<img height="1" width="1" style="display:none" src="https://www.facebook.com/tr?id=1324445537888680&amp;ev=PageView&amp;noscript=1">

Podcast: First Party, Third Party, Aggregators and Originators.

NetWise Aug 4, 2021 6:18:36 PM

Listen:

Click to Subscribe on Your Favorite App
!

Show Notes:

Constantly hearing about first party vs. third party data? Do you have to Google it to remember the difference every time? We do too, that's why This week we're back in the weeds talking about these different types of data, how that gets us to the differences between data aggregators and data originators, as well as some of the misunderstandings driving modern discourse around data regulation.

Here's the cheat sheet:

First Party data is data that your company has collected itself.

Second Party data is data you've gotten from another company.

Third Party data is data you've gotten from another source, which collected it from the original source.

That source out there collecting all the data and redistributing it is an aggregator.

Finally, this gets us to what we call data "originators" and this is where the meat of our conversation this week picks up.

Sure, originators might be the one collecting the first party data, but there's another sort of data origination which has to do with data science and basically creating new data by building out the graph connections between data points and trends.

So, where does this fall? It's not really first party data, or third party, its a whole new value add and this is where it gets interesting for the whole world of technology and especially the data-driven marketer. Have a listen if you want to hear us dig in further.

Links:

https://blog.hubspot.com/service/first-party-data

https://www.netwisedata.com/blog/podcast-what-is-the-data-in-data-driven-marketing

https://www.netwisedata.com/blog/podcast-what-is-an-id-graph

More Netwise:

YouTube | Twitter | Facebook | Linkedin | Web I Blog+Newsletter

Transcript:

Adam Kerpelman:

The reality since we started doing this cold intro format is, honestly, that every time I just want it to be like an '80s WWE hype session. I just want to roll into the cold intro like, "You don't know, man. The cream rises to the top."

Brian Jones:

So, you're looking for fireworks and entry songs.

Adam Kerpelman:

Just over the top. Can't smell with the data-driven marketer is cooking.

Brian Jones:

I need to slap my elbows and then put a bunch of [crosstalk 00:00:33].

Adam Kerpelman:

Baby oil? A plethora of baby oil.

Adam Kerpelman:

Hey, this is The Data-Driven Marketer, sponsored by NetWise. I'm Adam.

Brian Jones:

I'm Brian.

Adam Kerpelman:

Welcome back for another hang in the date of basement. Thanks for joining us. How you doing?

Brian Jones:

Doing great. I don't know why, but I'm bringing a lot of energy today to the afternoon.

Adam Kerpelman:

Yeah, it's good. I dig it. What are we talking about?

Brian Jones:

We are talking about business data, but from the lens of a classic conversation and terminology in our space that people struggle with, which is first-party and third-party data.

Adam Kerpelman:

And really, I think it breaks down to like what businesses are doing with their data, like what's actually happening in the space of all the data that's... We've done episodes about what we mean when we say data and how it gets to data-driven marketing, but there's a whole bunch of stuff happening, maybe in the data science department, maybe just by the data science people you have, maybe contractors. Who knows? Maybe just your marketing team. But it collides with this terminology that's increasingly out there, in part, because we have legislation popping up that's trying to deal with it and stuff like that. And as people in the position that you and I are in, I frequently am sitting there going, "Oh no, they don't understand this at all, and they're about to make a law that's going to do a thing."

Adam Kerpelman:

So, I think that's where we're trying to start. What are businesses, not what we mean by the data, but what are businesses doing with data? Right? So, I guess the first place to start in this context specifically is what do we mean by data? Because we did that episode before that was like, isn't the same feed that comes back at you off of ads that you're running and stuff, it's not so much campaign data or behavioral data. This is more like what's this internal [crosstalk 00:02:49]?

Brian Jones:

Yeah. We're just talking to anything. Right? What's being generated.

Adam Kerpelman:

Right.

Brian Jones:

Yeah. That's an important place to start with this. Right? Because I think this is a broader conversation about how to think about data assets and businesses and what's happening with data and how are companies connecting via data? I want to say it's everything that's getting digitized at companies which, I think, is a fair line to draw. Right? If you're not gathering on a computer, it's pretty hard to argue that you're going to be able to do useful data science with it. Right?

