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Speaker 1: Get in touch with technology with pluck stuff from how

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Speaker 1: Stuff Looks dot Com. Haythen everyone, and welcome to tech Stuff.

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Speaker 1: I am Jonathan Strickland, one of the two hosts, and

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Speaker 1: I am Lauren voc Obamb the other of the two hosts. Logically,

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Speaker 1: there we go today. We thought we would start talking

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Speaker 1: about a particularly important company as far as the web

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Speaker 1: and technology are concerned. It's kind of big. You may

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Speaker 1: have heard of it. Yeah, it's called Amazon. Um big,

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Speaker 1: big company and also one of the companies that that

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Speaker 1: famously weathered the great storm of the dot com crash. Yeah. Yeah,

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Speaker 1: because they started up way before that thing happened, like

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Speaker 1: five entire years. And yeah, but you know what, not

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Speaker 1: a lot of companies that were specifically web based can

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Speaker 1: make the claim that they started pre dot com and

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Speaker 1: made it through couple did Google did another thing that

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Speaker 1: you may have heard of? Yeah, So so anyway, Amazon

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Speaker 1: has become really a powerhouse. But to to understand where

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Speaker 1: it is now, it's it's good to look at at

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Speaker 1: how it started. And really Amazon is kind of one

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Speaker 1: of those companies, even though even though I would say

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Speaker 1: the founder is not necessarily as well known as someone

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Speaker 1: like Steve Jobs was right, Sure, he's not that kind

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Speaker 1: of level of rock star, but nonetheless his personality has

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Speaker 1: really driven the way that the company has developed end end. Yeah,

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Speaker 1: I mean without him, without his drive and without his

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Speaker 1: his vision. Uh and frankly, without the mistakes he's made,

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Speaker 1: Amazon would not be what it is. And we're talking,

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Speaker 1: of course about Jeffrey Preston Bezos. Preston's middle name. That's

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Speaker 1: a terrific middle name. Yes, makes me think of Princeton,

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Speaker 1: which he also went to. But that's spoiler alert. But yeah,

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Speaker 1: you need to know a little bit about him to understand, uh,

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Speaker 1: you know, where Amazon is coming from and sort of

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Speaker 1: the goals of the company and where it might be

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Speaker 1: going to. So to cast back the clock to to

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Speaker 1: the mid sixties, Uh, you need to understand a little

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Speaker 1: bit about his family background. So his mother, it was

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Speaker 1: Jacqueline Guys Jorgenson Jensen U. She had married, briefly a

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Speaker 1: man by the name of Ted Jorgenson. They were married

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Speaker 1: less than a year and she clearly wanted to keep

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Speaker 1: that name. Well, she lost she lost Jorgenson. Uh no,

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Speaker 1: but that was that was her name at the time.

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Speaker 1: But then she she became Jacqueline Guys again. And I

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Speaker 1: assume I'm pronouncing that correctly. It's G I S E.

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Speaker 1: So feel free to write us in and say how

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Speaker 1: wrong Jonathan is. And I love those emails. Yes, now

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Speaker 1: now she gets them, so um yeah, Jacqueline guys married

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Speaker 1: to Ted Jorgenson. Uh, and she gets pregnant and then

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Speaker 1: uh they divorce. Well, there was a fellow by the

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Speaker 1: name of Miguel Bezos, better known as Mike, and he

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Speaker 1: grew up in Cuba, but he took part in a

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Speaker 1: there was actually a program that sort of helped people

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Speaker 1: who were trying to escape Castro's regime to get into

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Speaker 1: the United States, and he was It was a program

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Speaker 1: aimed at at younger people. He was one of these people.

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Speaker 1: So he came over the United States as a young teenager,

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Speaker 1: like he was fifteen years old, doesn't speak English. He

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Speaker 1: goes to live in a small community where he's with

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Speaker 1: I think fifteen other people from and he learns English

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Speaker 1: and he starts he goes to school and uh and

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Speaker 1: really applies himself and eventually he goes to attend school

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Speaker 1: in Albuquerque, New Mexico, and starts to work in the

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Speaker 1: bank of New Mexico. And that's where he meets Jackie

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Speaker 1: guys and uh, Miguel and Jackie ended up falling in

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Speaker 1: love and they ended up getting married. And so then

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Speaker 1: Miguel applied for and became the adopted father of Jeff Bezos.

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Speaker 1: He Jeff took the name of his of his uh

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Speaker 1: adopted dad. And in all interviews, Jeff talks about Mike

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Speaker 1: as being his father. He says that, you know, he

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Speaker 1: may not be his biological father, but he's his dad

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Speaker 1: and uh and specifically, in several interviews, they all cited

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Speaker 1: the same statement where he said, the only time I

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Speaker 1: ever think about him not being my biological father is

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Speaker 1: when I have to fill out a form, which is

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Speaker 1: you know, it's just a It says a lot about

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Speaker 1: who who Mike Bezos is really and so uh he

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Speaker 1: grew up with you know, his his parents were very

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Speaker 1: hard working, they believed very much in scholarship and UH,

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Speaker 1: and so he really started to apply himself. His father,

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Speaker 1: Mike became a petroleum engineer for Exxon. UH. After he

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Speaker 1: graduated college, and Jeff ended up really getting interested in

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Speaker 1: science and electronics and engineering and particularly in space. That

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Speaker 1: will come into play a little bit later. But he

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Speaker 1: spent childhood summers working on his grandfather's ranch in Cotula, Texas.

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Speaker 1: And everyone in Catula who knows that I just mispronounced

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Speaker 1: the name of your town. I apologize their their places

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Speaker 1: in Texas that I attempt to say the name of

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Speaker 1: and I always mangle it many many places in America. Honestly,

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Speaker 1: there's really words. Words are hard. It's particularly tough in

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Speaker 1: places like Georgia and Texas where you have the regional

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Speaker 1: pronunciation of a place that is not the same as

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Speaker 1: the pronunciation of some other words. Pronunciation. Yeah, I think

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Speaker 1: we've talked before on the show about Ponsta Leone Street

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Speaker 1: around here. Yeah, great street, but yeah, you do not

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Speaker 1: call it Poste Leone. It's constantly in um Yeah, same

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Speaker 1: sort of thing. So I know I mispronounced that. I

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Speaker 1: apologize to to Texas. I do apologize anyway. His grandfather,

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Speaker 1: his grandfather's name was Lawrence Preston Pop guys pop in

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Speaker 1: a quotation box there so known as pop, and he

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Speaker 1: was he was a bit of a a go getter, uh,

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Speaker 1: someone who really kind of applied himself. He had worked

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Speaker 1: for DARPAH. He had helped develop space and missile defense technology.

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Speaker 1: Congress eventually appointed him as the manager of the Atomic

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Speaker 1: Energy Commissions Albuquerque Operations office, and he oversaw twit the

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Speaker 1: six thousand employees. Oh my goodness, gracious, so so so

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Speaker 1: so people in in Jeff's life had this kind of

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Speaker 1: drive and it definitely rubbed off on him. Yeah, and

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Speaker 1: his grandfather apparently just doated upon him. And uh that

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Speaker 1: he really encouraged Jeff in his love of things like

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Speaker 1: electronics and technology. Not a big surprise for someone who's

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Speaker 1: technically a rocket scientist type. Maybe not technically a rocket scientist,

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Speaker 1: but works field. Sometimes nerds like to talk about the

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Speaker 1: nerd things that they're excited about. No, that's not a

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Speaker 1: mark of a nerd. A passion for a subject and

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Speaker 1: to talk endlessly about it. I don't know anything about anyway.

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Speaker 1: Let me get on with Amazon. So Obasos his childhood

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Speaker 1: really he um, he started to build kits to help

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Speaker 1: him build electronics and various gadgets. He actually there was

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Speaker 1: a great story about how, uh he saw this toy

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Speaker 1: that was a mechanical electronic toy that was a box

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Speaker 1: that had mirrors in it, and it was called an

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Speaker 1: infinity cube and you would press a button and the

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Speaker 1: mirrors would align in such a way to give that

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Speaker 1: illusion of infinite. But the toy was twenty dollars. This

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Speaker 1: was in the mid seventies. Yeah, yeah, this would be yeah, yeah, right,

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Speaker 1: early seventies. Actually, um, maybe even no, it would have

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Speaker 1: to be early seventies. There's no way. It was when

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Speaker 1: he was four. But his his mother told him that

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Speaker 1: twenty dollars was too much to spend for a toy,

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Speaker 1: and he thought, oh, well, you know, that makes sense,

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Speaker 1: and he looked at around and he started to find parts,

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Speaker 1: and he figured out that buying all the parts would

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Speaker 1: be cheaper than buying the toys. So he bought the

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Speaker 1: parts and built one himself. Oh just yeah, like you do.

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Speaker 1: I did that all the time when I was a child,

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Speaker 1: and I just made my own toys where I made

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Speaker 1: tinker toys by bashing sticks together until they formed a pile. Anyway,

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Speaker 1: Bezos ended up being the the subject of part of

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Speaker 1: a book. The book was called turning on Bright Minds

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Speaker 1: of parent Looks at Gifted Education in Texas and uh

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Speaker 1: and it it kind of it talked about him, although

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Speaker 1: it changed his name for legal purposes exactly. Yeah, yeah,

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Speaker 1: as in minor as an underage, not as in let's

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Speaker 1: go get some coal out of that part of the ground. Um.

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Speaker 1: He he was featured in this book. What was funny

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Speaker 1: was that they talked to other teachers who who had

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Speaker 1: taught Bezos, and they had said that he was very intelligent,

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Speaker 1: he did very well in school, but he was not

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Speaker 1: particularly particularly gifted in leadership, which is wow. That got

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Speaker 1: to be He obviously developed those skills later on in

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Speaker 1: somewhere else. Yeah, apparently so well. Like I said, he

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Speaker 1: was fascinated by space in the space industry, and he

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Speaker 1: wanted very early on to kind of look into creating

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Speaker 1: sort of a privatized approach to the space industry because

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Speaker 1: having having it just in government hands meant that you

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Speaker 1: had a pretty narrow set of parameters you could work

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Speaker 1: within because you had to do everything according to government

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Speaker 1: approval and uh. And he also really felt that it

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Speaker 1: was important to develop lands in the event that Earth

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Speaker 1: could become the victim of some sort of interspatial collision,

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Speaker 1: so you know, like like a meteor media coming or

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Speaker 1: asteroid or comment or you know, death star. Yeah. Yeah,

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Speaker 1: he sat there and said, you know, we it doesn't

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Speaker 1: make sense for us to have all our eggs on

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Speaker 1: the Earth basket, we should spread our eggs around. That's

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Speaker 1: the other little planet bast that came out differently than

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Speaker 1: awkward in my head. But anyway, Yes, that's exactly what

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Speaker 1: he was thinking, was that we need to diversify. Yeah,

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Speaker 1: and and and the idea of a non government space

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Speaker 1: program at the time, I mean, if this was still

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Speaker 1: like like that was that was relatively radical. I mean,

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Speaker 1: obviously people talk about it all the time now that

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Speaker 1: the space Shuttle program has been shut down. But yeah, no,

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Speaker 1: this was this was pretty pretty crazy stuff, and he

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Speaker 1: was very much interested in it. Uh and and that

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Speaker 1: was an interest that didn't go away from with childhood. Well,

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Speaker 1: and like I said, we'll talk a little bit more

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Speaker 1: about that, probably in part two of our Amazon Focus,

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Speaker 1: because we're expecting that we're going to talk a lot

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Speaker 1: about this one. Yeah, it's a it's it's a company

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Speaker 1: that's not only large and not only interesting in its history,

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Speaker 1: but it does a lot of stuff, a lot of stuff.

