Sramana Mitra: How long did it take you to build out all the specs that you were getting from these customers?
John Wallace: We were experimenting only for about a year and a half. Then we spent probably another nine months building the modelling platform.
>>>Sramana Mitra: So, what you’re saying is that you got this input about what the market was looking for, and because they were paying customers on the first piece of the functionality, you were able to get them to give you access to data. Because in all of this, as you know, in building AI products, access to data is one of the big gating items so that you can develop anything without problems.
John Wallace: Yes. We cannot build these products in a laboratory. We need to do it in the trenches with customer data.
>>>Sramana Mitra: Now, let’s double click down on the concept of experiments. Once you were in these POC situations and started to gain some traction, what kinds of experiments are customers running?
>>>Sramana Mitra: So let’s double click down on a couple of things here. You mentioned a different dataset. So, what dataset is LiftLab using?
John Wallace: In our last company, we were essentially working with user level data, device level data, and log data. Now, we’re working with aggregated data. So we’re working with time series, and the methods are much more around econometrics. So it, it was a new data set and new algorithms.
Sramana Mitra: And what, what is the source of this data?
Sramana Mitra: John, welcome to the show again. What are you up to these days? It looks like we talked a while ago about your previous company DataSong and you’re up to a new adventure. So, tell us about it.
John Wallace: I’ve been fortunate to be building Lift Lab for the past five years. The team had built a company with me called DataSong, which, you covered. I feel very honored and fortunate to be a second time attendee on one of these interviews.
Sramana Mitra: This is very interesting. The way you’ve stepped through the line of thinking of why you’ve arrived at these decisions is very instructive. Where are your schools?
Pallav Pandey: All over India. These schools are very different from typical SME clusters. SME clusters are very local. That is not how schools are. Schools are evenly distributed across India. The only way you can go and cover schools is if you figure out a telephonic way to reach out.
Sramana Mitra: Definitely.
>>>Sramana Mitra: Education is the only passport to get to the next level.
Pallav Pandey: Absolutely. Everybody in India is very clear that if I have to go to the next level, it is my child who can take me there if educated properly. People are spending on education. If you are able to do EdTech in India at a thousand rupees per annum, then every single family is going to buy. We didn’t know how exactly it will play out. Blume got excited, so they put in some money.
>>>Pallav Pandey: Then we had another divine intervention, I would say. He started collecting whatever money was due from schools so that he can pool up whatever was left. He said, “There is one school in Delhi which was opposite to your house. They were supposed to pay us some amount. They’re not paying us. They want to meet somebody senior.” The principal was insisting on it.
I met the principal. She said, “I’m very sorry to hold your payment to meet you.” She thought I was the founder. She said, “I really wanted to meet you. We love your product. This is how we use it.” It was a very simple ERP. Think of like WhatsApp for schools so they can do the parent-teacher communication via the app. She said, “I will refer you to a school I used to work with. We have three branches in our current school. Before referring you, I wanted to know who these guys are.”
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