Adam Kerpelman:

Right. Well, I was going to say, yeah, it's hard to do the science on. So, if you want to back it up even further, just for fun, before we had it digitized, it was, what, your registry of customers, maybe a registry of potential leads that's coming from wherever it's coming from [inaudible 00:03:44] Jack Lemmon and-

Brian Jones:

Yeah. I guess it was just-

Adam Kerpelman:

... Al Pacino are fighting over them in the back row of the office.

Brian Jones:

It's just information. Right? We took it back. Right? So, it's anything. Right? It's everything about your business. It's where you exist, it's who your employees are, it's what you do all day, it's what your product line is. And all of that is information about your business. You don't even think about it as that. Right? It's just things you know, things your customers know, things you say, things you tell them, behaviors, processes, and what's happening is, as we digitize these things, all of that stuff gets quantifiable. Right? And so, all of a sudden it moves from just being a fact in the world to being like a set of related facts that are in a system that you can now analyze or look for a trend in, and now it becomes data. And everything about business is being digitized because it makes us more efficient in a lot of ways. Sometimes it makes us less efficient.

Brian Jones:

So, businesses are using all kinds of software to manage all the departments and to execute on all their processes and to manage their content and their media and their product lines and their warehouses and their shipping and their fulfillment. And that's all creating data streams, like massive, massive, insane amounts of data, that if you're not thinking about it right, it just disappears into a computer and it never crosses your desk again. But it's all important because it all reflects what's going on in your business and the business world at large. It's all connected. It's a big graph of what's going on with the world.

Adam Kerpelman:

The thing that I often mention in this context that's interesting is the data was always there in a lot of contexts, we just didn't have the capacity to collect it and make it actionable. So, it's sort of one of those funny things where you're like, "Where is all this data coming from?" It's coming from we suddenly have the capacity to look at every single... The example I kept thinking was like, okay, the way you used to do it is you got reporting from sales and so you understood that your widget was selling a lot in Pennsylvania, but that's probably like all you knew. And you could take guesses at why it was selling in Pennsylvania.

Adam Kerpelman:

And now we literally can go, "Okay, well it's selling more in Lancaster than it is in Bethlehem, and so maybe there's..." Again, you're still just guessing until you find the data point that is the difference, and this is what data scientists are doing, they're finding the correlation and going, "You know what it correlates with, is Amish population." And then you find out that your widget is being used for a thing that you didn't understand that has to do with fixing wagons.

Brian Jones:

I'm very familiar with both those towns. Good train story.

Adam Kerpelman:

So, this is a bridge, though, into the first-party, third-party conversation because this is where we're talking about what types of data you have, and so far, everything we've talked about I think would be classified as first-party data. Right? It's all stuff that is internal to the company, gathered by the company. It's what we know about our customers, it's what we know about our product sales, it's what we're getting back from our team regarding the interplay of all that stuff. What's third-party data?

Brian Jones:

Well, this is where this gets confusing right away for people because third-party data is just that same data but you gave it to someone else to use for something else. Right? So, I come to you and I'm like, "Hey, you sell wagon wheels and I sell wagon axles, can I get your customer list to sell my wagon axles to the people who are buying wagon wheels from you?" Now, all of a sudden, that data... The information's the same, but conceptually, because you've transferred it to me and you've given it to me for my own purposes, as opposed to there's this weird middle zone, second-party data that people talk about, or you don't really hear about it much, but you basically just sold me a list, a marketing list, so that I can sell a product that's complimentary to yours to a list that's really helpful.

Brian Jones:

Now, for me, it's third-party data. I bought it. I didn't aggregate it myself. I probably didn't get those people's permission to use it directly. Right? So, all of a sudden you're seeing like, back in the days of wagons, there was no one up in arms about privacy. Am I selling my wagon wheels and my axles to the right people with the right privacy concerns?

Adam Kerpelman:

Do I care if you tell him that I bought a wagon wheel from you?

Brian Jones:

Right?

Adam Kerpelman:

Right.