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Speaker 1: It does not just chippy books, Nope, not anymore so. Anyway,

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Speaker 1: he then ended up going into high school. He co

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Speaker 1: founded a student summer camp called Dream Institute. And Dream

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Speaker 1: wasn't acronym that standard for directed reasoning methods, and I love, love,

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Speaker 1: love this because not only did they stress science curricula,

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Speaker 1: but also literature. Stranger in a Strange Land was required reading,

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Speaker 1: so was Doune, so was Lord of the Rings. So

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Speaker 1: you sit there and you think, and and there were other, uh,

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Speaker 1: actual books that that people would say fit in the

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Speaker 1: world of literature. I know some people would argue that

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Speaker 1: Dune and Lord of the Rings don't. I am not

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Speaker 1: one of those people. I think Dune and Lord of

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Speaker 1: the Rings have a real place in literature. But I

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Speaker 1: know some people look down in it because it's science

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Speaker 1: fiction and science fiction and but yeah, yeah, that's I've

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Speaker 1: I certainly had a poetry teacher in college who would

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Speaker 1: argue with you, but you're right. No, I had a

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Speaker 1: creative writing teacher who told me that in creative writing,

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Speaker 1: he actually came up to me and said, now, Jonathan,

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Speaker 1: I want you to write real fiction because my father

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Speaker 1: is a science fiction author. You know, my dad writes

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Speaker 1: science fiction. So oh, I mean at the same time,

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Speaker 1: you know, I had I had that one professor who

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Speaker 1: was very down on it. But I also had another

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Speaker 1: professor who assigned us those sort of books for required readings.

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Speaker 1: In both you know, at a medieval literature professor who

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Speaker 1: would quote Tolkien and was probably the probably probably the

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Speaker 1: biggest geek in the class. And boy he was great anyway,

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Speaker 1: all of that aside. He designed this curriculum along with

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Speaker 1: another student, and it was for fourth, fifth, and sixth graders.

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Speaker 1: So this is when he's when he's getting into like

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Speaker 1: he's looking into college at this point forming this and

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Speaker 1: and uh it was I think six hundred dollars to

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Speaker 1: get in, and I think they had fifteen students apply,

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Speaker 1: two of them being Bezos's siblings, but other than that, um,

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Speaker 1: you had other kids in there too, And it was

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Speaker 1: just it was interesting that it was taking this approach,

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Speaker 1: and they really stressed the fact that it was a

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Speaker 1: new approach that also incorporated classic learning material. So it

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Speaker 1: wasn't just you know, this space age form of learning.

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Speaker 1: They said, no, the classics are important too, And uh,

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Speaker 1: I found that particularly fascinating. It reminds me very much

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Speaker 1: of a program I went to when I was in

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Speaker 1: high school called the Governor's Honors Program that was very

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Speaker 1: much stressing about its stressed, uh, various forms of learning

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Speaker 1: in a very concentrated way. But you were with a

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Speaker 1: whole bunch of other people who are really really jazzed

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Speaker 1: about that. So it made learning entire renaissance kind of

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Speaker 1: concept of learning that says that both science and also

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Speaker 1: arts are kind of important. Yeah, so that was that

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Speaker 1: was an interesting approach. He then when he graduated high

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Speaker 1: school and then went to Princeton, uh, and his in

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Speaker 1: his senior year, Uh, he received well. Before I get

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Speaker 1: to his senior year, he actually at first thought about

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Speaker 1: majoring in theoretical physics right right, you were telling me

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Speaker 1: about this, but decided that that actually the other kids

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Speaker 1: in theoretical physics were better at theoretical physics than he was. Yeah,

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Speaker 1: and he didn't like that, and he didn't like that,

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Speaker 1: and it wasn't so it wasn't so much that he

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Speaker 1: didn't like that there were people who were better at

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Speaker 1: it than he was, sure, but he was just he

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Speaker 1: just realized that that was not his niche Yeah, exactly.

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Speaker 1: He was like, there are people whose brains are wired

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Speaker 1: in a different way than my brain is wired, and

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Speaker 1: these people are grasping these concepts easily. They are doing

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Speaker 1: really well in these classes. I'm struggling. Uh, it's a

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Speaker 1: lot more work for me. Maybe there's something else I

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Speaker 1: should look into, and so instead he went into computer

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Speaker 1: science instead of theoretical physics. By the way, both of

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Speaker 1: those fields way more complicated than anything I ever did

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Speaker 1: in college. So you know, right for for the record

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Speaker 1: that the two of us English majors, you were I was,

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Speaker 1: I was English. Yeah, yeah, the English major I wasn't.

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Speaker 1: Actually I wasn't English, and then converted into Southern United States. No,

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Speaker 1: that wasn't me. Uh. I was always anyway, very similar, y'all.

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Speaker 1: He uh then joined well he in his senior year,

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Speaker 1: he was invited to join various companies. Uh. He received

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Speaker 1: job offers from Intel, little company, there Bell Labs, another one,

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Speaker 1: Anderson Consulting. But he ended up instead accepting an offer

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Speaker 1: to join a startup company called fightel f I T

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Speaker 1: E L. And this was a company that was trying

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Speaker 1: to build a telecommunications network that was for trading companies

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Speaker 1: like like uh, like finance organizations, and the whole purpose

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Speaker 1: was just to settle cross border equity transitions. Exciting stuff.

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Speaker 1: It sounds thrilling, but it meant building a network. And

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Speaker 1: this is we're talking about the same time when when

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Speaker 1: our pannett is going strong, the Internet is is starting

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Speaker 1: to take form at this point. Yeah, pretty soon we're

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Speaker 1: gonna have the web there too. And uh, and so

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Speaker 1: he's definitely seeing that's where the exciting stuff is happening,

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Speaker 1: and in finances specifically, that's where he got his financial Yes,

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Speaker 1: he got pretty he got pretty good at that. And

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Speaker 1: he ended up working for fight Tell for a little

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Speaker 1: while and then left that for a company called Bankers Trust,

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Speaker 1: where he stayed for two years. And then he left

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Speaker 1: that company to join a hedge fund firm called D

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Speaker 1: E Shaw. Uh. And while he was at d E

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Speaker 1: Shaw he met a research associate by the name of

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Speaker 1: Mackenzie whom he became enamored of. This was after he

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Speaker 1: had had an unsuccessful attempt to analytically find the right

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Speaker 1: woman for him. Uh. He tried something that he called

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Speaker 1: woman flow, which to him meant finding using the the

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Speaker 1: analysis that you would use in finance to find a woman.

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Speaker 1: That sounds like the absolute worst idea I have heard

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Speaker 1: all day. Yeah, it did not work. It turns out

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Speaker 1: it was a failed experiment. I cannot I cannot even

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Speaker 1: imagine that. Yeah that um wow, and and and but

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Speaker 1: but decades before match dot com he was really ahead

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Speaker 1: of the curve, well more like more like five years

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Speaker 1: because at this point game into the nineties. But yeah,

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Speaker 1: but he he uh yeah, he ended up meeting Mackenzy

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Speaker 1: and the two of them ended up getting married in

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Speaker 1: nine teen. And uh. Then at the Shaw he was

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Speaker 1: put in charge of developing business opportunities for the thing

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Speaker 1: called the Internet. Internet. Yeah, and uh that's when he

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Speaker 1: started to think this might be the right place to

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Speaker 1: really focus on business because as he was looking into it,

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Speaker 1: he realized that there was a growth on the Internet,

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Speaker 1: a growth of users, I should say, not just some

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Speaker 1: weird growth that growth. This is that more and more

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Speaker 1: users were joining the Internet at an incredible rate, like

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Speaker 1: twenty three hundred percent increase from one year to the next.

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Speaker 1: And so with this kind of increase, there's huge amounts

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Speaker 1: of opportunity. So how could we take advantage of this

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Speaker 1: this fact? And it all depends on on the story

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Speaker 1: you read, But eventually he came up with the idea

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Speaker 1: of well, with the assets that are already in place

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Speaker 1: in the United States, the fact that there were really

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Speaker 1: big book distributors in the United States, and those were

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Speaker 1: Ingram and Baker and Taylor, these two enormous entities have

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Speaker 1: exhaustive databases of titles of books. So all the work

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Speaker 1: of organizing the books, of cataloging the books, it's all

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Speaker 1: been done. So all that really needs to happen is

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Speaker 1: there needs to be some sort of website where someone

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Speaker 1: who is interested in books could go look up any

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Speaker 1: book that's ever been published and find out if they

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Speaker 1: can buy it. And so at first he kind of

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Speaker 1: talked about this over at d E Show, but it

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Speaker 1: was clear that that wasn't going to really pan out there,

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Speaker 1: and so instead he made a big decision in his life,

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Speaker 1: and that was he was going to leave this company.

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Speaker 1: And he was the youngest executive and yeah, but he

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Speaker 1: met with the company's the head of the company, who

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Speaker 1: whom he was friends with, and he said, I'm gonna

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Speaker 1: I'm gonna believe and start my own company. And that's

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Speaker 1: exactly what the founder of the Shaw Shaw had done.

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Speaker 1: But he said, you know, you're you're going to be

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Speaker 1: leaving behind security and a debt, and you know you've

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Speaker 1: got guaranteed success in this company. And he said, I'm

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Speaker 1: still going to do it, and so, yeah, I mean,

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Speaker 1: it wasn't just talking about leaving. I mean, this was

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Speaker 1: a Wall Street Company. He was talking about moving across

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Speaker 1: the country. Yeah, yeah, he He and his wife ended

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Speaker 1: up taking a bit of a scenic tour of the

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Speaker 1: United States, driving all the way out to Seattle and

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Speaker 1: uh the the You might ask, well, why why did

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Speaker 1: they go to Seattle? Why was that the birthplace of Amazon?

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Speaker 1: Why all the places the United States? There are a

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Speaker 1: few reasons. One reason is that Seattle happens to be

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Speaker 1: close to one of Ingram's distribution facilities. Not Ingram's, of course,

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Speaker 1: that was one of those big contributors exactly. So by

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Speaker 1: being close to the distribution facility in make it a

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Speaker 1: lot easier to ship books out to customers. Convenient. Yeah.

