This may be my favorite ever episode. And it’s a doozy!
I sat down with Nick Panayi, CMO of Inovalon, to explore one of the most comprehensive AI adoption stories I’ve encountered in healthcare technology marketing. Nick leads a 95-person marketing team at this 2,000-employee data and solutions company, and what they’ve accomplished in just two years is remarkable.
According to our recent survey of the HealthTech Marketing community, only about 7% of companies have an AI strategy roadmap, let alone reach this level of AI integration. This makes Nick’s insights particularly valuable for the rest of us on this journey.
What impressed me most was how they’ve made AI accessible across their entire marketing organization. They’ve created a unified platform called Amaru AI that serves as a no-code environment where marketers can build workflows without technical expertise. By integrating AI tools directly into their existing Monday.com workflow system, they’ve met their team where they already work rather than forcing adoption of new platforms.
Nick also shared fascinating use cases, including AI-powered voiceovers with Eleven Labs, conversational AI prospecting with Synthflow that makes outbound calls, and using Google’s Notebook LLM to transform dense white papers into engaging podcast content.
Key Topics Covered:
- (00:00:00) Introduction and Nick’s Background
- (00:03:00) Building an AI-First Marketing Team
- (00:07:00) Overcoming Barriers – Legal and Team Concerns
- (00:10:00) The AI Roadmap and Tiger Team Approach
- (00:12:00) Scaling AI Adoption Across the Organization
- (00:14:00) Content Creation with AI Scoring
- (00:18:00) Automated Website Tagging and Personalization
- (00:22:00) Agentic AI for Paid Search Advertising
- (00:30:00) Amaru AI Platform Architecture
- (00:35:00) AI Integration in Monday.com Workflows
- (00:36:00) Image Generation and Remix Tools
- (00:37:00) Tega AI for Prospecting and Lead Generation
- (00:40:00) Synthflow – Conversational AI Calling
- (00:45:00) ROI and Measurement Approaches
- (00:49:00) AI Voiceovers and Video Production
- (00:51:00) AI Podcasting with Google Notebook LLM
- (00:53:00) Advice for Agencies and Consultants
In this post, I lay out a strategic roadmap that emulates what Nick and team have achieved at Inovalon.
If you are interested in discussing this or any other topic, let’s have a chat. Reach out to me directly to schedule a no-obligation discussion. This isn’t a sales call, but rather an opportunity to talk through your questions and challenges.
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Thank you to our presenting sponsors, HIMSS, a leader in advancing health equity, digital innovation, and data-driven care through technology, policy, and community collaboration. And also HealthcareNOW, 24/7 expert shows, interviews, and podcasts, powering healthcare leaders with innovation, policy, and strategy insights.
Full Episode Transcript
Adam Turinas: [00:00:00] Well, Nick, welcome to the show. I’m so delighted you are here and wow, we got a lot to talk about. Let let’s get started. Tell us a little bit about yourself and your journey.
Nick Panayi: Thank you, Adam, very, first of all, thank you so much for having me. It’s a pleasure to be with you. so my name is Nick Panai. I am the CMO here at Innovalon.
I’ve been at Innovalon for two and a half years. I’ve been in marketing much longer than I care to admit on this podcast. So it’s quite a long time. I’ve been in technology marketing my entire career. And my last stop before Lon was actually for a conversation or was working for a conversation on AI company.
So I was the CMO there and that was my initial kind of introduction to ai. And of course I brought that passion to Innovalon. Of course is in the healthcare space. We’re a data and solutions company that serves the entire healthcare ecosystem, and our focus is [00:01:00] to improve healthcare outcomes and economics across the ecosystem.
Adam Turinas: You are a pretty large company. I mean, give us a sense maybe just in terms of the size of your marketing team, how many trucks on the team, you know?
Nick Panayi: Yeah. This is, the marketing team is a good size. It’s about 95 ish people. The company is approximately 2000 employees.
Adam Turinas: That’s a big team.
It’s great. That’s really decent
Nick Panayi: size team. I’m not complaining. I’m not complaining.
Adam Turinas: Team. Good for you. That’s great. So let’s get into talking about ai. in the study that we completed in the last month or so with the health tech marketing community, we had a, I think 110, 120 respondents completed the survey.
So it really is, it’s, you know, it’s Nick, your peers across the industry. And the thing that is remarkable, I think, is that seven, maybe 7% are anywhere near the level of [00:02:00] AI adoption and the way that you’ve got it integrated strategically. And so, we’re gonna go deep today in, in, understanding your approach, but yeah, let’s go back to the start.
How did you get this started? what did that look like and why, and, and how did you get it moving so aggressively?
Nick Panayi: Yeah, thank you. it’s been a fast journey. I will tell you. Based on what I’ve experienced in my last company, I already had a lot of passion for AI coming in, to this position.
So there was no question in my mind. AI is here to stay and it’s here to impact pretty much every profession included marketing. So I was always kind of AI curious and AI expert. I’m not, but they’re definitely an AI lever. And as soon as I landed, one of the first things I did, Adam, it was fortunate thing, is I brought with me a person, to run my digital marketing function that has, worked with me before [00:03:00] malar in two companies ago, DXC technology.
That person’s name is Chris Marin. Chris is my guy. You know how we always say I got a guy, so, yeah. Yeah. Got a guy. So, Tim, leave Jersey, would you? Yeah. Yeah. He’s my guy. Uh, and Chris happens to be, one of those rare individuals that brings obviously digital marketing expertise. That’s what he was hired for, but he’s also deeply passionate and a very much an expert in ai across the board.