Brian Jones:

Nah, man. I'm just trying to move my wheat.

Adam Kerpelman:

So, in this context, third-party data is just someone else's first-party data that they're willing to sell to you, or provide to you in some way.

Brian Jones:

Totally. And that's keeping this really, really simple. Right? Where a company just produces some information and then they give you that exact digital copy of that information.

Adam Kerpelman:

What is second-party data? I'm curious.

Brian Jones:

I always look this up because... I'm reading about it right now because I feel like every time I have this conversation, I have it slightly different.

Adam Kerpelman:

Well, every time I do talk about it, I always think about just narration. Right? First-person and third-person. And then second-person is weird because it's like someone else's voice explaining what they experienced the character doing or something.

Brian Jones:

The story we just told, actually, is second-party data based on at least how [Lotomay 00:09:18] defines it, and they're reasonably established. And the reason this doesn't get talked about is because it doesn't really work this way. Most companies aren't just licensing their customer list to another company directly. That's second-party data, according to this. Right? I'm the originator of the data and I sell it to you and then you use it for something. Third-party is what typically everyone's doing when they think about buying data in the business space. Some intermediary gets the information. Very likely they do something with it. Right? They get a bunch of sources of information and aggregate it, and then you buy it from them and use it.

Adam Kerpelman:

Got it. Okay. So, if I'm getting it directly from the company that collected it, second-party data, third-party data is some other aggregator in the middle, has gone to all the companies and said, "If I buy up all this data, I can resell it, and it'll be helpful for people."

Brian Jones:

Yeah. And the concept of second-party data, I think, is kind of dumb. There's no reason to really talk about it because it's the same data as first-party data, and then you're just buying it from someone. So, it's kind of the same [crosstalk 00:10:24].

Adam Kerpelman:

Just hand it off by a different person. Yeah, totally.

Brian Jones:

Yeah. Everyone's got different definitions for these, but the concept here is that someone originates information. Right? They're the first person to get it. Maybe they're the only person who can get it because, in this case, it's someone's information about their business internally, and then they can use it themselves. So, you can use your own first-party data for all kinds of analytics. That's like a traditional business use case of knowing about your business and making decisions that way. Or you can start to pass that along, whether you're selling that or giving it, whether you're editing it, manipulating it and just giving pieces or if you're just giving it all, whether you sell it to someone who's going to do something with it, or you sell it to someone who's going to aggregate and resell it, all the same in my mind after that. So, you essentially have data you gathered and then other data.

Adam Kerpelman:

Right. Well, so then that gets us to the next piece that I think always comes up when we're talking to people about this, which is the aggregator versus originator conversation. We mentioned the aggregators. Right? That's the company that's out there pooling together all this stuff and selling it third-party to whoever else, but that doesn't really cover the whole landscape of what's happening, and this is the space where the misunderstanding exists that, for example, the legislators are completely missing. Right? If you cut it off at just saying, "Okay, well it's third-party and anyone who's collecting third-party data is an aggregator," then it's cutting out this whole swath of data science and it gets to the ID graphs episode that we talked about. That's not really what's happening. There's a whole bunch of other stuff happening that is actually value add behavior that is why you want to work with these, ultimately, what we would call third-parties, but they're not necessarily just aggregators. Right? And it's the thing we deal with a lot because at NetWise, we think of ourselves as an originator, not an aggregator. And when somebody just says, "Oh, so you're just a data broker," it's like, well, not really because we're doing a lot of other things to [crosstalk 00:12:29].

Brian Jones:

Not at all. Get out of here, man.

Adam Kerpelman:

Yeah.

Brian Jones:

Get out of here, man. Get out of my face. This is an important conversation because technologically and philosophically, there almost is no such thing as just a pure data aggregator. It doesn't make sense. You have to do something to the information. You're merging it, you're blending it, it's additive or it's subtractive. Unless you're literally just like, "I'm buying a list of names from a company, and then I go resell that exact same name of companies," you did something in there. And that kind of is traditional. Right? I think a lot of people, when they think business data, they're just like white pages. Right? Which is not a horrible abstraction, but pretty simplistic given what's actually going on in the world now with information.

