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Making Sense of Big Data in the Contact Center

by James Mannion, Director of Marketing and Channel Development, Inova Solutions - March 25, 2013

Making Sense of Big Data in the Contact Center  
 By James Mannion, Director of Marketing and Channel Development, Inova Solutions

Jay Minnucci writes in his white paper Call Center Performance Metrics: Shaping Tomorrow’s Reporting Strategy, “the entire purpose of metrics [is] defining opportunities to make the greatest positive impact.” In today’s contact centers, it is no small feat to identify and manage the increasing array of data available, let alone to use that data to define opportunities that will have a positive impact on the key measures of business success! With the focus squarely on the customer experience, contact center managers are going beyond the typical statistics from ACDs and constructing, integrating, and analyzing custom metrics specific to their environments and service level goals. And this is just the start. Organizations are leveraging other supporting data metrics to provide more intelligence and measurement from platforms such as callback, outbound dialing, and workforce management applications as well as cross-channel touches from chat and other social media streams. Add other enterprise ‘mash-up’ data from various operational data sources to the mix and it can make your head spin. One thing for sure, Big Data, with its opportunities and challenges, is happening in the contact center.

The standard contact center metrics remain the backbone for center success. Certainly understanding the tried-and-true metrics such as calls waiting, agents available, abandoned calls, and expected wait time will always be beneficial in understanding both the real-time and historical picture of what’s happening in your center. However, organizations are both redefining standard metrics to better match their goals and adding new enterprise data sources to bring more intelligence into the center. To more easily think about these data sources, Inova likes to categorize them in six primary buckets:

  • Custom Metrics – This category is greatly influenced by the other data categories since areas like outbound calling and social media responses bring their own set of numbers to the equation. But even with standard data available from ACDs you can create custom metrics using the Data Analyzer function within Inova LightLink software to better measure your specific performance and objectives. The Data Analyzer tool can easily calculate averages, max and median times, etc., so that specific services levels and metrics can be created. Abandoned call percentage and custom services levels across all separate and disparate platforms are examples that are possible. Custom equations such as removing calls that are dropped within a few seconds before determining average handle time are also easy to create. Having this ability allows managers to look at all of the types of information available and then to select the specific data views that will best support their needs as well as the needs of other line of business owners and organizations.
  • Associated contact center data sources – Many contact center managers now integrate and display real-time data that is either directly associated with their contact center (Ex: outbound calling or callback applications) or directly affected by data coming from the contact center (Ex: workforce management platforms). Using the latter example, managers can combine schedules and skill queues for quick analysis of workforce alignment; or integrate messages to automatically announce additional shift availability when the WFM system detects a preset threshold for understaffed periods. In blended inbound and outbound environments managers and agents can get quick status views about proactive outbound or loyalty campaigns.
  • Result-oriented data – Contact centers strive to be viewed not as cost centers, but as profit centers responding quickly and intelligently to customer needs - cross-selling and up-selling products and services, and keeping customers satisfied. As such, managers want to understand metrics in terms of the real costs to run their centers and how performance affects overall profitability. They want to know more than just how many calls the center took and how quickly, but how this number applies to the top and bottom lines and overall customer satisfaction. To do this, some companies are displaying real-time snapshots of sales measures vs. objectives as a way to motivate their agents, correlate their efforts to the success of the business, and identify real opportunities for improvement. They are also measuring more customer experience related metrics such as agent generated holds, task completion rates and abandoned rates for example.
  • Behind-the-calls data – Most contact center managers would like to know what, exactly, is behind their call types and volumes; they want to be prepared for situations like sudden call spikes or an onslaught of similar topic calls. To do this some have begun to incorporate operational data, sometimes referred to as enterprise ‘mash-up’ data, into real-time reporting views. Incorporating this operational data on LCD screens and desktop applications provides a first-hand view, allowing managers and agents to prepare for potential changes in their environments. The status of a current product promotion, technical issues with an online catalog, or an alert at a utilities company center to drops in power or water pressure would all be example indicators for an increase in call volumes related to specific issues, allowing for more proactive management of the center.
  • Cross-channel data – With all of the new ways that companies and customers are interacting, you likely have access to a growing number of data platforms: emails and chats with customers as well as social networking interactions or statuses. Harnessing this cross-channel data is critical for managing the customer experience.
  • External / Environmental data – Your Inova real-time reporting solution can integrate data from the outside world as well such as weather, traffic, and news. For some contact centers, this information can sometimes be a lifesaver: consider again the utilities company incorporating live severe-weather feeds to make real-time staffing decisions.

In the end it’s up to leaders of each organization to determine what data should be accessible and viewable in real-time. For so many obvious reasons, real-time data is critical for understanding what is happening right now in the center; it allows leaders to make decisions that can have immediate impact toward achieving stated goals and milestones. Integrating custom metrics and data from peripheral and core operating sources is key for producing a 360-degree view of how your contact center is delivering value to your business and, more importantly, to your customers. As Minnucci wrote, “the contact center landscape is changing and the manner in which we keep score — our metrics — will need to change to keep pace with all this activity.”

Look for more detail in future newsletters on the value and the ability of LightLink to present powerful business views and insights from these varied data sources.







 

 
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