Data 1.0 to 4.0
Data and the way we use it has been evolving since the early days of the digital age. However, for most, that evolution has been slow, painfully slow. A recent article about Coinbase and its attempt to take the use of data to the next level illustrates, in some ways unintentionally, just how far we have to go. First, some background.
Data 1.0 is really just manually gathering data, processing and figuring out how to react to it. Think of it as customer surveys or going into your production records and manually entering that into spreadsheets so you can see it all and start to get some insight off that. If that sounds cumbersome – it is. Unfortunately, that is also where many companies are stuck these days. Perhaps the methods of gathering the data have gotten more sophisticated but it is still collecting a bunch of lagging data trying to plan the future off what was going on in the past.
Data 2.0 is more about using data and more advanced technology to automate a few basic functions, freeing people up to do more creative things. The processing of the data is faster but it is still lagging, leaving businesses to make their best guess about what the future will look like. Thanks to the improved processes, the guess is better, often good but it still is falling short of the potential that sound data management offers to any organization.
The article in question posits that Coinbase is leading the way to Data 3.0. Coinbase is a company that deals in the buying and selling of cryptocurrency. As such, it deals extensively with financial matters, the various crypto products they offer, and technology in the form not just of the software to allow customers to buy and sell crypto but of the blockchain technology that many cryptocurrencies make use of to ensure their ownership is secure and verified. Dealing with all of the different aspects of their business makes it imperative for Coinbase and any company operating in the digital world to improve their automation and decentralize their data so that everyone in the company can easily access it in order to streamline their operations. That’s what Data 3.0 is, it’s getting data out of the siloes we like to put it in and learning how to integrate it with multiple operations which helps keep the whole company on track. It also makes it much more flexible, nimble, better able to deal with the rapidly shifting digital environment.
However great Data 3.0 might sound, it is still dealing with the same information that Data 1.0 makes use of. In short, at the end of the day, Data 3.0 is still just a sophisticated 1.0. Yet, this constantly being in a rut despite the rapidly changing and improving technology available is only part of the story. We have to account for human nature as well. The fact is, we like to hear what we like to hear and people will often take the easy way out, manipulating data to get the information they think their bosses are looking for. That means leaders wind up making bad decisions based on worse data. This of course is a temptation at any level of data usage. However, it is even worse in today’s hypercompetitive environment. The constant pressure actually leads to shortcuts when in truth, having reliable data is more important than ever.
What is the solution? The solution is Data 4.0. With Data 4.0 you go straight to the source. You get your information not from algorithms, not by extrapolating from data skimmed off electronic interactions, but from actual people. This data is as close to real time as possible and is so specific that it becomes harder to manipulate. And who would want to? The whole point of going to the individual is to avoid all the middle men and the filters that can skew data in the first place. That is exactly what TARTLE hopes to do, create a Data 4.0 environment that will provide quality reliable data to help people make good decisions of genuine benefit to all.
What’s your data worth?
Data and the way we use it has been evolving since the early days of the digital age. However, for most, that evolution has been slow, painfully slow. A recent article about Coinbase and its attempt to take the use of data to the next level illustrates, in some ways unintentionally, just how far we have to go. First, some background.
Speaker 1 (00:07):
Welcome to TARTLE Cast with your hosts, Alexander McCaig and Jason Rigby, where humanity steps into the future and source data defines the path.
Alexander McCaig (00:25):
Okay. Data is a gold mine for a company.
Jason Rigby (00:29):
Alexander McCaig.
Alexander McCaig (00:30):
Obvious, Jason Rigby. Obvious. Thank you, Michael Li, Contributor to TechCrunch. Obvious.
Jason Rigby (00:41):
TechCrunch, when I think of it, I always think of like... Well, what's the really bad cereal for you, that was just jacked with high fructose?
Alexander McCaig (00:46):
Cap'n Crunch.
Jason Rigby (00:48):
Cap'n Crunch. Yeah.
Alexander McCaig (00:48):
Oh yeah, that stuff's great.
Jason Rigby (00:49):
I always think of Cap'n Crunch when I was a kid. I wonder how much sugar I was eating as a child.
Alexander McCaig (00:54):
Too much. I'll tell you right now, too much.
