Blis CTO Aaron McKee on Location Intelligence and the Future of Omnichannel Advertising

Summary

Marketecture Podcast Summary: "Blis CTO Aaron McKee on Location Intelligence and the Future of Omnichannel Advertising"

Release Date: May 27, 2025

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Introduction

In the May 27, 2025 episode of the Marketecture Podcast, hosts Ari Paparo and Eric Franchi delve into the evolving landscape of advertising technology with Aaron McKee, the Chief Technology Officer of Bliss, recently acquired by T-Mobile. This insightful conversation explores Bliss's innovative approach to omnichannel advertising, emphasizing location intelligence over traditional cookie-based targeting.

Understanding Bliss: An Omnichannel Advertising Powerhouse

Aaron McKee introduces Bliss as an "omnichannel planning, buying, and measurement platform" (01:39). Unlike conventional Demand-Side Platforms (DSPs) that rely heavily on cookies and device IDs, Bliss leverages geographic data to achieve comprehensive audience reach. By utilizing geo as the primary lens, Bliss ensures effective targeting across various mediums, including iOS, Connected TV (CTV), Digital Out-of-Home (DOOH), and other challenging channels where traditional identifiers fall short.

Geo-Targeting vs. Cookie-Based Targeting

The discussion highlights the limitations of cookie-based targeting, especially in an era where privacy concerns are paramount and data access is increasingly restricted. McKee emphasizes the shift back to market-based strategies, reminiscent of traditional advertising methods:

"It harkens back to what advertisers used to do ages ago, looking at things from a market-based perspective." (02:57)

By focusing on zip codes, Bliss can reach full audiences at scale, including segments that previously resisted digital tracking methods. This approach not only broadens reach but also enhances performance by tapping into location-specific behaviors and demographics.

Data Accuracy and Enhancements

A critical aspect of Bliss's success lies in the accuracy of its geographic data. McKee explains that Bliss employs proprietary machine learning algorithms to refine raw GPS data:

"On average, the accuracy of a zip code resolution is within about two miles." (04:56)

While acknowledging that zip code targeting doesn't match the precision of zip+4 codes, Bliss compensates by validating inferred locations against precise GPS data, ensuring reliable targeting across various programmatic channels.

Customer Workflow: Planning, Targeting, and Optimization

Bliss's platform facilitates a seamless workflow for advertisers, encompassing planning, targeting, and optimization:

1. Planning: Customers input their campaign briefs, whether aiming to outcompete a rival or launch a new product. Bliss's platform analyzes overlapping and unique audience segments using comprehensive data sets, including census demographics and purchasing behaviors.

2. Targeting: The platform offers both binary targeting (specific zip codes) and weighted targeting, allowing advertisers to focus on high-potential areas or adopt broader strategies with nuanced filters.

3. Optimization: Leveraging machine learning, Bliss optimizes media placement by identifying the best publishers, ad sizes, and timing to maximize conversions and minimize costs.

"We have some pretty special things that we do that allow us to punch above our weight." (11:18) — Aaron McKee

Comparison with Other DSPs

When compared to larger DSPs like Google and Amazon, Bliss distinguishes itself through its unique geo-focused approach and superior performance metrics. McKee shares impressive statistics demonstrating Bliss's effectiveness:

"We've delivered superior performance... 61% more conversions across every channel than those names we’re familiar with." (11:56)

This performance edge is attributed to Bliss's ability to reach audiences across diverse touchpoints without relying solely on traditional identifiers.

Frequency Capping Without Traditional IDs

Addressing concerns about frequency capping in a cookie-less environment, Bliss employs a technology called Flexi Capping:

"It uses a combination of signals to try to make sure that we don't over-deliver ads." (15:35)

Flexi Capping utilizes available identifiers when possible and falls back on network addresses or other contextual signals to prevent ad oversaturation, maintaining campaign effectiveness even without precise user IDs.

Advanced Measurement with Smart Holdout Groups

Measurement is a cornerstone of Bliss's offering, especially without traditional IDs. McKee introduces Smart Holdout Groups, a framework that ensures statistically robust measurement of campaign incrementality:

"It allows you to create a B zone—areas that you show ads to and areas that you don't show ads to—that controls for things that could affect the performance of your campaign." (16:46)

This method enables advertisers to assess the true impact of their campaigns by controlling for various demographic and behavioral factors, ensuring accurate attribution of results.

