-resolution rate as a balance between efficiency and effectiveness. It saves money if issues are resolved the first time, and customers are more satisfied if issues are resolved promptly to their benefit. But first-contact-resolution rate can be even more useful when linked with other metrics and actions. Applied to agents, for example, it lets companies identify best practices and adjust process and training so more agents can resolve more issue the first time. Linked to customers, it can tell who are the difficult customers and how they can be handled in the future. It can help identify why issues occur and what can be done to generate fewer calls. It can influence behavior, because agents will strive harder to resolve more calls at the first attempt. It can influence call-routing rules, so that more calls are routed to agents who resolve more issues the first time. Companies that think outside the box and across processes and lines of business can uncover even more benefits.

The point is that companies should review their key performance metrics to determine whether they help or hinder progress toward achieving business goals and whether they drive the right behavior. As they do this, companies need to understand the types of metrics needed from people and process that contribute to performance metrics. You need to look at how you produce their metrics. Most business-related metrics cannot be derived from a single source of data, and the “simple” task of cutting and pasting data into spreadsheets is time-consuming and prone to error.

Data analysis is too complex a process to attempt with a spreadsheet when you’re trying to integrate data from multiple sources. But there are now several products that can automate the analysis of data drawn from multiple business applications, speech recording, text (including social media) and desktop usage and subject it to operational, customer, agent, process, social media, cross-channel, predictive and root-cause analytics and produce actionable information.

Whether the customer is king or not, I recommend companies take at look at these products, because they support the production of more effectiveness-related metrics and can help improve operational and business performance.

Have you reviewed your contact center metrics lately? Are you thinking of adopting any of the new analytics products now available? If so, tell us more and collaborate with me.

Regards

Richard Snow – VP & Research Director