Jason Rigby (00:57):
Well, I know. It was just all... We had back in '70s-
Alexander McCaig (01:00):
I was probably pre diabetic for 15 years.
Jason Rigby (01:02):
We had to have been.
Alexander McCaig (01:03):
I do not even doubt that.
Jason Rigby (01:05):
I mean, were you raised the same way where it was just candy-
Alexander McCaig (01:08):
Whatever. I'd eat whatever I want.
Jason Rigby (01:10):
And cereal and peanut butter and jelly.
Alexander McCaig (01:11):
I ate whatever the hell I wanted.
Jason Rigby (01:12):
Yeah. It's just crazy. I mean, just the-
Alexander McCaig (01:15):
I was a total porker, dude.
Jason Rigby (01:17):
Because the peanut butter and the jelly-
Alexander McCaig (01:18):
You'd throw a donut in front of me, I'll eat all 10.
Jason Rigby (01:19):
Yeah, yeah, yeah. Same here. The peanut butter and the jelly-
Alexander McCaig (01:22):
Yeah. I know you're going to... You're good. You don't have to say it.
Jason Rigby (01:23):
The peanut butter and the jelly, I'm a glutton is what I am. I cannot-
Alexander McCaig (01:31):
That's a more gentle word.
Jason Rigby (01:32):
Yeah. [crosstalk 00:01:33]. I cannot, you put donuts right now in front of me, bro, I will eat them. You know that.
Alexander McCaig (01:38):
I know. I guess, you're the one that gets like the little crack candy on top of the food stuff.
Jason Rigby (01:41):
Oh yeah. It's the best. Shout out to Michael Thomas Coffee.
Alexander McCaig (01:45):
Yeah.
Jason Rigby (01:46):
Great coffee and they have cool... I think they get their donuts [crosstalk 00:01:50].
Alexander McCaig (01:49):
They get it from a Rebel Donuts. Also shout out to them.
Jason Rigby (01:52):
Oh, okay. Cool. [crosstalk 00:01:53]. That's cool. So data is a gold mine for a company.
Alexander McCaig (01:56):
If-
Jason Rigby (01:59):
If managed well.
Alexander McCaig (01:59):
Here's the operative thing, if managed well. So there's a couple... I think if respected properly is a better way to coin that. So data is a gold mine for our company. If you think about it, so the company is the only person out there that can reap the benefit. Why can't people work with their own data and mine their own value and you can share in that value with them?
Jason Rigby (02:27):
Why do we have to assume that that's our data that our customers have created for you as a company?
Alexander McCaig (02:35):
Yeah. In addition to an important tool to hold everyone accountable. Okay. What do you mean? What are you saying, data's holding everyone accountable? What's this guy, if data is managed well, it holds everybody accountable.
Jason Rigby (02:50):
Well, in our last episode, we talked about it.
Alexander McCaig (02:52):
No. I just want to make this clear. Data doesn't hold people accountable. People hold people accountable. Data doesn't care. It doesn't talk. It doesn't do any of these things. It's data. It's a record. And if you want to use that record and say, you're accountable for this record, that's a human-human interaction.
Jason Rigby (03:10):
But you know, as well as I do, when you try to take data and then hold people accountable with it, we talked about this last time, it depends on the bias. So let's say the CTO is trying to take out the CIO. So now he gets his scientist to get all this bias data and then turns around and brings it to the board and then throws this guy under the table. And the CEO is going off of a hunch and says, great job. Good reports. Loved the PowerPoint. Get the fuck out.
Alexander McCaig (03:38):
Yes, fire that guy. Get out of here.
Jason Rigby (03:40):
In fact, you, you did great.
Alexander McCaig (03:44):
Anyone associated with the guy, you're all fired today.
Jason Rigby (03:47):
They held nobody accountable.
Alexander McCaig (03:49):
No.
Jason Rigby (03:49):
It's just another tool in the shed. It's just another ax to chop somebody's head off.
Alexander McCaig (03:54):
That's what it sounds like.
Jason Rigby (03:56):
That's what data is. Data is being used to support biases now.
