Artificial Intelligence (AI)

A NICE Time in Wyoming

I recently attended my first in-person analyst event in18 months, and it sure was NICE (pun intended). The NICE team put on an amazing event, in terms of both content and the Analyst Experience (AX - a new term I coined). Taking place in Jackson Hole, Wyoming, we got to experience a scenic helicopter tour, and all that Jackson Ford Ranch had to offer including a choice of horseback riding, bison encounters, fly fishing, nature walk, archery/axe throwing, and more.

Four Signs You Could be Losing Your Contact Center Millions of Dollars a Year

Forward-thinking contact center IT managers are adding millions to the bottom line – by rethinking their role and status as Cost-Cutter-in-Chief. Is it time you did the same?

A typical contact center handles tens of thousands of customer conversations a day – and every one of those interactions is an opportunity to sell or increase customer loyalty. But, all too often, contact center IT managers are forced to see a customer not as a business opportunity, but as a problem to be dealt with as quickly as possible.

In this special edition Industry Buzz podcast, BCStrategies invites special guests Mike Nelson and Kane Simms of VUX W

In-Meeting Real-time Analytics - Are we missing the value of analytics to make our meetings better during the meeting?

On our recent BCS Expert podcast on best practices for using video, collaboration and teams, Kevin Kieller talked about the data from meetings and usage that is gathered in Microsoft Teams. He talked about how it shows issues in how people meet today. In fact, cloud-based communication and collaboration applications gather an amazing amount of information during every meeting event. Every time a new person speaks it generates a change that is noted.

When Algorithms Assume

Artificial Intelligence is a major topic today, not just in communications and Contact Centers, but across business. Most of the current crop of business-focused “AI” is in fact Machine Learning (ML). In ML, a large data set is used to “train” the algorithm to predict an outcome based on a range of interacting variables. Using modern data sets that have millions and even billions of test sets and thousands of variables, the ML program is able to train a neural network to predict an outcome.

TalkingHeadz Podcasts

In their TalkingHeadz on Enterprise Communications podcast series, BCStrategies Experts Dave Michels and Evan Kirstel talk with various guests most

TalkingHeadz Podcasts

In their TalkingHeadz on Enterprise Communications podcast series, BCStrategies Experts Dave Michels and Evan Kirstel talk with various guests most