Are you leveraging AI to streamline your business processes, or is it just another tech trend you’re observing from the sidelines?

 

In today’s episode, we demystify the integration of AI into less tech-savvy sectors, focusing on substantial benefits over the tech hype.

 

Joining us today is Benjamin Brown, Vice President at AKASA, a leader in generative AI solutions for healthcare revenue management.

 

With a rich background spanning from journalism to marketing major AI-powered platforms, Ben shares invaluable insights into marketing AI effectively, ensuring it’s accessible and beneficial to all.

 

Mentioned in this episode:

Transcript

 

Voiceover: This is Performance Delivered, Insider Secrets for Digital Marketing Success with Steffen Horst and Dave Antil.

 

Steffen Horst: Welcome to the Performance Delivered Insider Secrets for Digital Marketing Success podcast, where we talk with marketing and agency executives and learn how they build successful businesses and their personal brand. I’m your host, Steffen Horst. 

 

In today’s episode, we’re going to talk about how to market AI to a less tech savvy audience. Here to speak with me is Benjamin Brown, the Vice President of AKASA, the preeminent provider of generative AI solutions for the healthcare revenue cycle. Ben enables the country’s healthcare systems to embrace and adopt generative AI for revenue cycle management. 

 

He previously served as VP of Marketing and Customer Experience at ConverseNow, where his team led the widespread adoption of voice AI across the restaurant industry. Ben holds advisory roles for multiple high growth technology companies, and serves on the board of several universities. Ben, welcome to the show.

 

Benjamin Brown: Steffen, thanks a lot for having me. Excited to chat about AI, marketing, and everything in between.

 

Steffen: Perfect. Well, listen, before we start talking about AI, tell our listeners a little bit about yourself. How did you get started in your career and what led you to taking over the Vice President job at AKASA?

 

Benjamin: Yeah, absolutely. It has been a really fun route to get where I am today. And I think that most marketers would probably have an equally exciting story to share. My background is actually in journalism. And I really began my career as a writer or my marketing-oriented career as a writer. I use my journalism degree every single day in my role. Marketing, at the end of the day, is all about storytelling. 

 

Decided to go the business school route, to really get more into the marketing world. Started my career actually in corporate hospitality, which will raise some eyebrows on okay, how are you leading marketing with an AI company? We’re getting there, don’t worry. So spend some time with Carnival Corporation and MGM Resorts International. 

 

The entrepreneurial bug hit me. I made my foray into the startup world thereafter. Led marketing at a few early-stage startups and then eventually started my own hospitality technology company. When the pandemic hit, I knew I wanted to change course. And I wanted to stay in hospitality but at the same time go into the tech side of things, just because that’s where so much growth is. 

 

I came to find ConverseNow, which is the leading provider of voice AI services for large restaurant chains. Helped scale that brand into doing great things. And after several years with the company, loved it, loved the people, loved the mission. I had just another bite to change industries. I had really enjoy the hospitality, but healthcare had been calling my name for a long time. 

 

I grew up in a medical household. My father is an orthopedic surgeon, my mom is a registered nurse, and the opportunity to get into healthcare presented itself with AKASA. So I recently made the switch to AKASA. It’s a wonderful organization. 

 

As you noted, we are a provider of generative AI solutions for the revenue cycle, which is the long and convoluted process that involves health systems, communicating with insurance companies to make sure that they’re getting paid for the procedures that they do. It’s a highly manual, time-intensive process that is very ripe for AI. 

 

Our solutions are actively working with some of the country’s leading health systems and saving their teams countless hours, and allowing their teams to just perform more accurately, more comprehensively, ultimately saving everyone money and elevating the patient experience. So that’s a bit about me and about AKASA.

 

Steffen: Wonderful. Now, to dive into today’s topic, why do so many AI companies fail despite AI being such a hot topic?

 

Benjamin: Yeah, yeah, it’s a great question. And one that I think a lot of technology companies are asking themselves. AI is riding a hype wave. Virtually everyone knows that AI exists and that it’s really cool. There’s no question about that. The real question is, how is AI going to improve my bottom line? 

