Behavioral Signals Analyzes Human Behavior from Voice Data

HackerNoon Reporter: Please tell us briefly about your background.

I’m the CEO at Behavioral Signals, an enterprise software company that develops AI technology to analyze human behavior from voice data. In 2012, I led private equity-backed Cricut's turnaround from bankruptcy to profitability. Cricut held its $4.4 billion IPO in April 2021 and is worth approximately $8B today. In 2014, I founded TiZE, ML-based cloud software for specialty chemicals which was acquired in 2016. Among other companies, I’ve worked in leadership positions for Logitech and Kronos Inc.

What's your startup called? And in a sentence or two, what does it do?

Behavioral Signals is an enterprise artificial intelligence software company that excels at distinguishing signals in speech data with its proprietary deep learning technology.

Human communication is a complex process that depends on not just the words being spoken but also the way they are expressed. Our flagship product AI-MC uses the power of our patented tonality engine to build rich behavioral profiles (conversational bioprints) for parties involved in the conversation. AI-MC automatically matches each customer to the best-suited agent using voice data and emotion AI and affects the overall performance and outcomes of call center conversations.

What is the origin story?

The company founders, Alex Potamianos and Shri Narayanan, are accomplished scientists and academicians. Shri, who is a founder and executive director of the coveted SAIL institute at USC, built early models that analyze human emotions and behaviors from the tone of voice and used these models to increase engagement in emotionally challenged situations such as interactions with autistic kids. Behavioral Signals was spun out of USC in 2016 and has since focused on more CX-centered use cases.

What do you love about your team, and why are you the ones to solve this problem?

Our team includes accomplished researchers and senior engineers that deeply understand natural language and behavioral signal processing.

The goal of pushing the boundaries of current technology is at the core of what we do. Our algorithms analyze human emotions and behaviors, transform data into usable information, and lead to making better business decisions. Until now, human emotion has been considered impossible to quantify and impossible to measure. With our patented analytics engine, we have brought to market a science to measure and interpret the “how” part of human interactions.

We are bridging the communication gap between humans and machines by introducing emotional intelligence, from speech, into conversations with AI.

Based on extensive research spanning 2 decades, we have created an AI technology that enables matching a customer to the best-suited agent to handle a specific conversation. Humans have specific behaviors and traits that help us get along with some people better than with others. Our technology taps into this knowledge and equips our clients to improve call-related outcomes and customer satisfaction.

If you weren’t building your startup, what would you be doing?

I am an early-stage investor and sit on boards of several companies. I love leveraging my experience to help young startup founders grow both personally and professionally. I’m also an avid cyclist and tend to spend a fair share of my free time on the trails. I coach the NICA mountain biking team at Monte Vista High School.

At the moment, how do you measure success? What are your core metrics?

Up till now, communication with customers 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, the conversation dynamics between the two participants are rarely identical. We have specific behaviors and traits that help us get along with some people better than with others.

This is where AI-MC comes in. It automatically matches each customer to the best-suited employee, using Emotion AI and Behavioral Signal Processing, and empowers employees to perform better in each call. Our AI-powered match-making engine impacts several core metrics such as CX, FCR, Call-Time, Revenue Recovery, etc. Our deployments in the industry have consistently delivered a 12-17% increase in revenue recovery, +8% increase in call success ratios, and over 10% increase in customer satisfaction.

What’s most exciting about your traction to date?

The fact that we’re getting interest from companies from all over the globe, regardless of language. We derive signals from the tone of voice, basically ‘how’ something is being said and not the ‘what’ or words being spoken. This ‘special sauce’ allows us to be completely language agnostic. We have clients that speak English but also Spanish, Russian, Greek, and other languages.

An added benefit is that an absence of using a transcription engine frees us from aspects such as ‘redaction.’ There is simply no text to redact! This enables us to be GDPR and SOC2 compliant, which is a key ask from our clients in the financial sector.

What technologies are you currently most excited about, and most worried about? And why?

Ethics, bias, privacy, and security are important considerations in all technologies. This is especially true for AI. Many people think of AI as a black box, often as a tech that is bound to get out of control. This is not true, but AI may involve complex neural engines that we may not be able to effectively influence at some point. This is the concern with Singularity. AI has fantastic possibilities to accomplish things beyond a human’s reach.

AI has the potential to improve our lives in health, education, transport, communications, and within our homes. Having said that, I believe it’s imperative that the decision-makers have a clear understanding of the technologies involved and make informed choices that take into consideration aspects beyond just profit-taking. Privacy, ethical use, security, unbiased outcomes should always be of primary importance.

What drew you to get published on HackerNoon? What do you like most about our platform?

Hackernoon is my go-to place for great tech content, and I love the cultural platform you have created. I’m a fan of your work and grateful to be a part of this community.

What advice would you give to the 21-year-old version of yourself?

“Don’t play too safe. It’s not worth the risk!”. Our entire mindset around risk-taking is entirely skewed by society. What we hear about taking risks, and about what risk actually is, and what it means not to take a risk is entirely out of date.

The other thing of importance is to cultivate an early ability to see the forest through the trees. One always needs to look beyond what you’re currently working on. What often holds smart people back is their tendency to become so focused on what’s currently surrounding them that they lose their grasp of what’s ahead.

What is something surprising you've learned this year that your contemporaries would benefit from knowing?

I’ve learned that we are a lot more resilient than we think we are. Resilience is hard to assess as it differs from other concepts such as mindset or adaptability because it happens in the face of unexpected or difficult circumstances. To build your resilience skills in the new year, try some of these strategies: View your decisions as active choices - not sacrifices. Believe in yourself more View stress and setbacks as opportunities to push yourself.

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