Can AI Teach Us How to Become More Emotionally Intelligent?

Companies are wise to explore AI solutions that can help make their teams more emotionally intelligent, and better communicators. Indeed, AI can enhance our emotional intelligence by making us more self-aware and helping us manage key work relationships. Enhancing our emotional intelligence and communication skills makes us more efficient, productive, and empathetic. Although the technology is far from perfect, it is becoming more intelligent every day as platforms increase in data, scale, and sophistication. The technology is in place to make our teams more emotionally intelligent and companies more successful and profitable.

The debate over whether AI will replace humans in the workforce often boils down to a handy, twofold explanation: AI will replace humans for most repetitive and manual labor tasks, while humans will excel at soft skills like creative communication and relationship-building. While some of this is true — humans and machines will each play to their strengths — it probably oversimplifies AI’s role in our professional lives. We believe AI will help humans do better human work, namely by helping us improve our emotional intelligence, soft skills, and interpersonal communication skills.

Leveraging advances in emotion detection, natural language processing (NLP), and computer vision, and combining it with psychology and linguistics, AI algorithms have gotten better at detecting, analyzing, and processing how tone, pitch, facial expression, eye contact, body language, and dozens of other verbal and non-verbal communication features influence communication.

By letting AI tap into your customer conversations, either voice, video, or text, AI can take complex and often puzzling data and find patterns in effective communication not apparent to the naked eye. The potential applications of these technologies go beyond sales and customer success. Many professional roles requiring strong communication skills, including leadership, public speaking, product management, virtual therapy, teaching, language learning, and bedside manner will benefit from AI that measures emotional intelligence. Indeed, by 2026, the combined market size for emotion detection and conversational AI are projected to grow to more than $55 billion.

Success with Emotional Intelligence and AI

Since Peter Salvoy and John Mayer first defined Emotional Intelligence as “a type of social intelligence that involves the ability to monitor one’s own and others’ emotions, to discriminate among them, and to use this information to guide one’s thinking and actions,” researchers and companies have tried to demystify the art of being a “people person.” Data has proven that emotional intelligence is a strong predictor of professional success.

A study out of Yale revealed that emotional intelligence helps us make better decisions at work. Another study out of Harvard showed that emotional intelligence was more helpful than IQ in predicting team success. And a 10-year study at Google called Project Oxygen showed that emotional intelligence matters more to one’s success as a manager than IQ or technical skill. The principal takeaway: emotional intelligence is just as important as any “hard skill” and investing in it helps individuals and teams succeed at work.

A professional looking to improve their emotional intelligence must juggle working on their own self-awareness and emotional self-management, while at the same time matching the emotional state of the customers they talk to. It’s not only the context of the current interaction and reading the situation, but also the history with that person and their shared goals. AI can help make this process easier for customer representatives: it not only gives you clues on the emotional profile of the customer on the other line but enables you to simulate speaking with them.

This kind of insight is especially important in the high-stakes world of customer success, where the average customer success manager (CSM) manages $2 to $5 million in annual recurring revenue (ARR) and is often based outside of the U.S. For them, understanding the cultural and interpersonal nuances of U.S.-based customers is critical to success.

One company that has recognized this is Gainsight, a leading customer success platform located in the Bay Area, which incorporates EQ analysis into their hiring and onboarding, and is currently piloting with one of their customer success teams located in India.

Gainsight uses Gong and Zoom to record calls between their India-based CSMs and Americas-based customers, then feeds the data into a conversational intelligence platform to analyze and understand the learning styles, emotional responses, and personality profiles of their customers. This data then feeds into a training simulator to help other CSMs prepare for upcoming calls with customers in the region. By fine-tuning their delivery in a tailored way and meeting customers on their emotional level, CSMs can accelerate a win-win agenda with customers.

AI and Emotional Intelligence in Action

Sales data analysis firm, Gong, analyzes interactions between salespeople and customers to help sales professionals communicate better and close more deals. Gong leverages machine learning (ML) and NLP to index customer emails and video calls, and cull qualitative insights from quantitative customer data to craft better pitches and adopt more persuasive and empathetic language. Gong isn’t a small startup proselytizing the promises of AI. It was most recently valued at $7.25 billion and its roster of clients includes companies such as Accenture, LinkedIn, Service Titan, Slack, PayPal, Zillow, and many others.

