Customer experience (CX) remains a chief concern among businesses and brands with most competing solely based on their CX to differentiate themselves. As a result, the push to adopt technology for greater insight into customer data has risen.
In fact, according to new research from Gartner, in the next 10 years, service leaders foresee a large shift from simply handling customers’ requests to using customer data to provide high-quality service that handles both the issue at hand and customers’ end-to-end experience.
With the right technology, businesses can not only make improvements but help drive performance to encourage loyalty among customers and empower their agents. One such technology is conversational analytics.
What is Conversational Analytics?
Conversational analytics uses artificial intelligence to derive data from human speech, both written and verbal. In a nutshell, it’s a natural language processing (NLP) solution that helps computers “understand” and organize data in a way insight can be extracted from it.
How Does Conversational Analytics Work?
To start, you’ll need data and lots of it. This means all calls, emails, chats and other customer interactions must be captured.
The unstructured data trapped within these interactions are then matched with structured metadata such as the agent that took the call, the time and date a customer reached out and who the customer is. Once all the data is in the same format, the customer’s journey becomes clear, regardless of the channel (or channels) they chose to use.
As an example, if a customer reached out through both chat and phone, both would be captured for that customer to paint the full journey they took.
How Can Conversational Analytics Improve the Customer Experience?
Since you now have full visibility into the customer journey, the words and lexicons that come up in a conversation can:
- Provide clues as to faults in processes,
- Point to necessary product improvements, and
- Supply deeper customer insight including a better understanding of how customers feel towards various aspects of your organization.
This makes it easier to uncover and understand what matters most to customers and agents with data to support decisions and changes.
For example, let’s say the data is revealing one word that seems out of place and keeps popping up like “flashlight”. This word doesn’t apply to your product, yet it’s routinely said during customer interactions.
When the data is reviewed, it’s discovered that instructions included with the product were telling customers to use a “flashlight” to find the product number as part of the registration or troubleshooting process. Since this was a cumbersome step that irritated customers, the customer service team was able to present the data to the product team who moved the product number to a more convenient location and the customer service team no longer saw these complaints come through.
That’s just one example of the power of data.
Another example is fielding the same question over and over. With conversation analytics, you can easily track how many times the question comes up, add the question to the frequently asked questions page with the appropriate response, and help customers self-serve for a smoother experience.
These examples just scratch the surface of what’s possible. If you want deep customer insight, conversation analytics is crucial to unlocking the context of every conversation. With the right technology, businesses can elevate their customer experience by uncovering the critical insights that were once undetectable.