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Podcast Episode 121: the hidden value in your contact center and how to listen at scale with Authenticx’s Amy Brown

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Authenticx CEO and Founder, Amy Brown, discusses the power of listening at scale in the contact center industry. She shares her personal experiences and how they shaped her understanding of the importance of listening to patients and customers.

Brown emphasizes the need for organizations to listen to the authentic voice of the customer in order to drive positive healthcare outcomes. She also highlights the barriers to effectively utilizing conversational data and the ethical considerations of AI technology.

Brown provides insights into how Authenticx’s platform helps organizations unlock valuable insights and drive innovation through listening. She concludes by offering three key questions that organizations should ask when evaluating suppliers of systems for listening at scale.




00:00 Amy Brown

After looking at some graphs and some charts, we played a montage.

It was probably a minute long with maybe a few different customer voices.

And as soon as that call montage was over, we paused and we waited to see what the members of our client’s team in the room had to say, and we were not prepared for the emotion that they reflected back to us.

Most of these leaders in the room had never really heard their patient’s voice before and it was transformational.

We heard empathy.

We heard colleagues saying,

“I had no idea how hard your functional area was working to solve this problem.”

It was profound, a profound moment of elevation, of the whole purpose of why we were meeting, and we’ve just found over and over again that listening to the actual human voice, there’s just nothing quite like it.


01:20 Oscar Trimboli

In this episode of Deep Listening: Impact Beyond Words, we hear how to listen at scale in your contact center.

In this conversation, we speak to Authenticx’s CEO and Founder Amy Brown.

Authenticx is a software platform that analyzes and activates patients’ voices at scale to reveal transformational opportunities in healthcare.

Amy built her career as an executive in the healthcare industry, and during that time, she advocated for underserved populations, then led and mobilized teams to expand healthcare coverage to thousands of Indiana residents.

In 2018, Amy used her decades of industry experience to tackle the most pressing problems in healthcare through technology.

She founded Authenticx with a mission to bring the authentic voice of the patient into the boardroom to create positive healthcare outcomes.

After listening to Amy’s backstory, I thought it was so compelling, we should start there before we move on to that question, what’s the cost of not listening?

Let’s hear from Amy.



02:39 Oscar Trimboli

I’m curious. As we step back, there seemed to be some touch points in your educational background, in your family history that created the intersection of listening at scale and ultimately Authenticx.

02:55 Amy Brown

Yes. I’m the daughter of a pediatric cardiothoracic surgeon, who started his life as a farmer and put himself through medical school, farming. And when I was school age, my dad started to invite me into see some of his surgeries, and I don’t remember a ton about being in the operating room but what I do remember is how he spoke and listened to the families after the surgery.

I remember him being extremely present for that family and taking all of their questions and taking all the time in the world. And I remember one day he said to me,

“Amy, if you ever want to really understand and know what a patient is going through, you really just need to listen to them. They will guide you to the right diagnosis and the right course of action to take just by listening. Yes, we have all these diagnostic procedures and tests, but one of the most important things you can do is listening.”

And that has always stuck with me, and even though I quickly found out in my journey of education that I probably wasn’t made for the clinical side of care, I became really fascinated with systems of care and how we can use data and insights to transform how our healthcare system serves patients.

I pursued a career in doing that, really focusing on the macro side of our healthcare system, and I just found that listening to conversational data became the light of where to go next and what to do in terms of policy change, business change, etc.

04:50 Oscar Trimboli (04:50):

One thing he did do is show you the power of a heartbeat.

04:56 Amy Brown

He did, absolutely. I got to go on my first and only heart transplant.

He woke me up in the middle of the night and asked if I wanted to go on a heart transplant, and so I got up and we drove to an airport and got into a little plane, and I went down to the southern part of our country to harvest a heart from a pretty tragic situation, flew home, and I got to watch him put it into a child and watched it start beating, and it was pretty powerful.

05:31 Oscar Trimboli

Yet, you also got to listen to the family of that child afterwards. What did you notice?

05:41 Amy Brown

I noticed relief at a magnitude that I’ve never seen before.

I noticed the expressions of gratitude.

I noticed my dad really being quiet, using silence in between to communicate his care and compassion for their child.

And I realized that there’s more to healing than our medicines and our surgeries and our innovations, that part of the healing journey has to do with human connection.

And yes, in this example between my dad and the family, it’s a pretty dramatic example.

Even with what we do where we’re listening to call center recordings that happen by the billions every day across our world, even inside those five minute, nine minute, ten-minute conversations, there’s an opportunity to connect with another human being and that there’s something to be said for healing even in those little micro-moments.

