selling again the pickaxes to the gold miners they bought one of their own pickaxes now building

darwin helping e-commerce brands get smarter increase average checkout price you know increased lifetime

value of checkouts you know where where should product one go if it's a hiker looking on an

rei site they've scaled to about 36 customers paying a grand a month so call it 30 36 grand a month

right now on revenue team of four based in New York, kind of spread out

throughout the state bootstrapped, which I love. Too early to talk about economics, but growing

rapidly. Hello, everybody. My guest today is Frank McDermott. He is an entrepreneur and

technologist. Launched hundreds of sites, 50 plus apps, tens of digital products, launched nine

businesses, four for himself, and delivered a line

of high-end beverages to the market and consulted in the finance and tech industries. A lot of

experiences now building a company called Darwin. That's dar.wyn. Frank, are you ready to take us to the

top? I am. How the hell do you decide what to focus on? Yeah, you know, it's been a very interesting

career, and I've had a lot of exciting opportunities.

The kind of thread I found is just being able to bring products to market in different industries, different technologies, and we've kind of really good at that.

So when we decided to start Darwin, we really kind of had a core competency in e-commerce,

the core competency in technology and cloud technologies, and we wanted to try Darwin, we really kind of had a core competency in e-commerce. We had core competency in technology and cloud technologies.

And we wanted to try something really new, which was bringing machine learning into a production environment.

And so that's kind of where we decided to start to ideate on what could we do with that.

So tell us what the company does.

Sure.

So Darwin is a suite of products and services that essentially provide personalization for e-commerce.

So you install Darwin on your store and we instantly start tracking collecting information about the people who visit your site, the things that they look at, the thing that they click on, the things that they buy, and put that all onto our machine learning models to start to segment that audience and then allow you to start to make product recommendations

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