Skip to main content
Breaking Down 1st, 2nd, and 3rd Party Data

Breaking Down 1st, 2nd, and 3rd Party Data

The Sounds Profitable Podcast

Season 2 • Episode 20

Today on the show, Bryan Barletta speaks with Tyler Blot, Director of Client Development at TransUnion about data — 1st and 3rd party data, with a bit of 2nd party data thrown in there. They discuss the differentiating factors between the three of them and what you should know as an advertiser and consumer.

Listen in to learn about:
  • Transparency in data collection
  • How and why your data is collected
  • Why this conversation is important to have right now
  • And much more!

Here’s our favorite idea from this conversation: You have to do your homework. While your industry peers can vouch for a product to a certain extent, you won’t be able to make your decisions until you read the fine print.Links:


Bryan: First, second and third-party data and what it means for you as an advertiser, that's what we're talking about on this week's episode of Sounds Profitable: Adtech Applied, with me, Bryan Barletta.

Arielle: And me, Arielle Nissenblatt. Thanks to this month's sponsor, Claritas. As a third-party provider, Claritas's white glove service offers the science and proven methodology for accurate, transparent, and scalable podcast campaign measurement. Find out more at

Bryan: Special thanks to our sponsors for making Sounds Profitable possible. Check them out by going to and clicking on their logos in the articles.

Arielle: Bryan, hello, how are you?

Bryan: Hi, I'm good. How are you?

Arielle: Feeling very serious today.

Bryan: Oh, because we were talking about the serious, serious nature of data.

Arielle: Yeah, because I found out, unfortunately, that while we're talking about first, second and third-party data, it's not about a party, so I am going in the opposite direction and business in front, business in back.

Bryan: Not a lot of fun at these parties.

Arielle: Business all around.

Bryan: That's just a short haircut. I think that's my haircut business in front, business in back. Oh, no.

Arielle: Business on the side.

Bryan: No, there's a party on the side.

Arielle: Well, there's no party in this episode. There are cookies.

Bryan: Those are just as disappointing and disappearing. Oh, no.

Arielle: So Bryan, today you speak with Tyler Blot who is the Director of Client Development at TransUnion. Tell me how you got connected with Tyler.

Bryan: Yeah. So Tyler and I worked together when he was at LoopMe, the company he was at beforehand, and we had been collaborating on attribution and surveys and all sorts of cool things like that. And he went over to dig more into the data side at TransUnion. And one of Tyler's big passions has been podcasting and audio. So we stayed in touch as he went over there and TransUnion is starting to dig in further into audio. And it was very exciting to be able to catch up with him and understand how we can apply these different data sets and data levels to podcasting or how the changes in them impact podcasting.

Arielle: Let's get to your chat with Tyler. Anything we should know before we dive into this conversation?

Bryan: I think that what we need to think about when we're talking about data and podcasting is remembering that our touch points are IP address and user agent in the episode. From there, we can augment so many different things and we need to start thinking about all of the interesting ways we can augment that data from first, second, or third-party data, from identifying where something is physically located, time of day, everything. All of that is very interesting. That's where we bring the industry forward. But what we also need to keep in mind is that data collection and the ethical use of data is currently being challenged across the world.
So while we are figuring it out for the first time, really expanding out there, a lot of the industry is kind of taking a step back and reassessing. This is a great time for us to be part of the conversation because we have far less touch points and we can go about it in a safer way.
So let's kick off my interview with Tyler Blot, Director of Client Development at TransUnion.
So Tyler, can you explain a little bit about first-party and third-party data?

Tyler Blot: Yeah, absolutely. So I like to look at this based on how the data's actually collected from either the publishers or the organizations, kind of consumers that are interacting with it. First-party data is going to be data that you're actually collecting firsthand. Consumers are interacting with your site directly. Sometimes you're collecting a lot of this during the registration phase. Other times it's behavioral or interest based, all depending upon actions that they're taking on your site or interacting with your content, or what have you.
When you think about third-party data, this tends to be a bit broader. This is data that has likely been modeled out so you get a lot more scale for targeting purposes, but there's also, I would say more of an opacity when it comes to really where that data's coming from, what's in there. Typically, it's coming from a lot of different sources and it's really aggregated in a way.

