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Technology serves as a way to bridge the gap between the physical and digital worlds. It connects us and opens up channels of communication in our personal and professional lives. Being able to infuse these conversations — no matter where or when they occur — with emotional intelligence and empathy has become a top priority for leaders eager to help employees become more effective and genuine communicators.

However, the human emotion that goes into communication is often a hidden variable, changing at any moment. In customer-facing roles, for example, a representative might become sad after hearing why a customer is seeking an insurance claim, or become stressed when a caller raises their voice. The emotional volatility surrounding customer experiences requires additional layers of support to meet evolving demands and increasing expectations.

The rise of emotion AI

Given how quickly emotion can change, it has become more important for technology innovations to understand universal human behaviors. Humans have evolved to share overt and sometimes subconscious non-lexical signals to indicate how conversations fare. By analyzing these behaviors, such as conversational pauses or speaking pace, voice-based emotion AI can reliably extract insights to support better interactions.

This form of emotion AI takes a radically different approach than facial recognition technologies, more accurately and ethically navigate AI usage. Customer-facing organizations and their leaders must raise their standards for emotion AI to focus on outcomes that boost the emotional intelligence of their workforce and provide support to create better customer experiences.

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Emotion AI is not a new concept or practice of technology. It has been around for years, but recently has gained momentum and attention as more companies explore how it can be applied to specific use cases. Here are three ways that customer-facing organizations can use voice-based emotion AI in the enterprise to elevate customer experience initiatives:

Increase self-awareness

Think of emotion AI as a social signal-processing machine that helps users perform better, especially when they’re not at their best. In the world of customer experience, representatives undergo many highs and lows. These interactions can be abrasive and draining, so offering real-time support makes all the difference.

These situations are similar to driving a car. Most individuals consistently perform driving fundamentals, but do not drive as well when tired from a night shift or long road trip. Tools like lane detectors can provide additional support, and emotion AI is the workplace equivalent. Not only can it offer real-time suggestions for better interactions with others, but the increase in self-awareness helps foster deeper emotional intelligence. Ultimately, when better emotional intelligence is established, more successful customer service interactions can occur.

Improve employee confidence and well-being

Customer experience is intrinsically tied to employee experience. In fact, 74% of consumers believe that unhappy or unsatisfied employees harm customer experiences. The problem is that showing up to work engaged and at our optimal efficiency every single day and in every instance is not a realistic expectation for employees.

Emotion AI can remove anxiety and self-doubt around performance by helping individuals through difficult experiences and encouraging them during positive ones. This added support and confidence promotes employee engagement and creates a space for employee wellbeing to shine. Any investment in improving work experiences or making workflows more frictionless is a reliable way to boost employee experiences and see ROI across multiple enterprise divisions.

Understand the customers’ state

Consider the driving metaphor again. While it’s vital to ensure a tired driver receives the aid they need to get home safely, the context makes the difference.

Call center representatives consistently multitask — conversing with customers while updating or identifying records, seeking to find a solution and managing inquiries promptly. Utilizing voice-based emotion AI to analyze the sentiment on both ends of the line can provide detailed insights needed to perform and connect. When emotion AI can identify customers who are “highly activated” with excitement or anger, agents are more equipped to take stock of the situation and find the best approach forward. Expanding situational awareness around customers’ mental states and analyzing the data can help enterprises consistently improve call outcomes.

Investing in emotion AI technology could not be more pertinent as we look to the future. Forrester’s 2022 U.S. Consumer Experience Index found that the country’s average CX score fell for the first time after years of consistent, positive growth. While a myriad of influences are at play, from supply chain shortages to the Great Resignation, the reality is that customers have grown to have higher expectations of the businesses they interact with, and it is no longer an option to underperform.

Finding opportunities to ignite emotion across the enterprise and use technology to improve service interaction is critical to customer satisfaction. It’s up to organizations to invest in technology that celebrates and improves emotional intelligence for continued success — and it starts with introducing technology like emotion AI.

Josh Feast is CEO and cofounder of Cogito.

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