Regulatory Compliance

Operating in multiple jurisdictions, Bliss maintains stringent compliance measures to adhere to regulations like GDPR and sector-specific restrictions:

"Our system and our processes and our business teams understand what we can and can't do through each of those various lenses." (19:36)

This commitment ensures that Bliss can effectively serve clients across different industries without compromising on legal standards.

Lightning Round Insights

Ari Paparo engages Aaron McKee in a rapid-fire Q&A to uncover key elements of Bliss's strategy:

• Number One Competitive Advantage:

  "The ability to reach audiences at scale, to deliver the full audience, no matter what device or screen they're on, and to drive really solid performance." (20:39)

• Number One Challenge:

  "Doing something new and getting people to see what we're doing and to get excited about it." (20:51)

• Why Google, Amazon, and Others Won't Ultimately Win:

  "There needs to be a unifying layer that allows you to reach an audience simply across every single touchpoint... partners like us that have something really unique to come to market." (23:27)

Future Outlook and Industry Positioning

McKee posits that while giants like Google and Amazon will remain influential, there is ample space for specialized players like Bliss that offer unique value propositions and open marketplace advantages. The focus on unifying diverse advertising channels through location intelligence positions Bliss as a pivotal player in the future of omnichannel advertising.

Conclusion

The episode concludes with a light-hearted analogy, likening Bliss to a raccoon:

"They're really clever and they find opportunities where a lot of other animals miss it." (24:48) — Aaron McKee

This comparison underscores Bliss's innovative and opportunistic approach in the advertising technology landscape. As Bliss continues to integrate with T-Mobile, its commitment to location intelligence and performance-driven advertising sets a new benchmark for the industry.

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Listen to the full episode here or subscribe to the Marketecture Podcast for more in-depth discussions with leading technology executives.

Transcript

[Ari Paparo]

This podcast is brought to you by audiohook, the leading independent audio dsp. Audiohook has direct publisher integrations into all major podcast and streaming radio platforms, providing 40% more inventory than what could be accessed in omnichannel DSPs. What's more, audiobook has full transcripts on more than 90% of all podcast inventory, enabling advanced contextual targeting and brand suitability. Audio Hook is so confident that in addition to CPM buys, they offer the industry's only pay for performance option where brands can scale audio and podcasting with peace of mind mind knowing they are only paying for outcomes. Visit audiohook.com to learn more. That's audiohook.com welcome to Marketecture, where you can get smart fast with in depth interviews of leading technology executives. I'm Ari Paparo and I'm joined Today by Aaron McKee, who is the CTO of of Bliss, recently acquired by T Mobile. Aaron, thank you so much for being here.

[Aaron McKee]

Oh, it's a pleasure to be here and talk to you again, Ari.

[Ari Paparo]

So you're not wearing magenta, so strike one on the integration. Did they give you swag as soon as you joined?

[Aaron McKee]

We have so much swag and I think it has looked very favorably to where I didn't want to appear to be too much of a tryhard this time, but you'll see the events.

[Ari Paparo]

Do you have to do something subtle like a pocket square, magenta pocket square, or something along those lines? So we're not going to talk very much about T Mobile because the acquisition is pretty new. Let's talk about Bliss. I personally am a fan of Bliss. I've talked about it on my pod a couple of times, so I'm excited to hear about it. So what is Bliss?

[Aaron McKee]

Bliss is an omnichannel planning, buying measurement platform. I think the thing that's made us a little bit different is the approach that we take to reaching full audiences at scale rather than using or relying just upon cookies or IDs. We use geo as the lens and there's some clever stuff under the hood we can talk about in more detail, but what it effectively allows us to do is to reach every screen out there using this location intelligence and reach full audiences, including iOS, including CTV, including Digital out of home, including a lot of these very hard to reach places and people that either don't want to log into a website aren't running chrome or otherwise inaccessible and that's allowed us to deliver very solid reach, very solid performance off of the back of that.

[Ari Paparo]

So I mean, is it Fair to dumb this down to say you're planning a DSP solution.