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Speaker 1: Another reason is that the state of Washington, which, for

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Speaker 1: those of you who do not know, Seattle is a

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Speaker 1: city that is in the state of Washington. State of Washington,

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Speaker 1: in comparison to other states in the US, is fairly

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Speaker 1: sparsely populated. The reason why that's important is that, as

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Speaker 1: a business operating within the state of Washington, anyone who

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Speaker 1: purchased an item in the state of Washington would have

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Speaker 1: sales tax added to their purchase. The United States, this

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Speaker 1: is kind of complicated, guys, So Generally speaking, the way

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Speaker 1: the sales tax was working, at least at that point,

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Speaker 1: was that if you bought the you know, the sales

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Speaker 1: tax applied if you were within the same state as

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Speaker 1: the Yeah. Outside of that, uh, different rules applied. So essentially, Bezos,

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Speaker 1: this idea is that, Okay, I'm gonna be close to

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Speaker 1: the books and I won't have to add sales sales tax,

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Speaker 1: which is a complication. It's all other algorithm, right, and

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Speaker 1: it also ends up making customers less happy because I

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Speaker 1: have to spend more money to buy something. You know

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Speaker 1: that you quoted a price, and then sales taxes put

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Speaker 1: on top of it, and you know, it's a whole

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Speaker 1: dollar more. Yeah I wanted to eat today, Yeah, yeah,

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Speaker 1: I had. I had days like that. I had that

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Speaker 1: five centerraman. Why can't I afford you today? Oh yeah,

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Speaker 1: I guess I'll just be licking the this this piece

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Speaker 1: of plastic that once held American cheese. I guess it's

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Speaker 1: free pizza in the square again. I'll sign up for

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Speaker 1: another credit card. Good days. Um. Anyway, So these were

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Speaker 1: the reasons why he had decided to move to Seattle,

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Speaker 1: and on the way there he actually worked on a

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Speaker 1: business plan for this company, and like like on his

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Speaker 1: laptop in the passenger seat while his wife was driving,

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Speaker 1: kind of worked on yes, exactly, like like look over there,

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Speaker 1: Mount Rushmore, can't talk working on business plan. Um. And

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Speaker 1: he ended up stopping off in California before heading up

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Speaker 1: to Seattle, and there he ended up recruiting his first employee,

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Speaker 1: Shell Cappen, who was employee number one at Amazon, and

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Speaker 1: that was he was a programmer. So this is a

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Speaker 1: guy who's going to help build the actual software to

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Speaker 1: make the sight run right exactly. So, because you know,

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Speaker 1: Amazon is more than just a website. You've got you've

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Speaker 1: got the website part, which is the forward facing part

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Speaker 1: of the company, that's the part of the customer sees.

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Speaker 1: So so you and I we think of Amazon as

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Speaker 1: a website. There's a lot of stuff that has to

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Speaker 1: happen in the background for the for the actual business

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Speaker 1: amounts of infrastructure, of of of database management and yeah,

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Speaker 1: it's credit card systems, right. So so he had to

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Speaker 1: get someone who was a strong programmer, and Shell ended

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Speaker 1: up being his first recruit. And uh and according to

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Speaker 1: the interviews I read, it sounds like he must have

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Speaker 1: been incredibly persuasive because Shell came across as something of

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Speaker 1: glass is half empty kind of guy. To be fair,

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Speaker 1: he had worked for several companies that did not go anywhere,

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Speaker 1: so here he kind of expected it to be another

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Speaker 1: one of those. And according to one interview I read

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Speaker 1: with Bezos, Bezos was said, hey, I needed that guy

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Speaker 1: because he was the one who's like, Okay, no, that's

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Speaker 1: not gonna work. Let's try it this way. I already

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Speaker 1: know that's not gonna work because I did it before

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Speaker 1: and it didn't work. So you know, at a certain point,

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Speaker 1: that's a that's a very important thing. And it started

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Speaker 1: start up yep. And then they also ended up hiring

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Speaker 1: a or at least contracting a guy named Paul Barton Davis,

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Speaker 1: and they built the first version of Amazon dot com.

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Speaker 1: And of course this is a story about a company

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Speaker 1: that has its roots and technology. That means the very

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Speaker 1: first version of Amazon dot Com was built in a

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Speaker 1: garage because like, like all good bands have started on

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Speaker 1: the West Coast, I mean, there's so many other companies

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Speaker 1: we could talk about that had you know that that's

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Speaker 1: starting a garage, like Apple and Microsoft are both Google

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Speaker 1: had its first servers in a garage. I mean once

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Speaker 1: you got outside of the Granted, they had servers in

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Speaker 1: in college, but then once it became its own thing,

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Speaker 1: the servers lived in a garage. So garages play a

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Speaker 1: big important role in technology. Oddly enough, they almost never

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Speaker 1: house a car, but they are still very important. Uh.

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Speaker 1: And then Bezos and his his other employees, they ended

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Speaker 1: up meeting with a bunch of angel investors. Uh. And

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Speaker 1: angel investors are not these guys in business suits and

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Speaker 1: big fluffy white wings. Um, they are people who are

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Speaker 1: vampires with a heart of gold. Neither of those things. Well,

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Speaker 1: I guess it depends on again, upon whom you ask.

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Speaker 1: But these are these are folks who end up investing

429
00:24:52,960 --> 00:24:57,119
Speaker 1: in often risky ventures with the hope that this investment

430
00:24:57,200 --> 00:24:59,080
Speaker 1: is going to pay off in the long run. Uh.

431
00:24:59,200 --> 00:25:02,399
Speaker 1: He met with about fifteen of them, and together they

432
00:25:02,520 --> 00:25:07,160
Speaker 1: invested about one million dollars of seed capital in Amazon.

433
00:25:07,480 --> 00:25:09,479
Speaker 1: One of those fellows was a guy by the name

434
00:25:09,520 --> 00:25:14,320
Speaker 1: of Tom Ahlberg, and he was the first board member

435
00:25:14,480 --> 00:25:19,159
Speaker 1: of Amazon. And so with that million dollars invested, the

436
00:25:19,720 --> 00:25:25,080
Speaker 1: company of Amazon incorporates and they incorporate in July nineteen.

437
00:25:26,520 --> 00:25:28,760
Speaker 1: And there's a lot more to say, but before we

438
00:25:28,880 --> 00:25:31,040
Speaker 1: get there, I think it's important we take just a

439
00:25:31,160 --> 00:25:34,760
Speaker 1: quick break to talk about our sponsor, and now back

440
00:25:34,800 --> 00:25:37,680
Speaker 1: to the show. So the company has incorporated in nineteen

441
00:25:37,800 --> 00:25:44,400
Speaker 1: ninety four. A year later, July, Amazon dot Com officially

442
00:25:44,640 --> 00:25:48,560
Speaker 1: launches and they sell their first book. Do you happen

443
00:25:48,600 --> 00:25:50,520
Speaker 1: to know what that was? I do happen to know

444
00:25:50,640 --> 00:25:54,560
Speaker 1: what that was? Hit me with your knowledge? It comes um.

445
00:25:54,760 --> 00:25:58,760
Speaker 1: It is the fluid concepts and creative analogies, computer models

446
00:25:58,800 --> 00:26:03,560
Speaker 1: of the fundamental mechanism, the thought a real page turner. Actually,

447
00:26:03,600 --> 00:26:06,040
Speaker 1: it actually sounds pretty cool to me, but then I

448
00:26:06,320 --> 00:26:08,280
Speaker 1: think it's probably also way over my head. But yes,

449
00:26:08,359 --> 00:26:11,240
Speaker 1: that was the first title purchased. And uh, of course,

450
00:26:11,359 --> 00:26:13,800
Speaker 1: because you have Bezos there and he's kind of a

451
00:26:13,880 --> 00:26:16,280
Speaker 1: nerdy engineer type, and you've got these other guys there

452
00:26:16,320 --> 00:26:19,879
Speaker 1: who I'm guessing also shared some of that interest. They

453
00:26:19,960 --> 00:26:22,800
Speaker 1: might they might have been. They decided, did you hear

454
00:26:22,840 --> 00:26:25,879
Speaker 1: about what they rigged up to their computer? So they

455
00:26:26,000 --> 00:26:28,280
Speaker 1: rigged up a bell and the idea was that the

456
00:26:28,320 --> 00:26:31,600
Speaker 1: bell would ring every time they made a sale, so

457
00:26:31,840 --> 00:26:34,719
Speaker 1: you know, sale bing. And And I don't know if

458
00:26:34,760 --> 00:26:37,080
Speaker 1: any of you guys out there in podcast land have

459
00:26:37,200 --> 00:26:39,680
Speaker 1: ever worked for a company that kind of did something

460
00:26:39,760 --> 00:26:41,720
Speaker 1: like this. I used to work for a company that

461
00:26:41,760 --> 00:26:44,440
Speaker 1: would occasionally do one of those things where you'd land

462
00:26:44,480 --> 00:26:47,400
Speaker 1: a big deal and then everyone starts yea and applauding

463
00:26:47,600 --> 00:26:49,560
Speaker 1: and running around, and it felt like I was in

464
00:26:49,600 --> 00:26:51,440
Speaker 1: a pep rally and I wanted to be out of

465
00:26:51,480 --> 00:26:54,800
Speaker 1: there so badly. Yeah. I essentially never want anything on

466
00:26:54,880 --> 00:26:57,520
Speaker 1: the internet to make noise or or a computer. I

467
00:26:58,040 --> 00:27:02,359
Speaker 1: want complete silence. Were writers, We don't, we don't like

468
00:27:02,720 --> 00:27:05,679
Speaker 1: we don't like that. But anyway, so it turns out

469
00:27:05,720 --> 00:27:08,800
Speaker 1: they didn't like it either, well, mostly because it became

470
00:27:08,840 --> 00:27:10,920
Speaker 1: a problem because the site ended up getting a lot

471
00:27:11,200 --> 00:27:14,640
Speaker 1: more popular than they expected, a lot faster than they expected,

472
00:27:14,960 --> 00:27:17,760
Speaker 1: and so uh, within two weeks they had dismantled it

473
00:27:17,840 --> 00:27:20,520
Speaker 1: because it was driving everyone bonkers. Yeah. Yeah. Within within

474
00:27:20,600 --> 00:27:23,159
Speaker 1: their first month, they had shipped books to all fifty

475
00:27:23,240 --> 00:27:26,560
Speaker 1: states and forty five other countries, which was a big

476
00:27:26,600 --> 00:27:29,240
Speaker 1: surprise to them. They were not they didn't really think

477
00:27:29,280 --> 00:27:33,040
Speaker 1: that they were going to get international business that quickly.

478
00:27:33,600 --> 00:27:36,200
Speaker 1: And by the end of September, so remember they launched

479
00:27:36,240 --> 00:27:39,399
Speaker 1: in July. By the end of September, the revenues were

480
00:27:39,400 --> 00:27:43,320
Speaker 1: about twenty thousand dollars per week. Uh, and by the

481
00:27:43,480 --> 00:27:48,200
Speaker 1: end of nineteen itself, they made five hundred ten thousand

482
00:27:48,320 --> 00:27:51,520
Speaker 1: dollars in sales. Now, that sounds like a pretty good

483
00:27:52,160 --> 00:27:54,879
Speaker 1: first run, especially you know, you figured they started seven

484
00:27:54,960 --> 00:27:57,520
Speaker 1: months into the year, they didn't have a full year

485
00:27:58,280 --> 00:28:01,920
Speaker 1: to make. To make a half million in sales, not bad. However,

486
00:28:02,560 --> 00:28:05,240
Speaker 1: keep in mind that Amazon dot Com is the kind

487
00:28:05,280 --> 00:28:09,080
Speaker 1: of operation that, uh, that that costs a lot of

488
00:28:09,160 --> 00:28:11,280
Speaker 1: money to run. And I mean they were already a

489
00:28:11,320 --> 00:28:13,520
Speaker 1: little bit in the in the red technically from from

490
00:28:13,520 --> 00:28:16,159
Speaker 1: all of that startup money. So you know, you've got

491
00:28:16,200 --> 00:28:17,560
Speaker 1: money that you're going to have to pay back in

492
00:28:17,640 --> 00:28:19,840
Speaker 1: some way. Of course, most of those guys essentially what

493
00:28:20,080 --> 00:28:22,760
Speaker 1: what happens is they own shares in the company. But

494
00:28:23,240 --> 00:28:25,639
Speaker 1: but yeah, you still have you still you know, they

495
00:28:25,680 --> 00:28:28,959
Speaker 1: still expect a return on their investment. So you've got

496
00:28:29,040 --> 00:28:31,640
Speaker 1: you've got a lot of obligations to make. So, uh,

497
00:28:32,160 --> 00:28:36,480
Speaker 1: it'll be a while before years before Amazon. But yeah,

498
00:28:36,480 --> 00:28:39,640
Speaker 1: in fact, if you're waiting to hear that information in

499
00:28:39,720 --> 00:28:42,360
Speaker 1: part one, I'm just gonna go ahead and burst your bubble.