Bryan: A few things to point out there, right? For first-party data, I think it's easy to assume that it's all about like signing up and filling out a form and giving somebody your information, but it also, like you said, could be behavioral. Someone might go to Sounds Profitable and their IP and user agent combo, or me being able to first-party cookie them, which is still supported, shows that they come to the site on every Wednesday, so the day after my newsletter goes out and they look at about three articles on average and they continue to look at articles on attribution. And so that's behavioral. That means that I know them first-party. I don't know super granular data about them, but I know something that is targetable. I know something that is accessible by me that I can serve ads towards or learn more about or whatnot.
But that is first-party data as much as filling out a form and giving that info. Now, let's say me and you had a website and we both collected that data and we made it available to an aggregate partner, so both of our first-party data. Is that aggregate, if they put that first-party data together and make that accessible, is that then third-party data?

Tyler Blot: I think it's going to depend on the actual relationship you have with that end party. To me, I think there's elements of that that also put this in the second-party data category where it is that organization's first-party data, but you know where it's coming from. So if I have a website that you want to license some of that data to target against one of your campaigns, you know where it's coming from, I'm explicitly giving you the rights to do that, you know basically how it's collected, how it's modeled, if it's modeled, all that type of stuff that you really want to get into when you're vetting data for campaign usage.
But because you know where it's coming from, I would classify that as more second-party data rather than that aggregated third-party.

Bryan: Gotcha. So the difference between third-party and second-party is really transparency. Both could realistically be the exact same data, but it's how much visibility you give into it and how much you can do with it really, slice it up and do what you want with it.

Tyler Blot: Yeah, and I think going back to my earlier point too, when you think of third-party data, these are your large scale audiences. It could be just demographic data that could be collected from a wide variety of sources, or it could be auto and tender type stuff and it's just people scrolling along webpages looking at BMW site, or they're reading an article on Autotrader or something like that. It really is just the multiple sources coming together and being aggregated to basically help inform how that stuff is all being tied together from a third-party perspective.
And a lot of that you're not really going to get into, but I would encourage everyone to start to think about those questions, talk to the data providers, analyze your data usage on the campaigns that you're running, figure out how they are building out those segments. How is that segmentation happening? How is it collected? How is the privacy consent actually obtained? All that type of stuff.

Bryan: That's definitely a good point. I think that when people are working with data providers or really any third-party that they're working with for anything tech wise, they really need to understand the ins and outs, how they process everything, how they get consent, how they store it, use it, all of it. In podcasting, everything's kind of linear in the sense that we're basically a drop box. The podcast player calls the host for a file and gets the file, so everything happens from the host forward. The hosts in the ad server are so integrated in podcasting that there's no real ability for you to have a host and a separate ad server.
There is for the ad server to call another third-party through like fast and programmatic, but in podcasting, the only way to access this data for reporting or targeting is if both your hosts and your ad server, which are the same thing, chooses to integrate directly with a specific data partner or a platform that can pump in data and let you use it for targeting or reporting.
So in other digital channels, how do buyers get access to that data and how do they apply it to their campaign for targeting?