[Aaron McKee]

Yeah, that's the case. That space that we fit. We also have some really exciting measurement solutions that work with our DSP in theory could work work alongside other DSPs as well.

[Ari Paparo]

Right. Okay, great. So let's talk about GEO and why it works and what the positives and negatives are of using it. Obviously, GEO is sort of ignorant of cookies. It's a different vector for targeting and for measurement. So what have you found with using GEO throughout your system?

[Aaron McKee]

Well, I mean, the first thing is it sort of harkens back to what advertisers used to do ages ago, which is looking at things from a market based perspective. And a lot of marketers still use that, especially for linear and traditional out of home. It was sort of the natural place to expand into because people already think about it. You want to reach people in St. Louis differently than in San Francisco. So what we built is a solution that understands a lot of information about all of the zip codes in America and a lot of the zip code equivalents around the world in terms of who lives there, what do they do, what do they behave. And then we can overlay that with audience data from, from our own data sets, from customer data sets, from third party data sets to understand what makes people in those areas unique. You know, for example, one of the things that we can do is we can take visitors to, to Bloomingdale's, one of our clients, and we can see who goes into a Bloomingdale's shop. We can figure out roughly where do those people live, where do they work, zip codes, not home addresses. And then we can say what's about special about those Bloomingdale's audiences, and can look at Bloomingdale's audiences in 90210. And because Bloomingdale's audiences in 90210, they play these games, they go to these websites, they listen to these podcasts, and they do them at these times of day. We can come up with that view of that consumer, of that audience through the lens of jio, things like zip codes to target. But we can also overlay additional signals to try to restore addressability and precision into that audience, to deliver that performance on the back of that. And the great thing about the JIO is you can get that zip code from pretty much every programmatic buying opportunity, display, CTV out of home and so forth. And it really comes that common language that you can spread across advertising. And with some of our clients, it even expands over to what they're doing with traditional, out of home and linear. So there really is that holistic way of thinking about your ad campaigns, right?

[Ari Paparo]

Yeah, it makes sense. Zip code works across any media in theory. Let's talk about the data, though. How accurate is zip code and what does your system do to compensate in cases where it's less accurate?

[Aaron McKee]

Yeah, that's a really good question. And this was something that was really important to us early on. Our original heritage was much more in the location pure play space. You're seeing ads because you're in a McDonald's or you've been into a McDonald's and it's precisely built off of precisely GPS data effectively. So we have a really rich GPS data set. We built a lot of proprietary machine learning to sort of, you know, take the rather bad raw data and make it good, precise data. And that was sort of our heritage. One of the things about that level of personal data is it's shrinking over time. Not just cookies and IDs, but also GPS level data as people exert more control over the type of data they share into the ecosystem. But one of the things that's still been useful as we've expanded beyond GPS precise data into this more sort of coarse granularity, the zip code targeting is we can use the GPS data that we have that we continue to have to validate the accuracy of what we're doing with the zip code targeting. We'd ran a lot of evaluations over various ways of inferring zip code against that GPS truth set to figure out what was the right level of granularity. For example, in America, what we found is on average, the accuracy of a zip code resolution is within about two miles. And this is, this is important, right? Because some customers are saying, well, we'd love you to do zip +4. There's a bunch of challenges with zip +4. One of them is ultimately you're not able to make that determination with a high level of accuracy in the programmatic buying ecosystem across every single channel.

[Ari Paparo]

Right. Because IP address is not going to give you zip +4.

[Aaron McKee]

Generally, it's not going to give you zip+4. I mean, there's a few other things that we do to infer location. There's other signals we can look at in the bid request, as it were, but IP2GEO is one of those. And that comes down to how we evaluate the partners we work with, how we curate that data set, what other signals we look at, we ultimately validate it against that truth set of precise location data. To say, yeah, we do have confidence that we can make this, this determination accurately.

[Ari Paparo]

Right. So let's walk through what customers do with your platform in the natural order. Let's do planning, targeting, optimization. So go planning first.