500
00:28:43,400 --> 00:28:47,080
Speaker 1: Part two, Well, it won't be until we're into part

501
00:28:47,120 --> 00:28:50,160
Speaker 1: two before we get to Amazon becoming a profitable company.

502
00:28:50,680 --> 00:28:52,760
Speaker 1: But but actually that's parts of the amazing part of it,

503
00:28:52,960 --> 00:28:55,000
Speaker 1: which is incredible because it's yeah, if it, if it

504
00:28:55,120 --> 00:29:01,040
Speaker 1: incorporates ship and it is until after the year two thousand,

505
00:29:01,240 --> 00:29:05,760
Speaker 1: that before their before they're profitable. Yeah. And to to

506
00:29:05,880 --> 00:29:09,440
Speaker 1: express how amazing this is to someone like myself, I

507
00:29:09,520 --> 00:29:12,840
Speaker 1: look at companies now that generally speaking, you know, they

508
00:29:12,960 --> 00:29:15,440
Speaker 1: launch and within a couple of years, if things are

509
00:29:15,600 --> 00:29:18,800
Speaker 1: still kind of rocky, people tend to pull support, and

510
00:29:19,160 --> 00:29:23,280
Speaker 1: they don't they fall apart. So seeing a company that

511
00:29:23,480 --> 00:29:26,360
Speaker 1: was this ambitious, this large, I mean they were making

512
00:29:26,440 --> 00:29:28,280
Speaker 1: lots of sales, they were making a lot of money,

513
00:29:28,360 --> 00:29:33,240
Speaker 1: but their their costs outweighed their revenue. So it sounds

514
00:29:33,280 --> 00:29:37,600
Speaker 1: like it sounds like um businesses personal attitude about business

515
00:29:37,760 --> 00:29:40,760
Speaker 1: was a huge contributor to that. That he has always

516
00:29:40,760 --> 00:29:44,280
Speaker 1: been extremely focused on the long run and on no, no, no,

517
00:29:44,480 --> 00:29:46,360
Speaker 1: if we if we create the service, if we make

518
00:29:46,440 --> 00:29:49,920
Speaker 1: it just just kick butt, then people you know, it's

519
00:29:50,000 --> 00:29:52,280
Speaker 1: if if you build it, they will come kind of exactly.

520
00:29:52,720 --> 00:29:55,880
Speaker 1: And what was amazing was not just that Bezos really

521
00:29:56,040 --> 00:29:58,760
Speaker 1: believe this, but he was able to convince other people

522
00:29:59,440 --> 00:30:02,760
Speaker 1: exactly because without that without convincing other people, you don't

523
00:30:02,800 --> 00:30:06,760
Speaker 1: move forward. Uh. Speaking of moving forward, in nineties six,

524
00:30:07,560 --> 00:30:10,680
Speaker 1: a few things happened in Amazon. They launched the Amazon

525
00:30:10,800 --> 00:30:14,840
Speaker 1: dot Com Associates program, uh and the which was an

526
00:30:14,840 --> 00:30:18,480
Speaker 1: affiliate marketing program. So associates probably Amazon has done a

527
00:30:18,520 --> 00:30:20,760
Speaker 1: lot of stuff in order to kind of, uh, not

528
00:30:21,000 --> 00:30:24,480
Speaker 1: just get its name out there, but to reward people

529
00:30:24,880 --> 00:30:27,959
Speaker 1: people for helping them, right exactly. So the Associates program

530
00:30:28,080 --> 00:30:30,320
Speaker 1: was a program that will let let you put in

531
00:30:30,520 --> 00:30:34,920
Speaker 1: links in your web page to earn commissions through any

532
00:30:34,960 --> 00:30:37,120
Speaker 1: click through sales that happen and any time that a

533
00:30:37,160 --> 00:30:39,120
Speaker 1: friend clicks the link and then buy something, you get

534
00:30:39,200 --> 00:30:41,640
Speaker 1: you know, yeah, like a like up to ten percent

535
00:30:41,920 --> 00:30:44,560
Speaker 1: of whatever the value was of the sales. So so,

536
00:30:44,760 --> 00:30:47,560
Speaker 1: for instance, if you were here's a good example. Uh.

537
00:30:48,200 --> 00:30:51,040
Speaker 1: And I mean, there's no direct affiliation between my podcast

538
00:30:51,080 --> 00:30:53,400
Speaker 1: and this website. I just want to make that clear.

539
00:30:53,480 --> 00:30:56,200
Speaker 1: But chud dot com, which I've talked about many times,

540
00:30:56,240 --> 00:30:58,200
Speaker 1: I'd like to use that example because I like the website,

541
00:30:58,560 --> 00:31:02,800
Speaker 1: but it's all about movie news. And they had they

542
00:31:02,840 --> 00:31:06,080
Speaker 1: were part of this affiliate program where uh, you know,

543
00:31:06,120 --> 00:31:08,400
Speaker 1: they talked a lot about different movies, especially like when

544
00:31:08,440 --> 00:31:10,600
Speaker 1: movies would come out on DVD and so they would

545
00:31:10,600 --> 00:31:13,120
Speaker 1: do a review, which meant that you could click through

546
00:31:13,240 --> 00:31:16,320
Speaker 1: and actually buy the movie that you know you're h

547
00:31:16,320 --> 00:31:17,800
Speaker 1: You could just buy it with one you know, go

548
00:31:17,960 --> 00:31:20,280
Speaker 1: through to Amazon buy it there, and it meant that

549
00:31:20,360 --> 00:31:23,600
Speaker 1: you were not only getting to participate in the film

550
00:31:23,680 --> 00:31:26,080
Speaker 1: that was being discussed, but you were also supporting the

551
00:31:26,160 --> 00:31:29,760
Speaker 1: website that you loved, because Chud would get a little

552
00:31:29,800 --> 00:31:32,120
Speaker 1: bit of money every time someone would do that. So

553
00:31:32,240 --> 00:31:34,200
Speaker 1: that's an example of that, and that's just the first

554
00:31:34,280 --> 00:31:36,640
Speaker 1: of many examples of how Amazon started to partner with

555
00:31:36,840 --> 00:31:43,000
Speaker 1: other people, entities, organizations, UM and UH. You know. The

556
00:31:43,040 --> 00:31:45,960
Speaker 1: way it worked was essentially you would receive monthly payments

557
00:31:46,040 --> 00:31:49,880
Speaker 1: based upon the orders that came through from your center site.

558
00:31:50,480 --> 00:31:52,880
Speaker 1: So I think what would happen is like someone would

559
00:31:52,960 --> 00:31:55,360
Speaker 1: order something from a link that was on your site

560
00:31:55,960 --> 00:31:59,560
Speaker 1: thirty days after they had ordered that. UM, at the

561
00:31:59,640 --> 00:32:01,640
Speaker 1: end of that month, another thirty days. That's when you

562
00:32:01,680 --> 00:32:04,720
Speaker 1: would get the checks in, so you could easily get

563
00:32:04,760 --> 00:32:07,920
Speaker 1: an idea of how how persuasive you were based upon

564
00:32:07,960 --> 00:32:10,760
Speaker 1: the size of the check. Here's a check for a

565
00:32:10,840 --> 00:32:15,240
Speaker 1: dollar twenty five. It's time to go to Taco pell

566
00:32:16,000 --> 00:32:19,480
Speaker 1: um um. And then in nineties seven, Amazon made a

567
00:32:19,520 --> 00:32:22,800
Speaker 1: big move. It went public. Yep, they held their initial

568
00:32:22,920 --> 00:32:25,960
Speaker 1: public offering and uh and this was big news. They

569
00:32:27,120 --> 00:32:30,640
Speaker 1: entered NASDAC. That's the the exchange that you can find

570
00:32:30,680 --> 00:32:36,040
Speaker 1: Amazon on, and it was it was. It was interesting

571
00:32:36,080 --> 00:32:40,160
Speaker 1: because originally analysts predicted that the stock price would be

572
00:32:40,240 --> 00:32:44,800
Speaker 1: between twelve and fourteen dollars, but then the day before,

573
00:32:45,280 --> 00:32:48,840
Speaker 1: the day before the I p O, they adjusted that.

574
00:32:49,120 --> 00:32:51,320
Speaker 1: First they adjusted it to say, okay, no, it's gonna

575
00:32:51,360 --> 00:32:54,640
Speaker 1: be fourteen to sixteen dollars. Then they adjusted it again

576
00:32:54,720 --> 00:32:59,280
Speaker 1: and okay, no, it's gonna bears eighteen dollars. We're pretty

577
00:32:59,320 --> 00:33:02,520
Speaker 1: sure that's what's going to open at. So much anticipation

578
00:33:02,600 --> 00:33:06,160
Speaker 1: had built up that when it went uh uh when

579
00:33:06,240 --> 00:33:09,560
Speaker 1: when When the market actually opened, the opening price was

580
00:33:10,000 --> 00:33:13,880
Speaker 1: twenty nine dollars and twenty five cents per year. Uh. Yeah.

581
00:33:13,920 --> 00:33:16,560
Speaker 1: It hit a high of thirty dollars that day, and

582
00:33:16,800 --> 00:33:19,200
Speaker 1: it closed out the day at twenty three dollars and

583
00:33:19,240 --> 00:33:22,200
Speaker 1: fifty cents. So it was definitely one of those anticipation

584
00:33:22,280 --> 00:33:27,960
Speaker 1: things where spring back, this happens, but not nonetheless way

585
00:33:28,120 --> 00:33:30,920
Speaker 1: over what it was originally, right, even at eighteen dollars.

586
00:33:31,000 --> 00:33:33,520
Speaker 1: Yet when it ends at twenty three dollars fifty cents,

587
00:33:33,600 --> 00:33:36,120
Speaker 1: that was a great story. And they raised about in

588
00:33:36,200 --> 00:33:41,520
Speaker 1: that first day, they raised about fifty four million dollars. Uh. Meanwhile,

589
00:33:42,200 --> 00:33:44,960
Speaker 1: at this time in Amazon's history, they had a deficit

590
00:33:45,080 --> 00:33:48,920
Speaker 1: of nine million dollars, even despite the fact by the

591
00:33:49,000 --> 00:33:50,880
Speaker 1: end of the year they had made a hundred and

592
00:33:51,120 --> 00:33:54,920
Speaker 1: forty seven point eight million sales. Yeah. See, the problem

593
00:33:55,000 --> 00:33:59,440
Speaker 1: was that again, their their costs were greater than the revenue. Uh.

