What is Conversational Intelligence and How Does It Work?

Conversational intelligence is a term used to describe how humans naturally understand interpersonal communication. It includes both verbal understanding and nonverbal awareness (i.e., the ability to “read the room”). For example, during a conversation, if one person detects frustration in another and responds empathetically, he or she is demonstrating a high level of conversational intelligence.

Humans are naturally hardwired for conversational intelligence; however, that skill is often muted when shifting from in-person to digital communication. Without real-time, face-to-face feedback, humans struggle to accurately interpret conversational cues, like facial expressions or tonal inflections that may indicate sarcasm, disapproval or disengagement. However, recent advances in technology are helping to bridge that gap.

Conversational artificial intelligence, or conversational AI, can help augment the conversational intelligence lost during remote interactions. Combining artificial intelligence, machine learning and natural language processing (NLP), conversational AI software can not only understand what people say, but also how they say it, including the intent, sentiment and meaning driving every interaction. That ability to recognize and understand human language and conversations—including nonverbal contextual cues—is crucial to achieving conversational intelligence, particularly during remote conversations.

How does conversational AI impact conversational intelligence?

By understanding what people say and the nuances of how they say it, conversational AI can enhance a speaker’s conversational intelligence by alerting them to missed or muted cues and enabling them to make adjustments as needed. Taking this deeper, another concept of conversational AI is for the technology to understand not only when a person talks to it directly but also conversations between people. For example, during video sales calls, conversational AI can run in the background as a “copilot” and update the seller on the buyer’s level of engagement and receptiveness. This capability boosts the seller’s conversational intelligence significantly, improving their ability to connect with the buyer and—most importantly—their chances of making the sale.

Things get more complicated when multiple people are part of a conversation, such as in a meeting with several voices and people interrupting each other. However, with advanced conversational AI—enhanced with computer vision and emotion AI—conversation leaders can isolate, identify and analyze individual voices (and faces) in the crowd and leverage that data to ensure every participant is heard and understood.

Understanding the science of conversation

Conversational intelligence is complicated for a number of reasons. It’s often challenging for people to understand their fellow humans’ intent, so training machines to decipher conversation can be difficult. To understand how machines can transform remote interaction, it’s vital to understand the science behind human conversation.

Discussions between people involve a wide range of factors, from bias, connections and judgment to control, power games and trust. As such, conversations aren’t simply processes for sharing information; they also establish and exert emotional and physical responses in the brain that encourage people to trust each other, engage in meaningful conversations or cease a discussion.

The neuroscience behind conversation teaches that a discussion can produce hormones and neurotransmissions that stimulate the brain and nerves. If a person’s brain senses tryst, it activates a trust network in the prefrontal cortex, which processes complex thinking. This means the person is more likely to lean towards trust factors like bonding, creativity, innovation and openness.

On the other hand, if a person’s brain senses distrust, it triggers a fear network in the amygdala and limbic areas. When this occurs, the person will struggle to focus and switch off from the conversation. 

The need for conversational intelligence today

From a business perspective, conversational artificial intelligence helps organizations understand buyer motivation, build stronger connections, and coach their teams to become more customer-centric. AI conversation intelligence technology enables companies to capture buyer sentiment and engage with customers more effectively by recognizing verbal and non-verbal signals.

Conversational AI has the power to transform customer-facing teams with smarter, more effective processes and enable individual reps to become more effective than ever. The benefits of conversational intelligence for your sales organization include: 

Revolutionize Virtual Meetings

Conversational intelligence solutions use tools and techniques like emotion AI and generative AI to gain insights into live conversations. The technology can accurately capture post-meeting summaries and can empower sellers to conclude deals more confidently.

Unlock Qualitative Buyer Insights

A critical advantage of conversational intelligence is understanding the conversations, demos, products, slides, solutions and more that hit the mark with buyers. The technology measures a buyer’s reaction during interactions, helping you pinpoint how effectively your content and conversations truly resonate with customers. It goes beyond topic recognition to decode buyer reactions and gain instant feedback that provides brands with a lucrative competitive edge.

Validate Sales Methodology

Critically, conversation intelligence technology in business provides clarity on how well sales methodologies and processes are being implemented. You can gain insight into deals, sellers and teams to identify opportunities for employee coaching and improving the buying experience.

What is conversational intelligence used for?

Conversational intelligence is being used to improve sales engagements across multiple B2B industries. Here are a couple of examples of how Uniphore’s conversational intelligence solution, Q for Sales, is helping organizations worldwide.

Conversational intelligence enhances customer engagement

Digital consulting firm Lunavi operated a complex selling process that relied on teams to engage tightly with customers and build relationships through video calls. It often struggled to fully understand customers’ pain points and how to solve them. 

Uniphore’s Q for Sales technology enabled the organization to carry out deeper analytics behind its salespeople’s conversations. This enabled Lunavi to shape solutions precisely to meet its customers’ needs and drive efficiency across the organization. As a result, the conversational intelligence AI technology saves salespeople huge amounts of time and ensures sales leaders have the confidence that they’re meeting clients where they need to meet them.