That’s just a passion of his and ai, specifically AI uses in marketing. So I saw that as a plus. That wasn’t the reason to bring him in. The reason to bring him in was digital marketing expertise. But, you know, he brought along AI expertise and that really helped me go from, wouldn’t it be nice to use AI to sitting down with Chris and saying, Hey think AI first.
Anything that we do, you know, what can AI do for us? Before we even [00:04:00] go from glimmer in the eye to execution, you should be thinking AI first. And when was this? Last year, two years ago. So he joined me about two years ago. The reality is the world of AI has accelerated dramatically in the last two years.
So it wasn’t the first conversation we had, it was one of the first conversations, but it was definitely, Hey, let’s keep an eye out. Let’s have an AI first mentality. We have gained enough credibility in the company to be given the flexibility to experiment. Yeah. So thankfully I’m in a company where the leadership team, my CEO, trusts us and trusts our judgment and knows that we’re gonna do whatever we can do and gain a competitive advantage.
If that means uses using ai, then, then so be it. So we do have. The freedom to operate and the freedom to experiment, the freedom to make mistakes. And honestly, you know, that [00:05:00] that’s all we need is we just need the license to go at it and go at it fast.
Adam Turinas: So explain where it fits within your marketing strategy.
So, you know, just to maybe unpack your marketing strategy a little bit to start with.
Nick Panayi: Yeah, look, the way we’re organized is probably not atypical. We have a shared services model. So the way we go to market is in the healthcare space.
So our product marketing function serves those segments by putting out a marketing plan and the shared services model, including digital marketing, content, creative, A RPR, those are the shared services that we use to, in essence activate that marketing plan.
you know, in the marketplace. So from a strategy standpoint, we bring all of those tools and capabilities to bear, to activate the marketing plan as effectively as we can in the marketplace. So AI [00:06:00] becomes a way to get to market faster, better, most core, more cost effectively than anybody else.
And that’s how, that’s how we think about it. We don’t put any constraints on it, to be honest. We don’t think about, Hey, let’s only consider AI in these use cases or in these particular functions. We have the ability to experiment across all functions and across all tactics, across all approaches to marketing.
that’s the benefit of bringing in an in-house AI expert, that knows the marketing organization well, and knows what we can best use AI and at least knows how to prioritize some of those investments.
Adam Turinas: that makes, perfect sense. So overall, it’s an accelerator and a way of increasing efficiency.
what have been some of the barriers in this journey over the last couple of years?
Nick Panayi: I would say, I don’t know barriers, but a couple of speed bumps. One would be our [00:07:00] legal organization as you would expect, and I totally respect that, especially in a healthcare space. Anytime you think about ai, you start thinking about privacy and what information are you using, how are you modeling things, what are you doing with it?
Uh, thankfully in the marketing space, unlike. If you are developing a product for healthcare where you are using PII, we’re not using anywhere near PII, we’re using tools and, data sets that don’t really affect privacy in any way. So we’re able to put those kind of, I don’t wanna say fears, but concerns to rest early.
’cause we’re able to say, here’s the sandbox that we will play in and we will stay in this sandbox. And it’s all commercially available, widely available information. We just use it in a smart way. So that was the first that Speak Bomb would say. The second would be even helping our own marketers understand, how AI can be used without [00:08:00] necessarily affecting their value and their worth to the organization as, as a human reaction.
If you tell a content producer. Hey, I’m gonna bring in a tool that will help with content creation. The immediate feeling is one of hesitation, of course. It’s like, well, what do you mean that’s kind of my job, right? So, uh, you know, I are you looking to replace me? And all of those things are, human emotions that everybody understands.
Every, every time AI gets involved in a function or in a profession, you’re always gonna have the What about me kind of question. Again, we’re able to put those to rest very easily because this is, we’re not looking at AI as a way of replacing humans. We’re looking at AI as a way of making our humans better.
One of the best things I’ve ever heard explaining that relation between AI and human was a saying that when something like this, AI [00:09:00] will not. Take the job of humans, but humans with AI will take the job of humans without ai. Right. And that makes total sense. It’s about AI being a companion and a partner in what you do.
So we very much have a human in the middle and we very much value the human contribution, but it’s just simply done better, faster, more efficiently with ai.
Adam Turinas: that analogy makes perfect sense and I can understand how that would go some way towards assuaging fears. ’cause everybody feels sort of a bit, you know, a bit insecure about the impact.
Tell me about the roadmap. Have you got a, you know, we’re going to get into the, details of what you’ve done in, in a second, but I’m, curious as like, you know, do you have a, do you treat it like a product roadmap or how have you approached this?
Nick Panayi: We do, we have the benefit of having a Chris, having a digital expert whose [00:10:00] knowledge is very much up to speed and, up to the minute and his knowledge of marketing as well.
So he brings us a lot of these ideas so far. The beginning of it, we look at ’em as a leadership team and we decide which ones we’re gonna go pilot. They all started as a pilot, unless it’s a horrible idea, to be honest. Adam is like the time and energy that we’re put in a pilot. It’s far outweighed by the potential benefit.
So, you know, there were very few ideas brought forward that we said, ah, that just, you know, pass. Very few ideas. I can’t even remember. I remember a couple of discussions, but I can’t remember what they were exactly. So, the roadmap was our digital AI expert bringing in some ideas. We’re looking at them at the leadership level, and he’s putting him on a roadmap balancing, of course, the, what we call keeping the lights on bandwidth, right.
That he and his team have to have. We still need to have a website that’s running, right? [00:11:00] Uh, yeah. And the marketing automation platforms and email platforms and all of that. So we don’t want any of those to be kind of side wiped for this. But we also want to invest in AI in a very significant way.
So that’s the only gating factor is do we have the bandwidth to do one more pilot? Right. That’s so far been the case since we’ve been doing this and we’ve gotten everybody kind of on board and a lot of people excited. We’ve now formed an ai tiger team that has a person from each function.