 

How is it going to help me as a business owner or a decision-maker, make money, save money, and grow? And the inability to answer that question is why it can make or break an AI company. If you have really cool tech that is just another shiny object, then yeah, some people might add it as a free tool and play around with it. 

 

But if you’re looking to build a high-growth and financially sustainable business, then you need a lot more than a shiny object. You need something that adds demonstrable value using the objective criteria that the customers that you’re selling to are already using to evaluate their own financial success.

 

Steffen: It’s more about the benefits at the end of the day. I mean there are so many AI companies for the same thing out there, right? I mean, that sometimes, when you go out and look for solutions, like oh, this one does it, this one does it, this one does it. But they’re really doing a poor job in really differentiating themselves from who else is out there. And then, as I said, I think focusing more on benefits, is from my perspective, probably a good way to go.

 

Benjamin: Oh you’re absolutely right. Selling benefits and not features is the direction that virtually any brands needs to take. To quote a beloved mentor of mine, no one cares how the hotdog is made. So it’s really about, okay, what’s in it for you as the customer from the end product that we’re delivering? 

 

Yes, we can boast all we want at AKASA, about how we train our models. And we have this incredible way that we do train our models to outperform GPT4 by 40 percent. That language is over the heads of a lot of our customers. It’s important for us to make our products work. But the most important thing is that our product works. 

 

And here’s what is in it for you, because our product works. So like we could talk all about the innards of our tech, but what our customers are focused on are all right, we can help you complete prior offs up to 50% faster. And that is up to 15 percent more comprehensively. And that can reduce X dollars in unwanted denials. 

 

And that is money that goes straight back into the bottom line of our health systems. And ultimately making healthcare more accessible and more affordable. So when you frame it that way, instead of here’s how our tech works, the differences are pretty striking.

 

Steffen: I think you hit the nail on the head there. For me at least, it’s like, a lot of customers, they don’t care how things work. They don’t want to look behind it. All they care about is that it alleviates pain points they have or gives them back time that they can use for things where their brain probably has a bigger impact. Now, we started talking about marketing, we talked about benefits. So how is marketing for an AI company different than marketing for other brands?

 

Benjamin: Yeah, yeah, it’s a good question. So talking about how an AI company markets itself is very similar to any company that is marketing a completely new category. Because AI, well AI itself has actually been around for a really long time. AI as the general public knows it has basically been around since late 2022 where chatGPT absolutely exploded. 

 

So AI companies are tasked with not only selling their brands but really selling the entire category. We have not just created a new mouse trap. This is stuff that people just aren’t familiar with, because it just doesn’t exist anywhere else at this point. So we sell generative AI assistants for revenue cycle management. 

 

Yes, there are other tools that health systems are using to help streamline revenue cycle management. They have outsourcing, they have tools for full automation in some ways, but AI hasn’t really made its way into the process. So what we have to do is, one define the problem in that here is what your existing solutions are not giving you. And here is how you are suffering as a result. 

 

And then in turn to find the solution. Here is how AI is solving this problem in a way that your existing solutions cannot. So it’s about making sure that your customer is aware of the pain that they’re actually facing that they might not have otherwise thought about before. It’s like exposing a water leak in a house. You know in someone’s front lawn they may not have never even knew it existed. 

 

But all of a sudden, you know, a plumber comes in. Oh, you’ve got this water leak. Did you know that it’s actually costing you an extra $200 a month in your utility bill? I had no idea. And I’m so glad I know now. Let’s plug this leak as soon as possible and stop the financial bleeding. That’s the same type of approach that AI companies and any companies really inventing their categories need to promote to their prospective customers. 

 

So, I would say that that’s far and away the biggest difference in how AI companies have to market themselves. They really have to create awareness around the category, around the problem, around how AI is the solution to that problem, and then in turn matching the benefits that AI provides with the metrics that companies are using to evaluate their own bottom line.

 

Steffen: How important is that part of this communication to aleviate any fear that people have that AI will take over the job of people? I mean you and I look at it as like, well it actually takes care of certain parts that I don’t want a human being to do, because, it’s too time-consuming. 

