AI Has Contact Centers Re-Imagining Interaction Analytics

For Contact Centers, the conversations between agents and customers have long been a source of valuable insights into the customer experience. But getting those insights is often a manual or anecdotal process. Emerging technologies like AI-powered Interaction Analytics are changing the dynamic up by enabling companies to use natural language processing techniques to mine insights from every interaction.  

Overall, companies are dealing with monumental amounts of data, and it’s not slowing down any time soon. Interaction Analytics, among other technologies, is critical to help companies find value in the data they already collect and analyze today. But it will also help with the myriad types of data that has long been under-leveraged, including unstructured data like speech and text in the Contact Center or social media activity.

Interaction Analytics offer a way for companies to transform text and speech from customer interactions into quantifiable data points and insights. It uses technology like Natural Language Processing to help you uncover the full story behind every interaction.

Stratifyd was recently mentioned in “The Forrester Tech Tide™: Contact Center Technologies For Customer Service, Q1 2021” in the Interaction Analytics space, which they identify as an "Invest" technology, or an emergent technology category with high business value. So, we spoke with Kurt Trauth, SVP of Customer Experience Strategy and Analytics at Stratifyd to break down the what’s what of this space.

Contact Centers have used Interaction Analytics for a long time to understand the customer support experience, but the new generation of this technology is gaining more traction as a must-have. How is AI rejuvenating Interaction Analytics and why is now the time to invest in this technology?

Kurt: As Forrester mentions in their report, Interaction Analytics has traditionally been limited to customer service quality.  And even then, the analytics were highly manual and only looking at a very small sample of calls due to the limited capabilities of commercial speech recognition technology.  

It’s only been in the past few years that companies such as Google and Microsoft have achieved breakthrough performance leveraging AI that enabled speech recognition to become commercially viable.  The easiest way to recognize those advancements is in the rise of voice powered assistants, such as Alexa.  Now there are plenty of companies that transcribe high volumes of calls at usable accuracy levels, at costs that most contact center leaders can prove a business case for.  

Artificial Intelligence is a new technology for many people. What do Contact Center leaders need to know about AI-powered interaction analytics compared to traditional analytics?

: The most common pain point you see with any AI-based analytics tool is that they can be “black box” models. That means that the business end user can’t improve without custom development by the vendor, which really slows down the time to find new insights and keep up with, what is today, a rapidly changing customer experience.  

We regularly speak to Contact Center leaders who are frustrated that their speech analytics is accurate at identifying common words, but can’t accurately capture the most important phrases that are unique to their company or industry.  

Another key gap in interaction analytics is the strength of a vendor’s text analytics capabilities.  Although speech transcription is becoming close to a commodity, most vendors still struggle to analyze the text in the calls.  Buyers are often excited by a demo that shows a call being transcribed into text, but don’t think to test how well the vendor can analyze all of those transcripts – which is where the real analytics starts.

Interaction Analytics can unlock insights that go beyond the efficiency and quality of the customer interaction. As Contact Centers look to expand the range of their interaction insights, where else in the organization should they be looking to drive value?

Kurt: Contact Centers have traditionally been viewed as cost centers, so their KPIs have naturally focused on efficiency.  While this isn’t going away, the Contact Center has also always served as a critical source for understanding the Voice of the Customer.  Until the recent advancements in speech recognition, insights from these daily conversations with customers were limited (and biased) to what managers would hear from their agents.  However, now that every call, chat or email can be analyzed, teams across the enterprise are anxious to start leveraging the rich, real-time insights in the contact center.  

The obvious initial use case is for CX, Digital, and Contact Center teams to identify and accurately quantify the pain points driving customers to call.  Previously these teams had to depend on a limited set of call reason codes that agents would select at the end of the call, which could never keep up with the nuance and variety of new issues customers faced.  

We’re also seeing Sales and Marketing leaders analyzing calls to improve their messaging, and Product teams driving more agile enhancements based on customer feedback on new features.  Leading CX teams have also recognized that calls can provide them with insights that would take weeks, or most likely never, show up in survey feedback. This is not only changing the way CX teams deliver and act on insights, but also allowing them to repurpose legacy surveys to research more specific business needs.


There are so many ways to leverage Interaction Analytics in the Contact Center, but you won’t know the right use cases for your company without seeing the technology in action. See how Stratifyd can improve your Contact Center insights by scheduling a demo today!

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