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Is ‘Big Voice’ the Next ‘Big Data?’ (video)

by | Apr 7, 2016 | BIA, Blog

Even as messaging apps and chat bots take over the world, people still have a biological urge to communicate by voice. This applies to commerce, especially where there is complexity. And complexity tends to happen in high-consideration, high-value products (i.e. autos).

The high price tags in these categories is one reason why phone calls have become such a valuable lead form. And this value will grow, despite messaging apps. It’s true that messaging and chat bots could reduce overall call volume… but the reduction will come at the lower end.

In other words: we’ll see less calls about “structured” info like hours of operation. Automation will enable time savings for businesses of all sizes, by offloading those calls to AI-fueled chat bots. But the more “unstructured” conversations will still happen, and even grow in value.

But to make all this work requires analytics, routing, lead scoring and all the functions of the area that we call “call commerce.” As explored recently, “big voice” is the branch of big data that uses machine learning to automate some of the costly (read: human) parts of call analytics.

I had the chance to discuss all of the above with an all star panel at the recent Contact.io conference in San Francisco. The panel included Google, 3-Day Blinds (a big user of call analytics), and LeadID. You can see the entire session video below.

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