[Aaron McKee]

Yeah, I mean, oftentimes customers come to us with, with broadly speaking, one of two types of briefs. They'd really like to put a competitor out of business and eat some of their, their, their audience base. So they come in and say, you know, I want to, I want to sell more hot dogs, I want to sell more burgers, I want to sell more dresses. And we think there's a, these markets across these competition sets. And what we can do on our platform is we can pull up the audience that we're talking to. You know, maybe it's a Bloomingdale's audience and then we can pull up maybe a Macy's audience alongside of it. We can see what they have in common. We can see the areas that overlap, the areas that don't overlap, the sort of facets of these markets in terms of like census demographics. Maybe it's MasterCard purchasing data, maybe it's Experian mosaic type segment information, any of the other data sets that we have. Maybe in a lot of the markets we operate in, the type of apps that people use, the websites they go to, we can compare and contrast those audiences and overlay some of the other parameters that the, the brand wants to reach, socio demographics, specific market focus, etc. And then there's other ones where they come to us with a specific source of brief. They want to, they want to launch a new food line, a new type of lunch. You know, maybe Subway wants to go out to market with their new Doritos nacho tray and they figure out what's the right audience for that. And they come to us with a lot of assumptions and we help them reach them in our, in our planning platform.

[Ari Paparo]

And is the output like binary? Like you should be in these zip codes and not these, or is it weighted?

[Aaron McKee]

It's, it's a bit of both, actually. So one, it comes up with, you input your brief into the platform, you refine your filters, it makes a suggestion and you can obviously modify that. You can add additional filters, additional audience parameters and data sets on it to refine that further. One of the things that we come into bear, I kind of mentioned earlier is this sort of ability to target not just zip codes, but like the intersection of zip codes and content and times of day and days of week and this other sort of layers that sort of tease out that specific cohort better. And that's where the weightings come in. So you can target the those intersection points that are highly likely to reflect your audience, weakly likely to reflect your audience, or are actually under indexing because that's the biggest growth opportunity.

[Ari Paparo]

Right.

[Aaron McKee]

We show the various zip codes in terms of that strength of association as well as those intersections in terms of the strength of associations. And this sounds more complicated than what it actually looks like in the plot. It's really actually easy to dig in and say, effectively, I only want to reach the cream of the crop, the most likely to resonate with this audience because I'm doing a laser focused campaign where I want really high roi. Or you can go with a broader strategy and tease them those levers down a little bit.

[Ari Paparo]

Right. So the client can come in with either a set of general targeting criteria or they could come in with a deterministic data set that then can get bridged over to zip codes and then turned into targeting. One question I've been asked about this kind of solution is whether it works for regional advertisers or smaller advertisers. Can you talk a little bit about the minimum scale to have geo work?

[Aaron McKee]

There's no minimum scale per se, but it ultimately depends on your objectives. So you can bring your own customer data into the platform or you can use our data. And that works really quite well. And again, if you only have say 100 device IDs, you're not necessarily going to get national coverage of insights across that. But if you have 100 device IDs or 100 data points and so forth, but you're only focusing on, say Boston, that could be sufficient. It's really looking at what your regionality is. So if you come into New England, there's actually no problem reaching, you know, auto dealers in New England, which is a lot less than the auto dealers across America. It's understanding what you're ultimately trying to do, the scale of budget necessarily to hit that. And that's where our client service team really tries to advise clients on what are their ultimate objectives.

[Ari Paparo]

Right. Scale versus concentration.

[Aaron McKee]

Yeah, so I would say it's, you know, we don't really focus on one store type targeting, but you know, usually like a chain of stores, even if it's a regional chain or even a regional like CPG brand or health brand. I think those have worked really well on our platform.

[Ari Paparo]

Got it. Okay, so now moving from planning to targeting and operations. So I assume your product sort of works like most DSPs. How do you measure up against sort of other choices that advertisers may have for DSPs.

[Aaron McKee]

Yeah, I mean, their intention is to be very competitive with that. You know, we are a slightly smaller DSP relative to some of the big names we all know, but I think we have some pretty special things that we do that allow us to punch above our weight. You know, again, we're not going to give you Amazon prime inventory, we're not going to give you YouTube inventory, but what we generally give you is full reach across your entire audience with performance. And I know you spoke about T Mobile earlier. I think one of the reasons that they liked us and then ultimately bought us is they've been working with us from their own brand perspective for, for quite some time. And relative to some of the other DSPs that we could all think of, frankly, we've delivered superior performance.

