Harsha Mokkarala on Building AI for Modern Go-to-Market Teams

Welcome to Founders' Future, a podcast powered by Closers.io, where we explore the journeys of innovative entrepreneurs and the road ahead for their companies. I'm your host, Natalie Borofska, and in each episode we uncover the stories behind impactful ventures. The challenges faced, the lessons learned, and the strategies fueling future today I'm thrilled to be joined by Harsha Makarala, who is the founder and CEO of E.A.I. Driven Business Intelligence Platform that helps companies turn raw data into actionable insights and smarter go-to-market decisions. Before launching EQ, he spent over a decade shaping data and revenue strategy at Capital One and TwoU, where he led digital marketing, predictive analytics and revenue teams that helped scale business performance. I'm so happy to have you on the podcast today. Nice to be here, Natalie. No worries. What I like to do at the start of every podcast episode is I like to journey back in time. So take us back to before you started EQ. What were you doing at the time and what motivated you to start your company? Yep. I've about 20 plus years background in particular data science and data analytics, solving business problems, in particular growth challenges, marketing in sales and product sort of challenges. Started at Capital One, helped scale that business, particularly with digital side of that business, from being a small part of the business to a majority part of the business. Did the same at a company called TwoU in the tech space where I was a chief marketing officer and chief revenue officer. The thing I learned in both of those things was that good data science, good data analytics and data, strong data foundation are as much a competitive advantage for a business as sort of a good product and service in those kinds of things are needed. But good data science can be a real mode for any given business. But most smart to medium sized businesses are locked out of this functionality or this capability because it takes very particular skill sets when it takes building very particular infrastructure for it. And with generative AI and with gentry AI, beginning to take take shape, in early 2004, I felt like the opportunity was arrived to build this capability in a way that is accessible to companies large and small. And I took the leap on my entrepreneurial journey to solve for that. And yeah, so I speak to a lot of business owners. Do you feel like you had an aha moment that led you down the journey of entrepreneurship? Or was it like a gradual journey into it? I was very fortunate in the companies I'd worked for before as much as they drew to be large companies. I started when these were smaller and I got to be in roles that even as part of a large company were very entrepreneurial in that kind of event. So in some days, my experience before starting EQ was almost like for me, I've built up in a training ground to get to get to this point, to get to this point, if you will. And I'm one of those people that likes to build things. And this, I wanted to build a product and in some ways that led to the entrepreneurial journey as opposed to it being an aha moment, for example, to get me there. So it's been pretty much a journey up to this point. Yeah, it's great that the roles that you served in before have really given you the solid foundations for you to start your business now. I feel that happens a lot with business owners. They work roles and then they start venturing out into entrepreneurship and they find that the jobs they work before, they really gave them the skills to do what they're doing today. So let's dive into your business today just to give the listeners some more context. Who would you say is your ideal customer? You know, our ideal customer is that midsize company, the series A+, series A, you know, series ABC kind of company. They've got some revenue, they've got some track record underneath them. And they're typically looking to really scale the business, whether it is through go-to-market motion, through product innovation, whatever that is, for example. But, you know, are at a point where the inefficies in their processes are best served by using data and yet analytics to solve for a few else. So you know, how do I scale paid marketing or a large scale, go-to-market operation, for example, while still feeling like in control of how I'm making my investments and where I'm going, for example. Or, hey, I'm ready for some major moves on product innovation. But, sort of, I want to make sure I do that with, you know, consumer input and feedback and all that kind of thing as part of the journey for growth, if you will. But, our ideal customer is that sort of thing. We're usually, you know, 100 to 200 employees. They might have one or two people who are in analytical sort of job families. But like, do not really have the full capabilities of you know, water, data engineer, ML engineer, a world-class data science, test or data science, you can bring to there. And we serve as that for them. Sort of our platform and our services, our managed services, sort of, layers serve as the gap for them, serve as the accelerant for them. To get that capability up and running within a matter of weeks and then beyond their journey in terms of expansions like that's typically, that's typically what I see. We also tend to do well where there are some complexity involved in the customer