594
00:33:59,600 --> 00:34:03,560
Speaker 1: They never are once had a profitable quarter that year. Uh,

595
00:34:03,880 --> 00:34:06,280
Speaker 1: it was every single quarter. They were operating at a loss.

596
00:34:06,520 --> 00:34:09,000
Speaker 1: But they were making more and more money each time. Yea.

597
00:34:09,080 --> 00:34:10,959
Speaker 1: And they were also I mean they opened a second

598
00:34:11,000 --> 00:34:13,560
Speaker 1: distribution center on the east coast of the United States

599
00:34:13,600 --> 00:34:16,080
Speaker 1: in Delaware. Do you know why in Delaware? I do

600
00:34:16,160 --> 00:34:19,239
Speaker 1: not know why Delaware. So anyone who's traveled in the

601
00:34:19,320 --> 00:34:23,319
Speaker 1: Northeast will understand this, because everyone who lives anywhere close

602
00:34:23,360 --> 00:34:26,360
Speaker 1: to Delaware goes to Delaware to do their shopping. Delaware

603
00:34:26,400 --> 00:34:30,160
Speaker 1: does not have a state sales tak one of those places. Yeah. Yeah,

604
00:34:30,800 --> 00:34:34,839
Speaker 1: my wife is from Philadelphia, so whenever we do any

605
00:34:35,000 --> 00:34:38,200
Speaker 1: sort of shopping in the Northeast, we take little road

606
00:34:38,239 --> 00:34:41,640
Speaker 1: trip to Delaware. Uh. This is not by my choice

607
00:34:42,880 --> 00:34:47,000
Speaker 1: because I much preferred convenience over saving a buck twenty

608
00:34:47,080 --> 00:34:51,880
Speaker 1: five honey, I'll pay you back, I'll go out, and

609
00:34:51,920 --> 00:34:54,040
Speaker 1: I'll work an extra podcast if you need me to.

610
00:34:54,200 --> 00:34:57,759
Speaker 1: I don't want to go to Delaware. By the way,

611
00:34:57,840 --> 00:34:59,719
Speaker 1: Delaware is lovely. I just don't want to go on

612
00:34:59,800 --> 00:35:04,480
Speaker 1: the I'm sure the drive is gorgeous. Taking the mud

613
00:35:05,600 --> 00:35:07,560
Speaker 1: if you can go like a mile down the street

614
00:35:07,719 --> 00:35:11,319
Speaker 1: versus a state over. But my Ohio just came out

615
00:35:11,360 --> 00:35:13,359
Speaker 1: by by referring to as a stick in the mud.

616
00:35:13,440 --> 00:35:16,560
Speaker 1: That was really that's okay. I would hate to think

617
00:35:16,600 --> 00:35:20,279
Speaker 1: of what the southern version of that would be. I

618
00:35:20,320 --> 00:35:22,080
Speaker 1: wouldn't even be abill tell you, because I'm a nice person.

619
00:35:22,120 --> 00:35:25,000
Speaker 1: I don't call people things like that anyway. So also,

620
00:35:26,200 --> 00:35:30,719
Speaker 1: they became the first online retailer to to one million customers,

621
00:35:32,000 --> 00:35:34,120
Speaker 1: and uh, and you know this, this is kind of

622
00:35:34,200 --> 00:35:36,320
Speaker 1: interesting to you. You sit there and think about the

623
00:35:36,520 --> 00:35:40,960
Speaker 1: fact that Bezos kind of had this vision of totally

624
00:35:41,080 --> 00:35:45,479
Speaker 1: revolutionizing the way people do shopping, and and at first

625
00:35:45,600 --> 00:35:48,440
Speaker 1: you might think, well, that's just ridiculous, But then It

626
00:35:48,600 --> 00:35:53,880
Speaker 1: really wasn't that long ago that we had before before

627
00:35:53,960 --> 00:35:57,399
Speaker 1: the era of department stores. So the department store era

628
00:35:57,680 --> 00:36:00,799
Speaker 1: totally revolutionized the way people did shopping. Yeah, it's I mean,

629
00:36:00,880 --> 00:36:02,880
Speaker 1: you know it's there. There's more than one thing that

630
00:36:03,000 --> 00:36:04,840
Speaker 1: you sell here. You sell different types of things. I

631
00:36:04,880 --> 00:36:07,000
Speaker 1: can go to a different department and get clothing, and

632
00:36:07,080 --> 00:36:09,759
Speaker 1: then another one and get some housewares, and it's it's

633
00:36:09,960 --> 00:36:13,320
Speaker 1: it's not a general store where your selection is limited

634
00:36:13,400 --> 00:36:15,800
Speaker 1: by the actual tiny space or if you want to

635
00:36:15,840 --> 00:36:18,520
Speaker 1: go back even further. Uh, you know, you're talking about

636
00:36:18,560 --> 00:36:21,040
Speaker 1: buying things directly from the people who made them, or

637
00:36:21,239 --> 00:36:24,600
Speaker 1: from a traveling salesman, as is depicted in the documentary

638
00:36:24,880 --> 00:36:30,879
Speaker 1: music Man Um The But yeah, the uh, this wasn't

639
00:36:30,920 --> 00:36:34,000
Speaker 1: really that unusual to say we could completely revolutionized Lawrence.

640
00:36:34,080 --> 00:36:37,160
Speaker 1: Just it was just here, I was gonna be okay,

641
00:36:37,239 --> 00:36:40,200
Speaker 1: but I was like, no, it's the slow disapproval shake

642
00:36:40,280 --> 00:36:42,840
Speaker 1: of the head for the music Man reference, and I

643
00:36:42,920 --> 00:36:44,880
Speaker 1: could not make it through the sentence. But no, the

644
00:36:45,920 --> 00:36:48,080
Speaker 1: you know, it really wasn't that big of a stretch.

645
00:36:48,640 --> 00:36:51,760
Speaker 1: It just was hard to see at the time because

646
00:36:52,400 --> 00:36:54,040
Speaker 1: what was so new. Yeah, it was so new and

647
00:36:54,120 --> 00:36:57,160
Speaker 1: not that many people. I mean, I mean, goodness, my gracious,

648
00:36:57,200 --> 00:36:59,080
Speaker 1: that was still you know, people were still on geo cit.

649
00:37:01,040 --> 00:37:02,799
Speaker 1: Let's not talk about it like it was that long ago,

650
00:37:02,880 --> 00:37:06,080
Speaker 1: because I was well out of college and married by then,

651
00:37:06,200 --> 00:37:09,600
Speaker 1: so I was in high school. Shut up anyway. So

652
00:37:10,719 --> 00:37:14,640
Speaker 1: so so anyway, ninety seven comes to an end. That

653
00:37:14,760 --> 00:37:18,960
Speaker 1: was a big, big year for Amazon. And talk about

654
00:37:19,000 --> 00:37:24,960
Speaker 1: a big year. They hit a high of three hundred

655
00:37:25,040 --> 00:37:30,320
Speaker 1: and sixty one dollars per share um and uh and

656
00:37:30,440 --> 00:37:33,560
Speaker 1: really in I'm not I'm gonna go back to nine

657
00:37:33,800 --> 00:37:36,480
Speaker 1: in a second. They ended up splitting the stock a

658
00:37:36,560 --> 00:37:38,759
Speaker 1: couple of times. Now, on a stock split, what you're

659
00:37:38,760 --> 00:37:41,520
Speaker 1: doing is, you know, you're taking the amount stock you have,

660
00:37:41,719 --> 00:37:44,800
Speaker 1: you increased the number of stocks based upon that, and

661
00:37:44,920 --> 00:37:49,399
Speaker 1: you then reduce the uh, the the value of each

662
00:37:49,440 --> 00:37:52,320
Speaker 1: individual stock, so that the value of the company remains

663
00:37:52,360 --> 00:37:55,480
Speaker 1: the same, but you can sell to more people, right right,

664
00:37:55,600 --> 00:37:58,640
Speaker 1: So suddenly you have twice as much stock. It's worth

665
00:37:58,760 --> 00:38:01,400
Speaker 1: the same amount collectively what you had before. But now

666
00:38:01,480 --> 00:38:03,759
Speaker 1: if you wanted to sell half of it off, you

667
00:38:03,800 --> 00:38:07,719
Speaker 1: would still have a sizeable amount um. And so they

668
00:38:07,800 --> 00:38:09,600
Speaker 1: did that a couple of times, and they did it

669
00:38:09,640 --> 00:38:12,719
Speaker 1: in a three to one split, which reduced the the

670
00:38:13,880 --> 00:38:18,120
Speaker 1: the price to just over a hundred dollars per share. Uh,

671
00:38:18,600 --> 00:38:21,800
Speaker 1: back in, but we'll get into that in just a second.

672
00:38:22,920 --> 00:38:27,239
Speaker 1: They also bought another little website that you may have

673
00:38:27,320 --> 00:38:30,840
Speaker 1: heard of, the Internet Movie dat Database. Yeah. Yeah, what

674
00:38:31,000 --> 00:38:35,080
Speaker 1: a pleasant place that can be. That's I never never

675
00:38:35,160 --> 00:38:38,600
Speaker 1: read the comments on anything. And it's still it's still

676
00:38:38,840 --> 00:38:43,160
Speaker 1: much more civil than YouTube. Um, but then so was

677
00:38:43,239 --> 00:38:47,520
Speaker 1: Moss Eisley. Uh, but yeah, I am dB. Yeah, let's

678
00:38:47,520 --> 00:38:51,000
Speaker 1: say they purchased that. So, uh, it was an interesting

679
00:38:51,080 --> 00:38:54,400
Speaker 1: move again because for a moment you sit there and say, well,

680
00:38:54,480 --> 00:38:57,719
Speaker 1: what's up with that? And then uh, if you knew,

681
00:38:57,760 --> 00:39:00,320
Speaker 1: if you knew where Amazon was going. And except for

682
00:39:00,360 --> 00:39:02,000
Speaker 1: the fact that at the time they had still been

683
00:39:02,080 --> 00:39:04,360
Speaker 1: selling just books. Yeah, that's all they sold. All they

684
00:39:04,360 --> 00:39:09,000
Speaker 1: sold up until they also opened to Amazon stores music

685
00:39:09,120 --> 00:39:12,319
Speaker 1: and DVD video. That's right. And so you think about

686
00:39:12,360 --> 00:39:14,560
Speaker 1: the reason why they started with just books was that

687
00:39:15,160 --> 00:39:17,719
Speaker 1: it was it was something that was scalable and it

688
00:39:18,000 --> 00:39:22,160
Speaker 1: was a manageable business. And also he had the benefit of,

689
00:39:22,400 --> 00:39:26,319
Speaker 1: like I said, those two big distributors with their exhaustive databases,

690
00:39:26,560 --> 00:39:28,800
Speaker 1: a lot of the work was already done. Now that

691
00:39:28,920 --> 00:39:32,080
Speaker 1: he's raised money, Bezos, that is, now the Basos is

692
00:39:32,160 --> 00:39:34,040
Speaker 1: raised money and the companies raised money, the company could

693
00:39:34,080 --> 00:39:36,800
Speaker 1: start to look into diversification, which was kind of the

694
00:39:36,840 --> 00:39:40,680
Speaker 1: plan all along, but really starting with books was the

695
00:39:40,719 --> 00:39:45,680
Speaker 1: most important step. So once they opened up the music

696
00:39:45,840 --> 00:39:48,600
Speaker 1: and DVD stores. Music, by the way, we're talking about

697
00:39:49,040 --> 00:39:54,160
Speaker 1: hard mediads. We're not talking about digital files yet. Um.

