What Your Contact Center Metrics Aren't Telling You

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Customer Service
Customer Service
Companies often get into the rut of overanalyzing efficiency metrics. A more insightful approach is to analyze performance-oriented measures that reveal opportunities for customer retention and growth.

Some may call Headsets.com's contact center strategy nontraditional; others may view it as cutting edge. The company's CEO and President Mike Faith, believes it's just common sense.

That's because the company doesn't measure call time-one of the most commonly used contact center metrics. "I believe that what you measure is what you get tempted to change, and we don't ever want our team rushing a customer. It's not about call length; it's about customer satisfaction," Faith says.

One of Headset.com's often-used metrics is an "excellence ratio."This is determined after customers complete a survey and they rate the agent from "poor" to "excellent." For every "non-excellent," the agent receives a negative mark, even if the rating was "good." The number of "non-excellent" ratings is then counted against the number of "excellents" ratings to determine the ratio. The ratio of "excellent" to "non-excellent" should be above 10. If not, the agent will receive additional training. "Do we have high standards? You betcha.Maybe that's why we're growing and why we're profitable in what many consider to be a competitive industry," Faith says.

Given Headsets.com's excellence ratio, the question is, do traditional metrics like average handle time and cost-per-call still hold up?

Jeanne Bliss, owner of Customer Bliss, says no. "What we're finding is that companies are still stuck in the rut of production-only metrics," she says. "I think that you need to get rid of the problems customers are having, but there are customers who need help and want to talk to a human being and companies are trying to get rid of that [service]. That's why they become focused on the operational metrics."

Bliss adds that companies often get into the rut of analyzing random metrics that pin the front line into a box. Organizations would be better served, she explains, by investing in training and development, as well as in the tools that enable them to listen to customer feedback. "There needs to be a balance between operational metrics and the ability to manage and observe behavior," she says. "We're seeing an understanding of the importance of being reliable in the first place so that you don't drive your customers to call your helpdesk to try to get an answer."

Mariano Tan, senior vice president of professional services for Teletech, agrees with Bliss that companies must analyze behavior, but attributes the shortage of this practice to an overall data conundrum . "It's a data-sourcing problem. There's an old joke where someone lost their car keys by their car, but is looking for them 10 feet away. Someone asks, 'Why are you looking over here?' And he responds, 'Because the light is better.' [In contact centers], we tend to look were the light is best rather than where the data is. It's inwardly focused," Tan says.

Tan adds that industry veterans also worry about efficiency metrics like average speed of answer, abandon rate, and average handle time. "Those thingshave to be kept at a minimum," he says.

He says that speech analytics and sentiment analysis-a method of examining customer's tone through text and voice analytics-helps to solve that issue. The practice allows companies to record and analyze calls to uncover important events that transpired during the call. Companies can then analyze and determine behaviors like the reason for the call, how the agent responded, and why the agent responded the way he did. "If you understand what transpired during the callyou might be able to get some color from the call and therefore get a better analysis," he says. "In our world, it only matters if you can do something about it."

Bob Kelly, senior vice president of sales and marketing with HyperQuality, adds that contact center metrics such as average handle time and average speed of answer tell you a little about your customer service, but they don't expose the entire customer experience. He suggests aligning customer satisfaction with quality assurance scores along with deploying speech analytics. "Listening inside the interactions for insights into agent performance and business process impacts is vital to understanding how you are doing with your customers," he says.

Jeff Woodland, senior product marketing manager at Alcatel-Lucent Genesys Solutions, says he's seeing a drive toward more customer-focused metrics like first-call resolution, but there are still many obstacles that companies have to overcome first, like a lack of understanding of data across multiple channels and setting up metrics around specialty call queues like Spanish-speaking queues. This practice creates siloed data, as well as the inability to respond to customer issues in real time. "A lot of it is due to technology investments that were set up in the 70s and 80s. If you organize [contact centers] by queues, you won't have the same depth of understanding. As you manage your resources it blurs the quality of agents," Woodland says.

Despite these hurdles, Woodland sees a trend among progressive firms of incorporating non-traditional metrics and linking the resulting analysis back to agent teams, individual agents, and corporate goals. "The good thing is [this practice] allows contact centers to move away from average handle time and service levels. It's much better toask, 'Who are my profitable customers and how do I manage them?' You want to safeguard your best customers when preventing customer churn," Woodland says.

Woodland may see an increasing interest in adopting new metrics, but Kate Leggett, senior analyst, customer service, at Forrester Research, is witnessing more of the status quo when it comes to actual practice in many contact centers. "I see a lot of talk about new metrics, but when you walk into a call center, it's all about call rates, number of escalations, escalations in the queue, loading, productivity metrics, and attendance metrics," Leggett says. "It's very much a reactive, bottoms-up driven culture of measuring and slicing and dicing all the measurements from handle time to close time to productivity."

Leggett explains that correlating operational metrics with customer service levels is difficult to achieve in most industries because it requires entire organizations to be responsible for moving the Net Promoter Score (NPS) or similar measures and involves executive alignment and buy-in to the high-level business performance indicators that help to tie all activities to customer-focused KPIs.

Forward-thinking companies, Leggett explains, are in fact trying to align business outcomes with NPS, as well as deploying sentiment analysis. "In a down economy, companies have to move the needle [on NPS]," she says. "Focusing on the customer experience and focusing on customer satisfaction is of paramount importance in keeping your customer base loyal."

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