07:02 Oscar Trimboli

In your time in college, you probably took a nontraditional path to the C-suite. I’m curious how your college education created a very different listening perspective for you.

07:15 Amy Brown

Yes. After I decided I wasn’t going to walk directly in my father’s footsteps, I ended up pursuing a degree in a master’s program in social work.

I thought that I would spend a big chunk of my career either in social services or in government.

I quickly was able to move in a direction of the business side of healthcare, and my education really helped me approach business with a different perspective.

I wasn’t coming in with a master’s in communication. I was coming in with a deep understanding of the human condition, human development, a great deal of psychology, but I was also coming in with more grounding and knowledge on the consumers that we were serving because I had spent so much time understanding vulnerable populations.

And so I brought that perspective with me into the C-suite as my career had progressed and, honestly, some of my social work skills were used right there in the C-suite with colleagues and interpersonal relationships. I am grateful for my education.

08:28 Oscar Trimboli

Amy, what’s the cost of not listening?

08:30 Amy Brown

In our business, we listen to conversations that happen in healthcare, and the cost of not listening is resulting in patients not getting access to the medication they need, caregivers who are desperate to find help but can’t seem to get to the right people who can do anything about it.

The cost of not listening means that healthcare organizations in the United States especially are sitting on a dramatic amount of wasted effort and time while patients are suffering from not being able to get care, the care that they so desperately need.

So it’s a very significant problem in the world of healthcare, which is the world that my company resides in.

09:28 Oscar Trimboli

So we say the difference between hearing and listening is action.

A lot of organizations are sitting on a vast mountain of not only data, they’re also sitting on insights.

They’re hearing.

They’re recording the call for quality assurance purposes.

What’s been the barrier to them taking the information and the insights that’s collected on that call and converting it into meaningful impact?

10:00 Amy Brown

Yes, I think there’s a couple of barriers, one that’s more technological and another that is philosophical.

On the technological side, conversations, while they’re rich in nuance and insight, essentially it’s unstructured data, and unstructured data is very hard to mine, to organize, to make sense of it.

Organizations for decades have been recording conversations that they have with customers and literally just storing them in their digital storehouses, and they store them for regulatory reasons or for the occasional escalated call where someone needs to go find a recording and use that to retrain an agent.

More recently, technology exists to be able to listen at scale, taking that unstructured data and being able to sort through signals and allow human beings to really find and discover the types of insights they need in a data source that has been inaccessible historically.

11:16 Amy Brown

The philosophical barrier that has existed, and I used to be one of these people, there’s this notion or this idea that these conversations that happen inside call centers that they’re transactional in nature and that surely, they don’t include anything of value that might help my organization’s strategy or mission or innovation.

And it was through listening and doing work the hard way of actually listening to these call center interactions myself that I realized that there was so much humanity locked up in these conversations and so much opportunity for businesses to learn and to respond more effectively if they could only listen. We’ve been trying to help the industry understand that their call center data, it is so valuable, probably the richest source of insights they own, and they just need to change their paradigm about how they think about it.

12:19 Oscar Trimboli

Do you have a story that brings to life the power of the insights being unlocked?

12:26 Amy Brown

A health system, a system that’s geographically located that includes a hospital and clinics and multiple doctors’ offices.

This was during the heart of COVID. And what was being identified by the nurses on the ground was there was this sudden influx of conversations that were coming into their contact center, desperate parents who were seeking mental health care for their teenage children.

What had happened seemingly overnight was with all of the impact of COVID sending children out of the schools and onto their laptops, they were feeling this sense of isolation, and there was a growing number of concerns from parents that their kids were suicidal.

And what was happening is that these nurses were getting these calls one by one, but it wasn’t until Authenticx took in all of the calls that we could actually see the prevalence of them.

We could actually look at all the calls coming into their healthcare system and say,

“Hey, this isn’t just a one-off anecdotal situation. This is happening dramatically, abruptly.”

And there are some significant concerns in this hospital systems community where we were able to use this data to elevate it to not only the leaders of the nurse triage team but the hospital administrators who were able to take much better informed action to make sure that mental healthcare was accessible and available to these parents.

14:06 Oscar Trimboli

What is Authenticx listening for? Because there would be hundreds, thousands, tens of thousands of calls that are coming in and the way people express the same idea could be completely different.

14:21 Amy Brown

We utilize artificial intelligence, but AI is only as good as the data on which it is trained.

And so Authenticx trained its algorithms by employing human beings that work inside the healthcare system to listen with their own to human ears to conversations, thousands and thousands of them, who could start to interpret and label conversations with signs of friction that the customer was expressing.