698
00:39:54,719 --> 00:39:57,440
Speaker 1: You know. Once he did that, Basos also came up

699
00:39:57,520 --> 00:40:01,719
Speaker 1: with another decision which was an important one in Amazon's

700
00:40:02,280 --> 00:40:05,800
Speaker 1: um existence, and that was that he wanted to have

701
00:40:06,080 --> 00:40:08,239
Speaker 1: a lot of control over all of this. It's one

702
00:40:08,239 --> 00:40:10,040
Speaker 1: of the reasons why it was very it was very

703
00:40:10,080 --> 00:40:13,000
Speaker 1: important to him for Amazon to own its own warehouses.

704
00:40:13,680 --> 00:40:15,840
Speaker 1: And the reason for that was that if a customer

705
00:40:15,880 --> 00:40:19,319
Speaker 1: put in an order and asked for say, books from

706
00:40:19,440 --> 00:40:22,840
Speaker 1: different publishers as well as a c D and a film,

707
00:40:23,320 --> 00:40:25,480
Speaker 1: all of that could be placed in one box and

708
00:40:25,560 --> 00:40:28,600
Speaker 1: sent to the customer, as opposed to Okay, here's here

709
00:40:30,719 --> 00:40:33,239
Speaker 1: and all of these losses or or have to pass

710
00:40:33,280 --> 00:40:35,640
Speaker 1: that on to the customer and just everyone gets angry,

711
00:40:35,920 --> 00:40:38,520
Speaker 1: right yeah, or you know, they get two thirds of

712
00:40:38,600 --> 00:40:41,880
Speaker 1: their order but the final third is lost. Or now

713
00:40:42,000 --> 00:40:44,560
Speaker 1: this way, it gave a lot more control to Amazon.

714
00:40:44,680 --> 00:40:47,600
Speaker 1: That was very important to Bezos. So uh, he had

715
00:40:47,680 --> 00:40:50,320
Speaker 1: these warehouses and decided to make use of them in

716
00:40:50,400 --> 00:40:53,160
Speaker 1: that way. So here's an example I have created and

717
00:40:53,480 --> 00:40:56,440
Speaker 1: uh and listeners, you have a challenge here. The challenge,

718
00:40:56,520 --> 00:40:59,759
Speaker 1: listeners is to find out how each one of the

719
00:41:00,000 --> 00:41:03,239
Speaker 1: items I'm about to list has a connection to me.

720
00:41:04,239 --> 00:41:12,200
Speaker 1: Because I'm an egomaniac and the universe revolts. Here's my example. So,

721
00:41:12,600 --> 00:41:17,680
Speaker 1: I want to order the Kim McKee book Atlanta Bones.

722
00:41:18,640 --> 00:41:22,160
Speaker 1: I also want to order a CD of a production

723
00:41:22,239 --> 00:41:25,000
Speaker 1: of The Rats and the Walls, which was, you know,

724
00:41:25,080 --> 00:41:27,920
Speaker 1: an HP Lovecraft story that was produced by the Atlanta

725
00:41:28,000 --> 00:41:31,279
Speaker 1: Radio Theater Company. And I want a copy of the

726
00:41:31,440 --> 00:41:34,080
Speaker 1: film on DVD. I want a copy of the Signal.

727
00:41:35,080 --> 00:41:37,520
Speaker 1: So if I put all those orders in on Amazon,

728
00:41:37,600 --> 00:41:39,719
Speaker 1: because they have these warehouses where they have all the

729
00:41:39,800 --> 00:41:42,480
Speaker 1: different types of media together, they can put that all

730
00:41:42,560 --> 00:41:44,120
Speaker 1: in one package and send it to me and I

731
00:41:44,239 --> 00:41:48,720
Speaker 1: get it all in one neat delivery. And uh. So again, listeners,

732
00:41:48,840 --> 00:41:52,040
Speaker 1: tell me how I'm connected to all three of those things. Uh.

733
00:41:53,120 --> 00:41:55,160
Speaker 1: They may not be the same connection in each case,

734
00:41:55,200 --> 00:41:58,440
Speaker 1: by the way, it may be different connections. Moving on,

735
00:41:58,920 --> 00:42:02,399
Speaker 1: they also launched the uh the Amazon Advantage program, which

736
00:42:02,560 --> 00:42:06,680
Speaker 1: let companies and creators sell their works through Amazon. They

737
00:42:06,719 --> 00:42:11,319
Speaker 1: also acquired major booksellers in the UK and Germany. Uh

738
00:42:11,920 --> 00:42:14,239
Speaker 1: and yeah, it was more before the end of the year.

739
00:42:14,360 --> 00:42:16,239
Speaker 1: Um and and remember last year they had hit one

740
00:42:16,280 --> 00:42:21,239
Speaker 1: million customers. By the end of had hit three million. Yeah,

741
00:42:21,320 --> 00:42:26,359
Speaker 1: so so lots of growth. They're still, of course, not profitable. Uh.

742
00:42:27,120 --> 00:42:29,600
Speaker 1: Do you have anything else, because that's that's what I got.

743
00:42:29,640 --> 00:42:33,080
Speaker 1: All right, let's move on to h They opened up

744
00:42:33,080 --> 00:42:36,160
Speaker 1: another fulfillment center. I like that they call them fulfillment centers.

745
00:42:36,560 --> 00:42:39,440
Speaker 1: It sounds very you know, zen, it reminds me of

746
00:42:39,520 --> 00:42:44,839
Speaker 1: gladows honestly, but welcome to the fulfillment center. Uh huh,

747
00:42:46,440 --> 00:42:48,040
Speaker 1: that's not bad. But anyway, this one was in a

748
00:42:48,200 --> 00:42:52,160
Speaker 1: friendly Nevada. Now, the reason for opening in Nevada not

749
00:42:52,400 --> 00:42:55,880
Speaker 1: having to do directly with that state's sales tax. It

750
00:42:55,960 --> 00:42:58,400
Speaker 1: was actually more to do with the state of California.

751
00:42:59,120 --> 00:43:01,719
Speaker 1: They wanted to have of a fulfillment center that was

752
00:43:01,800 --> 00:43:05,800
Speaker 1: closer to California to deliver to California more quickly. But

753
00:43:05,920 --> 00:43:09,880
Speaker 1: California's sales tax is uh is fairly complex. And also

754
00:43:10,080 --> 00:43:12,359
Speaker 1: you know, it's something that that Amazon did not want

755
00:43:12,400 --> 00:43:15,520
Speaker 1: to deal with, so instead of opening up a fulfillment

756
00:43:15,560 --> 00:43:18,239
Speaker 1: center within the state, they opened it in Nevada. I

757
00:43:18,280 --> 00:43:20,880
Speaker 1: think they opened actually three other fulfillment centers other than

758
00:43:20,920 --> 00:43:24,719
Speaker 1: that one, and I have not written down where they are. Yeah, well,

759
00:43:24,800 --> 00:43:27,480
Speaker 1: at this point forward, they start opening up all the points.

760
00:43:27,680 --> 00:43:31,319
Speaker 1: Actually there was another point Bezos said, uh that there

761
00:43:31,400 --> 00:43:32,880
Speaker 1: was a point where he had a discussion with his

762
00:43:33,400 --> 00:43:37,480
Speaker 1: the other members of the executive team at Amazon, and

763
00:43:37,560 --> 00:43:41,200
Speaker 1: they were saying that he should open up four fulfillment centers,

764
00:43:41,320 --> 00:43:44,680
Speaker 1: and he said, no, we should open five fulfillment centers.

765
00:43:44,840 --> 00:43:47,960
Speaker 1: And they all balkedd that because I said, well why

766
00:43:48,080 --> 00:43:50,880
Speaker 1: we we we need for what we can use is

767
00:43:51,000 --> 00:43:54,399
Speaker 1: for right and uh And he ended up getting his way.

768
00:43:55,560 --> 00:44:00,399
Speaker 1: Often gets his way, note not all the time. And yeah,

769
00:44:00,440 --> 00:44:02,719
Speaker 1: there's sometimes where he talks about how some of his

770
00:44:02,840 --> 00:44:05,640
Speaker 1: employees like came up to him and gave him a

771
00:44:05,680 --> 00:44:08,360
Speaker 1: suggestion and he said that sounds like too much trouble,

772
00:44:08,400 --> 00:44:09,880
Speaker 1: and then they went ahead and did it anyway and

773
00:44:09,920 --> 00:44:12,440
Speaker 1: then came to him with the solution. He's like, no one,

774
00:44:12,760 --> 00:44:16,560
Speaker 1: no one listens to me around here, but thank you anyway, Um,

775
00:44:16,680 --> 00:44:18,239
Speaker 1: they did listen to him at this top point, and

776
00:44:18,280 --> 00:44:21,400
Speaker 1: they built the five fulfillment centers and uh and as

777
00:44:21,600 --> 00:44:25,480
Speaker 1: as it turns out, because of the the incredible growth

778
00:44:26,080 --> 00:44:30,200
Speaker 1: in customer base and orders and sales, that fifth fulfillment

779
00:44:30,239 --> 00:44:34,200
Speaker 1: center was necessary for them to maintain the customer service

780
00:44:34,280 --> 00:44:38,080
Speaker 1: that they had established. Again, just another very forward thinking,

781
00:44:38,520 --> 00:44:42,920
Speaker 1: very I like that phrase. I just I just realized, yes, alright, no,

782
00:44:43,080 --> 00:44:46,960
Speaker 1: that's fine, go ahead, let's let's promote it. Um, yeah, no,

783
00:44:47,200 --> 00:44:49,280
Speaker 1: you know, I agree. It was. It was very important

784
00:44:49,360 --> 00:44:53,560
Speaker 1: for him to uh, to think ahead and to anticipate that.

785
00:44:53,960 --> 00:44:56,960
Speaker 1: You know, it wasn't just that they could not have

786
00:44:57,120 --> 00:44:59,120
Speaker 1: done the job with four they might they might have

787
00:44:59,200 --> 00:45:01,719
Speaker 1: been able to, but with five they were able to

788
00:45:01,800 --> 00:45:05,080
Speaker 1: do it and ensure the customer service level that they

789
00:45:05,120 --> 00:45:07,319
Speaker 1: had already established. Yes, with the sort of growth they

790
00:45:07,360 --> 00:45:11,799
Speaker 1: were experiencing at the time. UM. Yeah, See, at that point,

791
00:45:11,880 --> 00:45:15,600
Speaker 1: their market value was about twenty two point one billion dollars,

792
00:45:15,680 --> 00:45:20,000
Speaker 1: which meant that they were more valuable than Kmart and J. C.