As a result, Lunavi can now gain more accurate insight into the interactions sales teams have with customers. It can also onboard new sales team members more effectively and help customer service reps unlock greater insights from a call. In the words of Lunavi President Shawn Mills: “Q for Sales takes a ten-person sales organization and makes them equivalent of a twenty-person sales organization.”

“Q for Sales takes a ten-person sales organization and makes them equivalent of a twenty-person sales organization.”

Shawn Mills, President, Lunavi – Formerly Green House Data

Conversational intelligence transforms sales operations

Software firm DuploCloud had struggled for years to manage the volume of calls it received through its existing tools. Sales leaders struggled to find the recordings and transcripts they needed to monitor customer interactions, experienced security issues, and the post-sale handoff to engineering was manual and time-consuming. 

Uniphore’s Q for Sales technology helped DuploCloud address these challenges, removing the need for manual searches to discover any call in seconds, recognize interaction engagement and sentiment at a glance and easily measure seller emotional intelligence. The technology also helped the company’s sales leaders speed up onboarding and analyze critical sales metrics like empathy, hesitation, politeness, ratio and talk speed to enhance coaching session quality. 

As a result, Q for Sales enables DuploCloud to save significant amounts of time by reviewing lengthy meetings in a matter of minutes. They could also share call recordings immediately to slash the post-sale handoff to engineering and help new salespeople get up to speed faster.

8 tips to optimize conversational intelligence

Companies across all industries can reap similar benefits by implementing conversational AI across their sales organizations. These results can’t be achieved by simply purchasing the technology and placing it in your technology stack. So here are a few best practices to maximize the potential of conversational artificial intelligence.

Align conversational AI with business goals

The first step to conversational AI success is to outline why you want to use the technology and the goals and objectives you need it to achieve. It’s vital to outline your specific challenges and assess how conversational AI technology will address them. Plan what you want the technology to achieve, put a timeline in place for this success, and set objectives to monitor its success. 

Ensure seamless integration with your existing tech stack

Any technology you implement within your sales organization must integrate with the existing solutions in your technology stack. Your conversational intelligence solution is no different, so consider how well the technology will integrate with the programs and tools your salespeople are currently using.  

Choose the right conversational AI solution

How to choose AI-powered conversational self-service solutions is a common dilemma for many businesses. It’s vital to assess several conversational AI solutions to ensure you find the technology best aligned with your sales team’s goals, needs and objectives. Start this process by evaluating the challenges you face then research and test the solutions available before making your decision. 

Focus on continuous learning and AI training

It’s crucial to continually improve processes and learn from the data your conversational intelligence AI technology generates. Look to AI technology to recommend new ways of working, opportunities to streamline your sales organization’s processes and workflows and tactics for improving salesperson performance. Continuously improving in this way will help you identify new trends and quickly adapt to changes.  

Implement robust data privacy and security measures

When introducing any new technology into your sales organization, it’s critical to protect data privacy and security. This includes implementing robust strategies and processes around data captured in all customer interactions and ensuring information is securely stored and easily accessible. You must also develop strict data governance policies that comply with increasingly stringent federal, industry and international data regulations. 

Target high-quality data

Conversational intelligence AI tools generate vast volumes of data from listening to, analyzing and transcribing conversations across your sales team. It’s crucial to prioritize high-quality data and integrate all customer channels into the tool to ensure the best results. 

Measure performance and adapt strategies accordingly

Selecting and implementing the right solution for your sales team isn’t the end of your conversational intelligence journey. By monitoring the performance of your conversational intelligence software, you can identify opportunities for improvement and discover new approaches that transform the performance of your sales team.  

Encourage real-time employee insights

The data-driven actionable insights generated by conversational intelligence put real-time assistance at the fingertips of your salespeople. These insights, such as emotion AI and  generative AI, help salespeople gain real-time insights, better understand customer needs, be more productive, achieve first-time resolution and build more engaging relationships with customers.

Boost your virtual sales strategy with Uniphore’s conversational intelligence solution

Technologies that enhance conversational intelligence strengthen the connections businesses make with their customers. Advances in conversational AI deepen machines’ understanding of the nuances of human language, which amplifies sellers’ awareness of conversational cues and variations—an essential component of successful selling, particularly in today’s increasingly virtual world. 

Innovative conversational intelligence platforms, like Uniphore’s multimodal conversational AI and data platform, use tools and techniques like emotion AI and generative AI to unlock deeper contextual information and ensure conversations are engaging, empathetic and multi-sided. Running on the platform, our conversational intelligence solution, Q for Sales, captures buyer sentiment and verbal and non-verbal behavioral signals to help sellers engage contacts more effectively and close more deals. With Q, every voice in the conversation is heard and fully understood—even when the speakers are thousands of miles away. 

Discover how Uniphore’s conversational intelligence technology can transform your communication strategy by exploring our conversational intelligence software.