As a matter of fact, we just putting this together they’re gonna be meeting on a regular basis and basically giving the various functions an opportunity to out, go out and scout for themselves, bring in ideas, have those discussions, and then start to formulate a more formal roadmap based on all those inputs.
Because the whole idea is that you don’t wanna have your innovation gated by one [00:12:00] person, as smart as he may be, or she may be. You want the rest of the marketing team thinking in exactly the same way. So we’re looking to institutionalize that now.
Adam Turinas: That’s interesting. So essentially it’s start with one expert who’s got a passion, who’s gonna drive this thing forward, and then as you scale it, then essentially clone, clone his capability, or at least sort of get that capability, replicate it in the other departments, and then spread it that way, sort of almost create a network effect.
Nick Panayi: Yeah, for sure. And, maybe less so capability, more so, scouting and bringing in new potential tools. I see. I don’t think anyone, I’m not gonna be looking for somebody in product marketing to become an expert in ai, but I’m gonna be looking at somebody in product marketing to let us know. If there’s an i AI tool that’s specific to the use case of product marketing should be something we should take a look at it.
Yeah. [00:13:00] Chris is one person I wanna be able to fan out. And there’s more tools than hours on the day in the day for us to be able to scan everything. So it’s about somebody who knows the function and knows the company and go say, you know what? Given our current posture, this is something we should be looking at.
Adam Turinas: Let’s dive in a little deeper on this. Can you kind of go through some of the kind of killer use cases where it’s where the adoption has accelerated and you’re really seeing an impact?
Nick Panayi: Yes. So let’s start with content, right? That was the first area that was a natural area for us to look at.
You think about generative ai. And again, you think about the fact that content, especially for leadership for us, is for leadership content is probably the most important lead magnet, let’s call it. Right? That’s what people are coming to us for, is they basically want to get smarter about some of these areas that we serve.
So we have great [00:14:00] thought leaders in the company. We have a great content team. We have the content team interviewing thought leaders and writing pieces, whether those pieces are white papers or producing webinars and things of that sort. Now, when the writing begins. we wanted some assistance for this content producer, so we put together a tool that is an AI driven tool that takes in the persona that we serve.
It’s about a hundred or so persona. Wow. The, brand voice, that we have, the brand positioning and also our approach towards content development, which we adopted a model called Make It Punchy, by Emma Stratton. Ah,
Adam Turinas: okay. I’m not familiar with that. I saw, something actually on, I think it might have been a LinkedIn post or one of your colleagues that said, I’m not familiar with that, uh, that not.
Nick Panayi: Yeah, it’s basically look in B2B marketing, especially in technology [00:15:00] there’s a sea of sameness out there, right? And at the same terminologies and acronyms and, you know, like best practices and best tools and all of these phrases that would use for years and years and years. And it’s very internal versus marketed customer end.
So make it punchy, an approach that thinks about what the customer really wants to hear, what kind of. Solutions they’re looking for, but also the acknowledging the fact that they’re human beings and human beings don’t respond to, phrases like we’ve been using that are written really more internally than anything else.
So make it punches about, just get to the point. Tell me in regular English what it is that you are trying to tell me, and then you can back it up with fancy phrases after that, but get my attention by telling me what the real deal is all about. Got it. So obviously I’m not doing it justice, but that’s the general approach.
But that is a writing [00:16:00] style. There’s some rules to that. Yes, there’s some dos and don’ts. So what we did is we fed, we trained the system based on that content philosophy and our brand voice and positioning and messaging and the hundred persona that we have. And we basically created a rubric’s cube that says you’re gonna fit in your content.
It’s gonna rate it based on those variables, and then it’s gonna tell you what you need to change to get it to be a hundred outta a hundred. So the writer starts first with the first draft. AI tells it, okay, given this persona and what he or she likes to hear and make it punchy and your brand voice, these are the things that you may want to change to it.
So it actually gamified content creation. Yeah. With the whole idea of making every writer your best writer.
Adam Turinas: Very interesting. That’s the idea,
Nick Panayi: right?
Adam Turinas: [00:17:00] Yeah. Yeah. Yeah. a lot of the content that we create, we might actually start with a persona. and possibly, with a really detailed prompt, get the ai, particularly for something like Claude to write the first draft, and then the human then intervenes with it.
We’ve then got some GPTs that we’ve created that optimize it for things like search, particularly EAT for, you know, for the AI answers. But, the notion of you of actually taking, a content creation framework and applying that in the process is really smart. I, in something that you shared with me, it sounds like you’re doing quite a lot around personalization as well.
Can you share a little bit more about that?
Nick Panayi: Yeah, sure. So again, you think about the jobs that AI can do better than humans, and there’s many of them, but. the one thing that they all have in common those jobs is that they’re long and [00:18:00] tedious, and the volume of things that needs to be done is just simply beyond human capability.
Or it would take many, many, you know, man months to produce. So how do we take something like that and, work it with ai? One of those things, and this is as long as I’ve been around in marketing, is the ability to take every one of your pages on your website and tag them with tags that are useful for you and further downstream as you are working marketing campaigns and marketing tactics, and you’re trying to drive traffic to that page.
So we’ve, in essence, taken all 1000 or so pages on our website, created an AI tool that basically scans the content and tags it with. The funnel stage, the business unit or the segment that is trying to appeal to the persona that would find this relevant, what [00:19:00] kind of content this is, and other predefined topics and freeform tags that our team kind of came up with.
And basically every page is now tagged with this. And again, imagine a human being going through every one of those thousand pages into it. Yeah. It’s just, it’s not gonna happen. probably not a good use of time. Yeah. It would happen at the end of my tenure, but it wouldn’t,
Adam Turinas: it wouldn’t, it wouldn’t.
