1Mby1M Entrepreneur Bootstrapping an AI Deep Learning Venture to over $5M ARR: Bharath Gaddam, CEO of Data Poem (Part 3)

Sramana Mitra: I remember some of the work we did on the positioning. Summarize the process of how you’ve got to product-market fit.

Bharath Gaddam: The important part of product-market fit understanding happened during those five- six months before COVID, where we had our interactions. One of the things that we realized early on was that you having a better solution is not the answer.

Sramana Mitra: It’s a perceived solution.

Bharath Gaddam: Yes, perceived solution. Because of our experience, we know that there is a theoretical problem, but the world is still living with it like the way the world lives with pesticide grown vegetables, right? We live with it; we cope with it.

Sramana Mitra: The world lives with a lot of problems. How big is the problem? Do people really want to solve it?

Bharath Gaddam: Absolutely. We understood that after we started the company with a very strong theoretical understanding that this is not how it should be. We had the MVP, and we said that we are faster, we are smarter, we are faster than the regular stuff.

Sramana Mitra: How did you define the problem that you were solving?

Bharath Gaddam: We were focused on marketing at the beginning, because we understand every nuance of that space. For marketing, the biggest problem is that ROI systems were broken, or the measurement systems were broken. We said, “If that is what the problem is, what are its dimensions?”

Its dimensions were not answering the synergistic effects. It was not answering the unified effect because there are multiple marketing drivers. Everything was siloed. Media was siloed; promo was siloed; shopper was siloed. It’s not unified. Then we said, “How do we create one unified system?”

Then it’s not agile enough. It’s very static. And COVID kind of built this new dimension called, I want to know what will happen faster enough rather than later. So, agility became an important dimension.

Last, but not the least, the evolving digital landscape also kind of disturbed the mental models. They wanted a faster, intelligent system which is unified and which they can act upon because COVID was fluctuating. They wanted a system that can intelligently tell them in a faster manner.

So, we were doing faster, smarter, and more agile.

Sramana Mitra: Who was the buyer?

Bharath Gaddam: During the product-market fit discovery, we thought CMO is a buyer. It’s true at some level. The budget is coming from CMO, but he’s not actually buying it. He might be the end consumer of the eventual outcome, but someone else is making the decision.

Sramana Mitra: So, CMO is an economic buyer, you still need the technical decision maker. Remember the module that I made you go through?

Bharath Gaddam: Yes, absolutely. It’s the critical distinction that you need to understand. One is this distinction that we are faster, smarter, and more agile. Then we are saying, the CMO was a decision maker.

During the several initial pitches that we did, we figured out that the CMO is putting us onto the analytics guy who’s the technical decision maker. It took us one year to figure that out.

We lost one year in our GTM.

That’s why I said COVID kind of helped us because we could do this iterative thing, and during the process we realized that agile is something that no one is offering. So, we narrowed it on agility because our system always had that capability.

Now, we understood that the buyer is not the CMO. We stopped all CMO outreach, and we started the outreach on analytics and predictive analytics sets.

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