In this special guest feature, Aviad Abiri, Vice President of Portfolio Sales Enablement at NICE, provides 5 ways interaction analytics can improve customer experience. Interaction analytics helps to improve the overall customer service experience, and can also assist companies in advancing their bottom line. Aviad Abiri is responsible for equipping all client-facing employees with the ability to consistently and systematically have a valuable conversation with NICE's customer stakeholders, across the entire range of our portfolio offerings and at each stage of the customer problem-solving life cycle. In 1876, the customer service industry changed forever with a revolutionary piece of technology: the telephone. Since then, customer service professionals have become dependent on their ability to understand, react and communicate to the voice of the customer.

Conversations about workforce optimization (WFO) have heated up in the past couple of months. Following several passionate discussions about its future – as the transition to the cloud accelerates – I was inspired to write about the category and its evolution. My first surprise was the broad range of definitions for WFO. I was struck by the number of people equating the three-letter acronym to recording and quality management (QM). Industry analysts concur on a much broader definition including workforce management (WFM), performance management (PM), and more advanced applications like speech, interaction analytics, and gamification.

This article is part 3 of a 4 part series, sponsored by Genesys. Blending artificial intelligence (AI) and machine learning (ML) tools with human contact center agents can help you deliver the best possible customer experience. But getting started with AI and ML can feel like a daunting challenge, especially if your company relies on customer support tools developed years ago. As with any technology transition, begin by asking key questions to help you identify goals and desired outcomes. What does the solution do?