A Great New Analytical Application from Nexidia (and an Idea to “Improve” It)


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Today Nexidia announced a new solution that allows call centers to use speech analytics in real time.

Normally this would have been very cool by itself (despite what you see in movies the technology we have cannot yet select a phone conversation from among millions – or even thousands – based on two or three keywords very accurately), but when I was being briefed on the solution I picked up on two additional things that I think are worth mentioning: the patented technology, and their desire to use it in new areas.

Briefly, speech analytics works by converting sounds to words. This is, usually, done word-by-word – and you can already imagine why real-time speech analytics is almost impossible to do. Traditional speech recognition techniques that interpret words one-by-one work at 3-4 words per minute, which means they can analyze one hour of audio in about 15-20 minutes. Nexidia found a way to accelerate the using a patented phonetic interpretation model that, just like is used to teach kids to read faster, speeds recognition up by magnitudes. What used to be done in a 4:1 ratio can now be done in a 700:1 ratio; what used to take 15 minutes can now be done in seconds. Behind the speech recognition engine there is a very powerful, very open analytical engine that was created specifically to handle real-time analytics.

Their announcement for today was a very cool application that I got to preview last week that takes clues from the conversation (key words, phrases, contextual information, etc.) and uses that to pull data and knowledge from the corporate systems and the knowledge base to assist the agents automatically as the conversation goes on. It is dynamic, so it is continuously monitoring the conversations and providing more assistance. I saw a couple of demos and they looked really good very interesting. When deployed, it should help call centers cut down on Average Handle Time, increase Customer Satisfaction, and promote Employee Morale. The results from the first clients showed significant improvements already.

So, why does it matter?

The only thing standing between Social Business becoming a reality is the lack of good analytical tools that can operate in quasi-real-time to help businesses make better decisions. Actionable insights, as I wrote in my introduction to the Roadmap to SCRM, is the key outcome of implementing SCRM. It is the value that business derive from interacting with customers across so many partners at the same time. Valuable information on how to improve the business and better serve their customers — even in real-time – is the reason companies become Social Businesses.

During our conversation I deviated the talk from speech recognition to the embedded analytical engine and they confirmed that is very flexible and dynamic, that it can take input from anywhere – even social media channels (they are evaluating how to use it differently in the future).

My light bulb went off — what about putting the speed of processing of their analytical engine, the ability to support cross-channel, and the very cool app they have and turn it into a social business analytical solution?

We will have to wait, but for now the call center can deploy a very cool solution for real-time speech analytics.

Disclaimer: I have not been paid for writing this, nor will I get paid in the future. This is my opinion, my position, my vision – my whatever-you-want-to-call it. I truly want to see this tool moved to Social Media without loosing the power of the speech analytics, and that is the purpose of this entry. Nexidia is not a client, nor do I have any friends or relatives that work there or for one of their contractors. Seriously, get a demo because this is cool stuff – yes, kinda like rocket science. As usual, do your due diligence and don’t take my word to be worth more than an opinion. We all know what opinions are…
Esteban Kolsky
ThinkJar, LLC
Esteban Kolsky is the founder of CRM intelligence & strategy where he works with vendors to create go-to market strategies for Customer Service and CRM and with end-users leveraging his results-driven, dynamic Customer Experience Management methodology to earn and retain loyal customers. Previously he was a well-known Gartner analyst and created a strategic consulting practice at eVergance.


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