[Ari Paparo]

Right.

[Aaron McKee]

I think in terms of conversions for driving people to sign up for T Mobile phone subscriptions, whether that's Metro or whether that T Mobile itself, I think something like 61% more conversions across every channel than those names that we're familiar with. 1.5 times more conversions on iOS for iPhone type subscriptions, 29% lower CPA. And we've seen those stats across other clients as well, that generally we're delivering better performance than, you know, the bigger DSPs out there.

[Ari Paparo]

And conceptually, should I think of it as I log into the bliss DSP, I do my normal business upload creatives at targeting, etc. And then geo is sort of a magical spec special overlay on top of that, or is it a little more that I do? A Is the workflow different from the way I described it?

[Aaron McKee]

The workflow is pretty similar to how you describe it. I wouldn't call it a magical overlay. It is front and center. So again, it's one thing to clarify, we do support all the traditional DSP targeting. If you have a bag of cookies or maids or other forms of targeting, we can absolutely target those. What we generally would suggest is you also run the special sauce, the magic on top of that, which is our Geo approached location intelligence tool that allows you to really reach much more of that market. So you can target, you know, the device IDs, the cookies, whatever that you think are laser focused. But we can also analyze those and very seamlessly connect those to these Geno insights that we have to really supercharge those, those campaigns. And so and you'll, you'll see that. You'll see this tool and you can go to our website to get Images of it. I know Ari, you've seen this before. You see the map based interface, you can overlay your data on the map. Everything is sort of front and center and it's not happening like a black box. You have control over what you're seeing and ultimately what goes live. But yeah, upload your budget, assign your other targeting parameters, upload your creatives. I mean you've built a dsp, you know this very well. It's, you know, it's all the traditional stuff people are used to being able to do.

[Ari Paparo]

Yeah. And so what's the line between targeting and optimization here? You know, geo. I think we've been talking in more of a targeting vein of there's certain geos, et cetera. But what about how do you drive better results beyond targeting?

[Aaron McKee]

So I mean there's quite a few bits of, of artificial intelligence, I think we're supposed to call it now.

[Ari Paparo]

You have to.

[Aaron McKee]

Well, it's machine learning that we operate underneath the hood. So there's the media optimization layer which understands the best publishers, ad sizes, times, all that sort of context to deliver the best results. Whether that's conversion pixels, whether that's footfall, whether that's click through recognition, all of those traditional media metrics that you have, we have machine learning can automatically optimize that. And then we also have the audience optimization that allows you to refine that audience to ultimately hit your goals. And I think the performance that we've delivered for brands like T Mobile are quite competitive with other DSP and superior in most cases. It's a combination of that really clever machine learning, but it's also a combination of being able to reach bid opportunities that frankly other DSPs are not able to effectively monetize. Because we're buying without dependence on an idea of some sort, we're able to get value out of the market that other brands and DSPs don't effectively.

[Ari Paparo]

Right.

[Aaron McKee]

And we're able often to do that at a more effective cpm. And that translates into better roi.

[Ari Paparo]

Well, the Safari, the black box of Safari that many, many folks ignore. Which brings up kind of one of the questions everyone always asks, which is how do you do frequency capping if you, if you're not dependent on IDs.

[Aaron McKee]

Yeah, that's a good question. That was one of the first things that we identified as a necessary aspect of the stack if we wanted to come out to market with something a little bit new and let's say cookie free.

[Ari Paparo]

Yeah.

[Aaron McKee]

We implemented this technology called Flexi capping. It uses a combination of Signals to try to make sure that we don't over deliver ads. If there's a cookie or a UID or some other alternative ID that we have access to that we can see, we'll absolutely frequency cap against that. And that'll either be like a user specific id, a device specific id, a context specific id, whatever type of id. If there's an id, we'll absolutely use it. We can also use things like the network address as a fallback. And again, it's not as precise as knowing, you know, that area. You've seen exactly five ads in the past five minutes. It might also be, you know, other people at your house, but it's a way of making sure that we don't oversaturate users. At the end of the day, if you don't have IDs, you may not have quite the level of precision, but you want to make sure you don't oversaturate people or spend all of your budget on, you know, just one entity. Because you're running, let's say traditional spray and pray tactics.