Brian Jones:

The concept of someone just buying some data and then reselling it, that totally exists, and what's interesting is that business model actually sucks, so you can't make very much money there. So, those companies tend to be shady. So, you don't want to buy data from someone who's just buying and reselling it right away. That's sketchy. They can't make any margin on it because they're not adding any value. So, capitalistically, their incentive to be shady is really high. So, you want to work with companies that are doing sophisticated things. You want them value adding to a product. I'm reminded of working, in my previous company in manufacturing supply chain, there's a lot of similarities with how manufacturers work. Right? They're companies that literally just resell what you manufacturer. You outsource your Salesforce to these intermediaries who cover different parts of the country, and they literally are just reselling the exact part. Right? I manufacturer a tire, then my like partner companies go out and sell those tires.

Brian Jones:

But then you also have these value-added resellers, which is a specific term in manufacturing, and they specifically will customize the tires. They'll bling them out or they'll change the treads on them, or they'll add things to them or they'll package them up and sell them as sets or for different types of vehicles or serve as different markets. And so, in data with computers, they're... And even in that manufacturing example, there just aren't very many companies that don't do something else. Right? Because it doesn't make sense. You've got this interesting middleman position where your business gets to be something different. The manufacturing part was already taken care of. Right? The data was already created. What do you want to do to it now to make your business more successful, make your products more valuable?

Brian Jones:

So, you pretty much always end up with people doing something now with the information, even the first-party giving it to other people. I don't just open my database as a business that's selling information. I'm not just going to give you all my accounting information like my finances for the last 12 years, I'm going to slice it up, I'm going to analyze it and give you something... I'm going to sell something that's not proprietary to me or not extra things that you don't need. And the subtlety here and the granularity that you get into when it's data, when it's information sitting in a computer, is like infinite. Right? So, slice and dice it an infinite number of ways. There's so much subtlety to it.

Adam Kerpelman:

Yeah. And it ends up being a misunderstanding like on the level of saying that a steel company doesn't provide any extra value because all they do is take iron ore and nickel and chromium and whatever and combine it into steel as an alloy. It'd be like the legislators going, "Yeah, but you're just mashing together a bunch of other metals so you're just in the metal masher. Actually, that's kind of shady, and we think people should know where their metals come from, so we're not going to let you build skyscrapers with your steel."

Brian Jones:

Right. Right. Well, you're hitting on an interesting thing here. Right? As we've moved from the physical world to the digital world, people don't recognize a lot of the stuff that's happening in the physical world. Right? If all I do is resell your iron ingots that you've pulled out of the ground, I'm still shipping them, I'm still moving them, I'm still communicating with people about them, I'm still making marketing material about them, I'm still a business transacting, I'm still making financial transactions. There's a tremendous amount of process around everything. In the digital world, you have to face all that because you have to engineer software that does it. It's not a person anymore like driving a truck full of metal somewhere, where you can just abstract it out of your mind. In a computer world, an engineer has to write a line of code for literally every single tiny little piece of interaction. So, you see this stuff in a very different way where you end up breaking it down.

Brian Jones:

And so, from the technical side of data, it's super frustrating for me being on the technical side, because whenever we're looking at compliance and regulations and people are asking questions like first, second, third-party data, sources, et cetera, it's super specific to their. Right? What are you trying to figure out? What are you trying to plan for? How do you look at this industry? How do you want to use this information? And then it's not an opaqueness that I'm trying to present, but it's a transparency. It's complicated. Right? Whether or not your information is first, second, third-party and how it applies to different conversations is just wildly different in every conversation.

Adam Kerpelman:

Well, and I think the easiest way I think of to look at it, and this is where I should just post the link to the ID graph episode that we did, because we cover a lot of this stuff, but the essence of data science, in a sense... I mean, sure, there's the testing and the correlations and the matching and the whatever, but ultimately what you're creating as you do data science is new data that's about how the data points relate inside of your dataset. If you say you've got A and you've got C and B is how they're linked, and B I observed by doing science and I added that to the dataset, well, I just made B up out of taking A and C and looking at them.

