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Establishing Customer Experience Metrics in Contact Centres is a Critical Factor for Success

10-24-2014 06:49 PM CET | IT, New Media & Software

Press release from: Interactive Intelligence

Shaheen Haque, Territory Manager, Middle East & Turkey at Interactive Intelligence

Shaheen Haque, Territory Manager, Middle East & Turkey at Interactive Intelligence

Expert Article Author: Shaheen Haque, Territory Manager, Middle East & Turkey at Interactive Intelligence

If you were to ask a vice president of Customer Care the metric they think is most important (to their careers), the bet is they would respond with “Customer Satisfaction Score.” And if you were to ask this same VP how deeply they care about making sure customers enjoy their interaction with employees and the company, they would say “I care very deeply.” As intuitive as it is, a good customer experience will lead to more business, or better “word-of-mouth marketing.” Certainly, we also know that in the era of social media, a single negative customer interaction can lead to a public relations nightmare.

All of the other contact centre metrics we use to measure “service” are proxies for this most-important-of-all contact centre scores. Service Level and Average Speed of Answer (ASA) are maintained because we believe that long wait times lead to customer dissatisfaction. Abandons are a great proxy for customer satisfaction, because a customer who hangs up is almost always, by definition, not happy with their wait time. Agent quality scores are maintained because we would like to maintain a consistently excellent interaction with our customers, and the agent quality score is the mechanism we use to ensure consistent excellence.

Different flavors of experience metrics have similarities
There are as many “best” customer experience metrics as there are customer experience consultants. Different types of metrics can include customer satisfaction, First Call Resolution (FCR), Net Promoter Score (NPS), agent quality score, and others. Internally, companies will focus on experience scores that can vary from other business units that focus on customer scoring. But even if the scores are called the same thing, they will almost always be calculated using different algorithms. This, of course, makes perfect sense as different customers — calling the same company — are contacting our contact centres for different purposes. The experience should therefore be attuned to the purpose of the contact.

This doesn’t mean that different ways of measuring experience doesn’t have similarities, however. When you think about these metrics, they must all have certain properties — and our understanding of these experience metrics shows this to be the case. For instance, these metrics, like most other contact centre metrics, have seasonality. Our customers call us for different purposes at different times of the year, and their patience and expectations are likely to change, too. An agent, for example, may be more or less motivated seasonally and will score differently week over week.

These experience metrics are also differentiated by contact type, location, or staff group. This is intuitive; we all know that differently trained groups (especially in a multi-skilled workgroup) will behave differently. For instance, a sales-oriented group and a service-oriented group will score differently, even if they are taking the same type of call. Different geographical centres may score differently because they have different management. Experience scores exhibit trends, and as a workgroup improves or declines, or as our company performance (even outside of the contact centre) changes, it is understood that focused training can positively affect the trajectory of an experience score; that is the purpose of training.

How can planners use customer experience metrics?
Customer experience scores exhibit seasonality, trends, and differences across contact centres. What does this mean to us planning analysts? Data streams that exhibit this sort of behavior are similar to many of the other time-series data we typically work with, like contact volumes, handle times, attrition, and shrinkage. We analysts cut our teeth developing forecasts of items that look just like experience data. This means that we should be able to forecast experience data streams.

This adds yet another dimension of planning. If we forecast customer experience scores by centre and staff group, we can use these new forecasts in a host of ways. First, we can draw out the week-over-week customer experience trends, simply to view where we are heading. By applying a forecasting technique (like Holt-Winters) to a customer experience metric, we can make explicit our expectations of where “our math” expects customer experience outcomes to be weeks and months into the future.

These forecasts act to set executive-level expectations. If the trends are favorable, then good for us. We can watch to see that actual expectations are met. If they are trending in the wrong direction, it will show that our given path needs to be adjusted. In effect, this time-series experience data will act as our early warning device. Similarly, forecasts, and the resulting expectations, serve to soothe executives, as well. If we have a traditional seasonal dip in customer experience scores, then we shouldn’t be too alarmed when it comes to pass this year as well. The data and the forecast may simply be describing a seasonal change in our customer’s calling patterns or expectations. But also, if we expect a seasonal dip in experience scores, we may be able to head it off this year by developing an agent training program in time.