So it wouldn’t be done well, you know?
Nick Panayi: Yeah. It wouldn’t be done well, it wouldn’t been done consistently using a consistent set of tools. Again, you can maybe brute force it by, give it to some outsourcer and say, Hey, put 50 people on this. But then there’s 50 slightly different interpretations of this.
Right? Yeah. And how do you figure out the persona and all of that without ai, so, well, why even do that, right? Because. Once you do that, then you feed your marketing automation system with that information so that when your demand generation function, or people who are building campaigns or building a campaign, you can [00:20:00] recommend what pages would be relevant for a particular campaign.
Or a campaign can basically drive traffic to five pages. You’ll know what five pages to go to because you wanna optimize for a particular persona or a content type or something like that. And very importantly, you analyze your web traffic Later, you try to figure out not only what pages people went to, but again, you look at things like what personas were attracted to your website and, and why.
And did you have a good match between what you thought the right persona was gonna come to or not? And you make adjustments to that. So it’s gonna be the gift that keeps on giving. And again, this is not something that would be possible without ai.
Adam Turinas: I can see a million different use cases that, I mean applications of that.
Yeah. For example, you could create personalized email sequences for different personas and based on those tags. That’s really smart. I’ve not heard that one. That’s great. you also, I believe you [00:21:00] guys are using agents to create ads. Can you talk a little bit about that?
Nick Panayi: Sure. So that was also one of those cases where you, try to find areas where AI could really help.
the art and science of, pay per click advertising is one of those areas that until now you, you kind of have to outsource that to an agency, right? I mean, it’s just, there’s so much there to, go through before you determine what to write in that ad block. if you’re doing it right. so we thought that that was a perfect opportunity for ai, and not just AI in general, but agentic ai.
So that was one of those first experiments of Magen AI for us. and, I can tell you it’s, it makes all the sense in the world. We’re already starting to see kind of the, difference between the before AI and after [00:22:00] ai, and we’re now looking to scale it. We also wanna have a human in the middle as well to make sure that we’re doing it right.
But just to kind of summarize, you have, in essence, multiple agents, which the whole idea is almost kind of a, a specialization of labor, right? You take one agent who is responsible to scan the whole marketplace for what competitors are saying. And bring that back. And you have another agent that’s responsible to take that content engine we just talked about and apply that content engine to do a first draft of an ad.
And you have another agent that basically critiques that ad. you have yet another agent coming in and basically figuring out what to bid for that ad given the competitive environment. And then it goes on and on. So like multiple steps of putting these ads together. And at the end, we want to have a human of course look at that and say, okay, [00:23:00] are we sure here we’re not going off the rails.
Make sure that, you know, again, we’re stand within our brand voice and we stand within our budget parameters and all of those good things. and actually the human starts with some initial, uh. You know, content or copy that they write, and then the agents take over and then the human at the end does the final check.
and we go, and that is a perfect example because again, it needs constant refinement. the minute you put it in the marketplace, something can change, you know, either in the competitive landscape or some keywords can come in or out of favor. Something happens in, in, in government policy that impacts certain things, and you wanna be able to take that into account, especially in healthcare.
So all of those things are, good, strong reasons why a model like that could work for SEM because of how quick it turns and how reliant it is [00:24:00] on science as well. It’s not just, you know, you’re creating a, an out-of-home. Advertisement is one thing. This is about search engineering. And now with AI as well, coming into the mix of search, that’s making things even more complicated and more
Adam Turinas: interesting.
Oh, yeah, yeah. I know. So you are using it for paid search. So, and that, I mean, that makes perfect sense. Yeah. Google ads. are you able to do that with, you know, maybe more brand ads that are sort of upper funnel? They might be programmatic ads in display, maybe LinkedIn ads. are you using it with those where there’s a little bit more, where you might want the human to be much more involved?
I don’t, I’m not sure how you, how it’s applied there.
Nick Panayi: We’re not doing that there because it’s not a burning bridge for us. In that particular case. The variations of advertisements that you are running are nowhere near the same. the same volume as it would be for PPC because you [00:25:00] want so many different variations and you only pay per click.
So you know, you can just have at it. Whereas with display advertising and at home and some other things we take more of a human based approach. Having said that, the humans who are writing the copy are using the rubrics that we talked about to write good copy. even creative copy as well.
So we are using AI in a different way, not in an agent way, but we’re using it to refine the ad development, but less so than in the PPC space.
Adam Turinas: I wanna double click on something. You’ve used the word agent. I hear this a lot and I’m, yeah. I know what an agent is. I know what A GPT is. Agen is like, it also sounds to me like something where I think you asked 20 people what agen tick means.
You’re gonna get 20 different answers. what is agen? But I’ve got two part question for you. What does ag agentic mean? And the other thing is, is in one of the documents you shared with me, you talk about GPT is a zero shot. I didn’t [00:26:00] understand that.
Nick Panayi: Yeah. So I’m gonna give you the non-technical person’s, understanding.
Good. Please do. Yeah. Uh, because I, I’m sure I’m technically not correct, but I mean, if I were to just generalize, agents are, are basically software models with varying degrees of autonomy and they’re equipped with, specialized tools and knowledge. By definition. Ai right now it’s all about specialization, right?
We, we don’t have, general. so I mean chat, GBT is general ai, but most AI systems are, very finely refined on what it is you train them on. So agent basically takes that concept and says, great, I’m gonna train five different agents on five different parts of the problem. I’m gonna send them off to do their part, and I’m gonna bring back the answer at the end.
Right? So instead of trying to figure out one general AI system [00:27:00] that will have the answers to every part of PPC advertising, you know, I created an, I didn’t create it, Chris did, created an agent that created an agent that goes out and searches for competitors. That’s all it does, it knows the competitors.