These are individuals who not only understand the spoken word in the conversation, but they understand more deeply the context of the situation.

These data labeling linguists have been trained to understand and interpret how different cultures, how different demographics, how different ages, races, speak about their concerns.

And it’s through that process of labeling and calibrating internally that we’ve been able to develop algorithms that listen for customer pain, that listen for the very human expressions of desperation, of hopelessness, of worry, of concern, and that’s how we use AI to find signals or pockets of interactions that contain some negative sentiment.

But then of course, nothing replaces actual human ears. Our technology is not only designed to detect these signals but to allow users of our technology to drill into them and listen with their own ears so that they can really validate and contextualize the signals that AI has brought forth.

1610 Oscar Trimboli

That massive effort in coding with humans, one of the things that people calling into these contact centers have a vast range of queries.

They may have clinical queries, yet equally, they may have billing queries and they may just have very simple administrative requests to update certain records.

What was surprising in the process of having these humans start to code?

16:41 Amy Brown

One of the earliest surprises was just how stuck customers are in trying to solve simple problems. We saw vast evidence that healthcare consumers, caregivers were spending hours a day trying to solve a problem, and this became evident because we were able to collect all the interactions associated with a single customer, and we were able to quantify the total amount of time that customer had spent across those interactions.

We could also quantify the amount of business time being spent on these problems.

And I remember going home one day and talking to my husband about this phenomenon we were seeing in the data with people just cycling over and over again, and he pretty insightfully reflected back to me that sounds, that phenomenon sounds like a river Eddy, which is water flowing down a current of a river, when there’s an obstruction in the current, it creates a countercurrent flow like a whirlpool.

From that early experience of studying the data, we developed an algorithm called the Eddy Effect, and it’s really designed to listen for friction where customers are just working really hard and businesses are spending a lot of time on problems that are truly preventable if they only understood what was at the root of driving those problems.

18:18 Oscar Trimboli

One of the things that people don’t realize about the contact center is it’s the biggest source of innovation. It’s the biggest source of research and development.

One of the things when I work with my clients is stop doing additional research. Go back and listen to the top 10 things that people are coming into the contact center for.

Now when people think of innovation, a lot of people think about light bulb moments that create products, but there’s also innovation in process and ultimately, there’s innovation for the purpose of the organization.

How does Authenticx unleash innovation through listening at scale?

19:02 Amy Brown

Yes, I love that description of innovation.

One of the things that we have seen inside these very large organizations that we serve is that the insights that are locked inside of an operational contact center, they’re actually value inside of those conversations that could inform strategy, that could inform the C-suite, that could inform shareholders, that could inform the innovation side of the business.

What we’ve seen happen is leaders who have transformed how they glean insights by using conversational data as a unifying source. And so no longer are call center operators the only ones who are leveraging this technology.

Now we’re seeing organizations create corporate listening programs where they bring all the functional areas together not only to review visualized data from conversations that are listened to at scale, but they’re also listening to what we call montages.

Think of them as compilations of segments of customer voices that are talking about a topic or a theme that matters to our clients and that have been tagged accordingly.

And what we’re seeing happen with these leadership teams cross-functionally is that they’re being inspired to change because it’s that combination of the visualized data and listening to the actual literal voice of their customers that is triggering both their cognitive brain and their primal brain, and it’s creating this really in-depth aha moment, and that is what we’re seeing drive change within organizations.

It’s like this data back storytelling movement that is the biggest innovation is just how they listen and what they do with this conversational data.

21:04 Oscar Trimboli

It sounds like you’ve built a Spotify playlist to bring the voice of the customer to life.

21:11 Amy Brown

Yes. We incorporate call montages in almost every customer engagement because we’ve seen how powerful they are.


A few years ago, we were a part of a launch of a new pharmaceutical product that was really geared towards solving a pretty significant chronic healthcare condition. And the team we were working with at this life sciences organization, this was a big deal, a big launch, and we were preparing and finally had our very first insight session where we were showing our clients the data,


  • What were the early calls in these call centers?
  • What did they sound like?
  • What were the customers and the caregivers of the patients talking about?

And I remember we played our very first call montage. After looking at some graphs and some charts, we played a montage. It was probably a minute long with maybe a few different customer voices.

And as soon as that call montage was over, we paused and we waited to see what the members of our client’s team in the room had to say, and we were not prepared for the emotion that they reflected back to us.

Most of these leaders in the room had never really heard their patient’s voice before, and it was transformational.

We heard empathy. We heard colleagues saying to colleague, “I had no idea how hard your functional area was working to solve this problem.”