journey, right? So, you know, verticals like, you know, education, finance, healthcare, farmer, those kinds of verticals where the customer journey has some complexity involved, their qualification hardwoods or revenue recognition happens over a long period of time with repeat bunches and subscription and those kinds of models, for example. We tend to do well in those setups because data can have a substantial impact on sort of improving that customer journey or improving efficiency KPIs. Those kinds of examples. So, so it's where that intersection of like small to medium-sized business in, you know, a complex vertical where data can sort of be the lifeblood of the operation. That sort of tends to be RIC. Yeah, all the answers are in the data. And when you're especially like when you're a medium-sized company looking to become like a big company because that's when like the little things like start adding up. So, once you have the data, you have like the full picture and it sounds like that's exactly what your platform allows those companies to see where they do more efficient and take them to the next level. So, let's shift you client acquisition. What are you currently doing from like a lead generation standpoint to really be able to target your ideal clients? So, we use multiple channels and multiple mechanisms. We do a fair amount of part leadership and putting our point of view out there. For a company our size and this early and by the way like selling something that is like fairly different. It's not like people wake up in the morning and say, you know what I want today? I want an AI data team, right? You know, it's not sort of a, you know, it's a new, it's a new, it's a new vertical almost, it's a new category almost that we're trying to establish. I think having a point of view is extremely important. And so, we are reasonably aggressive about talk leadership, you know, and I have, you know, with my level of experience and sort of network and that kind of thing, you know, establishing us and, you know, me as a little bit of a thought leader is sort of an important priority. So, we are out there a bunch whether it's on platforms like LinkedIn, you know, putting, you know, putting out observations and, you know, and talk leadership content, whether it's through podcasts like this one, whether it's conferences, whether it is actually, you know, getting in front of companies, right? We do a lot of work with companies even before we, you know, even before their prospective client, where we'll go and sort of talk to their teams on, you know, best practices and what they're missing out and how to build a good data stack and, you know, how to look at their sort of data and analytic practices differently, for example. So, one pillar is definitely thought leadership that helps build our organic presence and we measure that through things like our LinkedIn following, engagements, site traffic, sign up to a newsletter. Those are our critical KPIs that we track against that sort of talk leadership and talk leadership. We also do a decent amount of, you know, what would be more outbound push kind of marketing if you will, you know, through channels like LinkedIn, email, we've got a few different mechanisms through which we go out with, go out with email marketing, all of those things typically need to sort of, you know, our website and a demo or a free trial, for example, so it comes sign up and, you know, we'll do a demo, it comes sign up for a free trial of our tool of our product. Those tend to be our KPIs on that one, for example. And then, sort of, of course, we're trying to convert those in and full subscription clients and members. So our word market strategy consists of, those two buckets, those two buckets. - Yeah, so it consists of mostly like a word of mouth, like networking and also a bit of like organic strategy. Have you guys considered utilizing like paid ads for, and does that like, would that work well with your like type of business model? - We do. Yeah, yeah, so we do, we do a fair amount of LinkedIn. We have tested with things like, you know, Google Adwords and sort of ads based, Google ads based, based advertising as well. And of course, sort of a lot of the email strategy work is basically, I count that and sort of that kind of paid marketing kind of bucket, bucket as well. But yeah, we do a fair amount of LinkedIn advertising. You think that is, you know, we think that is kind of our sweet spot in terms of channels that sort of wear our ICP largely aggregates. You know, if you're again a smart medium sized company, you're constantly looking for that edge in terms of like, what's out there and what's moving fast and things like that. And you know, we think LinkedIn's a great place to share, share and gather that kind of attention. - Yeah, on LinkedIn definitely, it's like the place where your ICP will like, will be the most. So with like the LinkedIn ads, is it like traditionally, like what type of ads is it? Are they like booking like sales calls with you or are you adding them to like your email marketing, like funnel and much of them there? How does it kind of work? - Yeah, most of our sort of, you know, ads are sort of either messaging, right? So they are sort of, you know, the sponsored messaging type products that LinkedIn has to offer or sort of the infeed kind of ads, for example. What, what, what call to action they drive to, kind of depends on a little bit