In the past call centers measured their success using a combination of general metrics and monitoredagent performance byrandomly selecting phone calls. Today, some call centers still measure their success using these simple methods because its easy to get general metrics. But only using general metrics to measure performance and quality in the call center is no longer enough, thankfully, this is the era of Big Data Analytics.
It is easy to collect a myriad of structured and unstructured data that can, in turn, be used to analyze all facets of a call centers performance. If you invest in modern Big Data Analytics technology, you can ensure that you are operating a smart and efficient call center. However, its important to select the right big data analytics solution for you call center, many solutions are only looking at part of the phone conversation, and it is important to select a solution, like RankMiner, that looks beyond the words to unlock hidden value from every call that passes through your center.
Using Big Data Analytics to Analyze Call Center Performance
The key to this is to analyze, all calls. You might find that 98% of your calls are good or normal, and your staff handled them in the best possible way. However you are discovering the 2% of calls were bad, and a different approach would produce positive results. This may sound very small, but think, if we translate the percentage into actual calls on a monthly basis, then to an annual basis, youll see that small percentage translates to thousands of bad calls, which have a much greater impact on your business.
There has been an explosion in different types of analytics, which a call center can use to measure its customer experience and business performance. Including, speech analytics, text analytics, and predictive analytics. All of these can be used to track and evaluate aspects of the call center experience, both from a client and from an employee point-of -view.
The sheer quantity of analytics solutions available may at first seem overwhelming, but each type has its use, depending on which area of operation you want to focus your attention. For instance, big data analytics, such as what RankMiner, provides extremely valuable insight for gauging the customer experience and agent performance. RankMiner is a unique big data analytics engine because the analysis looks beyond the words in a conversation and into the unstructured data unlocking hidden value and data. Whereas, Text analytics allows you to ensure agents adhered to their script, and desktop analytics ensure agents are not using their computer for unproductive activities.
The Changing Landscape of Analytics in the Call Center
A rapid rise in affordable technology has levelled the playing field. Initially, it was only the largest call centers with the deepest pockets who were able to introduce any advanced technical and analytical systems. However, now even the smaller centers can afford systems to record all of this data.
Of course, it is one thing to collect the call data, much of it unstructured. It is another thing to convert this big data into information. Within this big data lies valuable information for call center management to make profitable business decisions. The easy availability of this recorded call data, call centers can now using RankMiner for big data analytics tool will uncover valuable information hidden in their unstructured data. RankMiner goes deep into the unstructured call data, pulling our emotional and behavioral features that live within the voice, RankMiner translates that data into meaningful information regarding your agent and customer interaction. In turn, that data can also be used to predict future business outcomes.
With emotional intelligence and the customer experience becoming huge areas of interested to call based business, emotional analysis of conversations between agents and clients can provide valuable insight to the health of your call center. As stated in our previous post Emotional Intelligence: I LOVE YOU vs. I love you, the key to a phone call is often not what was said, but rather how it was said, i.e. the sentiment behind the words.
So how does your call center measure up? Have you kept up-to-date with the wide variety of analytical tools available to help you improve your performance, or are you still operating the same as you always have been? Have you kept up with technological innovations or has your business stood still, in a time warp? Just how smart is your call center?