Another great use of a customer experience forecast is as a point of comparison. The best companies view all of their forecasts (volumes, handle times, attrition, shrink, etc.) as a baseline for variance analyses. As weekly performance data is tallied, it can be compared to the forecast. Any differences between forecasted and actual performance implies that something has changed. If we are forecasting and tracking customer experience scores, any deviation should be noted, explained, and potentially acted upon. In order for this sort of analyses to have any meaning, it must be compared to seasonally adjusted customer experience forecasts.

Use customer service forecasts to plan better
The final, most interesting use of forecasts of customer experience metrics is as an input into the staff planning process. We have heard from several customers that customer experience scores are used to help allocate their calls amongst their competing call centre vendors. Those companies are actively attempting to improve their customer satisfaction by sending more contacts to those vendors who score best.

Who can blame them? But there is also no reason why a company couldn’t increase staff levels in their centres that also score well. If improving customer satisfaction is important to your company — and your execs all think it is — then it makes perfect sense to include the customer experience forecasts in your staff planning process and decision-making. It’s simple. If you’re using a hiring and extra time optimizer for long-term planning, you can instruct it to hire in such a fashion as to maximize customer experience scores. If you are developing hiring plans by hand, it should be pretty straightforward to manually move new classes toward those centres with the better scores.

By developing customer experience time-series data, using this data to forecast expected performance, and applying this forecast to your variance analyses and staff planning, you can greatly improve your customer’s experience.

Organizations are investing millions of dollars to improve the customer experience in the contact centre. They’re offering special sales and servicing programs, providing multi-lingual agents, investing in new technologies, and presenting a wider diversity of products and solutions. At the same time, these servicing strategies are being tied to an unprecedented number of customer contact points, including inbound phone, outbound, email, web chat, and social media. Consistent customer service delivery therefore has become a challenge, as is planning for it. New technology platforms are available today that help with contact centre agent capacity planning and analysis and are designed to optimize resources and performance throughout any contact centre operation. In making strategic planning easier, faster, and more accurate, these platforms enables centres to get the right number of agents in the right place at the right time to deliver exceptional service.


About the author
Shaheen Haque is the Territory Manager, Middle East & Turkey at Interactive Intelligence.
Originally from Bangladesh, he spent his early years being educated in London, UK and subsequently has worked in the UK and Europe for predominantly US software companies since graduating from University in 1993. The list of organizations includes SPSS (now IBM), LBS, Oracle, Seagate Software, AppSmart Software. It was his job with Micromuse (now IBM) that first brought him to Dubai. After his stint in Micromuse, he worked with IBM Middle East for a while in the Tivoli division. Then in 2007 he joined Interactive Intelligence when the company opened its first Middle East office in Dubai Internet City.

About Interactive Intelligence
Interactive Intelligence Group Inc. (Nasdaq: ININ) is a global provider of software and services designed to improve the customer experience. The company’s 6,000-plus customers worldwide have benefitted from its cloud and on-premises solutions for contact center, unified communications, and business process automation. Interactive Intelligence is among Software Magazine’s 2013 Top 500 Global Software and Service Providers, and has received a Frost & Sullivan Company of the Year Award for the last five consecutive years. In addition, Glassdoor honored Interactive Intelligence with its 2014 Employees’ Choice Award as one of the Best Places to Work in the U.S., and Mashable ranked Interactive Intelligence second on its 2014 list of the Seven Best Tech Companies to Work For. The company was founded in 1994 and employs more than 1,900 people worldwide. Interactive Intelligence is headquartered in Indianapolis, Indiana and has offices throughout North America, Latin America, Europe, Middle East, Africa and Asia Pacific. It can be reached at +1 317.872.3000 or Visit Interactive Intelligence on the Web at; on Twitter at; on Facebook at; or on LinkedIn at

Interactive Intelligence is the owner of the marks INTERACTIVE INTELLIGENCE, its associated LOGO and numerous other marks. All other trademarks mentioned in this document are the property of their respective owners.

Colin Saldanha
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