Tyler Blot: Yeah, I think while the underlying infrastructure is somewhat different, I mean, there's some similarities there as well, but you still need those integrations in order to get the data to and from one platform to basically where you're running the campaign if you don't own that data yourself. And even if you do, chances are you have to work with some level of an on boarder to bring that in and make it actionable and the ad medium that you're trying to work with. But I always think of this is kind of where the alphabet soup of the ad tech world comes into play, because when you think about the broader digital landscape, this is where your DNPs, your DSPs, your CDPs, all come into play here. Anyone that is basically touting an audience builder type of product that allows you to mix and match different segments or behaviors that roll up into audiences, that's where you're going to get access to a lot of these.
I would say the easiest place to grab them is probably from a DSP that you're already working with and that is talking to your ad server. And again, that can be one preferred data partner, it can be a wide variety of third-party data partners. There's a ton of different ways that you can go about it. And you also have the broader marketplaces here as well. There's a few of them in market, some really well known and some up and coming, but chances are, they're going to be that one stop shop for you. So if you're trying to go more towards a strategy where you want more variety, maybe you have a very diverse client base, maybe you don't want to be pigeonholed into one provider type of thing, sometimes the marketplaces are the better bet to go after because they've already brokered those relationships for you.
As long as you're willing to do the integration work there, then you have the opportunity to start to tack on those other audiences and start to test and learn and figure out what's really performing best for the campaigns that you're running.

Bryan: So it sounds like for buyers, this is a reason to pick specific platforms to buy through based on the relationships that they develop.

Tyler Blot: Yeah. I mean, I think so. I mean, it's just spending the last, I guess, approaching 10 years in the ad tech space at this point, that seems to be the best route here. And that's a lot of the vendor evaluation stuff that happens constantly in this space. There's always a new player coming into market. And then obviously you have your big behemoths as well, but you want to figure out who you're working best with, who's going to provide you the necessary support. Do you want to work in a managed service capacity or do you have a team that likes to get their hands dirty a little bit and do everything self serve?
So yes, I think as you go through an RFP process to try and figure out who that right vendor is, these are the important things that you want to consider. I don't know if there's a one size fits all for everyone out there, but it's a definitely an important part of kind of the evaluation set to how you want to build out your tech stack and who you want to partner with.

Bryan: Got it. So that data, how is it priced and what are the industry ranges for using that data for targeting a campaign?

Tyler Blot: It's really going to vary. And again, I think the first thing to establish here too is obviously we're focusing on podcasting and audio here, so that's just one medium, but you will see, depending upon if you're going a marketplace route or just a DSP, those CPMs are going to vary based on the advertising medium that you're running the campaign in. So connected TV data CPM is likely going to be higher than programmatic display, for instance, because it's all in relation to what the media CPMs are going for as well.
And then your actual data type. Your broader demo data, it's going to be on the lower end of the spectrum. I mean, I've seen things 15 cents, 25 cents, CPMs. I would say behavioral and interest data buy and large you're falling between $1 and $3 range on the CPM. Purchase data is probably a bit more than that and obviously the more finite you get, the more deterministic the sets. I mean, sometimes you can see double digit CPM, so it really does vary.

Bryan: Okay.

Tyler Blot: But again, this all goes back to the earlier point of you got to dive in and start to ask those questions on where the data's coming from, how is the cost justified, that type of stuff.

Bryan: Yeah. And so that leads me to my question, double digit sounds crazy to me in a world where podcasting is based on IP. Now we know that IP match is valuable, but how strong is IP based match for data? I mean, would you recommend someone use one of those double digit CPM data sets in an IP based match?

Tyler Blot: That's where the testing and learning comes into play, and also the partner evaluation. I think it's interesting how these questions are kind of coming full circle and we're kind of addressing this full on narrative here. But you want to understand how one, the IP matching is actually done, if the provider that you may be using to facilitate that match, how they go about things, what underlying data do they have in order to help facilitate that match?
In a marketplace, for instance, if endemically things are done at the IP level versus a cookie or a made level, if you're starting at that IP level, you're going to have likely a higher match rate if you're working off of IPs, rather than going cookie, converting to IP, then matching to IP. So you want to try and eliminate those steps that you have there because there's inevitably going to be drop off every step along the way to figure out how much scale or how much overlap that you have with the inventory that you're looking to target the campaign on.
There's just a lot of nuances to this. This is one of those things that I'd love to give you a hard and fast percentage on what match rates look like, but it really does change. It's about the quality of the data. You have the volatility of the IP address as well. While it's certainly more constant than other identifiers in the space, there is some turnover there. So you have to make sure you're staying on top of that and you have the freshest data possible when it comes to your IP addresses. But you even have things like IPV4s versus IPV6s and when that comes into play and you'll have much stronger match rates on IPV4s just because that's what's been in market for significantly longer. Match rates on IPV6s are certainly on the lower end, but as more of that type of IP address data comes into market, I expect those match rates to go up.
But we're just at a state in the industry right now where there's not a ton of it yet. So it's all these little nuances that come in. So it's hard to like give you that like, "Oh my God, it's an 85% match 90% of the time type of thing," but it's really just nuanced to the entire situation.

