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AI Mediated Conversation is the Key to Maximizing CX

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Khushbu Raval
Khushbu Raval
Khushbu is a Senior Correspondent and a content strategist with a special foray into DataTech and MarTech. She has been a keen researcher in the tech domain and is responsible for strategizing the social media scripts to optimize the collateral creation process.

Rana Gujral, CEO of Behavioral Signals, reveals how their Emotion AI tool reshapes business interactions. Learn how customized AI-mediated conversations are the future of customer engagement.

In an era where technology continues to redefine human interaction, Rana Gujral, the Chief Executive Officer at Behavioral Signals, stands at the forefront of innovation. With a diverse background spanning from revolutionizing specialty chemical processes with TiZE to pioneering Emotion AI at Behavioral Signals, Gujral’s journey as a tech entrepreneur is a testament to his vision and adaptability.

In this exclusive interview, Gujral shares insights into the transformative power of Emotion AI. This groundbreaking tool is poised to open new doors for businesses, offering customized and finely-tuned interactions aligned with individual customer profiles. Here, Gujral provides a deep dive into the intricacies of this technology and its potential to revolutionize how businesses engage with their customers.

Excerpts from the interview;

What parallels and distinctions define your journey as a tech entrepreneur from TiZE’s specialty chemical processes to pioneering Emotion AI at Behavioral Signals?

I have had the fortunate experience of being a part of several iconic product journeys. At TiZE, we set out to improve archaic business processes for a well-established industry. It was an opportunity to create immediate value in a sector screaming for innovation. The value creation was instant, and we enjoyed the rapid growth from that. 

At Behavioral Signals, we are looking into the future and spearheading the transformation of conversational AI using emotion and behavioral science. We apply our new-age behavioral AI to existing Natural Language Processing (NLP) and Natural Language Understanding (NLU) technologies and, in the process, unravel experiences and capabilities that significantly improve human-to-human and human-to-machine interactions.

Whether a tech entrepreneur or a tech leader, you must stay focused on the ‘why.’ The ‘why’ is your vision statement. It’s your North Star. Leaders may change, founding members may leave, and products may evolve, but the established vision guides your team forward. As a leader, it’s your job to articulate and own this vision. Building a product, solving a problem, or innovating a service category is not a ‘why’, it’s a how.

What are some of the industry sectors that Behavioral Signals cater to?

Our technology can be implemented in any industry that uses voice for communication. Our current customers are in finance and sales. Behavioral Signals has developed an AI technology that, while being language agnostic, allows us to understand the underlying emotions in the flow of a conversation. 

Our technology is called AI-Mediated Conversations, or AI-MC for short, and it’s an automated employee-to-customer matching solution that uses Emotion AI and voice data to match the customer to the best-suited employee to handle a specific call. This match is based on profile data and our AI algorithms developed from years of research and experience in NLP and Behavioral Signal Processing.

Tell us how businesses benefit by integrating Oliver API into their existing systems.

The Oliver API interface protocol empowers enterprises to use our technology outputs and develop custom software solutions. On the other hand, AI-MC is offered as a complete software solution that can be integrated directly into existing telephony software. Businesses don’t have to hire developers or machine learning engineers to integrate it; they just have to add it to their telephony system. We are now integrating with major telephony software providers such as Genesys, among others, to bring AI-MC to all companies via their marketplaces.

So, either a company uses our API directly or AI-MC via their provider’s marketplace, they have the same benefits. Until now, customer communication usually involved random pairing between employee and customer, regardless of a customer profile or employee skillset. Often, that did not work well, causing friction, diminished customer satisfaction, and lost revenues. Regardless of the type of business communication, a sales call, a support call, or a revenue collection call, it will always be an interaction between real humans, where rarely is the affinity identical between two pairs of people. 

We have specific behaviors and traits that help us get along with some people better than others. This is where AI-MC comes in. It automatically matches each customer to the best-suited employee, using emotional AI and Behavioral Signal Processing to empower employees to perform better in each call.

How does AI-mediated conversation prioritize privacy and agent-customer pairing?

We don’t see privacy as enhanced or less-enhanced. For us, it’s absolute, and that means making sure no human can identify who the speaker is. To achieve that, we have very specific processes in place, both in how we handle data and which engineers handle this data. Each customer has different requirements that could lead to deployment on-premises or in the cloud. Data is always treated for removing personally identifiable information (PII); we use strong encryption in all transfers. We are GDPR- and SOCII-compliant; only specifically certified employees can access our customers’ data.

That is the data handling part, but the interesting part is how our technology works. By nature, it protects speaker privacy because it’s language agnostic. We listen and analyze how something is said, not what is said. To give you an example of how AI-MC works, in human terms, our brain can understand anger or enthusiasm when we hear someone talking in a foreign language, even if we don’t understand what they’re saying. Our brains have evolved to grasp the emotional state of other humans, regardless of context. Similarly, AI allows machines to do the same thing more extensively and in a fraction of the time.

What key challenges do your clients seek to address with your tool, and which industries will be most impacted by Emotion AI?

AI-MC impacts several aspects of business, mainly customer satisfaction and revenue recovery. Working with optimal customer-agent behavioral matching means building great rapport between two humans, which can lead to less handling time and first-call resolution. 

Financially, AI-MC allows an enterprise to guide the conversation dynamic to increase collections or sales by predicting which customer-agent match will yield the best chance of a promise to pay or buy. Beyond the improved performance, positive conversations end with satisfied customers and fulfilled employees. A business should treat each customer uniquely and provide the best service to achieve desired results.

Managers can learn from their best-performing agents and focus on positive emotional and behavioral examples to guide everyone’s conversation dynamic and reduce employee attrition. We should not forget that a happy customer means brand loyalty and great word of mouth. Everyone wants to tell a good story of a conversation that went well and might lead to a good outcome without frustration and bad feelings. Good conversations accumulate a positive reputation and love for a brand.

What is that one leadership motto you live by?

Manage the ‘now,’ but don’t lose sight of the ‘goal.’ To be a successful leader, you should be able to process vast amounts of data as you navigate the challenges at hand but continue to see the forest through the trees.

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