It’s common for issues to pop up during day-to-day contact center operations and with a lot of customer interaction and agent activity within your PureEngage platform, many of those issues may be hard to find.
Contact centers continuously monitor metrics to:
- Analyze data that affects customer experience (CX)
- Ensure that performance goals are met
- Catch issues
The tools they use often only show summarized data and don’t help much when the “devil is in the details”. When issues fall within what those tools look for and capture, they are easy to spot and solving them is usually straightforward. For example, if the call volume is unexpectedly high, the contact center will make more agent time available (e.g. bringing on more agents or canceling off-queue time).
However, for issues lurking beneath the surface, evidence may show up in the CX metrics, but standard tools don’t offer an easy way to pinpoint the detailed contact center activities behind the issue. Worse still, is that there are likely activities causing issues that companies don’t even know about.
For example, there could be agent behavioral issues occurring, such as this issue (happened to one of our clients), where some agents were placing customers on hold immediately after greeting them and increasing customer frustration. While this issue was caught by accident (by the VP of Customer Service’s office assistant!), the contact center didn’t have the tools to know who was doing this, how long it had been happening, nor how widespread this hidden issue was.
These more complex issues take time to identify and figure out, causing a lot of time to pass before a resolution is found and put in place. For contact center directors and customer experience executives, this means that their key customer experience metrics (like NPS and CSAT) are affected.
Wouldn’t it be great if contact centers could find those hidden and complex issues much faster, and reduce the impact on customer experience? This is possible but requires contact centers to shift from traditional methods.
Making do with traditional methods and tools
Contact centers use many tools to measure customer experience and identify customer experience problems when they arise. They look at contact center operational metrics (often aggregated data), analyze conversations, or pick up issues directly reported by customers and agents.
Reports, analytics (such as customer journey analytics), WFM, and QA, are tools that contact center professionals use to see how customer experience is impacted (such as higher call volumes, or agents adhering to their schedules), but these tools barely offer a glimpse into those harder to find day-to-day operational problems.
Basically, contact centers are “making do” with the tools they have.
New methods and technology to detect poor customer experience in real-time
To understand those hard to find or unknown issues affecting CX, without spending tons of time sifting through low-level system details, contact centers need to adopt a new way and new technology.
There are new and emerging ways to more quickly, accurately and proactively examine the contact center activity for issues and problematic agent behavior that can affect the customer experience. These methods and technology also help monitor these issues to keep them at bay.
For example, Aria’s Visualizer for Genesys that works on PureEngage helps contact centers:
- Identify agent behavior and compliance automatically by listening to ALL calls instead of just spot checking a small sample of calls.
- Analyze calls by learning and improving what is defined as a problem call.
- See detailed analysis in real-time that captures all the low-level activity in a contact center. This will provide a visual picture of the customer experience, making it easier to spot issues you didn’t even know you had and that are beyond the reach of listening to calls.
Contact centers now have options for resolving issues that happen in day-to-day operations and can reduce the effect on customer experience. Visualizer provides the detailed insights that find the issues quickly so they can be actioned immediately, and affect a smaller number of customers.