Adam Kerpelman:

And so, that's why we get to the originator versus aggregator thing, because if you look at a company like NetWise, a small percentage of what we're doing is scooping up the stuff that we need to scoop up. Most of what we're doing is creating completely new data by looking at the relationships between all of those things and people... It's not that people discount it, it's just a weird mental model thing. The idea that you can just... And this is where the steel analogy breaks. Right? Because you can only make as much steel as all of the resources that you bring in. Right? So, if you bring in two tons of iron, two tons of the other thing, and two tons of the other thing, you're not spitting out 20 tons of steel. It's physically impossible. So, everybody, it's easy for you to see how you synthesized all of those materials down into this alloy, so that's where the value is.

Adam Kerpelman:

With data, you still have data point A and you still have data point C that have the value that they always had, but now you added B on top of it and you just fattened that dataset and you went, "Look, I put some work in here so now I'm going to charge you a little extra for this dataset," compared to if you just had A and C. And everybody goes, "Wait a minute, but where did B come from?" It's like, "I just made it up with science."

Brian Jones:

I made it up.

Adam Kerpelman:

It makes sense that it sort of breaks brains in terms of trying to understand what's happening here because it cascades, because then once you have B, you can go, "But then you also have D and F and E is how they relate, and now you're seeing that B relates to E and now you have..." I don't even know what letter to give that one because the sequence breaks when you start to try to connect those to Epsilon something. And it compounds and compounds until you have this blob that's this graph thing we described in the other episode that's just all of this useful data.

Brian Jones:

Yeah. You just told it in a great storyline. Right? And the analogy that I try to use sometimes of bringing those metals in and then making something physical out of them, like bringing a bunch of aluminum and turn it into an aluminum alloy wheel, that doesn't really... It's not a perfect analogy because of what you said. Right? You use up the aluminum in the process. But with information, digital information that's stored on a computer, it's always just additive. You're always just adding things to it. If you give me a bunch of information about a business and then I'm able to look at a market at large and understand its industry and then apply a bunch of categories to those businesses, I've invented something, I've added something, I've created something that's a derivative product of what you gave me. It existed there somewhat inherently, like at a spiritual level in the universe. Right? I needed something underneath of it to come up with it, but no one had done it yet. It hadn't been organized or structured or given a name.

Brian Jones:

And so, now, not only is the original information that was someone else's first-party that maybe someone bought and then resold to you, now you have it as a third-party, but then you did something to it, that new data is something different. It wasn't gathered from somebody, it was created. It was manifested by your data science team. And so, now it's like, it's your first-party data, but it's sitting on top of someone else's data that is third-party data to you. And now it's all mixed up and confusing.

Adam Kerpelman:

And that doesn't even get to the aspect of scale. That is what makes it so mind boggling. Because if you want to double back to our cave painting version of this way back before the digital stuff, yeah, you have your towns in Pennsylvania, well, now you have every town everywhere all at once and you can put all those linkages together. And then all of those linkages have linkages. It cascades into this place where without the computers to help us weed through it, we wouldn't even be... It just would take lifetimes on lifetimes to even go through the lists of data. But now that the computers can do it, we can go, "Oh, here's a trend here."

Brian Jones:

And that's where we reach the modern marketing where modern marketers are relevant. Right? I'm sure people didn't like yellow pages and white pages and stuff back in the day when you were in a phone book, and their business model was very similar. I think you had to call the yellow pages and pay them to not publish your information, that was part of their business model. But the scale of data collection now is such, and the ability to execute technological concepts and execute, in our case, marketing across the digital ecosystem so effectively, people just, they feel what's going on. Right? Very few people have any clue how ads work in the digital space, like why they see ads on their phone or on the internet or inside an app they're using, but they can feel inherently what's going on. They know. Right?

Brian Jones:

This started happening five or six years ago, is programmatic advertising really took off. People were like, "I was just looking at that shoe the other day on a website and now I see it on the New York Times while I'm reading an article," and they're like, "Stuff's happening. Information's exchanging hands." And now, because marketing touches humans, as opposed to just being pure business analytics, there's an emotional response to it now and so there's this flurry of how do we handle privacy and transparency? And how does the industry come to terms with the regulations? Marketing is just where customers, where people interact with businesses, so that's all we're seeing and there's already a lot to figure out there.