It searches for competitive ads. It brings back the intelligence in a certain way. And then I created another agent of Chris did that goes and critiques the ad that was written and that’s all it does. So it’s easy, I see, develop the specialization, but they’re all working towards the same end. And so forced two multiple ends, they’re working towards the same end.
You stitch together an answer at the end. and that’s how, you go at it. and zero shot is really, the idea that chat gt, for example, and, and models like it, like Gemini from Google, they’re built to be able to understand, comprehend the question, understand what it is obviously that you’re trying to get [00:28:00] to, and then use pre-existing knowledge to go synthesize and answer for you on models that they’re on, information that they haven’t been trained on yet.
So one of the best examples I heard was, well, you know, like, I dunno if you use Google Photos, I use Google Photos. Google Photos uses obviously AI to do face recognition. Right? and you basically actually train it like, oh, this is Nick’s face, and it goes and does some measurements and it looks for Nick’s face and, it kind of figures it out.
So it’s been trained on my face, whereas with Zero Shot, I may ask it, you know, who’s Nick Pan? Nick, yeah. Pan. and they’ll go like, okay, have understanding, have context of what you’re trying to do and use other methods to find you without necessarily having been trained on who you are.
Yeah. That’s probably not the best example, but in general, that’s what it is. The gist of it. Zero, yeah. Is zero shot in that it hasn’t been trained [00:29:00] on this data set that you are asking about. It’s able to use pre-existing knowledge to go synthesize and answer for you.
Adam Turinas: Yeah. that’s a great explanation.
and you know, the way that you’ve described AG Agentic versus A GPT, reminds me of an analogy that I heard somewhere, which is, you know, chat GPT is like having a fantastic specialist consultant that you can only interact with through chat, maybe through voice, but you know, basically through chat.
Whereas a, an agen approach is like hiring McKinsey to solve a problem where you’d have multiple departments, you might have the financial analysts analyzing certain aspect of competitive analysts, and they all come together to give you a solution, and it’s a much more comprehensive approach.
Nick Panayi: specialization of labor. In this case, it’s specialization of ai. towards a common goal.
Adam Turinas: Yeah. Yeah. makes perfect sense. don’t wanna get too technical here, but I was really interested in the [00:30:00] architecture some of the tools that you’ve built, and you’ve, developed this resource called Amru ai.
Is that right?
Nick Panayi: Or Amru? Yes. Yeah. I don’t know how to pronounce it. the name is, I, I understand is an Inca God. Ah, and, I think it, represents duality of, uh, human and, God I believe in, one. Oh, okay. Uh, something like that. I’m not doing it justice. Chris, who is my guy, He was also born in Ecuador. so he used some of his heritage for that. And that is a tool that, platform that he has built called the Marro ai. and we’re actually in the process of going from, okay, that’s great, Chris. how do we then make sure others who are not as smart as you, meaning me and pretty much the whole marketing organization, figure out how to use this and what does it do?
So what he’s built, and again, he’s thinking a step ahead, right? [00:31:00] He’s thinking, okay, so we have 15, 16 different AI pilots as we speak, and I, I can share some others as well, some amazing stuff. But if he, he’s thinking down the line where we’re gonna need an AI for marketing place where all of the best knowledge is housed, and all of that starts to share information.
Among one another, right? So as opposed to just having a content AI thing and an image generation thing, and a personalization webpage tagging thing, if we were to bring some of these models together into one place, you have this great effect of the various models learning from each other as well, number one.
And number two, it allows non-technical people to have a place where they can create workflows, multi-agent workflows of [00:32:00] their own, like for example, right? So it’s supposed to be a no code multi-agent workflow, right? So he’s got, the ability to create prompts automatic. So as you know, in, in AI, search prompts are the most important.
Adam Turinas: Absolutely
Nick Panayi: right. Uh, I was trying to explain people, it’s like what people are using charge GBT or Gemini as a search engine that’s like one 1000 of the value. It’s almost like, find me this, you know, I can still use generic search engines for that. Just fine. It’s still valuable in that I don’t have to click from there.
It gives me the answer. But if my question is multi turn as comprehensive as it can be, the answer is directly aligned with the complexity and the validity of my question. So the more valid, the more comprehensive my question, the more valid, the more comprehensive the answer. And people haven’t necessarily figured that out is.
You can go in and [00:33:00] have the question be like two paragraphs. They say, I want this and this and this, but not that. And make sure you do this and then don’t do that, but do this. Right. I mean, a very, very complicated, and a human being will be like, hold on. I’m still unlike step one of your question, the beauty of AI is a beauty of AI doesn’t have the limitation.
This was, the more torrent you give it, the better. But you have to know how to phrase the question correctly. So Chris thought of a way, he said, look, okay, if you are a copy editor or a creative writer or the CMO or a marketing strategist, tell me what it is you’re trying to do and I’ll synthesize the prompt and go ask ai.
Yes. So it’s almost like prompt engineering, for example. Yes. Yep. So he’s trying to simplify the world for all ai, all marketers, regardless of function that they serve in. Mm-hmm. To come in. Use the most out of the AI tools that we have. Single place to sign in, single place to go, [00:34:00] as opposed to every marketer having their own, you know, like Yep.
credentials to four different engines as subscriptions to four different engines come to one place and get your AI powered marketing in one place, in one platform. So that’s what he’s working on. I saw the first variation, like anything else, version 1.0 is, I had more questions than answers, but it seems very, very powerful and he’s working on the next generation as we speak.
Adam Turinas: Very interesting. I also was quite impressed and curious about the way that you are, you’ve basically got it integrated into Monday.
