SaaS Interviews with CEOs, Startups, Founders
The Math Behind Donald Trumps Brain, EP 293: Brian Ley,
16 Jun 2016
Chapter 1: What is the background of Brian Ley and his company Alpharank?
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Chapter 2: How does Alpharank analyze word-of-mouth networks?
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You are listening to episode 293 and coming up bright and early tomorrow morning, you're going to hear from Eddie Vaca. He will show you exactly how to get 100,000 quality live viewers instantly. Okay, Top Tribe, good morning. Our guest this morning is Brian Lay, and he's the CEO of AlphaRank, a data science as a service company that helps brands understand their word-of-mouth network.
He started in the world of computational, which I don't even understand, underestimating how diseases spread and has now taken the same science to help marketers target the right people at the right time.
Chapter 3: What is the connection between emotions and marketing strategies?
Brian loves positive people, healthy habits, and human networks. Brian, are you ready to take us to the top?
I am so ready, Nathan.
Thank you for that introduction. I butchered this word. I can't even pronounce it. Okay, I didn't graduate college, so forgive me. Computational what?
Epidemiology. Epidemiology.
Chapter 4: How does Donald Trump utilize emotional triggers in his messaging?
Yeah, how diseases spread. And it's, in my mind, one of the most fascinating aspects. You can kind of think of it as how anything spreads. Right. So happiness spreads through human networks. Obesity spreads through human networks. Decisions to buy a product or upgrade to a specific technology fashion would go to going to see a movie.
All of those things are what's called socially contagious, meaning that one person gets them, then another person gets them. And what Alpharank does is it basically infers network structure so marketers can understand. If they're going to send out 100 discount codes, who should they send them to in order to get the most impact and have that offer ripple through the network like a virus?
Chapter 5: What is the viral coefficient and why is it important?
So Brian, real quick, give us some context. How old are you? I am 26 years old. Okay. And is this your first kind of thing into entrepreneurship or not?
Yeah, this is my first venture-backed company, but I've been obsessed with this for years and years and years. How much have you guys raised?
About half a million dollars. Okay. And before we get more into the business model, how does Alpharank make money?
Chapter 6: How does computational epidemiology relate to marketing?
Alvarink makes money by charging sort of a data provider fee. So we basically go into customer databases and we give each customer a score. You know, how influential are they? We say who are they're connected to, which other customers are they influencing? And then we provide a predictive network LTV, meaning, hey, Nathan here is buying $100 worth of stuff, but he's influencing
$600 to $700 worth of spending on other people.
Okay, interesting. And what... Okay, and give us a sense of what year did you start the business?
AlphaRank started about a year ago. Okay.
Chapter 7: What are the challenges of tracking network connections?
And before that, we did a series of experiments.
Which is 2015, right?
Yeah, a series of experiments called BidRocket. So we didn't stumble on this or we didn't do this on purpose. We kind of stumbled on it. We were doing a series of...
apps and experiments around human behavior everything from gambling to a crowd tilt competitor to a nightclub app and we were doing the nightclub app i was at this nightclub for about 90 days with a clipboard trying to understand the patterns of human behavior to make it more efficient and what we noticed is that you could look at the order and sequence of people walking into the venue
So imagine like a crowded mall, right? People swarming around. Very hard to understand social structure just by looking at that, right?
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Chapter 8: What advice does Brian Ley give to young entrepreneurs?
Because there's so many people. Lines, like nightclub lines are super cool for a lot of reasons. But one of them is that it's very easy to see how people are connected. So obviously you stand with your friends, right? Sequentially, which is cool in and of its own. And so if you stand with your friends and you walk in, there's a pattern. So you go boom, boom, boom, right?
You and your two friends just walked in. But if you're there long enough and you look at enough nights, you start to notice there's another pattern hidden, meaning that if a group of three people walk in, boom, boom, boom, later in the night, another group of three, boom, boom, boom, might walk in that knows the first group of three.
It could be completely random, but if you see this pattern enough, you start to notice it. So that was when we first started realizing that if you look at time series, and that's basically what Alfrank does, is it's automated time series analysis. You can see these, monkey A did something, monkey B did something. And I was actually doing a self-hack at... Chipotle, eating only Chipotle.
Don't do it unless you supplement with magnesium. You'll get terribly magnesium deficient. But, you know, I was there for lunch hour a lot and I would notice one person would come in, pay, sit down. And then, of course, other people would be coming in. But then another person would pay and then sit down with that same person.
Interesting.
So if that pattern repeats enough, you can draw a connection or an edge and further network structure.
So I want to go deeper into that. But first, give us a sense of success so far. 2015, what was total revenue?
So we're still in private beta. We're doing a series of free case studies. We're proving it out. We're now just transitioning to paid.
Okay, so no revenue 2015, right? No revenue. How much have you guys put in the business so far?
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