Customer satisfaction has always been the primary focus of contact centers, which generally requires achieving accurate resolutions as quickly as possible. Agents and their supervisors use various metrics to determine if they’re efficiently and effectively resolving issues for their customers. However, the number of metrics available can make it difficult to make sense of all this data without access to proper optimization software.
Metrics that affect customer satisfaction in a contact center include:
- Queue time
- Hold time
- Solve rate
- Call time
Queue time is the length of time customers spend waiting for their call to be answered. And typically, the longer the queue time, the less satisfied a customer is with their overall experience.
The queue time for abandoned calls is of particular importance in assessing customer satisfaction. The reason being, customers who hang up before reaching an agent were obviously not satisfied with their experience.
Hold time is the length of time a customer is on hold with an agent. Many customers will tolerate a little hold time, but if extended for too long, it can make it difficult to please a customer even if the agent is able to resolve the issue. Even worse is when the hold time causes the customer to completely abandon the call, which definitely results in poor customer experience.
Hold times are driven in part by the realities of the modern contact center, which often have to distribute resources across multiple channels like social media and the web. One approach to reducing hold time is to implement a call-back solution, which can lower costs while improving customer experience.
Solve rate is the rate at which agents solve customers’ problems. You can calculate it by dividing the number of calls that resulted in a resolution by the total number of calls that reached an agent. Agents aren’t always able to solve a problem while they’re with the customer. In some cases, the agent has to send it up to the next tier or open a help desk ticket. Other times, the customer is asking for something the agent can’t do, like removing a charge from their account that seems to be warranted.
Solve rate is a key metric for measuring the performance of individual agents. However, increasing the solve rate often requires agents to spend more time with the customer, thus increasing call time. Identifying the root cause of time-consuming problems often allows agents to increase solve rate without adversely affecting call time.
Call time is the time that a customer spends on the phone with an agent. It may seem that contact center managers would want to minimize call time no matter what, but this isn’t necessarily the case.
The trade-off between problem resolution and speed is often described as white-glove treatment vs. an effortless experience. White-glove treatment refers to providing customers with the best possible service, no matter how long it takes. However, this approach increases queue time since agents aren’t able to handle as many customers within a given time period.
On the other hand, an effortless experience is one in which the customer’s interaction with an agent is as easy as possible. It’s a more transactional way of addressing and solving a customer’s problem compared to a white-glove experience.
An analysis of both historical reports and real-time data is essential for determining where you need to focus your efforts on improving your customers’ satisfaction. Tracking your metrics in a way that allows you to reach this goal requires you to use software dedicated for this purpose. Contact us today to learn more about how our suite of solutions can benefit your team.