Brian Jones:

There's so much more behind the scenes within businesses and how they communicate with each other and information they share and what's going on and how networks are built and customer pipelines. There's just unfathomable amounts of information being generated right now by businesses and really, truthfully starting to be used and executed on and shared. Right? Data is such a valuable product and such a valuable tool that we're just going to see a continued flood of sharing and technology products and data products and...

Adam Kerpelman:

Well and continued synthesis of new stuff or the capturing of relationships that we previously didn't articulate. And so, it feels, in the end, to me like a long way of just saying, "If you're just thinking about first-party versus third-party data and aggregators, then you're completely missing what's actually happening here."

Brian Jones:

Right. Yeah.

Adam Kerpelman:

And what you're saying about marketing and all that kind of stuff, this is the exciting time to be in marketing because of the stuff that you can do and how it's novel. But I mean, here's a great way to kick it into this back portion and talking specifically about stuff that we deal with, anyone who has used HubSpot or some of these ABM tools knows that you can do things now where I can say, "Okay, well, if I have you in my CRM, I can now make the website say, "Hi, Brian, thanks for coming back." Right? But we also still live in a world where I as a marketer am not sure I want to do that. I'm completely comfortable doing it inside of a dashboard because they logged in, they feel like you should know that it's them, but if I do it on a site where all I know is that they visited four times and they filled out a form, somehow that feels a little creepy. And so, I don't know if I want to do it or not. And that's just the tip of the iceberg in terms of what data I could have to play with to build an interesting experience.

Adam Kerpelman:

So, where does that leave us as marketers and stuff. Right? It's almost like The Imitation Game, or whatever it was. Right? Like the thing where they figured out the code, but then they couldn't use it right away because then the Germans would know that we cracked the cipher and-

Brian Jones:

That's another good analogy.

Adam Kerpelman:

It's the same thing where there's so much we could do that could be so cool for users, and in a not creepy way. If everyone could just get on board with the idea that like, okay, look, everyone knows everything, and let's just treat the whole web more like an app.

Brian Jones:

Right. Well, for marketing in particular, because it's at the center of a lot of these conversations, but for data as a business, data as a business model, as a product line or whatever you want to call it, we need to recognize that this all needs to be understood more broadly by people. If information is being used that's about people or about another business or about another entity, in some capacity it seems fair, it seems reasonable that they should have some say in that. Now, from business sense, if there's a transaction, like when you sign up for newsletter you give your information away and there's terms there. There're reasons why there's a contract on that. And people don't think about that, but you entered into a contract with that business that allows them to use your information in a certain way. So, we just need to make that better and more accessible and more transparent, and then people will ease up to this.

Brian Jones:

If you look at generationally how comfortable everyone is with technology, it's not just the technology that people are comfortable with, but it's like the publicness of living within technology. Right? Kids younger than us... I used to be the hip crowd. I'm old now. I'm like middle generation with social media. Young kids just live in video. Right? I'm not comfortable just producing video all day and putting it online. I just intrinsically feel funny. The hairs on the back of my neck go up. But my nieces and nephews, TikTok. They don't give a shit. It's a mind shift, too. Right?

Brian Jones:

Not only do we need to get more comfortable with this concept, but we need to build out systems that enable people to understand everything better, and that's our job as technologists. Right? People running technology businesses and people specifically, us at NetWise, as a data company, it's really important for us to push this kind of stuff forward. We want regulation. Right? We want there to be transparency in our industry. We want there to be rules and ways that you're allowed to use information and ways that as a society and as businesses we decided you can't use it, because that creates a stable business environment. Right? And it allows companies to innovate and build products that not only make a difference, generate wealth for their employees and their families and their partners and customers, but that society can be comfortable with and happy with and know that it's moving everything in positive directions.