Alexander McCaig (03:58):
It is. But you want to know why? Because no one's looking at the provenance of the data. People still don't want to associate data to a type of ledger where people can say, oh, this actually happened here at this time, this was recorded. Anybody can throw together a PowerPoint and be like, look at all the data. It looks fantastic. Look at my spreadsheet. [inaudible 00:04:15]. But really, you're blind. In the rain, you've been hit in your face 30 times and you're [inaudible 00:04:22]. You're just lucky you made it out of there alive.
Jason Rigby (04:23):
Yeah. It's very, very simple to manipulate data. It's like, I could-
Alexander McCaig (04:29):
How simple is it to manipulate people?
Jason Rigby (04:31):
Oh yeah. Same.
Alexander McCaig (04:32):
Come on.
Jason Rigby (04:32):
Yeah.
Alexander McCaig (04:33):
So if you're going to be looking at the data and someone does an analysis, it'd be great if you had something that says, here's the provenance of what the data actually is. Can we test your model to verify that the data 1 in there is actually legit? That's interesting.
Jason Rigby (04:48):
Too legit to quit.
Alexander McCaig (04:49):
Too legit to quit.
Jason Rigby (04:51):
That was MC Hammer.
Alexander McCaig (04:52):
Yeah.
Jason Rigby (04:52):
So data 1.0, and he said most companies are stuck in data 1.0, which means they are leveraging data as a manual and reactive service.
Alexander McCaig (05:02):
Everybody's reactive. I don't want one... If this article says that data 2.0 automation-
Jason Rigby (05:09):
3.0. He's into 3.0.
Alexander McCaig (05:12):
This person completely jumped over the whole thing of reactive. Data 1.0, 2.0 and 3.0, all these things are reactive. Every single one of these things in here.
Jason Rigby (05:21):
Yeah. And he said some have started moving towards data 2.0, which employs simple automation to improve team productivity.
Alexander McCaig (05:27):
Right.
Jason Rigby (05:27):
The complexity of crypto data, well, let's not get into that. I want to stop right here. So manual reactive is 1.0. 2.0 is automation to improve productivity. We'll take the team part out. Let's just say in an organization.
Alexander McCaig (05:41):
Is this industry standard what this guy's talking about? Did he come up with data 1. 2... Why can't you say data 1, data 2?
Jason Rigby (05:49):
Yeah. Yeah.
Alexander McCaig (05:49):
Data 3.
Jason Rigby (05:50):
Yeah. I don't know. Yeah. But when we look at data 1.0, manual and reactive, the manual side of things I think is really important because when you look at a company and they turn around and for instance, I can give you a prime example with TARTLE, I could say, okay, we ran ads to everybody in the world. To everyone.
Alexander McCaig (06:12):
That's what we do.
Jason Rigby (06:12):
Okay. Yeah, we totally do. And we spend tons of money. As the CEO, I could turn around and show you a PowerPoint of the data from just 25 to 34 year old moms. Because that data set looks the best for me.
Alexander McCaig (06:28):
It looks so good. [crosstalk 00:06:30] else.
Jason Rigby (06:30):
Even though you have no proof of everybody else, the 65 and older where the click-through rate is like through the roof. And cost is crazy because no one wants the product like-
Alexander McCaig (06:42):
Yeah, but look how low the cost is with this one group.
Jason Rigby (06:44):
Yeah, exactly. That's what they're doing. This is the manual part of extracting information out of data to make themselves look good because it's legal.
Alexander McCaig (06:54):
What is not working? That's what I want to know. I don't really care about what's working. What's not working well for us?
Jason Rigby (07:00):
Yes, exactly.
Alexander McCaig (07:00):
Let's focus on that. I don't want to keep hyper-focusing on one tiny little thing that's going well. I want to figure out what else in the whole process of our workflows and analysis, what is not working?
Jason Rigby (07:10):
And then when you look at the reactive, reactive service, he says, the reactive part, I think to me is because we're looking at trailing data.
Alexander McCaig (07:20):
All the time. There's no leading indicators for this. You want to know why, because you don't know what people are going to do because you're not actually talking to them. You're watching them. And then assuming they're going to do something else and you say, look at our highfalutin algorithm. We know exactly what they're going to do next.
Jason Rigby (07:33):
They're our best guests.