of format and a little bit of, you know, a little bit of like who we're targeting and what, what messaging, you know, for that matter. The ultimate goal of all of these is for them to come to our site and, you know, set up either a demo with us or to sort of sign up for the free trial where they can, you know, they can try out the product, they can try out sort of what the, what the analysis layer of our product sort of feels like, feels like a fuel. The mix of those two, whether it's a demo request or whether it is sort of the free trial, sort of depends a little bit on the format in terms of which advertising format we are sort of driving at. These are also fairly early days in terms of all of that experimentation. So we are, you know, constantly trying to test out sort of what gives us an edge, right? Should we drive to a content page? Should we drive to a landing, landing and sign up page? Or actually just be a talent lead that sort of they can actually go drive and hook, you know, book meetings against. The story isn't settled on any of that at this point. We're still in very much experimentation kind of phase with that stuff. And by the way, you know, if you know my background, that's what I love about sort of what I do, right? You know, they chance to try new things, experiment, you know, you know, I always talk about sort of, if you're not constantly running on experiment at least on these channels, you're leaving money on the table. So like constantly being able to rotate through different things and try them out. And by the way, like whatever you learn now will not be the right answer, six months from now. So also be open to the fact that like you'll have to change that change that again, for example. But you know, we're still in early days of figuring out like what that right, you know, top of fun also the experience if you will looks like for our users. - Yeah, 'cause you can experiment. And then you gather the data and then you're really able to see like what works. And clearly like that's the business you guys are in. - That's the business we are in. Like that's it like you said something that I, that I'd speak my interest. It's sort of, you know, you experiment, you gather data, you learn, you figure out like, hey, this one's working and this one's not working. I think though it's very important to not be wed to that. But it's if there's one learning I have from doing this over like any number of years, it's that like, you know, these things are always in more right. Like what do you think is working today, you know, will not work three months from now. And so it's also very important to not be wed to any of it. And in fact, like if I'd sort of go further, I would say like sort of embrace the randomness of it a little bit. Like you think, hey, this is working and you've in your mind created a nice narrative as to like why this is working. You're like, hey, the sponsored ad is like a, the messaging ad is a lot for personal. Therefore like the booking and meeting thing works well there. I've got a nice narrative in my head. Well, you know, that now it is only good as like the next set of data you get that tells you that it's wrong. That's wrong. And it's something else, for example. It's like also don't be wed to, don't be wed to your data. Constantly be trying to try to create new data if you will. Yeah, it's all yeah. And the answer is will be in the data. Like there's no doubt about it. It's just being able to like pivot. Because yeah, you're right. Like sometimes things just like stop working. Like they've worked so long and then they stop working. So then you have the new thing so that you guys can like stay in business. So it's just the fun of it. It's fun of the game. It's fun of the game exactly right now. So we're at the start of 2026. So when you think about your vision for the next 12 months, what are your goals, targets, what milestones do you guys really looking to get? Yeah, I mean, there's obviously, you know, growth and we want to be, we want to grow and we want to sort of grow responsibly. We are a product that's very much about delivering R.O.I. for our customers. You know, it's important to me that sort of what we are doing translates into value for our customers. I think that's the right call. We have very good signals of that. You know, very good signals of that right now from our customers. All of our early customers have, you know, re-up asked for expansion, ask for more use cases, all of that kind of thing, for example, which is great to have. I think on the growth and scale side, which I know that's what sort of the topic of this conversation is, I think for me, it's very important to be a established system, right? I think the actual numbers in terms of like what your cost of acquisition is or what you cost per leaders and, you know, what you're actually, what you've actually achieved in terms of revenue. For me, that is very much all about the executes, but the fundamentals of it is a system. The fundamentals of it is, you know, are we settled on, you know, precisely targeting what are ICPS and sort of how do we express that through both targeting as in like, how do we, you know, would we, would we, who are we in front of and how do we get in front of them all that rooming, but also using messaging as a way to target it. How do we get to a precise point in terms of how we are generating value propositions and news and things like that to get