 

I can use that person on something else and add or create value. But for the normal person, they might think, well, you know what, am I going to have a job after my company takes on this software? How important is it to take care of that element in your communication?

 

Benjamin: Job displacement is unquestionably a top priority. It’s always the elephant in the room. If we add AI, will it take people’s jobs away? The quick answer to the question in the case of AKASA, and the case at my previous venture, is no, it is not designed to displace jobs. Rather, it is essentially giving superhuman abilities to your existing staff. 

 

Because in the case of revenue cycle teams, you have just a limited number of people you can hire. And there’s only so much work they can do. And you’ve got these people that are working as hard as they can. And they’ve just got this mounting backlog of work that they can’t keep up with. 

 

And when you have a task that takes someone 20 minutes, and they have to perform that task, like dozens of times a day, just think about the hours in a single day, let alone a month or a year that stack up. If you have AI that can reduce that 20-minute process into seconds, then all of a sudden, these people can be performing much more value-added responsibilities. 

 

So in the case of AKASA, we are taking these analysts and instead of having most of their day being focused on data entry, and researching medical documents, now they’re operating at the top of their license, and they’re able to use strategic thinking and problem-solving. And they are validating the suggestions that AI is giving. 

 

And they’re able to go more in-depth onto each of the encounters that they’re processing. So they’re submitting these encounters with greater accuracy, greater comprehensiveness. And it’s ultimately resulting in fewer denials, which in this case, is if something is denied, it’s basically saying, alright, insurance is not going to pay for it. 

 

So health system, you have to find a way to alter it or pay for it yourself. And then it starts the process over again. So ultimately, people don’t want to work for free if they don’t have to. So this prevents a lot of downstream issues from taking place. And alright, instead of just doing the work, people are doing the work better. 

 

And it’s resulting in a huge, huge improvement. So enabling people to perform to the best of their potential, instead of just having them try and keep their head above water. Like, that’s where AI is really thriving right now. 

 

As far as taking away jobs, the technology that AKASA is utilizing, and the technology that my previous company is utilizing, the goal is just to help people. It’s to help companies reach better financial stability. It’s to help staff perform better and have a better quality of life, and to ultimately have the consumer enjoy a better experience.

 

Steffen: That makes sense. Now, what are the biggest marketing challenges that AI companies face?

 

Benjamin: One is competition. So you brought up competitors earlier in this discussion, and our biggest competitors at AKASA, and I would argue for virtually any AI company or not other AI companies. Our biggest competitors are incumbents and legacy systems. There is tremendous inertia in virtually any vertical where if people have a system that works, it’s going to take a lot to convince them to dislodge themselves from that system and adopt a new way of doing things. 

 

So we have to prove to our customers that not only are we the better AI solution, but we’re a much better solution than your existing platform, whatever that might be. So if you’re working with your EHR, your electronic health record system, and they have a solution to help you with prior offs, well, okay, you’re getting this amount of denials and it’s taking your team this long to process things, we can process them three times faster. 

 

We can reduce denials by X, Y, and Z. And if you show them where the money is, then it’s a very clear decision on okay, this is the pain that I have with my existing system. Here’s what’s going on. And AKASA can give me 3x benefits, then, yeah, we can talk further. And then the next step there is saying, alright, this is what it looks like to implement AI into your existing business. 

 

People think AI, they think oh, this is highly technical. It’s going to take our IT team months to do this. We’re gonna have to build out X, Y, and Z Absolutely not. As a marketing team, we have to communicate that this is actually a very low lift. The stuff that we’re doing is really technical, but on your end, it’s just about plugging things into the right outlets, and really not much more than that. 

 

So those would be the biggest items. Yep, competitors are definitely the incumbents. AI as a category is just too young to be fully focused on itself. It’s really about what else is out there. What are the non-AI solutions that we’re competing with? And how do we demonstrate value?

 

Steffen: Now, from a marketing perspective, what can AI companies do to avoid these pitfalls? I mean, you started talking about proof points, basically to show how an AI solution or your AI solution is better than any legacy solution. At the same time, I’m always thinking about the example back in my days working for big global agencies, we used to work for a telecommunication company like a mobile phone provider. 