Alexander McCaig (07:34):
Nice best guess. Yeah. I'm going to win the lottery. [crosstalk 00:07:38]. Let me buy a lottery ticket right now.
Jason Rigby (07:40):
Yeah. The complexity of crypto data has opened up new opportunities in data, namely, to move to the new frontier of data 3.0, where you can scale value creation through systematic intelligence and automation. This is our journey to data 3.0.
Alexander McCaig (07:52):
What the hell does that even mean?
Jason Rigby (07:53):
So I think what he's talking about, here's how I am interpreting this.
Alexander McCaig (07:58):
You have to interpret it because it lacks clarity.
Jason Rigby (08:00):
Yeah, exactly. 3.0 data to me is, okay, if you take blockchain and you had mentioned that earlier, you have timestamps. Okay.
Alexander McCaig (08:06):
Timestamping. You and I talked about the [crosstalk 00:08:06] timestamps.
Jason Rigby (08:09):
Yeah. Yeah. So we have that. And then in turn, we have this ability... When he's talking about scaling to create value creation, when you take data and you scale it out, now you're... So maybe I'm creating all these data points.
Alexander McCaig (08:24):
Sure.
Jason Rigby (08:25):
And when we do that, as the user base grows, we're getting more and more data, more and more data packets. It's a marketplace.
Alexander McCaig (08:31):
It's insane.
Jason Rigby (08:32):
So as we scale, it creates more value to the buyer of data.
Alexander McCaig (08:39):
Yeah, because they can do more correlations.
Jason Rigby (08:41):
And then the seller gets more value.
Alexander McCaig (08:44):
Yeah, because they get paid more.
Jason Rigby (08:45):
Because they get paid more. Right.
Alexander McCaig (08:46):
And then the not-for-profits get more value because people can get more donations towards causes on the big seven.
Jason Rigby (08:52):
Right.
Alexander McCaig (08:53):
Does anything about that whole cycle suck? No.
Jason Rigby (08:56):
No, but you have to look at it in corporate 3.0.
Alexander McCaig (09:01):
I don't give a shit about corporate 3.0. Whatever Michael Li wrote here is completely unclear. And frankly, I think it's absurd. TechCrunch, don't ever let an article like this go out.
Jason Rigby (09:15):
He talks about Coinbase, which is a crypto company, which this is where I'm excited about cryptocurrencies in general. Whether it's the funny one, the Dogecoin with the little dog or whether it's Bitcoin, which we're at 60,000-
Alexander McCaig (09:29):
Yeah, 61,000.
Jason Rigby (09:30):
... which a lot of people think will be going to a million.
Alexander McCaig (09:31):
Who cares?
Jason Rigby (09:33):
Yeah. But it's the whole idea of taking a system and decentralizing it to the point of, and we talked about this last episode, but not even gatekeepers, there's no control. So now you're having a financial system and governments are going to catch onto this. They already are, our SEC guy.
Alexander McCaig (09:57):
They're trying.
Jason Rigby (09:57):
The new one, we did a whole-
Alexander McCaig (09:59):
Yeah. I don't even... He's so unimportant to me.
Jason Rigby (10:02):
He's in expert in cryptocurrency.
Alexander McCaig (10:02):
I've already forgotten his name.
Jason Rigby (10:03):
But it's going to take 10 years before they reign in Bitcoin.
Alexander McCaig (10:06):
Not even. It's growing, it's too fast.
Jason Rigby (10:08):
Yeah.
Alexander McCaig (10:10):
Unless someone says, we're banning it all together for use. It's illegal. We're coming in to arrest you.
Jason Rigby (10:13):
Yeah. I was listening a top cryptocurrency guy the other day. And he's like, "We've been working with cryptocurrency for the past 10, 15 years or longer." He goes, "Now we have all these, like high-end people coming in, these billionaires." And he goes, "these hedge fund managers. And then we're also getting like professors of finance and stuff like that. And they just want to pop in. We've been having discussions for 10, 15 years. We've been watching this grow, believing in this." And then he goes, "The reason we're so rude to them because people were like, 'Why are you rude to this top professor from Stanford?'"
Alexander McCaig (10:46):
I don't care.
