This year marks the 50th anniversary of the iconic 1964 New York World’s Fair. A showcase for the technology of the future, the fair gave visitors a glimpse of the electronic conveniences that would revolutionize modern life. A telephone that lets you see who you’re talking to! A computer that can answer questions!
From the vantage point of the 1960s, the devices that were the “primitive” forerunners of today’s cell phone or internet-connected personal computer seemed like the stuff of science fiction. Today, we take their 21st century versions for granted, but it makes you wonder: what will the next big leap in technology bring us?
When we talk about analyzing interactions between people, especially phone calls, you won’t have to wait 50 years to find out. The next big leap is here, and it’s delivering capabilities with convenience that we couldn’t have imagined even a couple of years ago. Today’s leading tools provide insight into customer and agent behaviors that let companies understand and influence their customers’ journey, but there’s still more to come.
A couple of meaningfully different technology approaches led us to the current state of the industry. The first is a dictionary-dependent approach, often referred to as automatic speech recognition (ASR); and the second is a dictionary-independent or phonetic indexing approach. Historically speaking, the second method was invented to overcome some of the issues the first method has when analyzing phone calls. In other words, ASR wasn’t quite the right tool for the job, so a new method was invented, one more purpose-built for the job of analyzing the wildly divergent types of audio that come into call centers.
These competing approaches – each with its own advantages and limitations – have been the de facto tools for interaction analytics practically since the dawn of the speech analytics industry. As the industry has evolved from “speech analytics” into “interaction analytics,” research hasn’t stopped. Now, a new breakthrough approach that combines elements of both of them promises to make the old way of doing analytics as outdated as a rotary dial phone. Isn’t progress wonderful?
Combine and Conquer
This next generation of interaction analytics methodology blends the DNA of its ancestors with new genes to create an entirely new species of capability, one that applies the right techniques to the right challenges at the right time. Based on extensive lab research into the science of speech and interaction analytics, this new solution operates via neural networks, a computational model that mimics the workings of the human brain. Neural networks offer complex problem solving capabilities in a scalable computer framework that won’t put undue strain on a company’s technology budget.
By applying the artificial brain power of the neural network to investigate customer interactions, Neural Phonetic Speech Analytics strategically leverages the combined strengths of its predecessors to yield results that surpass what either could deliver on its own.
More specifically, this new generation uses elements of ASR exclusively in the early discovery phase of the analysis process, where it’s at its most effective, helping analysts surface topics of interest and events from the customer-agent conversations. The word level transcripts and sentiment scores the system produces make it easy for analysts to create focused, robust business topics that set the stage for successful, quantifiable analysis.
With the business topics clearly and cleanly defined, a phonetic indexing and search technique takes over. Phonetic indexing enables you to go where no dictionary-dependent tool can go, investigating the entire universe of your customer interactions to determine root causes for all events, whether you knew about them ahead of time or not. With 100 percent of your interactions examined and accounted for, you can base strategic decisions on a solid foundation of evidence, not sample-based projections.
Innovative Combinations = Enhanced Impact
So what’s the upshot of this new innovation? Your enterprise gains insight on two fronts: perspective into the mindset of your customers, and a better understanding of the performance of your contact center team. Used properly, this key information can have a measurable impact your company’s success, and can be used to inform strategic business decisions far beyond the contact center.
The future of interaction analytics is now, and it’s not science fiction. Check back next week when Jon Ezrine discusses what this next generation technology can mean for your business.