 

And it was hard to get people to switch their mobile phone contracts because it was convenient, the cost just came out. And although they would save a good amount of money, that alone didn’t persuade a big group to make that switch. What other things do you think marketing can do to help avoid the pitfall that agencies or that AI companies potentially can’t convince their target audience to make that switch?

 

Benjamin: Yeah, the best way to bring any customer to the finish line is to speak their language. So any AI company and really any brand should be deeply familiar with the language the customer speaks, their psychographics their tonality. And making sure they’re using all the right lingo in all the right places. 

 

And that they know the customer’s needs, they know the customer’s way of doing things. And that because they’re so deeply familiar with how things work right now that they know how to make them better. So at AKASA, we have an in-house team of revenue cycle experts that have a collective decades of experience among them, and they have lived and breathed revenue cycle for their entire careers. 

 

So they’re seeing this product, and they’re putting, they can easily put themselves in the shoes of our customers, because they’ve been the customers before. They know exactly how it works, and what it’s like to be an end user of the product. So any AI company that is looking to sell to whatever vertical, should be deeply familiar with that vertical. 

 

Definitely get advisors that have deep familiarity with the end user experience, and to do your research. Conduct surveys, in depth interviews, ethnographic testing. How is your product being perceived and used in the wild? And to have a very realistic perspective on those items will help companies go a long way. 

 

AI companies, it’s very easy to get egotistical because you’ve got this groundbreaking technology. But will people use it as intended? And will people embrace it as intended? Being able to answer those questions will create a pretty critical foundation of whether people will actually like the product and be able to get the value that you’re looking to create.

 

Steffen: Now, to determine whether you penetrate your market, what KPIs do you suggest to use to determine success or failure?

 

Benjamin: Oh, absolutely. KPIs, of course, the governing entities of any organization, the KPIs that an AI company should focus on, are the KPIs that its customers use. And that’s to evaluate product success. So if your customers are focused on, let’s say, denial rates in the case of AKASA, that should be top of mind. 

 

Is AKASA producing denial rates that exceed the standards that our customers had before? Time to complete a task. Is the AI able to decrease time needed to complete tasks by the threshold, or the hurdle rates that customers are looking for? 

 

So making sure that you’re in lockstep with your customer on how do they evaluate success, and that you are in turn able to report those metrics with an exact match, and that you’re reporting them frequently, and that you’re calling out where you’re exceeding, where you’re not exceeding and the plans in order to improve. 

 

So from an external standpoint, those KPIs are quite important. And then internally, right, that’s completely up to the organization. But the universal marketing metrics that I look at, sales accepted leads are the Northstar metric for my team. 

 

We’re making sure that we are generating leads that are not just qualified but are nurtured enough for our sales team to then work with. And then ultimately, CAR, contracted annual recurring revenue. Because once marketing is handed off to sales, our job is not done. Effectively, it’s really just started. 

 

So making sure that we’re supporting our sales team to take these deals to the finish line. A company is not going to grow unless its revenue grows. So we’re just making sure that we as a marketing team are being held accountable for that end metric.

 

Steffen: You touched on the fact that working together with other teams at the end of your response. So how should the marketing team work together with other departments within the company to achieve overall success?

 

Benjamin: This mentality applies to organizations of all sizes. And when I deliver my answer to this question, it’s noting that there are smaller teams where people are wearing many hats. And there are, of course, larger teams, where you have multiple individuals that are doing work that could otherwise be reserved for one person, just because there’s so much work to do. 

 

So with that being said, I see marketing as a nucleus of virtually any organization where marketing is the connector across sales, product, engineering, customer service. And that marketing needs to be in the know, of everything being developed from a product and engineering standpoint, so that we know the exact product that we’re selling. 

 

That we’re working with customer experience on our customer health, and really understanding the KPIs that our customers value. Being able to shift those KPIs as needed. And then, of course, to collect data from those customer discussions to talk about the results that we’re delivering. 