Jason Rigby (10:47):
"You're coming in and you got excited because it's at 60 grand."
Alexander McCaig (10:52):
Now you want to talk about it.
Jason Rigby (10:53):
And then in one month, you want to make yourself the expert."
Alexander McCaig (10:55):
Yeah. Now that everybody has adopted and accepted it, now you want to talk about something you accepted. Why don't you talk about something against the grain? Okay. Grow a spine.
Jason Rigby (11:06):
So the crypto family is using the power [crosstalk 00:11:10]. No, they're using the power of memes.
Alexander McCaig (11:11):
I'm amped up.
Jason Rigby (11:12):
So they [crosstalk 00:11:14], which we know, Qanon and all that stuff, the far right, use the power memes. Memes are extremely powerful in the way people communicate and they go viral and all that. And super important. So now they're taking these people, these arrogant assholes and they're making memes on them.
Alexander McCaig (11:32):
Unbelievable.
Jason Rigby (11:32):
And then they're going viral. So here's the problem. It's like, then these people get their feelings hurt in their own Twitter. Like, "I can't believe this community shun me like this."
Alexander McCaig (11:41):
Here we go.
Jason Rigby (11:43):
"These people need to be canceled."
Alexander McCaig (11:46):
You know what's cool about a meme? It's decentralized.
Jason Rigby (11:50):
Yes, exactly.
Alexander McCaig (11:54):
Send it. You ever seen that video of the guy who says, "I'm still going to send it?"
Jason Rigby (11:54):
Dude, I was thinking about this when I was listening to this. I was like, I cannot wait till we get a ton of memes for TARTLE.
Alexander McCaig (12:00):
I would love TARTLE memes.
Jason Rigby (12:01):
It would be the funniest thing ever.
Alexander McCaig (12:02):
We need some creativity here, people to pump it up.
Jason Rigby (12:02):
Yeah.
Alexander McCaig (12:05):
We can't be the only ones trying to be creative.
Jason Rigby (12:08):
No, I think it's awesome.
Alexander McCaig (12:10):
All right. Let's get rid of this article here. So he says, Coinbase is neither a finance company, nor a tech company, is a crypto company. What are you talking about? It is a finance company. It is a tech company. It is a crypto company. The distinction is how they work with data and they do that through three types, blockchain, product and financial. I don't know, what's then-
Jason Rigby (12:31):
Well, the part I liked in this article was the end.
Alexander McCaig (12:34):
Tell me what you liked.
Jason Rigby (12:35):
Our focus has been on, how we can skill value creation by making the... I can't read this. By making this very data work together, eliminating data silos, which we've talked about, solving issues before they start creating opportunities that wouldn't exist otherwise. I like this focus because he said our focus.
Alexander McCaig (12:56):
Who's the value for?
Jason Rigby (12:56):
This is for Coinbase, but-
Alexander McCaig (12:58):
Oh, only Coinbase's value.
Jason Rigby (12:59):
Yeah.
Alexander McCaig (13:00):
Oh, we're going to mine all this data on our customers.
Jason Rigby (13:04):
Yeah. But this is what I'm talking about. Like TARTLE, wherever you look at it, we talked about the scale value creation ahead of it on that, eliminating data silos. How do we eliminate data silos in TARTLE? It's really, really simple.
Alexander McCaig (13:17):
Yeah. It's really, the power back to the people.
Jason Rigby (13:19):
Yeah. And having people that are anonymous.
Alexander McCaig (13:23):
That's great.
Jason Rigby (13:23):
And then you don't have that ability to... Because if you're an organization, you want to come in and purchase data from TARTLE, you're going to incentivize them. And they know that they're anonymous. So now you've given them the motivation to be truthful.
Alexander McCaig (13:39):
Do you know what? I like to use this metaphor, trolls.
Jason Rigby (13:43):
Yes.
Alexander McCaig (13:43):
On YouTube comments, you don't know who they are.
Jason Rigby (13:46):
No.
Alexander McCaig (13:47):
And they know that. So they're going to say whatever.
Jason Rigby (13:49):
That's what they love to do.
Alexander McCaig (13:50):
They're going to say whatever they want. So imagine if you get someone anonymous telling you how they really feel, and you paid them to tell you how they really feel. Think about that. Wow. That's some gritty stuff we're learning right now.