[Ari Paparo]

Yeah, makes sense. So let's talk about optimization. So I think this is not optimization, I'm sorry, measurement where I think this is an area where your product has some pretty unique approaches because you have a geo holdout concept. Can you walk us through that?

[Aaron McKee]

Yeah, exactly. I think that's again, part of delivering a new type of approach to targeting is you need to make sure that you can measure that and we can support all the traditional measurement solutions out there that people are used to. But one of the things you find is that as you look at an omnichannel plan, there aren't that many traditional omnichannel measurement solutions that work even when you don't have an id. So we can run those. But what we also suggest, either running alongside or in replacement, is a framework that we have called Smart Holdout Groups and Smart Holdout Groups, just to be clear, it also works with third party measurement. We don't want to be in a position of marking our own homework, but what it allows you to do is to take your campaign, your targeting that you want to do and your audience looked at through a geolens. And it allows you to create a B zones, areas that you show ads to and areas that you don't show ads to that controls for things that could affect the performance of your campaign. So we know a lot about the zip codes, we know all the census data, we know purchasing data, we know a lot of stuff about that. And what we can say is, you know, Mr. Or Mrs. Marketer, you want to run this campaign, what do you want to control for? Maybe you want to control for commute time, maybe you want to control for income, maybe you want to control for, you know, the number of cell towers in your area. We can use those as control parameters, assign those characteristics to the individual zip codes and we can make sure that when we split sectors into sort of this is the treated group and this is the held out group that we're comparing like for. Like, here is the high net worth, a set of zip codes on the control side and on the test side, here are the low net worth. Here are the high cell tower density and the low salad tower density. The other thing that we have from our heritage is we know how people move between zip codes. You don't want to put a control zip code right next to a treated zip code if people commute back and forth because then you're just mucking up your audiences. You don't know if they're controlled, you don't know if they're exposed. Our system separates out your targeting into these various controlled and treated groups in a way that controls for the things that are different between the zip codes that are relevant to your campaign and controls for people moving between zip codes. And there's other clever stuff under the hood we create like these buffer zones you can still show ads to, or not show ads to, but sort of segments. How you do measurement to really allow us to create statistically robust ways of measuring incrementality of a campaign using our metrics or even third party metrics.

[Ari Paparo]

Yeah.

[Aaron McKee]

So like with T Mobile, they brought their own store sales data, their own online sales data to us through that zip code lens and we were able to demonstrate uplift on that. And we've done that for other clients as well, like DC Lottery and many others.

[Ari Paparo]

To be clear, you're talking about T Mobile as a customer, not as an owner. Yeah. So how does your system deal with regulatory issues? Like, it's illegal to target by zip code for like finance in some cases. So what is the overlay of compliance?

[Aaron McKee]

I mean, the first thing I would say, I mean, our business was headquartered in London prior to acquisition and GDPR was pretty relevant for us. And we took that level of compliance very seriously very early on, at a time when a lot of American companies sort of pulled out of the market because it was too hard. So we've built compliance in both as a business function as well as a technical capability. Since day one of GDPR back in 2018 and have only expanded that going forward. So we take very seriously things like the financial regulations, the things we can and can't do. So for example, you know, in America you can still do sort of ethnic targeting, whether it's language or ethnicity, for, you know, food products, but you can't do that for financial services. In Europe, you can't even do the ethnic targeting even for food products and so forth. Our system and our processes and our business teams understand what we can and can't do through each of those various lenses.

[Ari Paparo]

Got it. All right, let's move on to a lightning round. Relatively quick questions with relatively quick answers. What is your number one competitive advantage?

[Aaron McKee]

I think the ability to reach audiences at scale, to deliver the full audience, no matter what device that are on, what screen they're on, and to drive really solid performance off the back of that.

[Ari Paparo]

What's your number one challenge?

[Aaron McKee]

The number one challenge is we're doing something new and getting people to see what we're doing and to get excited about it. I think once we are able to show them to this, they get pretty excited about it. But it is a new thing that has its own sets of challenges.