It was a profound moment of really elevation of the whole purpose of why we were meeting.

And we’ve just found over and over again that listening to the actual human voice, there’s just nothing quite like it.

23:02 Oscar Trimboli

The difference between hearing and listening is the action and the impact. As I hear these stories, they reinforce that return on investment is visible in your contact center if you just took the time to listen to the insights that were created.

Every impact is a collection of one story at a time, every patient, every employee, every researcher, every clinical trial, every review of somebody’s treatment plan.

Listening at scale has ethical consequences because it allocates resources, it builds models that include and exclude information that are used to train systems.

Amy, as you think about the future when it comes to ethically listening at scale, what are the big investments Authenticx has made to ensure that they’re ethical in the way they build technology to serve patients and customers?

24:10 Amy Brown

When we think about AI and AI listening, one of the most important things I think all potential buyers of AI technology must know and pay attention to is that AI is trained on data. And it is critically important that we become very wise consumers of AI technology by asking how and what is training your models.

The reality is that many AI solutions today are getting their training data from very publicly available sources that are massive across the internet, Facebook, Wikipedia, these types of sources. And the problem is that that training data may or may not be accurate and it likely is very skewed in terms of being inclusive across cultures and demographics, and what that can lead to is way too many assumptions being made by AI that are incorrect.

There’s this just crazy phenomenon going on right now with the AI hype cycle that buyers are assuming that AI is smarter than humans, and the reality that AI is trained by human data and often it gets it wrong.

So Authenticx has made a pretty significant investment of the capital that we have been able to raise over the course of our tenure, and we’ll never be able to completely eradicate all bias, but one of the most important things we can do is be intentional. Be intentional about how we are training our algorithms.


And for Authenticx, one of the investments we’ve made is to not outsource our data labeling efforts to instead employ human beings who represent a diverse group of individuals in our community, ones that come with different languages, different races, different demographics, and who carry this significant responsibility of not only listening but also interpreting what’s being said.

And we take that very seriously, and we calibrate internally as a team on a regular basis to make sure that what we’re tagging and labeling makes sense for the use case.

The second part of our investment is when we launch with a new client, we always invest a part of our time listening to tune the models to be appropriate for that client’s set of conversational data.

We might have one client that has customers that are on Medicaid and they have unique challenges compared to customers who are commercially insured.

It’s important that we approach AI solutions with a knowledge that different types of humans bring different types of problems and perspectives to their healthcare. And that must be captured if we’re going to have truly meaningful AI that actually solves some business problems.

27:33 Oscar Trimboli

And in that story, I can hear your background around serving underserved communities.

How do you think you approach and listen differently because of your deep empathy for these underserved communities?

27:48 Amy Brown

Much policy change, whether we’re talking inside corporate worlds or government, the voices that are loudest are well-funded and that have an agenda that drives back to a financial or commercial opportunity.

And the great thing about conversational data as a new source, a new channel, is that it brings accessibility of a more diverse, inclusive set of voices to the table because we’re able to take in a hundred percent of the universe of a big organization’s call center data and find the prevalence of issues and surface those voices that have historically been underrepresented or not had a place at the table.

And so that makes me very excited because if we’re going to make policy change, then we better do so with a complete set of data, and this is a great opportunity to do that.

28:57 Oscar Trimboli

Amy, we’ve talked a lot about how Authenticx listens and how it listens at scale on behalf of their customers.

Yet, for people who are evaluating suppliers of systems that help you listen at scale, what are the three questions they should be asking?

29:12 Amy Brown

The first, how are they training their algorithms?

It’s supremely important because if you’re counting on making an investment that actually drives business value, it’s important to have confidence in the training data that created the foundation for those algorithms.

Secondly, what are the business results that you have actually driven with this technology?

Because there’s such a hype cycle right now of individuals being told to go purchase AI, it seems that so many people are focused on buying AI without actually tying that AI solution to a true business result.

Ask those suppliers, what business results have you or do you drive?

The third question is what about the customer voice?

And the reason I say that is because most call center AI technologies are really focused on evaluating the agent side of the conversation, auto-scoring their quality, using data to correct during a phone call what the agent is saying, and there’s another side of the conversation, and that side of the conversation is the customer.

And most technology is just really not focused on that customer’s voice, and that’s a really important component to compounding the value of conversational data.

30:51 Oscar Trimboli

How has the Authenticx platform helped you and your leadership team listen differently to each other?

30:59 Amy Brown

I would say that it’s harder than it may seem.

Here we are, our business is designed to help humans understand humans through the power of listening.

