Sramana Mitra: You’re catering to French clients?
Daniel Nathan: Actually, we don’t have any French clients.
Sramana Mitra: Where are the clients from?
Daniel Nathan: US – a lot of them from San Francisco.
Sramana Mitra: How did you find these clients?
Daniel Nathan: I was traveling a lot. I was going to all the conferences. I had a name in the industry. When people receive an email from me, they’d open it. I was trying to get introductions and I was traveling like crazy. I got the Golden Mile ticket in six months.
Sramana Mitra: The types of clients that you were going after were mobile app developers?
Daniel Nathan: Exactly.
Sramana Mitra: Were these small companies, large companies, or mid-sized companies? Where were you gaining traction?
Daniel Nathan: Very large ones. Most of our clients are multi-billion dollar companies. Our clients are valued, at least, at $100 million to $200 million. Our bigger clients are Uber, Lyft, Yelp, and Social Point.
Sramana Mitra: You managed to get into major accounts and do mobile marketing for them and started to generate revenues for your company that way from France.
Daniel Nathan: Yes.
Sramana Mitra: You started doing this in 2013 or 2014?
Daniel Nathan: We started in December of 2014. The real business started in 2015.
Sramana Mitra: How much did you do in 2015?
Daniel Nathan: We did about $9 million.
Sramana Mitra: In one year, you did $9 million. That’s a huge amount of revenue in one year.
Daniel Nathan: Yes, and we were just five guys.
Sramana Mitra: Tell me more about what, strategically, did you do to go from zero to $9 million in one year.
Daniel Nathan: First thing is building an amazing product that is extremely scalable. In the first three months, because we were thinking that we’re going to become a SaaS company, we put a lot of effort into the technology. We had to be scalable.
Sramana Mitra: When you think about the core features of your SaaS product that helped you achieve that level of scalability, can you identify what you did from a product marketing point of view that helped you identify where you were going to get the leverage from this product?
Daniel Nathan: If you think about the way a typical media buyer and an agency works, they’re going to set up 10 or 20 companies a day. Then they’re going to download a CSV file and make a pivot table. They’re going to try and understand the patterns and try to optimize it. It’s going to take, at least, six to seven hours to find those patterns. What we have done is cut that work and do it with an algorithm which is based on machine learning. A user can set up 300 companies in 10 minutes and with one button, two days later, optimize all of them in 10 minutes. With one click of a button, it will tell you how exactly to optimize. This is the key stuff.