Nick Panayi: Yes.
Adam Turinas: Yeah.
Nick Panayi: Yeah. that’s another thing is we wanted to put it in a place where marketers live every day. Yeah. So monday.com for us is our workflow. Platform. You know, we are our own agency in many ways.
We use agencies, we use contractors, but we have our own content team. We [00:35:00] have our own demand gen team, our own product marketing team. So a lot of the workflows are similar to what you would find in an agency. So we have, at any given point in time, two or 300 projects with various people having a part of that project, oh, you need to approve this.
Does this look okay? Does that look okay? So that’s where they go every day. So it made total sense if you’re writing content to put the content generation AI tool in there. So we have in there, for example, the content, tool. We have an image remix tool again, back to using multiple engines, instead of you having to go to like four different AI engines and say, can you make me a picture with a nurse, you know, holding.
You know, a tablet and in front of an elderly patient seeming concerned, I could do that. I could go to an engine and do that, but if I’m a creative, I wanna get maximum [00:36:00] options. So he created this tool that you put one prompt, it goes and interrogates, I think four or five different engines comes back with images and you can see like, oh OpenAI did this, Google did that, that one did this.
And you are looking at all of them in front of you, and you can say, okay, take this one, regenerate this one, and regenerate that one. So it’s almost like process. It’s so cool. Yeah. But I imagine how many steps it saved Oh, yeah. From doing Absolutely. Yeah. Absolutely. end, what happens is this is pure generative ai.
You own that image. So you basically own that image. You make it available to other marketers, it goes into your content library, right. In the same spot. Right, right,
Adam Turinas: right, right, right. Yeah, I was That’s a brilliant idea. Wow. there was some other tools that you use. I think you’re using, there’s one that I hadn’t, I hadn’t heard of, called, is it Tega AI or Tiger ai?
Nick Panayi: Yeah. Yeah. Tega. yeah. I’ll tell you about Tega then. Remind me to also [00:37:00] tell you about synth flow. yeah. So remember in the beginning I said that, you know, we have a combination of approaches. One is things like you need a crisp for, right? Things like what I just described. You need somebody to be able to take all these AI engines and, bring something together for you, for your people, for your company.
And it has context of everything, which is great. That’s what Chris does for us. Not everybody has a crisp, some people it can just go out. You know, and look for platforms that already exist. Tega AI is one world’s platforms. it was actually, founded by, the CTO of Eloqua, if you remember. Oh, yeah.
Not Brian. so he and I, uh, were friends ’cause I was an Eloqua customer, so he led me in on a beta program for Tega ai and we’ve been using them ever since. So, Tega AI allows you to do AI based prospecting in a very specific way. You basically have agents that you tell the agents [00:38:00] what it is you are looking for, you know, your ICP type of person you’re looking for.
What kind of, basically what the ideal prospect would look like and conditions that would make them an ideal prospect. They go out and scan the web. For them. Mostly they use other sources as well, but they do their best work in LinkedIn. They find them on LinkedIn. They begin a conversation based on information that you’ve given them.
They do the initial outreach that says, Hey, wonderful post finding. You should say that, you know, we have a white paper that you may be interested in because it goes towards this. Right. person says, oh, that’ll be great. Go ahead and send it to me. AI agent passes it to the human, the human continues the conversation.
So it’s a great marriage of AI and human collaboration in prospecting.
Adam Turinas: Right. Clever. Very interesting. Yeah.
Nick Panayi: Yeah.
Adam Turinas: it’s also, it’s doing the thing that we’ve been. [00:39:00] Training salespeople to do for the last 10 years, which is, this is a basic way to use LinkedIn, and very few of them do it.
Nick Panayi: Yeah. And it doesn’t scale, you know, so, you know, you basically, that’s where AI can come in and, make it scale. yeah. And of course to be authentic, once AI does the first introduction, you want the human to get involved because, you know, you could carry this on forever, but at some point we’re not yet at a point where humans are super comfortable going all the way with ai.
They’re comfortable with AI doing those first kind of steps, and they don’t want to deal with the human right. So that’s the beauty of this. But at the end of the day, I can see this going further and further, the better the, the AI gets. It also is very good at finding RFPs, which in B2B, RF P hunting is, very, very.
Valuable exercise. You know, going out there scanning the horizon for our,
Adam Turinas: it’s easiest
Nick Panayi: too, right? Yeah, yeah, exactly. Finding the ones that are most relevant for you, [00:40:00] bringing them back. And again, the human is gonna take over from that. The other company that is also in prospecting that is very promising for us, it’s still early days, but we’re starting to see some of the ROI, it’s a company called Syn Flow.
Mm-hmm. So S-Y-N-T-H Flow, syn Flow. They happened to be out of, Germany, out of Berlin. they were, relatively small when we started working with them a few months ago. They’re growing by leaps and bounds. I mean, you look at their logo, page, you’d be like amazed at how many com companies are using them already.
So what these guys do is conversational AI prospecting agents. So they have conversational AI competency, obviously any language, you know, obviously we train them on, on English in our case, we didn’t train them on English, but we use them for English language. But they reach out and they do the initial phone outreach, which again, humans don’t scale very well for that, right?
You tell [00:41:00] some, you know, a human, hey, you’re gonna be spending your whole day placing a hundred phone calls. You may get to speak to like two humans. One of them is gonna curse you out. The one and other one may be interested in what you have to say, right? Yeah. It’s not a very fun exercise. And that’s a good dad, by the way.
Yeah. And, and that’s not a good dad. AI does this very, very well. It acknowledges, it says, you know, I’m an AI agent from company A, B, C, like to see if you’re interested in signing up for this webinar. Or, we have a white paper which we think you’d be interested in, can we send it to you? Or something like that.