But it turns out that actually practicing that in your leadership team, especially when you’re on a fast-growing business, a tech startup, it’s hard. It’s hard.

What I can say is that our mission is front and center at all times. When we feel that we’re getting off track, it’s really helpful for us to step back and say,

“Hey, if we can’t listen to each other in a way that is productive, then how are we going to lead a movement, a global movement to change the way humans inside corporate organizations listen?”

And so it’s a great accountability holder for sure.

31:57 Oscar Trimboli

Whether you work in large organizations with contact centers or you’re one of those people who’s called a contact center, today, I’m sure you’ve discovered something that will help you think about listening in a completely different way.

A few things I’ve taken away from today’s conversation are how do you listen ethically, not just at scale?

  • How do you listen ethically in a one-on-one and a group situation?
  • How are you coding what you hear?
  • How are you making sense?
  • What does it mean to you?

And more importantly, are you hearing from all the voices or just the voices of the loudest who’ve got their own outcomes to focus on?

I was touched by Amy’s story and particularly how her and her father spent their teenage years together.

I think that’s a unique gift that a farmer who became a doctor was able to pass on to his daughter, and more importantly, the gift that Amy is passing on and the legacy she’s creating by making healthcare more cost-effective, more accessible, and when the healthcare is delivered, it has the intended impact.

I love that story about the pharmaceutical company and the research they were doing to get medication to market as quickly as possible, and the director that rarely heard from patients’ voices and the impact of that compilation of just minute of client’s voices and how it changed the emotion in the room.

Over to you, I’d love to hear from you. What are you taking away from today’s discussion with Amy?

Send me an email at

with the subject line  SCALE

and let me know, what did you take away from this conversation as somebody who is a patient in the healthcare system? Maybe you’re part of an organization that uses a contact center.

  • Are you getting the most out of it?
  • Are you really listening to the compilation of voices or are you just looking at graphs?
  • What was the one thing that Amy said about listening at scale that really changed your mind?
  • And finally, what’s one thing you’ll do differently as a result?

To mark the first day anniversary of the three-time award-winning book, How to Listen: Discover the Hidden Key to Better Communication, we created a visual summary, 24 pages that outlines each chapter of the book in visual representations, created by Rebecca Lazenby.

I want to share with you a message left by Charity when she was going through the visual summary of the book.

34:59 Charity Becker

As an adult with ADHD who had the real thick book on my pile of books to read for it must be close to 12 months now, if not more, this visual representation of it.

I’ve sat down and read this once already. I’m going to flick through it again. I’m going to be able to show this to my kids. It is accessible, absorbable, beautiful, completely suits my learning style.

There’s already moments in this that I’m attaching to pictures, so I’ll be able to click through it and go, “Oh, what’s that thing that Oscar says about that thing?”

And find the picture. It is a gorgeous, delightful addition to this work, and I’m very grateful for it and impressed by it. So thank you.

35:40 Oscar Trimboli

To mark the first anniversary of the book, I’m giving away 12 copies of the visual summary, a 24-page representation of over 40,000 words in the book, How to Listen.

Just send me an email at with the subject line, SCALE, and the answer to those three questions.

Now for staying all the way to the end, we’ve got a little bonus, Amy’s reflection on how I was listening.

I’m Oscar Trimboli, and along with the Deep Listening ambassador community, we’re on a quest to create 100 million deep listeners in the workplace, and you have given us the greatest gift of all, you’ve listened to us.

Thanks for listening.

36:32 Oscar Trimboli

Is there anything you’re noticing about how I’m listening?

36:35 Amy Brown

I’m noticing that you are taking a breath in between when I stop a sentence and you start one. It feels very intentional.

36:47 Oscar Trimboli

Anything else?

36:51 Amy Brown

I appreciate your very open-ended questions.

When you say, “I am curious about, can you tell me more about,” that is a great way to elicit from me details and elaboration.

You’re not making any assumptions.

37:09 Oscar Trimboli

And is there any examples that will help me reinforce my learning there?

37:13 Amy Brown

Yeah. When you mentioned the heartbeat, I’ve never heard that reflected back to me, and that definitely elicited some stories and some thinking on my part that I wouldn’t have otherwise shared.

And you drilling into the story of watching my dad speak and talk with the family after the fact, I’ve never shared that before.

I want you to know that the other day, I had given the book to our chief technology officer. He’s an engineer. Okay? He’s an engineer.

And so I gave him this book and he just got right into it. And a few weeks later, I got wind of a message he sent to our head of sales. His text message said, “Your salespeople need to read How to Listen,” and it was just a humorous moment. So your book is making a difference, and I’m amazed at how much it resonates with me. So great work.

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