The final piece of this blog series I would like to take some time to discuss the customer. There are direct and indirect ways to capture the voice of the customer to help drive better experiences and better prepare your workforce.
The voice of the customer should be the loudest voice when it comes to measuring quality, because customers have the purchasing power that makes your enterprise successful. Customers are giving you feedback during every interaction, but how do you extract that feedback from a wealth of unstructured data? Customer survey software is often used to understand what the customer is really thinking, and provides a source of structured feedback that is critical to changing business practices and process.
The other source for unstructured feedback is your wealth of voice and screen recordings. Speech and text analytics, although not perfect, are very effective tools for collecting unfiltered customer feedback, i.e., feedback without structured survey questions.
We talked about monitoring at least one call per agent per week as a minimum standard, but random monitoring and surveys typically account for less than 1% of all calls. You will undoubtedly miss most of the good quality calls and most of the poor quality calls for any given agent. That’s where analytics becomes important. Speech and text analytics software give you the capability to search through 100% of your customer interactions and uncover agent best practices as well as issues with individual agents, teams, or operational issues that may span the entire contact center. With the power of Big Data and analytics at your fingertips you can search for positive outcomes such as high customer satisfaction, high quality, high efficiency, or completion of sale, and from these interactions determine what agent technique was used to make the interaction a success. Likewise, you can search for negative outcomes such as low customer satisfaction, disconnects, high average hold time (AHT), holds or transfers, silence or dead air, repeat calls or anger to determine what agent actions created noticeable problems. Analytics can categorize the most important calls for evaluation providing quantifiable data to drive your quality focus.