Bryan: No, no, that's good. And the advantage there is that podcasting will be probably the tail end of getting IPV6 up and running because we've spent a lot of time talking about it and no time acting on it. You know, data is interesting, like you talked about making sure that you understand how everybody is set up, how it's been vetted and whatnot. So are there any third-party organizations that vet the accuracy of the data? Are there any obligations for the ad servers or the connecting partners to vet the accuracy that they see the test? Because obviously if an ad server decides to integrate with a data provider, they've made the decision that that works for them. It's got to be kind of hard for a publisher to say, "Hey, ad server and data provider, I would like to vet this myself and therefore I shouldn't be charged to try it to see the accuracy."
So what are the options? How is this handled? How is this maintained and held accountable?

Tyler Blot: It's a great question to be honest. And maybe this is just me coming back into this side of the business after a few years on the measurement side, but I haven't really seen many organizations or data providers that are actually doing that. So I think a lot of it is that homework that you have to do as a potential customer of one of these organizations. You just have to ask those questions. You have to build a trusting relationship. Unfortunately, I don't know of many situations where you can try it before you buy it type of thing when it comes to the data usage just because of how the ecosystem's been built out and the infrastructure and all the different parties involved when it comes to activating.
But again, a lot of this comes down to privacy, especially now. How is consent gained? How does that ultimately contribute to an increase in scale or maybe likely a decrease in scale with everything that's going on and opt out's happening and all that type of stuff happening in the market right now? So you really just have to dive in, you have to ask those questions. You have to be upfront with what you want, what you care about, what's really important to you, and you just have to build those trusting relationships with the vendors that you're going after.
I think, like it or not, that's why some of the larger organizations that have built up good market reputations tend to win out in these instances because you're more likely to buy from people that your friends are buying from and you get that comfort level and all that good stuff. So it's tough. I don't know of anyone off the top of my head that's actually validating third-party segments per se. There's certainly stuff in organizations out there, like the MRCs and the neutrons of the world that are going out and more validating panel based data for measurement. But when it comes to the accuracy or validity of third-party segments, for instance, I haven't really heard of much that's going on. I mean, you have your Nielsen Dar ratings and things like that that do go through some level of qualification, but you're probably not going to get a ton of that stuff on your auto and tender audience.

Bryan: Yeah. It's all interesting, but having some sort of third-party that vets in validates these things is tough because when you try and grade a bunch of things that don't have to conform in any way to each other, that level, that ruler allows some to be over vetted and some to be under vetted and I think that it creates sometimes a false sense of trust. But the message that you're saying here that's really attractive is basically you need to do that due diligence yourself, right? You can buy in and accept, "Hey, my friends use this," or "Hey, I know the reputation," or whatnot and give it a shot and trust it and if that works for you, that's fine. But now is a great opportunity for each company, each person looking to do this to really spend the time and learn it.
If they can't explain the methodology, if it doesn't make sense to you, if they don't want to do a test, then maybe it's not the right fit. And especially right now, we need to make those decisions ourselves as buyers and sellers. We need to really understand what our data's being used for and how data's being used on our inventory.

