Speech Analytics: What’s the Big Deal?

My first introduction to the concept of speech analytics occurred with an on-site visit by a vendor about 12 years ago, when at a prior employer I was a user of digital recording primarily for QA purposes.  I’ll honestly admit that my initial impression and lingering thoughts following the meeting were something along these lines: “That seems pretty cool, but it’s an awful lot of money to just detect a couple of words in the calls.” and “How could this technology possibly help us?  We have monitoring teams in place who collect a bunch of data for us already, so what’s the big deal?”

Fast forward a couple of years, and found myself accepting a job at NICE as a Business Consultant supporting the Interaction Analytics solution.  (Talk about a 180-degree turn, huh?) But even then, as I learned the ropes on how to use the solution and got my first few clients up and running, I still didn’t comprehend the full power of the technology I was supporting.

After five years as part of a team of NICE consultants, I made another career change to once again be the customer versus the vendor.  The organization I joined was already bought-in to the concept of analytics, and we continually produced impressive results (annually achieving sufficient ROI to more than cover the costs of the solutions we had in place).

Now, with over five years of tenure at my current company, we’re kicking things into high gear.  Our recent upgrade from NICE IA to Nexidia Analytics was successful, and through the migration we deliberately broke-out of the constraints of primarily supporting the operational contact centers and instead have taken a full enterprise-wide approach to our services.

So what’s my point?

The point is that as I reflect back through the last 12 years of my career, my appreciation for and application of speech analytics has certainly evolved.  And as much as I’d like to consider myself a pretty knowledgeable guy when it comes to this technology, I continue to learn new things and to discover new ways to apply the solutions on a regular basis.

Here are some of the many ways we’ve found success utilizing speech analytics technology far beyond the skeptical and limited “detection of a couple of words in the calls” mindset I started with years ago:

• Customer Experience correlations by Call Type (allowing for trending, alerts, and rapid root cause analysis to continually improve Customer Experience) - Self-Service Containment improvements (allowing for relatively flat agent staffing levels despite rapid growth and notably increased inbound call volume)
•  Automated detection of Potential Risk (increasing insight and quality control coverage while significantly reducing testing team FTE requirements)
•  Census testing of Revenue-Generating Offers (bringing awareness and accountability of agent behaviors and enhancing offer effectiveness)
•  Best Practices sharing with a “social media-style feed” of call examples versus the legacy “call library” concept (enhancing agent recognition, coaching, training, and motivation)

In summary, I am a believer in and advocate of Interaction Analytics.  I’m open to ideas and to the discovery of new ways to put this technology to use.  And for those of you out there who are skeptical or who are wondering “What’s the big deal?”, just know that an open mind and a willingness to succeed despite your doubts can take you a long way.

Whether you’re new to the idea of Interaction Analytics or you’re a seasoned veteran user like me, I invite you to join our new virtual NUG Analytics Chapter where we can share our success stories, compare lessons learned, exchange best practices, and compile a repository of materials and resources.