Tethr and Awaken Intelligence join forces as Creovai
Tethr and Awaken Intelligence are becoming Creovai, bringing together best-in-class conversation analytics and real-time agent assistance.
Robert Beasley
June 3, 2024
Sara Yonker
June 29, 2022
You can track all kinds of customer contact center statistics and metrics, but what do those numbers tell you? You need context. If you monitor your customer experience metrics, it helps to also know how you stack up against your competitors.
After all, customers shape their expectations based on not just their experience with your brand, but also everyone else.
That's why we decided to analyze 4.1 million calls to contact centers and provide our findings in a new ebook. In it, we benchmarked 29 different call behaviors to show you what many customers experience when they call a company contact center.
Think of it this way: If you’d never had to wait for a table at a restaurant before in your life, and then you happen to wander into the hottest new spot in a major metropolitan area. You might be shocked and irritated to wait 45 minutes to sit down. Comparatively, if you lived in that trendy neighborhood, only waiting 45 minutes at a place where waits can sometimes last hours might seem like a stroke of good luck.
Our expectations shape what we’ll tolerate as customers. As industries adapt to new technologies, customers expect a higher level of service everywhere, not just at companies that have adopted performance-enhancing technology.
Think about how technology can change customer expectations again, using the same restaurant analogy. Once customers grow accustomed to making reservations or getting on a wait list from an easy-to-use app, it makes those long restaurant waits even harder to tolerate.
So how do you know if you provide a good experience? You need data, not just a gut-check.
That’s where Tethr’s conversation intelligence platform comes in. When you use Tethr, data from all your customer interactions gets automatically digested and analyzed. We track your call center performance by integrating with your existing call and chat systems to provide in-depth analysis. We also tell you what those numbers mean with benchmarking on every major metric.
In the ebook, we explore where companies fall on the spectrum for a wide variety of customer service issues. These metrics were more than just call volumes, call transfer rates, and other generic call center industry stats. We evaluate the entire customer service experience and use our AI-powered system to analyze the overall customer experience.
You can download the ebook now for free, but here are some key highlights from our research:
Some moments in a customer conversation can derail your customer’s experience. When customer service agents work proactively and display positive behavior, those actions can create a ripple effect that improves the entire interaction.
Likewise, a negative agent behavior - such as an agent who is confused by their company’s own policies - can be difficult to recover from.
Our research found that of the positive agent behaviors, advocacy statements enhanced the customer experience more than traditionally emphasized agent language, which we call acknowledgement.
Advocacy differs from acknowledgement because it requires the agent to take an active role in resolving an issue. Acknowledgement merely tells the customer they’ve been understood. While both can help improve a conversation, advocacy matters more.
When we analyzed 4 million+ calls, we noticed some trends in the call center statistics. Even though some companies excel at providing good service and others need work to get there, we found some commonalities.
The eBook goes into more detail - especially on outliers in each area - but in general, we found:
One other common negative agent behavior we detected in our analysis can show company leadership a need to update policies. That behavior we call “Powerless to Help” and it occurs when a company’s own procedures prohibit contact center agents from solving a problem.
In these cases, the agents need to ask a supervisor for authorization, or can’t address a customer’s concerns in a phone call. In our analysis, the top-performing company had “powerless to help” language detected on 1.7% of calls. The worst-performing company had it 10 times more - 17.7% of calls.
When companies have a high percentage of calls where agents are powerless to help, it can highlight a need to revise policies so that agents can help customers easily.
We also examined metrics that show how your customers’ journey went. We looked at this a few different ways.
If you’re interested in learning where you stand on customer contact center metrics, you can get a peek at those when you sign up for a Tethr trial. In our 30-day free trial, you can upload up to 1,000 phone calls and see analysis of these key data points. Get started now.