Tyler Blot: Absolutely. And I think now is kind of that perfect time too. I think if there's one major takeaway from this conversation that I want people to have is now's the time for education, because there's certainly a lot of different things happening in market from that privacy standpoint, and just general change in the ad tech and data landscape. You have to be well informed. You want to be able to future proof your business. You want to make sure that all of your assets are protected and that you're going to be able to grow for many, many years to come. So all that starts with knowledge.
So my big encouragement here is just ask questions, dive in with your vendors. Chances are, if they are your vendors and you're a client of theirs, you have that trusting relationship anyway, so go in and prod them a little bit. They'll engage in the dialogue and you'll be able to hopefully come out a little bit smarter, a little more educated, and it'll also help that relationship as well.

Bryan: That's great advice. Thank you so much for joining me.

Tyler Blot: Yeah, no problem. Really appreciate the time, Bryan, and this was great.

Arielle: Great conversation, Bryan. Let's recap. You two discuss the difference between first, second, and third-party data and how with slight variation, which is usually transparency, the lines can be blurred. Tyler says that you have to do homework as a potential customer of these data usage companies, be upfront about what you want and what you care about. Why? Why do you think that's the case? What happens if you don't do your homework, Bryan?

Bryan: I think it's really critical right now that every single partner in this space, both publisher and advertiser, really evaluate every company that they work with. They need to know them ethically, they need to know their goals, they need to understand their process. Because by using a piece of technology, by using a data set, you are choosing to align yourself with it. It's not as simple as throwing your hands up and saying, "That's not your responsibility," if something goes wrong, if you don't agree with it.
You are endorsing it by using it. And so that's really critical. It needs to become part of your entire operation and you need to understand it inside and out.

Arielle: And you can't try it before you buy it so you got to do your own homework, do your due diligence, ask those questions, talk to people who are also customers of these companies that you know through your work in the industry. Now is the time for education, says Tyler, because there's change going on in ad tech. You got to make sure that you're protected. You got to ask questions of your vendors. Why is this conversation so important to be having now? What is going to happen to our data going forward that now is the time for education?

Bryan: Well, there's a lot of legislation coming out about what is personal data, how people can collect it, what we're going to store, what we can augment on, and really the reclaiming of the rights of the individual. So we've seen the recession of the mobile device ID, which was just kind of available everywhere. It moved from something that was ubiquitous across your entire phone to specifically by app and now it's rolling back to ask for consent. We're seeing third-party cookies. So, that's the idea of like a Facebook pixel being on, that would be third-party, whereas first-party cookies being a pixel.
We're seeing third-party cookies being pushed back by browsers. So the glut of data is kind of being turned off. So now we're trying to get better data and we're trying to get consent for that data and we're trying to organize it in ways that the data Sounds Profitable collects could be used in a way that it could match with other data sets that also have consent in an anonymized way. So we had a gather it all up and sort it out later mindset, and now we need to know how it comes in and we need to know how it matches that origin. So far less waste, far less invasion, but it's a lot of restructuring.
And ad tech, for all the technology side of it, it's more like a train than a car. It's set to go in one direction and they build towards it. And now it needs to be versatile. It needs to rethink the tracks. It needs to kind of reassess everything. And so that's where we are as an industry.

Arielle: That's good. That's a good metaphor. I like that. And for another metaphor, while there was no real partying here, at least we got to talk about some cookies and we hope you learned something folks.
What do you think of the show? We want to hear from you. Please reach out if you have any questions or comments. We're on Twitter @soundsprofnews, @bryanbarletta, or @arinissenblatt. And if you want to send us an email, that's

Bryan: This show is recorded with Squadcast, the best place to record studio quality video and audio for content creators. I use Squadcast for every interview and product deep dive and I encourage you to check it out. Go to for a free seven day trial. And please let me know what you think, and heck, invite Arielle and I onto your podcast recorded with Squadcast. We'd love to be a guest.

Arielle: And we could take squad shots. Do you want more from Sounds Profitable? We have two more podcasts that you can explore. First up is Sounds Profitable: The Narrated Articles, and next, The Download, our podcast about the business of podcasting. And both of those are available in Espanol. Find links to them in the episode description. Thank you to Ivo Tara and Ian Powell for their help on this episode.