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Technology serves as a way to bridge the gap between the physical and digital worlds. It connects us and opens communication channels in our personal and professional lives. It has become a top priority for leaders eager to help employees become more effective and genuine communicators, to imbue these conversations with emotional intelligence and empathy no matter where or when they take place.
However, the human emotion that goes into communication is often a hidden variable that can change at any time. For example, in customer-facing roles, a sales representative may become sad when they hear why a customer is making 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 changing demands and rising expectations.
The rise of emotion AI
Given how quickly emotions can change, it has become more important for technological innovations to understand universal human behavior. Humans have evolved to share overt and sometimes unconscious non-lexical cues to indicate how conversations are going. By analyzing these behaviors, such as conversation interruptions or speaking rate, 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, navigating the use of AI more accurately and ethically. Customer-facing organizations and their leaders need to raise their emotion AI standards to focus on outcomes that drive the emotional intelligence of their workforce and support them to create better customer experiences.
Emotion AI is not a new concept or technology practice. It’s been around for years, but has recently gained momentum and attention as more companies explore how it can be applied to specific use cases. Here are three ways customer-facing organizations can use voice-based emotion AI in the enterprise to improve customer experience initiatives:
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, reps go through many highs and lows. These interactions can be abrasive and exhausting, so providing real-time support makes all the difference.
These situations are similar to driving a car. Most people consistently do the basics of driving, but don’t drive very well when they’re tired from a night shift or a long car ride. Tools like lane detectors can provide additional support, and emotion AI is the equivalent in the workplace. Not only can it provide 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
The customer experience is intrinsically linked to the employee experience. In reality, 74% from consumers believe that dissatisfied or dissatisfied employees harm customer experiences. The problem is that showing up to work every day and in any case enthusiastic and with our optimum efficiency 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 extra support and trust promotes employee involvement and creates space for employee well-being. Any investment in improving work experiences or making workflows smoother is a surefire way to improve employee experiences and see ROI across multiple business divisions.
Understand the customer’s condition
Think again about the driving metaphor. While it’s essential to ensure a tired driver gets the help they need to get home safely, context makes all the difference.
Call center reps consistently multitask—talking to customers as they update or identify records, find resolution, and quickly resolve queries. Using voice-based emotion AI to analyze 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 better equipped to take stock of the situation and find the best course of action. By expanding situational awareness around customers’ mental states and analyzing the data, companies can consistently improve call outcomes.
Investing in emotion AI technology couldn’t be more relevant as we look to the future. Forresters 2022 US Consumer Experience Index found that the country’s average CX score fell for the first time after years of consistent, positive growth. While there are myriad influences at play, from supply chain shortages to the big resignation, the reality is that customers have come to have higher expectations of the companies they interact with, and underperforming is no longer an option.
Finding opportunities to fuel emotion across the enterprise and using technology to improve service interaction is critical to customer satisfaction. It’s up to organizations to invest in technology that celebrates and enhances emotional intelligence for continued success – and that starts with the introduction of technology like emotion AI.
Josh Feest is CEO and co-founder of Cogito.
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