1Mby1M Entrepreneur Bootstrapping an AI Deep Learning Venture to over $5M ARR: Bharath Gaddam, CEO of Data Poem (Part 1)

It is always thrilling for me to listen to 1Mby1M entrepreneurs achieving great things. This interview capture’s Bharath’s 6-year journey of bootstrapping to over $5M ARR. At this point, I am fairly confident that Data Poem can blitzscale to become a legitimate Unicorn. Not fluff, not fumes, clear, concrete ROI-driven revenue growth that is set up for repeatability and velocity. 

This is a text book case study of the 1Mby1M Bootstrap first, raise money to Blitzscale later philosophy. I have no doubt that VCs are going to salivate to get into this rocket.

Sramana Mitra: Bharath, let’s start at the very beginning of your journey. Where were you born? What were the circumstances and what kind of background did you come from?

Bharath Gaddam: I was born in a small town in Andhra Pradesh called Tenali. My father is a production manager in a large dairy farm, and my mother is a professor in a graduation college. I did my graduation from Osmania University in instrumentation. During that time, I realized that maybe I’m not cut out for hardcore engineering, but some of that still stays with you.

I knew that at the time that that’s not what I want to really do on a day-to-day basis. I started thinking about what I wanted to do.

One of the core things that I figured out in that journey of identifying what should I be doing is that my core being enjoys the most when my thinking influences something great or makes something better.

In a way, I understood at that point of time, that role can be three ways. One, I can go into active politics because you can influence at a higher scale, but I didn’t know what’s the profession there. In India, there’re no organized political professions like campaign strategists at that time. This is way back in 2002 when I was thinking what needs to be done right after my graduation.

Then the second part was my profound passion personally for brands and anything to do with brands. Brand marketing used to influence me a lot without knowing that I’m actually getting influenced by brand marketing. I used to be an ardent follower of Pepsi because it used to tell me ‘Nothing is impossible’ or the next generation messaging appealed to me.

Another great brand was Nike with its tag line ‘Just do it’. The brand you wear can tell something about you and what you want to do. In a way, the brand was resonating with what I wanted to do. I was deeply interested in it because of that, I read a book – The 22 Immutable Laws of Marketing. That’s when I decided that brand marketing can be the second option.

At that time, it zeroed down to two options, active politics and brand marketing. I chose the easier option of brand marketing, and I pursued my postgrad from, one of the communication schools in India. I specialized specifically in brand marketing. I joined different communication groups like WPP and Omnicom, and worked as a brand strategist, media planner, digital strategist, and performance marketing specialist.

When I was working, even from day one of my job, I was seeing this gap. At the time, I was naïve with no influence of any sort except for theoretical understanding and the foundation of post-graduation communication strategy. I realized that all communication planning was done in silos. I was thinking, why is it done on siloed metrics, not as unified effectiveness metrics?

Then as you progress along in your career, you figure out that same question is still not answered. You’re still either putting your siloed metrics or you’ve a conviction that everything is working because there is some correlation of sorts. I was the Country Head for a communication groups, had worked with Fortune 100 and 200 companies as well as small organizations.

However, I realized that across the board, the intelligence systems are broken. No one has a clear, unified view about why something is happening and why something is not happening. They all know it’s working or it’s not working broadly, no one can really point out when something is working, what is working, how much is it working, or why something is not working or why something is working.

They didn’t have that answer, and everything is done in silos. Because they don’t have the whys, everyone is trying to optimize the silos across the board – within the organization and within the consulting firms. Anyone who is guiding organizations for their growth is optimizing silos in order to pursue the end goal of growth of the organizations.

That’s when I realized that this is not how it should be done. At that time, this is 2018 I’m talking about, big data is really in for using large data sets to find patterns, understand, and find a solution. We pursued that path, but we realized that even there, there is no real solution. They’re all getting the data in one place, but they’re still using disconnected techniques, which is still very siloed.

The fundamental premise of any statistical technique is that different factors are independently influencing the outcome, right? But our experiences otherwise as human experiences, otherwise as professional experiences, all of these are interconnected factors. If your learning system is disconnected, how can you get the real truth?

Then back in 2018, we were recommended an applied mathematical solution called deep learning stroke neural networks, which was solving all my problems statements. The way I saw it was the system has to learn the interconnected effects, synergistic effects, and should be very granular in nature. It should not have any limit on the number of features that it can take, it should be able to adapt and learn continuously with the same learning as we go along.

At the time, the only solution that was ticking all the boxes was the neural networks method. No one really understood how it worked in real life. It was in the academic world at the time but was ticking all the boxes.

I was still heading Omnicom at that time, and then we said let’s try this. And it worked.

This segment is part 1 in the series : 1Mby1M Entrepreneur Bootstrapping an AI Deep Learning Venture to over $5M ARR: Bharath Gaddam, CEO of Data Poem
1 2 3 4 5 6 7