Not Tracking Real-Time CX Analytics? You’re Sabotaging Your CX

What Does Real-Time CX Analytics Mean?

Real-time CX analytics are calculated to the second. They can cover every aspect of contact center performance; from queue length to the number of incoming calls, to average wait times for individual customers.

• These analytics usually relate to the contact center as a whole. If you’re projecting data onto a wallboard for everyone to see, you want that data to be relevant to everyone who sees it. That means overall performance analytics.

• The downside of this is that, the more general the real-time CX analytics, the less useful they’ll be to the individual agents. If all your wallboard can tell you is that the queue is presently long, all the agent knows is that they need to keep answering calls. Hardly a radical departure in strategy. And seeing an enormous queue might do more harm than good; agents could feel demoralized, rather than ready to tackle a challenge.

• To unleash the real potential of real-time CX analytics, you need to provide information that allows agents to make changes in the moment, during an interaction, to ensure a positive resolution for the customer.

Real-time CX analytics, then, has to mean more than just ‘up-to-date analytics’. It has to mean valuable insights that support real-time adjustments in service, to better resolve customer inquiries. It has to mean essential data that supports agents to provide a better service to customers during an interaction.

AI-Powered Real-Time CX Analytics

Artificial Intelligence represents a revolution in real-time CX analytics. This transformation begins with transcription and summarization. Generative AI gives you the power to accurately transcribe every customer interaction; and once you have those conversations transcribed, you can subject them to analysis.

• Sentiment analysis involves assigning every word in a transcript with an emotional or ‘sentiment’ value. These values provide an overall sentiment value for an interaction. You can ascertain how the customer feels automatically, without having to ask them.

• Generative AI transcription allows for sentiment to be calculated in real-time, during an interaction. The agent can see a detailed breakdown of how an interaction is going, as that interaction takes place.

• From here, the agent can work to adjust their tone and address the customer’s concerns. They don’t have to wait until after an interaction to implement feedback.

• Supervisors, too, can see a full breakdown of customer sentiment during ongoing interactions. They can be notified if customer sentiment drops too low, and make an intervention where necessary.

And this doesn’t just apply to voice calls. In an omni-channel world, you can’t afford to focus only on voice. Sentiment analysis allows for a complete picture of contact center performance, across every channel.

Optimizing Contact Center Performance with Real-Time CX Analytics

Real-time sentiment analysis provides an unprecedented level of insight into interactions as they happen. It enables agents and supervisors to deliver outstanding CX, countering negative sentiment in real time and working to resolve it before the end of an interaction.

But that’s not all that real-time sentiment analysis can do for your contact center. All insight is invaluable for setting strategy and planning your approach.

• Measuring customer sentiment at different points of the customer journey can identify pain points. When customers switch channels, escalate a contact, or are transferred from one agent to another, taking regular customer sentiment measurements can track how the customer’s mood evolves across an interaction.

• From here, you can identify opportunities for streamlining. If customer sentiment regularly declines after escalations or switching between agents, working to improve your routing seems like a good place to start.

• Real-time sentiment analysis can also aid with customer segmentation. By tracking how customer sentiment evolves over time, you can identify groups of customers by need, and figure out ways to tailor your responses to customer needs. Customers calling up to request information, for instance, will have different needs and expectations to those seeking a resolution to an urgent problem. Sentiment analysis helps you segment your customer base.

Real-time CX analytics provide new insights into your contact center performance; from here, you can identify opportunities to optimize and tailor experiences.