Jason Rigby (14:02):
Well, it's like, I was at an Airbnb and it was okay. It wasn't great. They kind of catfished me with the pictures.
Alexander McCaig (14:08):
They do that all... There's a new thing [inaudible 00:14:10].
Jason Rigby (14:12):
And then the lady's like all worried at the end about ratings. But here's Airbnb, their flaw. If I don't give a good rating, then I'm going to get a bad rating from them too. So then if I go get another Airbnb, then they're going to see the last Airbnb that I got. They're going to say, he left dishes in the sink. He did this. Or he did this. I had a friend that had that happen to him. He was honest through the rating.
Alexander McCaig (14:41):
Like, this dude [crosstalk 00:14:43] my Uber.
Jason Rigby (14:43):
So now what Airbnb has created is everybody's just given five star reviews for everything.
Alexander McCaig (14:49):
So, what's the value?
Jason Rigby (14:51):
So now let's look at it. So we've created data issues. We've created data silos. We haven't solved the issue because now the next person's going to go and purchase that Airbnb thinking it's five star.
Alexander McCaig (15:01):
And they're going to be catfished.
Jason Rigby (15:02):
They're going to be disappointed, but the system has created its way where you have to put the five star out there, even though you don't want to, which they know that. I mean, Airbnb knows this process. They're just needing more fees.
Alexander McCaig (15:17):
Their fees are insane.
Jason Rigby (15:20):
Yeah. It's like, here's $100 a night for this, but by the time you add it up, it's like 200-something dollars a night.
Alexander McCaig (15:25):
Thank you for eviscerating me. Yeah. I'm trying to pull my organs back in my body because you've taken all my [crosstalk 00:15:31].
Jason Rigby (15:30):
But where is the decentralization of that? And where is the value creation in that?
Alexander McCaig (15:37):
There is no value creation.
Jason Rigby (15:38):
Who is there creating-
Alexander McCaig (15:39):
There was value back in the day.
Jason Rigby (15:40):
It's creating value for Airbnb.
Alexander McCaig (15:40):
Back in the day, there was value for the people.
Jason Rigby (15:44):
Right.
Alexander McCaig (15:45):
Airbnb, it all started with people, literally blowing up mattresses at their house.
Jason Rigby (15:49):
Yes.
Alexander McCaig (15:50):
And say, come stay on my air mattress. That's all it was. It left the value of the person and then turned over, what's the value to Airbnb?
Jason Rigby (16:00):
Well, it's the same here at TARTLE if we begin to look at different countries and assign different value to people. I mean, think about it. Think about that.
Alexander McCaig (16:13):
I am thinking about it. Nice.
Jason Rigby (16:17):
It's the same, exact. We're creating data silos.
Alexander McCaig (16:19):
How many times do you and I have to say, there is no human being that is worth more than another human being.
Jason Rigby (16:28):
100%.
Alexander McCaig (16:30):
We cannot reiterate that enough.
Jason Rigby (16:33):
But Airbnb, this is why I want to get back to Airbnb because this is really important. Their value creation is for them.
Alexander McCaig (16:40):
I know.
Jason Rigby (16:40):
So they're saying, we don't care about the people. What we care about is making sure that we have an exchange-
Alexander McCaig (16:47):
More listings.
Jason Rigby (16:48):
... that we have an exchange on their marketplace, and we need that fee. And so the more exchanges that we get, the more money we're going to make, and it just brings profit. And so, however we have to do this... Because that's a slippery slope that a company goes down. The minute that it begins to value profit over people is the minute you have a problem.
Alexander McCaig (17:13):
That's a huge issue. Think about TARTLE. We are looking at the value of human life. And once you value a person, you gain their trust and they want to share that with others because we're not here to abuse them. We're not here to look at them as some sort of labor statistic or just how much money we can milk from them. That's not what it's about. We want to look at you as a human. We want to give you all the power to be you, do what you can, uplift yourself, empower yourself. And we're here to join you on that rise.
Jason Rigby (17:45):
Well, everything's so transparent with TARTLE too.
Alexander McCaig (17:47):
Yeah.
