Speech Analytics and AI - a closer look

Amitt Sharma
April 30, 2019
Genesis of Voice AI

" The key to artificial intelligence has always been the representation" - Jeff Hawkins

As a kid, I had always been fascinated by man's ability to imagine. We imagined flying objects, magical contraptions, aliens and what not. Technology has been man's best friend when it came to seeing some of these fantasies to light. In the modern era, the likes of Isaac Asimov and Ray Bradbury dreamt of Artificial Intelligence through their works of fiction and put forth the idea of existence of humanoids capable of replicating us - both in form and function.

You may be wondering what am I about with the aforesaid. Well the point is that often imagination is a precursor to reality and this time AI is what has come knocking on our doors. General AI, a-la intelligence to power human-like Androids who want to take over the world and take us for slaves, is eons away to say the least. However, we are indeed now face to face with narrow AI that can help us automate certain repeatable and simple functional tasks. These tasks may not necessarily be cognitive in nature and can be accessed by machine learning cycles. When Sundar Pichai recently successfully demoed the Google Voice assistant, we were privy to a tiny sample of what narrow AI(the simple non-threatening AI!) is capable of. You can use VoiceBots book restaurant tables, tickets to a movie or a game, plan your visit to the beautician and so on.

Voice - the cornerstone of human communication

It's inevitable that I now talk about voice as a preferred channel of interpersonal communication, a medium of instruction through which our human intentions are made known. As a medium of such objectives, voice has no parallel. We use voice to reach out and communicate our desires and needs. Corporations want to capture the same voice, understand the context and act to satisfy the asks - as long they are rational. Voice based AI takes up the mantle to do the same albeit in a more simple rule based and pattern driven scenario. I'll spare you the how. But let's delve for a moment into the why.

Voice and Natural Language Understanding

Voice is an expensive channel to deploy, maintain and service. And rightly so. It involves human labour. And on the plus side it can be leveraged to capture not only the words but also the emotions and feelings of the speaker. Together businesses can piece up customer sentiment, customer's propensity to buy more, pain areas, feature affinity, expansion ideas. The list is rather long and inconclusive and ever evolving. The recent developments in voice analytics are fueled by Artificial Intelligence and the advent of machine learning and natural language processing(NLP).

Voice AI in contact centers

As always the business objectives revolve around either A. cutting costs by doing utilizing resources infrequently and optimally, and B. maximizing gains by opening up new avenues that can bring in more. While the former reduces the bottomline the latter adds to the top line. For example, a contact center that's leveraging voice analytics through AI can manipulate both to their advantage.

While it is much more scalable to QA calls on the support channel and effect a call flow remap to a more customer centric model. It is also possible to understand call themes and drivers and move them to a more appropriate desk, say product development, almost immediately. This real time nature of conducting analysis purely on the customer's voice is laced with a keen understanding of customer's tonality and mood. The fact that all of the above is free from human error and bias is an added boon. Another example would be fine tuning of sales calls and understand the success metrics and replicate the same. Leaderboards are now more accurate than ever and so is the reward, feedback and accountability that can now be implemented.

We at Observe.AI believe you can do so much with your customer's voice, think of it as precious crude oil the distillates of which can feed into customer support, product development, where to focus marketing dollars, up-sell/cross-sell opportunities to name a few. Every by-product is monumental in it's own right and you get to maximize your own ROI on every single penny spent on implementing a voice driven contact center.

About the Author: Amitt leads Customer Success practice at Observe.AI and has deep insights in the CX domain.


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