 

Because ultimately, it’s really hard to argue with the facts. If we’re saying that we’re driving customer XYZ’s metrics by 50%, a great way to promote that. Talking with sales as well to understand alright, where are we excelling in the sales funnel? What gaps exist, where can marketing ads support? 

 

And then of course, with executive leadership, to make sure that marketing is holding itself accountable and delivering the results that the company needs. Because marketing has been under fire for quite some time, understandably so. 

 

Because it’s a squishy area. And in some cases, it’s really hard to objectify results. But being able to show how sales-qualified leads actually pass through the funnel faster when they’re engaging with marketing content, or how we’re driving pipeline, because of the surge in sales-accepted leads that marketing has generated through its nurturing material. 

 

Again, you want to make it so that there is indisputable fact about the benefit that you’re providing, as an AI company as a whole, and then within marketing to showcase to the rest of the organization, the impact that you’re making.

 

Steffen: And then what you just said applies to any marketing with many organizations. So that’s not just what we do in an AI company, I think that is really something that is universal in that regard. Now, last question before we come to an end, Ben. What makes for a successful AI marketing team? And is a successful AI marketing team different to a successful marketing team in any other company?

 

Benjamin: I would think that the components for a successful marketing team definitely provide the foundation. And the components to that, one, people who are masters of their craft, you want to make sure that you’re bringing all the right people on the bus, where depending on the size of your team, you want people that are thoroughly antiquated with product marketing. 

 

You want people to be masters of content strategy. You want to have people that are skilled designers, skilled copywriters. If you have a strong event strategy, like we do, we do a lot of our business at events, someone who is deeply familiar with the event world in your particular space. 

 

And then it expands out beyond that, where if you’re big enough to have an in-house PR team. People that know that landscape very well, and the list goes on. So people who are masters of their craft, people who are truly bought into the company’s mission and vision, you want to make sure that everyone’s a cultural fit. And then depending on the size and speed of your organization, people that are completely gung ho with how your team is operating. 

 

So at AKASA, we’re a relatively sizable organization. And that said, our marketing team operates in a really lean fashion in comparison to the size of the organization. So having people that can operate with the speed and agility that you might need, is quintessential. 

 

So that would be the foundations of a general marketing team. But beyond that, for AI, I wouldn’t necessarily say that you need someone with a deep AI experience. It’s like asking someone in 2007 who has deep social media experience. Anyone who has that from a marketing perspective, well, that’s just an interesting thing to think about. 

 

But people who are genuinely fascinated by AI, who have some backgrounds in the b2b SaaS world, because there’s a lot of overlap between that and general AI. But people who are just genuinely curious about the technology, and just passionate about the company’s mission and how AI ties to the customers that we are serving. 

 

So a lot of marketing best practices transcend verticals. So there’s just so much between the restaurant industry and the hospitality industry that I’ve seen to overlap in just a really interesting way. So I wouldn’t like to pigeonhole people into you are a hospitality marketer, you are a CPG marketer, you are an AI marketer. 

 

I really think that people can shift very easily among those. It’s about people who understand the organization and understand the path that they need to follow within their respective craft in order to move the needle for a marketing lens.

 

Steffen: That’s a great, that’s a great last word. Well, Ben, thank you so much for joining me on the Performance Delivered podcast and sharing your knowledge on how to market AI to a less tech-savvy audience. Ben, if people want to find out more about you, about AKASA, how can they get in touch?

 

Benjamin: Yeah. Thanks, Steffen. Really appreciate the conversation. And if people want to find out more about AKASA, you can just visit us at akasa.com. And you can just find me on LinkedIn. I think because there are a lot of Ben Browns out there, if you probably just search Ben Brown AKASA, then you’ll find me pop up.

 

Steffen: Perfect. Well, thanks everyone for listening. If you like the Performance Delivered podcast, please subscribe to us and leave us a review on iTunes on your favorite podcast application. If you want to find out more about Symphonic Digital, you can visit us at symphonicdigital.com or follow us on X at Symphonic HQ. Thanks again and see you next time.

 

Voiceover: Performance Delivered is sponsored by Symphonic Digital. Discover audience-focused and data-driven digital marketing solutions for small and medium businesses at symphonicdigital.com.