[Ari Paparo]

So I want to just dive on that for one second. Do you have customers who just are very cookie centric and don't. Or potential customers and just don't really get the idea of not using certain, you know, audience segments, etc.

[Aaron McKee]

I think that's becoming less. I think people are seeing this a lot more as being. They need to have a post cookie strategy. It has been a challenge certainly in past years. And you know, one of the things, there was a company that we'd worked with, you know, a big name we'd all recognize at a big agency we'd all recognized. And when we asked them, they were pretty senior to dig into their campaigns, they realized they were delivering almost everything on Android and Chrome.

[Ari Paparo]

Right.

[Aaron McKee]

And ultimately this is, this is a CPG brand. You know, imagine it wasn't this, but imagine it was diapers. If you're selling diapers, you want to be able to sell diapers to everybody, men, women, iPhone users, you know, Android users. And they realized they weren't reaching their full audience. And once you can show them what's missing, the light bulb moment goes off and they say, yeah, I really need a strategy that goes beyond that. I need to reach the full market out there and deliver roi. Not ROI over a tiny segment, but ROI that actually affects the business as a whole. So it's becoming easier as people are realizing the Limitations of where cookies are. Even in the light of Google walking back from the brink, I don't think it materially changes that you need to post cookie strategy in 2025, but what.

[Ari Paparo]

About when they want to use your solution for reaching the customers, but then behind the scenes they're using a multi touch attribution that's cookie dependent? That must be a challenge.

[Aaron McKee]

Fortunately, we actually work really well with we generally come out ahead, even on the multi touch attribution sides. But oftentimes that's a subset of the overall delivery. What we generally recommend for the customers who are a little bit more new to this approach is we run both alongsides. We show how one type of result relates to the other one and build up that comfort zone because they often correlate quite well. And then ultimately where we can get them to tie this back to their own business, KPIs. And this is what we've done with the likes of T Mobile as a brand customer, as well as DC Lottery and others. When they see the numbers in their own dashboards and their own systems independent of media, it really sort of puts proof to everything that we're doing on that.

[Ari Paparo]

Got it back to the lightning round. That was not a short answer. No, it was my fault. All right, we ask everyone this. Why won't Google, Amazon and all the giant companies ultimately win?

[Aaron McKee]

I mean, they're not going to go away, let's be honest about that. But I think there's room for space between them. I think what we're going to find. Google has their own sets of challenges. Do they continue to exist in a couple years as they exist now, or are they just a route to Google search and YouTube? We'll see how that plans pans out in the future. Ultimately, we're able to deliver better performance in those platforms. We're able to reach audiences across the full ecosystem of the Internet, across ctv, across out of home. I think there needs to be a unifying layer that allows you to reach an audience simply across every single touchpoint. The walled gardens aren't going away, going away. I do think that, you know, there's, you know, 100 million walled gardens right now. I think that kind of reduces over time because people don't want to have to have 20, 30, 40 different relationships out there. But I think what we're going to find is the rise of environments, partners like us that have something really unique to come to market, coupled with unique inventory, maybe from us, maybe from other sets of entities like you've mentioned, or unique sets of data across that there's going to be a smaller number of those that deliver unique value. And I don't think that's going to go away. And I think there continues to be value in the open marketplace, in the open Internet as well. As long as you're surgical about where you where you buy and what you buy.

[Ari Paparo]

Yeah, I appreciate that. Final question. If Bliss was an animal, what animal would it be?

[Aaron McKee]

I'm going to get this wrong. I like raccoons. They're especially Cuba. They're really clever and they find opportunities where a lot of other animals miss it.

[Ari Paparo]

All right. Plus the opposable thumbs. All right, Aaron McKee, the CTO of Bliss. Congratulations on the acquisition and thank you for being on marketecture.

[Aaron McKee]

Thank you, Aaron.

[Ari Paparo]

Foreign thank you for listening to the marketecture podcast. New episodes come out every Friday and an insightful vendor interview is published each Monday. You can subscribe to our library of hundreds of executive interviews at marketecture tv. You can also sign up for free for our weekly newsletter with my original strategic insights on the week's [e-mail] and you. If if you're feeling social, we operate a vibrant Slack community that you can apply to [e-mail].