Jason Rigby (17:48):
I mean the buyer, the seller, the exchange fee between the two, it's all there. It's not like Airbnb are Delta Airlines or Southwest where-
Alexander McCaig (17:56):
How do I calculate this? I can't use this points on here and then it's like [inaudible 00:18:00].
Jason Rigby (17:59):
Or when you go to Vegas and the room's $59, but by the time-
Alexander McCaig (18:03):
I love that. "Oh, we comped you. It's 59 bucks." By the time you're done-
Jason Rigby (18:07):
300 a night because you got the city taxes, the state taxes, the entertainment taxes. There's one hotel, it took me three months, I forgot what hotel it was, but they were charging me monthly. Like, I was part of their program and knew nothing of this. So I'm thinking, okay, they charge me, it was like three bucks a month or whatever. And most people will be like, oh, okay, whatever hotel it is, da-da-da, casino.
Alexander McCaig (18:35):
Why?
Jason Rigby (18:35):
2.09 a month. But if you think about it, if they're having millions of people who will all be there-
Alexander McCaig (18:40):
And they keep coming in, they're all collecting $3.
Jason Rigby (18:42):
It's Costco.
Alexander McCaig (18:43):
Be like, "Oh, do you want to sign up for this and we can comp..." Yeah, it's Costco.
Jason Rigby (18:46):
So let's end this. I want to make sure that we understand what should be the focus. We'll go data 4.0. Let's just go with this guy.
Alexander McCaig (18:52):
With data 4.0.
Jason Rigby (18:52):
Yeah. TARTLE's data 4.0.
Alexander McCaig (18:55):
Yeah. Would be the infinity.
Jason Rigby (18:57):
What should be the focus for a company when they're looking at their data and humanity?
Alexander McCaig (19:04):
If a company is looking at their own data, recognize it's a lagging indicator, understand that you lack balance. If you need to fix that balance, if you want to fix that balance so that you can secure your future as a company and do some good for this world, you need leading indicators.
Jason Rigby (19:22):
Yes.
Alexander McCaig (19:22):
Leading indicators come from people, connecting with them directly. And there's one way you can do that. You can do it on TARTLE and you can know, you can feel good that you ethically sourced the information. You economically uplifted that individual. And you helped push the world further forward to solving a lot of these things that are part of the big seven.
Jason Rigby (19:44):
And you can go on our website and see... By this time our website should be up, our 2.0.
Alexander McCaig (19:50):
Yeah, our 2.0.
Jason Rigby (19:52):
And you'll have the big seven on there, which is really cool.
Alexander McCaig (19:53):
1.0, 2.0, 3.0.
Jason Rigby (19:53):
But number one thing we want you guys to do is subscribe on YouTube. So if you haven't done that yet, go to YouTube, type in TARTLE and subscribe to our channel. We'd love to have you be a part of our community.
Alexander McCaig (20:05):
We're getting a bloom of subscriptions.
Jason Rigby (20:07):
Yes.
Alexander McCaig (20:07):
Our data champions are like, "We need [inaudible 00:20:09]." You know what's awesome is when we get emails back all day long, "Thank you so much. Thank you."
Jason Rigby (20:14):
Yes. Yes.
Alexander McCaig (20:17):
Usually when you're out in public and you have your own interaction, you get a thank you, it's great. These people don't know us, but they're saying thank you. That's amazing.
Jason Rigby (20:25):
Well, it's because this is needed in the world.
Alexander McCaig (20:28):
I Can tell you this though. I don't think we got one sign up from the US and any of them said, thank you. It's everybody else. Something's a little off.
Jason Rigby (20:39):
A little off. Thank you. Wow. Well, let's use that word today, guys, in our day. Maybe we could go for 24 hours where we just tell people, thank you.
Alexander McCaig (20:46):
Thank you.
Jason Rigby (20:46):
I think that would be awesome.
Alexander McCaig (20:47):
Thank you.
Jason Rigby (20:48):
A little bit of gratitude.
Alexander McCaig (20:48):
Thank you.
Speaker 1 (20:48):
Thank you for listening to TARTLE Cast with your hosts, Alexander McCaig and Jason Rigby, where humanity steps into the future and source data defines the path. What's your data worth?