793
00:45:20,160 --> 00:45:22,560
Speaker 1: Penny combined. And keep in mind, this is before Kmart

794
00:45:22,640 --> 00:45:26,759
Speaker 1: had its financial problems. Um. They also opened six new

795
00:45:26,840 --> 00:45:30,440
Speaker 1: stores on Amazon dot Com. Consumer electronics, toys and games,

796
00:45:30,480 --> 00:45:34,160
Speaker 1: home improvement software, video games, and gift ideas is grown

797
00:45:34,200 --> 00:45:37,359
Speaker 1: in there. Gift gift ideas is one of those UH

798
00:45:37,800 --> 00:45:40,520
Speaker 1: user experiences that is also really critical to the way

799
00:45:40,560 --> 00:45:44,640
Speaker 1: that Amazon has grown and become uh the leader in

800
00:45:45,320 --> 00:45:49,320
Speaker 1: online sales. Yeah, they they really invested heavily in getting

801
00:45:49,400 --> 00:45:54,080
Speaker 1: programmers to design algorithms that would help customers in their

802
00:45:54,120 --> 00:45:57,480
Speaker 1: shopping so that and really help Amazon ultimately to help

803
00:45:57,520 --> 00:46:00,120
Speaker 1: Amazon stuff. You have the idea that you know, are

804
00:46:00,200 --> 00:46:02,799
Speaker 1: customers who were interested in this also looked at blah

805
00:46:02,840 --> 00:46:05,640
Speaker 1: blah blah, or hey, you bought this thing, you might

806
00:46:05,719 --> 00:46:08,000
Speaker 1: also want this thing. All of those recommendations that you

807
00:46:08,040 --> 00:46:09,759
Speaker 1: get every single time that you get on Amazon are

808
00:46:09,800 --> 00:46:11,879
Speaker 1: are based on a lot of your of what you're

809
00:46:11,920 --> 00:46:15,160
Speaker 1: looking at, what people that you know might be looking at,

810
00:46:15,280 --> 00:46:17,239
Speaker 1: what other people who yeah, and what other people who

811
00:46:17,520 --> 00:46:19,839
Speaker 1: purchased the same thing you bought what you know, things

812
00:46:19,880 --> 00:46:22,440
Speaker 1: they found useful. There have been times where I that

813
00:46:22,680 --> 00:46:25,799
Speaker 1: service has been invaluable to me where I've purchased something

814
00:46:26,040 --> 00:46:27,640
Speaker 1: and I said, hey, you bought this thing. If you

815
00:46:27,719 --> 00:46:31,000
Speaker 1: wanted to work, you may also want this thing, Like, well, yes,

816
00:46:31,080 --> 00:46:33,040
Speaker 1: I do want it to work, I will buy that thing,

817
00:46:33,160 --> 00:46:35,440
Speaker 1: and sure enough, I mean it wasn't It wasn't opportunistic

818
00:46:35,480 --> 00:46:38,759
Speaker 1: and it was genuinely helpful to me. So, uh, you know,

819
00:46:38,920 --> 00:46:41,480
Speaker 1: it sounds like it can be opportunistic, and I guess

820
00:46:41,520 --> 00:46:44,479
Speaker 1: in some cases it can be, but ultimately it's trying

821
00:46:44,520 --> 00:46:46,960
Speaker 1: to give the consumer the best experience, because if it's not,

822
00:46:47,360 --> 00:46:50,919
Speaker 1: then it isn't working and it's just a distraction. Um. Also,

823
00:46:51,040 --> 00:46:54,800
Speaker 1: this is what makes some of those really snarky Amazon

824
00:46:55,000 --> 00:47:00,560
Speaker 1: dot com uh product reviews so incredibly entertaining. If you've

825
00:47:00,560 --> 00:47:03,560
Speaker 1: ever found one of the products that just has people

826
00:47:03,680 --> 00:47:08,040
Speaker 1: writing up complete farcical yeah, really, there's there's a Two

827
00:47:08,080 --> 00:47:11,719
Speaker 1: of my favorites are the bick for her. Yes, those

828
00:47:11,760 --> 00:47:13,800
Speaker 1: are so those are so funny. That was delightful that

829
00:47:13,840 --> 00:47:16,520
Speaker 1: that was. That was bigs adventure into pens for women

830
00:47:16,719 --> 00:47:19,520
Speaker 1: and they were all pastel colors and I guess ergonomic

831
00:47:19,640 --> 00:47:24,280
Speaker 1: for lady fingers. I'm not sure that means fingers belonging

832
00:47:24,320 --> 00:47:27,719
Speaker 1: to a lady. Not the delicious not the delicious snack

833
00:47:27,800 --> 00:47:32,400
Speaker 1: kick Um that that one. And my my current favorite

834
00:47:32,480 --> 00:47:36,040
Speaker 1: is that banana slicer. Oh, yes, yes, that's a good one.

835
00:47:36,440 --> 00:47:38,200
Speaker 1: Now there's a whole bunch too. There's one that's like

836
00:47:38,400 --> 00:47:40,279
Speaker 1: for gallons of milk. There was one that was for

837
00:47:41,000 --> 00:47:45,840
Speaker 1: for for specific kind of warning tape. Uh, it was

838
00:47:45,920 --> 00:47:48,640
Speaker 1: a kind of duct tape. There was one for uh,

839
00:47:49,080 --> 00:47:52,960
Speaker 1: for enriched uranium. There's some fun ones out there. And

840
00:47:53,080 --> 00:47:56,120
Speaker 1: and the nice thing is is that because Amazon's algorithms work,

841
00:47:56,320 --> 00:47:59,680
Speaker 1: it actually will point you to other ridiculous products that

842
00:47:59,800 --> 00:48:02,719
Speaker 1: also have and I don't delightful. I don't know that

843
00:48:02,840 --> 00:48:07,000
Speaker 1: that's intentional, but it does work, and it's funny. It's

844
00:48:07,000 --> 00:48:09,120
Speaker 1: a great way to lose an entire afternoon. By the way,

845
00:48:10,760 --> 00:48:14,280
Speaker 1: they also ended up launching a product called Amazon Auctions,

846
00:48:14,360 --> 00:48:17,600
Speaker 1: which was kind of their answer to eBay. Um. It

847
00:48:17,880 --> 00:48:21,480
Speaker 1: ended up not really getting a lot of traction and uh,

848
00:48:21,560 --> 00:48:25,960
Speaker 1: and eventually they would abandon Amazon Auctions. And that's not

849
00:48:26,280 --> 00:48:28,719
Speaker 1: unusual in fact for Amazon. They've They've got quite a

850
00:48:28,760 --> 00:48:32,799
Speaker 1: few projects that they ultimately either phased out or made

851
00:48:32,960 --> 00:48:36,600
Speaker 1: or reincorporated in a different way, kind of took down piecemeal.

852
00:48:37,040 --> 00:48:39,800
Speaker 1: Z Shops is another thing that they opened, which was

853
00:48:39,960 --> 00:48:45,520
Speaker 1: their third party retailer outlet. Yeah, they eventually phase that

854
00:48:45,640 --> 00:48:49,200
Speaker 1: out in favor of the marketplace. But yeah, that's another

855
00:48:49,360 --> 00:48:51,160
Speaker 1: that's a great example that was where they built in

856
00:48:51,200 --> 00:48:53,280
Speaker 1: all these features and then they said, this isn't working.

857
00:48:53,960 --> 00:48:57,800
Speaker 1: Let's rebrand it. Let's let's let's tweak it, maybe incorporate

858
00:48:57,880 --> 00:49:00,239
Speaker 1: some of the stuff and something new. They also wired

859
00:49:00,239 --> 00:49:03,880
Speaker 1: a company called tool Crib of the North. They inquired

860
00:49:03,920 --> 00:49:06,040
Speaker 1: they acquired their online and catalog sales. There was a

861
00:49:06,120 --> 00:49:09,279
Speaker 1: great story about Bezos saying talking about how how to

862
00:49:09,400 --> 00:49:13,160
Speaker 1: make it profitable to to ship a one ton drill press.

863
00:49:14,600 --> 00:49:17,560
Speaker 1: That was kind of funny. Um, like you said, they

864
00:49:17,560 --> 00:49:22,560
Speaker 1: started offering up lots of other products in various categories. Um. Oh,

865
00:49:22,640 --> 00:49:25,719
Speaker 1: and from a great article and Wired. I know I

866
00:49:25,800 --> 00:49:27,520
Speaker 1: mentioned Wired all the time, but they really do some

867
00:49:27,680 --> 00:49:31,400
Speaker 1: great stuff. And they in edition of Wired, in an

868
00:49:31,520 --> 00:49:34,680
Speaker 1: article called the Inner Bezos. Uh, there was a quote.

869
00:49:35,360 --> 00:49:38,080
Speaker 1: One thing to keep in mind, this is from Bezos.

870
00:49:38,160 --> 00:49:41,080
Speaker 1: He says is for many of these people, meaning the

871
00:49:41,600 --> 00:49:44,840
Speaker 1: people who are suddenly wealthy in Amazon, the wealth that

872
00:49:44,960 --> 00:49:47,520
Speaker 1: they have is paper wealth, and it will exist at

873
00:49:47,560 --> 00:49:49,640
Speaker 1: that level only for as long as we continue to

874
00:49:49,760 --> 00:49:52,480
Speaker 1: serve our customers. Well, so what he's staying here is

875
00:49:52,560 --> 00:49:56,359
Speaker 1: that there were people in Amazon who had become millionaires

876
00:49:56,960 --> 00:49:59,520
Speaker 1: because they owned stock in the company, and the company

877
00:49:59,600 --> 00:50:04,200
Speaker 1: stock was on the rise, and Basis was pointing out like, well, yeah,

878
00:50:04,360 --> 00:50:06,759
Speaker 1: if you look at it on paper, we're millionaires, but

879
00:50:06,880 --> 00:50:09,320
Speaker 1: in reality, if we would have to cash out and

880
00:50:09,400 --> 00:50:12,360
Speaker 1: liquidate all those assets in order to really be millionaires.

881
00:50:12,680 --> 00:50:15,960
Speaker 1: And so we have a responsibility to keep our company moving,

882
00:50:16,480 --> 00:50:19,640
Speaker 1: moving ahead and being in good shape. This is incredibly

883
00:50:19,640 --> 00:50:24,000
Speaker 1: important because this is what I'm saying in n and uh.

884
00:50:24,280 --> 00:50:27,640
Speaker 1: Well but before were no, no, no, I'm gonna say

885
00:50:27,680 --> 00:50:29,680
Speaker 1: like in a in a year, that's going to be

886
00:50:29,800 --> 00:50:34,640
Speaker 1: a very ympathetic thing, right, Yeah, And and yes, that

887
00:50:34,719 --> 00:50:37,759
Speaker 1: that was the was also the year that Basis was

888
00:50:37,880 --> 00:50:41,600
Speaker 1: named Times Person of the Year. Yeah, that's a big deal.

889
00:50:41,719 --> 00:50:44,400
Speaker 1: And also, um, that was the year that Barnes and

890
00:50:44,480 --> 00:50:49,400
Speaker 1: Noble made a move that was potentially scary for Amazon.