Adam Kerpelman:

That's a good place to tease a series of episodes we'll have upcoming soon with some cool guests to talk about the cookiepocalypse and cookie-less solutions and all that kind of... Those fun buzz terms that anyone in the marketing space has heard lately. But it relates to this. Right? Some of these solutions, part of the problem, the saying, "Well, it's first-party and it's third-party and it's aggregators," doesn't... It's what we've got right now because we cobbled the whole thing together on the fly because we invented this internet thing, and then we invented this web thing, and everybody went, "We can do this with it. What if we do this? Oh, what if we try that?" There's just tons of dead standards in the wake of things that just didn't work, so it completely makes sense that it... When's the last time you used Gopher for anything? Ever? Did you ever use Gopher for anything?

Brian Jones:

I don't even know what Gopher is.

Adam Kerpelman:

Certainly most of our listeners never used Gopher for anything.

Brian Jones:

What is Gopher?

Adam Kerpelman:

It used to be an equivalent like FTP protocol. It was a file transfer protocol between academic institutions and stuff. It died in spite of having a cute mascot and everything. So, it makes sense that we are where we are, but now we're at the point where we're having a conversation about, well, what should the future look like? And that's where all this cookie-less stuff is coming from. And some of it is companies saying, "Look, cookies don't work the way we wanted them to. It's kind of a hack together a way to do the thing that we're doing."

Adam Kerpelman:

And so, as it lands on NetWise, we're working on incorporating open standards to make this data universe not to go away, but then do it in a way that has what you're talking about, that level of transparency. The whole conversation, "Is it first-party? Is it third-party?" only even matters in a world where, like you said, people aren't aware of these structures and how this stuff works. And then they compare it to how it used to be, and it's certainly like 30 years ago, there's none of this.

Brian Jones:

Right. Totally right. We only have those labels in context of the conversation of like, is first-party better than third-party? Is it dangerous? Is it going to get regulated? Is it going to get sketchy? I'm going to tell everyone a secret, everybody's just buying data and using it for their businesses, so some people are doing super shady things, some people are not. Most people are just using information to be more effective at their jobs. And this is not just a plug because we sell data about businesses, but everyone is using information intelligently these days. It's very functional. It's a product like anything else. Right? Lotus 1-2-3 when it launched and it allowed spreadsheets, like open the floodgates for people to start using information. This is the latest iteration of it. They're hugely important conversations to have. There's going to be hugely important, regulation and legislation globally that comes in to effect this, and it's probably going to shake up major industries. But this isn't going to go away. We're not going to shut off the idea of learning about things and sharing the things we've learned. That's ridiculous.

Adam Kerpelman:

Yes. [crosstalk 00:33:47].

Brian Jones:

The tech industry is going to keep existing and keep doing great things. But there are things that is happening right now that may be problematic, and some of those are really obvious and they need to be corrected. So, this is just a cycle. And big data, which I don't think we've used that horrible buzz term this entire conversation, or on any of our [inaudible 00:34:06], I don't think I've ever said big data.

Adam Kerpelman:

I think you're right.

Brian Jones:

Big data is here to stay.

Adam Kerpelman:

For sure.

Brian Jones:

End with a horrible cliche.

Adam Kerpelman:

Yeah. Right. There's two pieces of what you just said. The first one is one that we repeat a lot, which is the idea of shutting it down doesn't work. Right? Because first-party, third-party, blah, blah, blah, whatever, the web runs on this information and digital products. If you want to continue going to a website to look up the menu for the restaurant you're going to go to tonight, this stuff has to exist. They need to be able to serve you that information via a server, which means you got to tell somebody where you are, like literally geographically, what node are you near so I can send the electricity to you-

Brian Jones:

You're not a ghost.

Adam Kerpelman:

... so you can see the things? Right?

Brian Jones:

You have to physically exist in some capacity to do these things. It's very philosophical at this level. Right? Because it does come down at some level, especially when you're talking about information about people, it's how do you feel? Right? Because your example is great. If I go to a store to buy something, no one cares that the person at the store saw me there. No one's ever complained about that. Right? I have to physically be there to buy a suit. Right? You can't say the store can't track me that I was in the store. I was there. I went there to buy the suit. If I go to someone's website and buy a suit, everyone's all up in arms all of a sudden, that they know you were there. Give me a break.

