What criteria do you use to measure agent performance? Is it based solely on the number of calls they are able to handle within a given hour or are there other elements that play a part? Performance standards can vary by company and by industry, making it a challenge to accurately report success and overall customer satisfaction.
Customer expectations can also vary by industry, putting more pressure on contact center leaders to better understand these expectations so as it capture the desired competitive advantage. When applying findings across the agent base, it can be difficult to hit the numbers you want. Agent skills, personalities and experience all vary, which places a priority on individual assessments so as to better align your strategies.
Setting aside individualized attention, training and assessments isn’t an easy thing to do, however, as it takes time and resources. One of the best ways to streamline the process is to apply statistical performance analytics. Capturing this kind of data allows you to dig deep into the process and better understand how agents are applying their skills – or lack thereof – to each customer interaction. You can then assess the outcome of that interaction and whether or not customer satisfaction targets are being met.
For instance – are you able to match customers to agents based on personality? It may be easy to assume that such a detail isn’t necessary. After all, agents have a script and a process to follow, it really doesn’t matter if their personality matches that of the customer on the phone. But if you dig a little deeper into what you’re trying to accomplish, you may see the benefit of this extra step. If an agent is better to connect with the customer, wouldn’t the chance for upsell or cross-sell opportunities increase?
Likewise, if the agent and the customer fall easily in sync, wouldn’t first call resolution be more likely in a shorter amount of time? Ultimately, you’re seeking the best outcome for the call in the shortest amount of time. If you could use statistical data and speech recognition to match the personality of the customer to the agent, you not only reduce the time of the call, you also improve the outcome.
This example is just the tip of the iceberg when it comes to the benefits associated with using statistical performance analytics to improve agent performance. To learn more, transera and TMCnet are offering a free webinar, Statistical Performance Analytics: Case Study for Agent Scoring on Wednesday, September 17, 2014 at 12:00 p.m. EDT.