891
00:50:50,000 --> 00:50:54,200
Speaker 1: They purchased Ingram, one of those two of the giants

892
00:50:54,640 --> 00:51:00,080
Speaker 1: distributors and Barnes and Noble and Amazon obviously competed in

893
00:51:00,200 --> 00:51:03,239
Speaker 1: the space of as far as booksellers go, and and

894
00:51:03,320 --> 00:51:06,200
Speaker 1: Barnes and Noble was probably out of all the other

895
00:51:07,200 --> 00:51:08,920
Speaker 1: brick and mortar stores. They were the ones doing the

896
00:51:09,120 --> 00:51:11,480
Speaker 1: doing the best job, and they were extremely savvy. They

897
00:51:11,520 --> 00:51:14,520
Speaker 1: have been for for basically their entire and in the

898
00:51:14,560 --> 00:51:19,040
Speaker 1: publishing industry as compared to other big box stores, to say,

899
00:51:19,120 --> 00:51:22,560
Speaker 1: for example, Borders that didn't make it. Yeah, and and

900
00:51:23,120 --> 00:51:27,040
Speaker 1: really Barnes and Noble and Amazon had been competing quite

901
00:51:27,040 --> 00:51:29,520
Speaker 1: a bit, uh and so that that kind of raised

902
00:51:29,600 --> 00:51:34,160
Speaker 1: some potential threats. But but Amazon was actually working very

903
00:51:34,239 --> 00:51:39,759
Speaker 1: hard to create relationships directly with publishers. So since you

904
00:51:39,920 --> 00:51:43,280
Speaker 1: skip the distributor entirely and you go straight to the publisher,

905
00:51:43,600 --> 00:51:46,560
Speaker 1: this would of course change even more in the future

906
00:51:46,680 --> 00:51:49,799
Speaker 1: when we talk about the publishing, right, we're still years

907
00:51:49,840 --> 00:51:54,440
Speaker 1: away from that. Um and then uh, we kind of

908
00:51:54,480 --> 00:51:56,680
Speaker 1: move into two thousand and this is this is a

909
00:51:56,840 --> 00:51:59,120
Speaker 1: monumental year on the web. It's also where we're going

910
00:51:59,200 --> 00:52:03,640
Speaker 1: to conclude the episode. Uh, two thousand is when in

911
00:52:03,840 --> 00:52:06,200
Speaker 1: March two thousand, Specifically, in fact, if you want to

912
00:52:06,239 --> 00:52:10,279
Speaker 1: get really specific, March two thousand is when the the

913
00:52:10,760 --> 00:52:15,760
Speaker 1: dot com bubble burst. Now, this was something that happened

914
00:52:15,800 --> 00:52:20,479
Speaker 1: because the web was seen as this wild West land

915
00:52:20,520 --> 00:52:23,120
Speaker 1: of opportunity. It was like the gold rushed Yeah. Yeah, Ever,

916
00:52:23,239 --> 00:52:26,879
Speaker 1: everyone was was out in uh Silicon Valley and doing

917
00:52:26,920 --> 00:52:29,000
Speaker 1: crazy stuff, and everyone was really psyched about it and

918
00:52:29,120 --> 00:52:30,920
Speaker 1: running around, and everyone's saying like, this is the way

919
00:52:30,920 --> 00:52:32,960
Speaker 1: we're gonna be able to print our own money. Essentially,

920
00:52:33,000 --> 00:52:36,200
Speaker 1: we're gonna be uh, we're gonna be so rich. And

921
00:52:36,280 --> 00:52:38,640
Speaker 1: you have lots of dot com companies going public and

922
00:52:38,840 --> 00:52:42,520
Speaker 1: raising crazy amounts of money in in crazy stock deals,

923
00:52:43,000 --> 00:52:46,319
Speaker 1: and employees being paid in stock and said like, okay,

924
00:52:46,360 --> 00:52:48,200
Speaker 1: well we can't afford to actually pay you a paycheck,

925
00:52:48,280 --> 00:52:51,320
Speaker 1: but here here's a here's ten thousand shares in the company.

926
00:52:51,440 --> 00:52:55,840
Speaker 1: You are surely nothing will go wrong overnight. You're a millionaire.

927
00:52:56,000 --> 00:52:58,239
Speaker 1: So just like Basis was saying, like on paper, these

928
00:52:58,280 --> 00:53:03,680
Speaker 1: people were millionaires. But the problem was that the expectations

929
00:53:03,920 --> 00:53:06,600
Speaker 1: of how the web was going to deliver versus the

930
00:53:06,680 --> 00:53:10,680
Speaker 1: reality of what it actually could deliver didn't match up.

931
00:53:10,840 --> 00:53:13,719
Speaker 1: And then investors started getting scared because they're saying, wait

932
00:53:13,760 --> 00:53:15,960
Speaker 1: a minute, I thought this was gonna just be a

933
00:53:16,040 --> 00:53:18,120
Speaker 1: license to print money, but now I'm not seeing any

934
00:53:18,200 --> 00:53:20,960
Speaker 1: return of my investment. I'm getting out right and and

935
00:53:21,040 --> 00:53:22,440
Speaker 1: and there were a lot of reasons for it. I mean,

936
00:53:22,440 --> 00:53:25,520
Speaker 1: there was an infrastructure problem where you know, not not

937
00:53:25,800 --> 00:53:29,600
Speaker 1: enough people were online, and there were a lot of

938
00:53:29,640 --> 00:53:33,080
Speaker 1: companies that were just terrible at managing their funds. This

939
00:53:33,200 --> 00:53:34,719
Speaker 1: is one of those things I've talked about in the past,

940
00:53:34,800 --> 00:53:37,560
Speaker 1: how a small company could get a huge amount of

941
00:53:38,080 --> 00:53:41,839
Speaker 1: money and then mismanage it terribly because they that wasn't

942
00:53:41,880 --> 00:53:44,479
Speaker 1: what they were expecting, Like they're they're operating costs would

943
00:53:44,480 --> 00:53:46,920
Speaker 1: have been at a certain level. They raised way more

944
00:53:47,040 --> 00:53:50,200
Speaker 1: money than that, and then they say, well, heck, let's

945
00:53:50,239 --> 00:53:54,640
Speaker 1: get a penthouse for everyone. Everyone gets a super cool

946
00:53:54,800 --> 00:53:58,719
Speaker 1: desk made out of steel and glass. We're all lex

947
00:53:58,840 --> 00:54:02,200
Speaker 1: Luthor in this world. And then, you know, eventually they think, oh,

948
00:54:02,280 --> 00:54:04,120
Speaker 1: wait a minute, we were supposed to deliver something for

949
00:54:04,200 --> 00:54:06,040
Speaker 1: all that money they gave us instead of just you know,

950
00:54:06,160 --> 00:54:09,840
Speaker 1: giving ourselves these amazing offices, and things started to fall apart,

951
00:54:10,280 --> 00:54:12,359
Speaker 1: and uh, you know, it's not that the people were

952
00:54:12,400 --> 00:54:16,640
Speaker 1: necessarily bad people, it's just that things didn't and uh.

953
00:54:16,800 --> 00:54:20,080
Speaker 1: And actually Amazon was hurt by this in multiple ways,

954
00:54:20,160 --> 00:54:23,560
Speaker 1: one of which was that, you know, unlike the other companies,

955
00:54:23,640 --> 00:54:30,600
Speaker 1: it had not expanded so um, but they did invest

956
00:54:30,840 --> 00:54:34,839
Speaker 1: invested a lot of other stuff and took dramatic losses. Yeah,

957
00:54:34,880 --> 00:54:38,560
Speaker 1: like Pets dot com, Living dot com, Cosmo dot com.

958
00:54:39,160 --> 00:54:41,920
Speaker 1: He said specifically, here's another quote from that article. We

959
00:54:42,040 --> 00:54:44,680
Speaker 1: invested in a lot of high profile flame outs. The

960
00:54:44,760 --> 00:54:46,920
Speaker 1: only good thing is we had lots of company. It

961
00:54:47,000 --> 00:54:48,759
Speaker 1: didn't take us off our mission, but it was a

962
00:54:48,840 --> 00:54:51,320
Speaker 1: waste of capital. So in other words, you know, a

963
00:54:51,400 --> 00:54:54,879
Speaker 1: company that already has not turned a profit has lost

964
00:54:55,000 --> 00:54:57,239
Speaker 1: more money in bad investments. This would not be the

965
00:54:57,360 --> 00:55:00,560
Speaker 1: only time this happens. To get some other utments coming

966
00:55:00,640 --> 00:55:04,320
Speaker 1: up in our next episode. Yeah, but I mean, I mean, meanwhile,

967
00:55:04,360 --> 00:55:06,120
Speaker 1: they I mean, a lot of stuff happened for Amazon

968
00:55:06,200 --> 00:55:09,920
Speaker 1: in two thousand. They launched Amazon France, Amazon Japan, UM,

969
00:55:10,520 --> 00:55:14,520
Speaker 1: and Uh, they launched Marketplace, which would would eventually replace

970
00:55:14,680 --> 00:55:17,320
Speaker 1: z shops. At this point they were two separate entities.

971
00:55:18,120 --> 00:55:21,640
Speaker 1: Um they started selling kitchen goods and also Cameron Photo. Yep,

972
00:55:21,800 --> 00:55:25,720
Speaker 1: so you know, Amazon still diversifying. But but two thousand

973
00:55:25,840 --> 00:55:27,920
Speaker 1: was a tough year. And that was a tough year

974
00:55:27,960 --> 00:55:30,719
Speaker 1: for companies across the web. We saw lots and lots

975
00:55:30,760 --> 00:55:33,440
Speaker 1: of them fold and we even saw big ones like

976
00:55:33,520 --> 00:55:35,879
Speaker 1: Amazon take a hit. And uh, and that's a good

977
00:55:35,880 --> 00:55:38,080
Speaker 1: place for us to wrap up. In our next episode,

978
00:55:38,400 --> 00:55:42,080
Speaker 1: we will talk about how Amazon went from pros possibly

979
00:55:42,120 --> 00:55:44,040
Speaker 1: the lowest point of the company as far as the

980
00:55:44,120 --> 00:55:47,880
Speaker 1: market value is concerned to really turning it around and

981
00:55:48,000 --> 00:55:52,960
Speaker 1: becoming you know, a juggernaut again in industry, and and

982
00:55:53,080 --> 00:55:56,440
Speaker 1: again that's another way of pointing out that there is

983
00:55:56,480 --> 00:55:58,600
Speaker 1: no such thing as being too big to fail. And

984
00:55:58,680 --> 00:56:05,960
Speaker 1: also we'll learn more about Bezos's fascination with space, but

985
00:56:06,280 --> 00:56:08,239
Speaker 1: that's that's in our next episode. So guys, if you

986
00:56:08,320 --> 00:56:11,040
Speaker 1: have any requests for things that we should cover in

987
00:56:11,200 --> 00:56:13,759
Speaker 1: future episodes of tech Stuff, I highly recommend you get

988
00:56:13,800 --> 00:56:16,200
Speaker 1: in touch with us. Let us know in an email

989
00:56:16,320 --> 00:56:19,680
Speaker 1: our addresses tex stuff at Discovery dot com, or drop

990
00:56:19,760 --> 00:56:22,279
Speaker 1: us a line on Facebook for Twitter or handle up

991
00:56:22,360 --> 00:56:26,239
Speaker 1: both those locations. Is text Stuff H. S. W and

992
00:56:26,360 --> 00:56:28,760
Speaker 1: Lauren and I will talk to you again about Amazon

993
00:56:28,840 --> 00:56:32,520
Speaker 1: as it turns out really soon. For more on this

994
00:56:32,719 --> 00:56:35,200
Speaker 1: and thousands of other topics, is it how stuff works

995
00:56:35,239 --> 00:56:35,640
Speaker 1: dot com