How to Boost Contact Center Efficiencies with Customer Experience Analytics

Customer Experience Analytics can provide contact centres with a significant advantage in the quest for efficiency optimization, although they are often overlooked by contact centre leaders as being for the benefit of other departments.

This article explains why cross-channel analysis is critical to understanding the customer experience and outlines the relative value of the most common and high-volume channels.

The most comprehensive CX Analytics solutions merge speech and text analysis with the metadata elements needed to manage efficiencies including handle time, talk time, transfers, etc. Low-performing agents and their calls can be identified in seconds, and pivoting to speech analysis exposes specific areas that require further coaching and training.

For decades, contact centre leaders have been managing staffing models, handle time, service levels, hold time, transfers, speed of answer, time-to-proficiency, first call resolution, quality assurance and more. While standard switch and ACD reports have given way to more sophisticated reporting packages, the sources of the data set are still primarily phone systems and QA tools. It’s no wonder that contact centre leaders are still facing the same challenges that they had in the 1990s.

Contact centre leaders are under constant pressure to “optimize” cost-to-serve. It’s a safe bet that each has periodically been asked “can you bring handle time down by 20 seconds?” or, “can you handle the volume with 5% fewer agents?” in order to meet the budget. Undoubtedly, most contact centres have performance management programs in place and follow some form of the outlier management protocol. While there may still be room for minor improvements, contact centre leaders repeatedly find themselves trying to squeeze blood from a turnip.

To change this “Groundhog Day” paradigm, we must look beyond the current boundaries of contact centre data.

Let’s use the example of a contact centre that has been directed to decrease it’s AHT. A typical course of action is for the call centre director to issue an edict to the managers and supervisors to identify their bottom performers, and to coach them back to the mean (thereby bringing the overall AHT down). While it may be easy to identify the lowest performers, “coaching” is far more difficult. It is typically comprised of a discussion about call control, a review of QA scoring around call control, listening to a handful of calls, and the setting of goals. With the limited data available, that’s about the best scenario for which the contact centre leader can hope.

What if there was a different data source that allowed a supervisor to know the exact call topics that were causing problems for the agent – to identify the precise moments that confused the agent and understand exactly what occurred at those critical moments?

Customer experience analytics solutions, sometimes called voice-of-the-customer (VoC) solutions, can provide contact centres with a significant advantage in the quest for efficiency optimization. At first glance, these solutions appear to measure customer perception of a company’s products and services and are often overlooked by contact centre leaders as being for the benefit of product management, marketing and sales. A deeper look at the data produced by these solutions reveals something that should be of interest to EVERY contact centre leader: speech analysis all the way down to the individual agent level.

The most comprehensive CX Analytics solutions merge speech analysis (or text analysis for a chat and email channels) with the metadata elements needed to manage efficiencies – handle time, talk time, silent time, number of contacts handled, hold time, transfers and more. Finding the low performing agents and their calls is achieved within a few seconds. More importantly, the ability to pivot to speech analysis and see what is being discussed on those calls exposes the areas that require further coaching and training, and this deep dive into the contextual details takes just a few clicks.

Let’s look a couple of examples…

EXAMPLE 1 – Individual agent

Casey works as a contact centre agent for a retail company that sells and supports home goods. Casey has been in production for 75 days and has an AHT of 405 seconds. The site’s AHT is 355 seconds. A quick look at the handle time chart with a tenure filter applied for shows that the AHT for Casey’s peer group (0-90 days in production) is 422 seconds in the same call type.

We can also see that Casey’s peer group’s Silent Time ratio is very high at 43.5%. We know that silent time can be an indicator of confusion, lack of knowledge, or inefficient system use. With a few clicks, we can isolate the calls in which the agents with 0-90 day tenure have extremely high silent time. By identifying that set of calls, we can review the speech analysis (at the bottom of the screen) for those specific calls to look for common themes that are occurring across the subset.

Here we can see that Inventory calls are prevalent, and more specifically, Order calls resulting in Inventory discussions. From here we drill down into the individual calls and confirm that this peer group is indeed having issues dealing with inventory questions on new orders. Once confirmed, the supervisors can focus the coaching on how the team is handling those Order/Inventory calls.

Leveraging speech analysis to understand what was being discussed on those long handle time calls is the game-changer. With the right CX Analytics solution, all of this analysis should take no more than a few minutes.

EXAMPLE 2 – Group or Team

Building on the example above, we can look at Casey’s peer group of agents with less than 90 days in production. As with Casey’s individual performance, we can quickly see how the group’s collective performance compares to more tenured agents.

With either metadata or speech analysis, it is immediately clear that their transfer rate is significantly higher than for the tenured agents. While this is no surprise, the learning curve can be shortened significantly by using speech analysis. A CX Analytics solution can help identify the specific situations where agents are making the decision to transfer calls so that coaching and training can be focused on those opportunities to mitigate call transfers.

Customer Experience Analytics connects the dots between call driver, agent, sentiment, topics discussed on the call, and even CRM data about the customer, providing the contextual detail to identify and understand the challenges of delivering service at an aggregate level and for individual agents, right down the transcripts and recordings of specific calls. These insights will have an immediate and lasting impact on training and coaching strategies, ultimately resulting in better service and improved customer experience.

Source: Topbox