Adam Kerpelman:

And I don't want to break anyone's heart, but the reason that they have customer loyalty cards is not so that they can give you a discount because they're bros, it's so they can know exactly what you bought and connect it to your phone number. So, the last piece, though, I think, it's the thing that you and I talk about a lot personally, and also on our other podcast, is the idea of... You didn't call it knowledge, but it's essentially knowledge and the sharing of knowledge. And there's, again, a funny disconnect where once it's digital and it's trivial for me to send you all of the world's knowledge by saying, "Here's the Wikipedia, look at it," people get weird where when you say...

Adam Kerpelman:

You said it some way earlier that made me say like, "And is that any different from a textbook?" Except the textbook costs way more than it should for the paper and you have to go to school. It's just full of data that you're going to take in and then synthesize ideas from and then do stuff with, and we're like, "Yeah, totally. Of course. Everyone should have access to libraries." That's like, well, what about libraries of data? "No, wait a minute. Hey now."

Brian Jones:

Yeah. Again, it's the digital divide. Right? It's going from like an individual human having to go to a library at a physical location and read a whole book, versus press a button and my computer system all of a sudden has an artificial intelligence that can make better business decisions based on the entire planet's behavior. Huge difference. Right? There's something there. We can't just give these analogies. It's not quite fair to reduce it to like, "I bought a suit at a store." It is really important to draw those similarities, as well. Right? Because it's-

Adam Kerpelman:

Yeah. And so, that's to say-

Brian Jones:

... neat stuff.

Adam Kerpelman:

... that the first-party, third-party debate, it's not, not real, but it's kind of not focusing on the right thing to actually solve for the better world that, certainly, marketers hope for. But I think, also, that all the consumers in the world want, they just don't understand how it works, and so they don't realize that they want it.

Brian Jones:

The summary for a marketer looking at using information, or purchasing data or partnering with a company to share information, is don't work with sketchy groups. If you're going to get information about an industry, about a market, if you're looking for an audience list, like the kind of stuff we provide, look for a company that has invested time and money in trying to be above board and transparent. Right? Who is following industry regulations, who engages with third-parties to audit them, who has tight security, who has language around their websites that talk about this stuff. Because this stuff does matter and it will matter legally and compliance-wise and regulatory-wise for your company, so you want to make smart decisions.

Brian Jones:

But in no way at all do I think you should be limited in the information that you want to go seek out. Right? I think that's a wonderful place in the world right now with technology. There's so much information at our fingertips and not just personally like with Wikipedia. Right? It's in business, too. Right? We get to make our economy more effective and more interesting and more robust and more productive, and information's a huge part of it. So, engage in that, participate in that. Just do your best to be good about it.

Adam Kerpelman:

That feels like as good a place as any to wrap it up. This one felt extra philosophical and meandering but it is what it is. We;'re literally talking about the types of what-

Brian Jones:

I'm standing on a soap box on top of a soap box right now, by the way.

Adam Kerpelman:

Right. But hopefully that, still, it's a helpful overview ultimately of first, second, third-party data, aggregators, originators, all that kind of different stuff, and I hope the structure of the conversation helps people understand where it's going in the future because it's really not... We as data-driven marketers live in this space, we're really like... And I don't just mean me at you. I mean, anyone listening to this also. We can affect our own destiny in this space, and it's important to understand all of these pieces rather than just going, "Well, but the guy making the laws tells me third-party is scary, and so I guess that's the future. Google says they're going to shut off cookies for privacy." That's what we're dealing with, and it's like, it's just not that simple.

Brian Jones:

That's every big industry in history.

Adam Kerpelman:

For sure.

Brian Jones:

Everything's cool.

Adam Kerpelman:

If you enjoyed this conversation, we'll have plenty more coming, so like, subscribe, do the thing, wherever you're listening. This has been the Data-Driven Marketer, sponsored NetWise. I'm Adam.

Brian Jones:

I'm Brian. Stay cool out there, everybody.

Adam Kerpelman:

It is [inaudible 00:40:46].

Brian Jones:

[inaudible 00:40:46].

Adam Kerpelman:

Pop my shirt off [inaudible 00:40:49].

Brian Jones:

[inaudible 00:40:51].