Yeah. In essence, getting somebody to raise their hand in some sort of way. Yeah. After they raise their hands during your system. Now I’ve heard, you know, obviously we have video of this system is, it’s available to you. Everything is recorded. You can listen to these conversations because blown away by the concept, because I came from a conversational AI company and I was there three [00:42:00] years ago.
The degree to which this has matured is absolutely mind blowing. There is no way I could play that voice and you would know that it’s ai really, the only time you, the only time you would know there’s still some of the wrinkles being worked out. Is that. There was some delay sometimes because like the AI knows not to interrupt the human, so if the human starts talking, it stops.
So you have some of these awkward moments where literally there was one where it was like 30 seconds worth of goodbye. Like, okay, goodbye. Thank you, goodbye. You know, one would interrupt the other, so you have some of those awkward moments. Mm-hmm. But the ability of the AI to understand what the human is saying and take intelligent routes to answering those questions that come back is incredible.
So we, we taught it obviously enough to know about our products and a webinar series or multiple webinar [00:43:00] series that we’re running. It would place the phone call. I’ve heard conversations where the person on the other end would say. First of all, you know, are you human you know, and I’ve heard many of those.
And he would say, I’m an AI agent, you know, here to help you. Of course I can, you know, connect you to human if you like. After that, you know, the person would say, well, this would be great for Jane, but Jane is on vacation and she’s not gonna be around. Yeah. I would say, thank you so much for this information.
I understand Jamie’s on vacation. How about I send it to you and you let Jane know? I mean, that kind of thing. You cannot script that. the beauty of ai. If I had to script. Every possibility of the conversation would go, I would be called God. Yeah. There is no way that you can script any of these conversations, but AI is smart enough to know how you must communicate.
and you give it some leeway and you make sure it’s polite [00:44:00] and you make sure that it doesn’t do anything silly. But some of those interactions were actually just mind blowing. I, I ended up like sharing some of them out. Now again, ha has this blown the doors open yet? Not quite yet. You know, ’cause you’re still gonna get the people who hang up don’t wanna ever talk to an ai.
Yeah. But this is the worst it’s ever gonna be today. It’s gonna get better. It’s gonna get better and better and better. And if it’s mind blowing now, I imagine, like, you know, a year from now,
Adam Turinas: I will look into that. And for anybody listening, there’ll be a link down below in the show notes. I wanna switch gears and talk about two of the issues that came out of the study.
So these were the two top issues. So the first issue is a lot of the marketers in the survey said the number one thing that they’re getting pressure from their CEO about is, how can we use AI to increase the top line? That’s number one. And number [00:45:00] two, how do we measure the impact of all this AI investment?
They may be the same thing, but not necessarily. So I’m, curious about where you are on the journey on those two, two topics.
Nick Panayi: Yeah, it’s interesting. When I first presented, our executive, uh, my boss at the time, we’ve had a change in, the leadership team since then. But I presented this to my president at the time, that was his first question.
It’s like, wonderful. What’s the ROI? And, we had already developed, in essence a custom RI calculation for each one of these because it depends on the use case. Like, for example, something as simple as, you know, content creation actually take image creation. Yeah, I know, I know what I have to pay Getty for, right?
and I know what I have to pay for generative images, which is zero. So I can do that calculation very, very easily. And it’s [00:46:00] a cost containment calculation. I can use those dollars it to be something else, especially if I do that at scale, right? Same thing with content creation is what I’ve just shaved X number of cycles from my content creation.
That means my content developers can create. Why number of assets more per year than they could otherwise. Right. Those assets bring in leads. Yeah. So I’m able to kind of tie the leads that I bring in because the content brings leads in, when it comes to prospecting tools and things like that. Honestly, it’s a no-brainer.
I don’t if the one, the last case that I mentioned to you, the cost is per completed call. It’s not even per call made. It’s per completed call. And it can be a voicemail, it can be like an IVR system. So the fact that I’m only paying X number of cents per completed call, and then I can basically look at one deal that came through.
I paid for it like [00:47:00] for the next 10 years. Yes. One deal. One deal. Yeah. So it’s very, very easy to do those things because ai. Does not require significant upfront investment. it’s directly related to your usage, you know? Yeah. And even that direct relation to your usage is so small dollar wise that it becomes a no-brainer discussion.
But it’s always good to document regardless. Yes. You know, regardless of the tool. So well, each two, each tool has its own ROI calculation,
Adam Turinas: but I think there’s something kind of, you know, really, important learning that I’m taking away from this, and that is that the way that you’ve got this organized is into very specific pilots and work streams.
And that for each one, there’s a KPI, which is related to that particular work stream. So if it, for the, the image one’s a great example that there’s A-A-K-P-I, which is the cost of images. So there you go. that’s how you Yeah. You can measure the impact. On the outbound [00:48:00] calling, you can measure the impact and then tie that back.
’cause then you can track the lead all the way through to deals. You can see the impact of that. So that’s, that. That’s very helpful. And you have to get really granular to do that. Right?
Nick Panayi: Yeah. and I should have mentioned another example that I believe is even easier to demonstrate, right?
So one of the things that we do as marketers, right, is create video. and as we know, the more video, the better, right? I mean, we’re, human beings are very much attracted more so to the visual, content assets than, writing. so video is very, very important. We produce a lot of video. sometimes it’s presentations, sometimes it’s just animated videos and things of that sort.
voiceover is very important. In yesterday’s world, we had to go higher. voice talent, to be the voice of your video, right? You don’t have to do that anymore. There is high quality AI [00:49:00] voiceovers that can give you that the fraction of the price and fraction of the time that it takes you to go to an agency to get five, you know, samples of voices, to pick one, to do the reading, to play it back, to go change.