In early 2020, as the pandemic forced global lockdowns, Zillow began using Gong to help its sales professionals transition from in-person to virtual sales. Zillow created a video tour and paired it with Gong trackers to monitor which key phrases helped close more deals. Zillow also used Gong’s Whisper product, which ranks sales team members based on their performance, to determine how their top performers were communicating and pitching differently than the rest of the team, enabling managers to institutionalize those best practices.

Another example is BenchSci, which helps pharmaceutical companies and scientists advance their clinical trials. A key aspect for VP of Customer Success Mike Egan is for his team to be proactive with customers to give them exactly the right support at the right time to turn them into evangelists of their platform. Since pharmaceutical companies can’t record online meetings due to privacy and security concerns, BenchSci worked with an AI conversational intelligence platform, to capture signals from emails, support tickets, and surveys. The platform can run personality and behavioral analyses on the emotional state of the customer and enable the customer service representative to better mirror it and respond to customer service tickets.

The AI Feedback Loop

Because customer interactions are so critical, the customer success field has been fertile ground in establishing a 360-degree AI feedback loop: insights on the emotional state of customers are provided before, during, and after a customer interaction. In this section, we break down each stage of the customer journey and the ways in which AI can help improve emotional intelligence.

Before a customer interaction: Customer success managers should have an environment to train and practice before they speak to customers, especially when they can classify the conversation. Is this a renewal? A customer cancellation? An upgrade request?

If you have talked to a customer before, Cyrano.AI has patented technology that analyzes previous conversations to create a profile of the customer. That profile might include the customer’s communication style, identifiable priorities or goals, and even their exhibited levels of commitment in the last conversation. If you look at the emotional moments of the call and how they drive motivation, you could alter your presentation to your customer’s personality type and see how they respond.

During a customer interaction: Customer service and customer success leaders can get real-time feedback and tips to better close a deal, handle objections, or empathize with unhappy customers in real time. Cresta, for instance, uses AI to give call center workers real-time feedback through text prompts, so they know what to tell customers in the most common situations. If a customer has an objection the technology surfaces a step-by-step prompt to help reps overcome it. An unhappy customer? The technology surfaces key phrases or words to calm the customer.

EarthLink, a privately held internet service provider (ISP), used Cresta to modernize their contact center operations, helping their agents to communicate with more empathy. Within the first month of using Cresta, EarthLink reported experiencing an 11% reduction in Average Handle Time (AHT) and a 124% improvement in value added services conversion rate, which is a success by any measure.

After a customer interaction: Insights post-customer interaction is where the real power lies, because AI can read from past conversations with the customer and provide improvement feedback. Like a virtuous cycle, the more the AI is used, the better the feedback becomes.

Reciprocity, a leading risk and compliance platform headquartered in San Francisco, enables exactly that scenario for their CSM team as part of their tech stack. While their customer meetings are recorded in Gong, they analyze those calls with a conversational and emotional intelligence platform, which provides not only a personality profile of their customer’s stakeholders based on past conversations, but uses Natural Language Generation (NLG) to advise CSMs on how to work with specific people. The software can also match CSMs to customer stakeholders based on their similarity in personality and communication style, which reduces friction in the buying or upselling process, and enables customer-focused individuals to communicate more authentically and effectively.

Companies are wise to explore AI solutions that can help make their teams more emotionally intelligent, and better communicators. Indeed, AI can enhance our emotional intelligence by making us more self-aware and helping us manage key work relationships. Enhancing our emotional intelligence and communication skills makes us more efficient, productive, and empathetic. Although the technology is far from perfect, it is becoming more intelligent every day as platforms increase in data, scale, and sophistication. The technology is in place to make our teams more emotionally intelligent and companies more successful and profitable.

Editor’s Note (1/31/22): We’ve updated the piece to reflect that EarthLink is a privately held company.

 

Copyright 2022 Harvard Business School Publishing Corp. Distributed by The New York Times Syndicate.

 

 

 

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