out, for example? So among our goals for the year is actually a little bit of that feedback and system, if you will, right? How do we get to where we're constantly producing new messaging? We're constantly tweaking that messaging, getting the readout effect and going back to the well, for example. For me, you know, as a bit of a process guy who's done this many times before, you know, if you get that right, if you get that system right, growth will happen, right? You know, growth tends to be sort of an output of that, you know, not the other way around the field. So like our primary goal from a scale perspective is just that, is sort of getting, getting that experimentation for structure right, if you will. Yeah, just having like that system in place from the get-go is like very important. That's exactly right. The scale, if you don't have that like from the beginning, then potentially like, like even a couple of months down the line, it's going to like show up. So if you just have it like in place to begin with, that's like the ideal position that you can in. Like is going to be like the biggest challenges to making like your goals happen. Yeah, I mean a couple of things, right? I think I alluded to it earlier as well. We're, you know, somewhat of a new category, right? And not just as like a lot of the AI, you know, agent AI sort of, you know, tools and solves are in like new categories. If you are a sort of establishing new categories of your well, it's a new way to get work done if you will, right? And explaining that succinctly and translating that into how work happens today, sort of, you know, what is the before and after in terms of, you know, how do you do analysis today? Right? How do you sort of work with data today to how this new paradigm sort of improves that, for example, communicating that, particularly communicating that the people who may or may not live technology day in day out, which is sort of our ICT. Our ICT is sort of, you know, the business leader of the chief marketing officer, the chief financial officer, that kind of thing, for example, getting that right, getting that crisp is a significant challenge. And again, that's, that's not a challenge just for just for positive cue. I think like a whole lot of sort of AI native businesses have to figure that out in terms of sort of getting business, getting through to that ICT piece to think in entirely different ways as to how work happens differently with this and sort of trust that sort of these tools can actually serve the purpose that they, you know, that they intend to, for example. So like one of our definite challenges is that communication and messaging crispness kind of challenge challenge for us. So we continue, we'll continue to have to learn from our customers, refine that. Hey, like, you know, this is how I'm using it. And so this is the right message to sort of convey, for example, that kind of, I think that's definitely one of our, you know, one of our challenges for sure. second is we are we are not when you buy EQ you are not buying. just a platform, a simple self-service platform that you can just give us your name and email address and you have something in all of that thing for example. It takes for customers to get value out of it, it takes some real integration work, it takes getting data on boarded, those kinds of things, for example. And that means it's necessarily a more complex sale than a straightforward getting yourself a $20 SaaS subscription, for example, if you will. And so getting that motion, getting that motion right, figuring out how to engage with the right stakeholders for that kind of thing, I think those are also sort of challenges that we need to work through. And lastly, just making sure product delivery and customer support are in really good shape. I think a lot of our wins will come from happy customers who will refer us and who review us and that kind of thing, for example. Who will talk about how this is genuinely improved their business. And so continue to hammer the quality of our delivery, the quality of outcome our customers get. I think those are some of our bigger challenges. Yeah, just making sure that fulfillment stays up to the same level like while scaling, because sometimes business owners get very caught up in the front end and forget about the quality of their fulfillment. Absolutely. Making sure everything is up to par. But I'm excited to see what 2026 has installed for you. If our listeners want to find out more about what it is that you do, where would be the best place to find out? Look up EQ AI on Google or go to EQ.ai. That's probably the best place to find information. You can also find us or find me on LinkedIn. Please drop us a follow sign up for a newsletter. Sign up for a demo of your in a fair in the market for that next big sort of AI tool. For example, but you know our website in LinkedIn are probably the best places to find us. Perfect. Thank you so much for coming on the podcast today. It's been a pleasure. It's been a lot of fun. I love talking to folks who are curious like you about sort of where the space is going. Awesome. Thank you so much. And if you are a business owner and you're looking to scale your business, and you really want to enhance your sales and marketing efforts, visit Closers.io to hope on a cool with our team and discover how we went from zero to 30 million per year in less than three years. Until then, keep on climbing.