Oh, by the way, somebody says, oh, I’m sorry. You know, I’ll just change this. One line needs to change. The talent goes back to the studio. It’s done with AI instantly, with the company. We, use 11 labs.
Adam Turinas: Yes. Yeah, I use them too. Yep. Yeah.
Nick Panayi: Yeah. 11 labs is one. so that’s a very, very straightforward ai.
I give you another data point. I don’t know how I could put any RI to this, but, we had. a fantastic event. our CEO was one of the presenters. 99.9% of the presentation were just spot on. There was one phrase, and I forget what it was, maybe it’s just selected, like, just got it outta my memory that he [00:50:00] set their own phrase.
it was just the phrase didn’t make any sense for the context. We had something else in mind. He said it, so it wasn’t like, you know, mispronunciation or something, like, it was just the wrong phrase, you know, so at that, it’s like, what do you do? I mean, it was a live event. We wanted the video up there because he was getting hits left and right.
So we used one of his, you know, AI voiceovers, trained it on his voice and had it say that phrase correctly. put it back in the video. you wouldn’t know it. I mean, obviously, you know, and we took his face off, the video,
Adam Turinas: right? So there’s no syncing issues. Brilliant,
Nick Panayi: in fact.
But it was, it was literally 99. It was 0.1% or the presentation, but it could have been one of those moments that somebody said, what? That doesn’t make, that doesn’t make any sense, right? So, so we did that. The other thing that, we find fascinating, at least I do, is, AI podcasting. So, [00:51:00] oh yeah.
Obviously podcasting is so important. Now, again, you can take like a hundred page white paper and boil it down to an 11 minute podcast, right? And you have yourself an amazing, peripheral asset that sometimes even becomes decentral asset. So we had one of those cases, which became the impetus to, to use this capability, we use Google Notebook, LLM.
For this? Yeah. it’s on our website. it’s, you know, the first one we did, we did multiple, but it’s, it was one around, uh, study we did with Harvard. it had, I think, four or five white papers. As much as I like the healthcare industry that I’m in, you know, I could not read all five white papers and retain that content.
I listened to the podcast and I got it if I got it right, you know, that was, a good kind of gauge and it was, it’s literally two AI podcasters, you know, a male [00:52:00] voice, a female. Yeah. It’s unreal. Again, you cannot tell there. The banter between the two of them and the joking around, we didn’t have to script that.
You basically load, you give some guidance to it. Yeah. the good news is you can say make it funnier, make it shorter, make it longer. Make it more serious. Yeah. You know, focus more on the facts, less on kind of opinion, but it’s amazing what you can do. So we are using that for our podcast as well.
Adam Turinas: So I’ve got two closing questions for you. Yeah. by the way, I mean, we’ve been talking for an hour and honestly I could talk for another three. you don’t have the time for that. first question is a very personal one. So I run an agency.
What’s your advice for consultants? You know, service providers. Now obviously you guys have, you are probably because of the size of your team, you probably don’t use agencies as much as other, many other companies do. But what would your advice be for a firm like me?[00:53:00]
Mine?
Nick Panayi: Yeah. I would say be the Chris that others don’t have. that, to me, knowing the art and science of marketing and understanding how AI can empower marketing is a huge value add to any company. And I can tell you, and I, I’ve done presentation, the deck that I shared with you, Adam, I presented it as I said, multiple times.
And almost every single time people say, how do I get a Chris? I’m like, well, either you get a Chris or you get an agency that has a Chris or is a Chris. So the agencies can play that. Many, many companies don’t have the ability to have the size of marketing organizations that we’re blessed with, right?
So, but agencies can play a significant role. It is not just about producing stuff, it’s about, doing things more effectively, more efficiently. And producing stuff is part of the mix. You know, it, it’s really part of the mix going forward.
Adam Turinas: Yeah. I’ve, I’m reassured to hear you say it because I completely agree with you.
and [00:54:00] any agency that’s not figuring this out or is in denial about it though, they’re gonna be in trouble. this is fundamental. anyway, enough about the agency stuff. So I, you know, as I mentioned, right, the vast majority, so you’re on the sort of high end of the top 7% of marketers in our category in healthcare technology.
terms of the way that you are using ai, what advice do you have for your peers in what they should be doing as they think about their journey?
Nick Panayi: in addition to get it, Chris, this, this, the second thing I would do is make sure your marketers, are immersed in ai. they need to be comfortable themselves.
They need to understand the role that AI has to play, and they need to ensure that their head is nowhere near the hole in the sand. because it’s, gonna happen to marketing, but it doesn’t, it’s not a bad thing. it’s a good thing. it makes us as humans focus on the things that we [00:55:00] do better and it lets AI.
You know, do the things that we don’t like to do anyway. It just frees up our mind to do the things we like to do more of it, just the explosive opportunities for creativity. I mean, the fact that you can write what you want the video to be and that you see it play in front of you a few seconds later.
I mean, what creative person would not love to have that? Which one of us has not had an idea, says, I know what the next video should be. And of course, you’re not gonna sit there, you know, oh, that’s gonna take a few hundred thousand dollars to do so. No, you know, it democratizes creativity as long as you, know how to work with it.
So yeah, I would say free up their minds, make them comfortable, and tell ’em to go experiment and make mistakes.
Adam Turinas: I think that is a great piece of advice. To finish on Nick, I am blown away by what you guys have accomplished. I found it [00:56:00] completely inspiring. I know as an agency leader, I should probably be terrified by it.
But actually I’m completely inspired by what you’re doing and, wanna start an agency called Get Chris.
Nick Panayi: I’ll send you a t-shirt. I think we’re about to make one. Nick, thank you so much. Thank you. It’s been a pleasure. Thank you, Adam.
