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Precision at Scale: Rethinking Data, AI, and Consumer Control with Alex Boras
00:21:53
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- [00:01]
A
This podcast is brought to you by the Build, a new podcast from the guys behind Sincera, Michael Sullivan and Ian Myers. They built their company by figuring out clever solutions to a few important ad tech problems in our industry. And that's exactly what the show is about. Mike and Ian interview some of the smartest tech minds in the biz to hear about how they identified opportunities, solved their hardest challenges, and grew their businesses in the process. Listen to the Build with Mike o' Sullivan wherever you get your podcasts. Hi, this is Ari. We're happy to bring you another recording from our Architecture Live event in March. This one is with Alex Boras, the president of US Bliss, which is part of T Mobile Advertising. And the subject is precision and scale in the era of consumer control. I hope you enj enjoy it.
- [01:03]
B
All right. Market Live. Right, we're here. Yeah, we're here. We made it. Glass House. Thank you all for being here with us. I'm Alex Boris, President of Bliss, now a part of T Mobile. T Mobile made the brilliant decision to bring Bliss in house as their Omnichannel DSP powering their ads business. We are the exclusive home for their data as an omnichannel platform and a singular activation route. I am joined by Chrissy Kupak, who is head of product at pmg. Chrissy, do you mind telling us a little bit about your role, how it's evolved? I can't believe I'm on stage with the head of product from an agency, but this is such a singular role in the market and really the evolution of these agencies today.
- [01:55]
C
Sure. So head of product at PMG. I'm the first one. I've been there almost 20 or 20 years. Two years, but previous to that was always in advertising technology. And what I think it means for the agency world is that we have to be investing in our technology. We need to be building proprietary systems that are really bringing value to our customers directly. It's not just about relying on third party technologies anymore to be different, to be a survivor. Frankly, in this age, we as agencies need to be bringing differentiation and the way that I think we can truly do that is through our tech. Now, PMG historically has actually always been very tech driven and tech first. In fact, our CEO was an engineer. His first two hires were both engineers and they just had a passion for marketing and brought that into the technology. From the beginning, it's always been about this transparency between our team and our customers and making sure that we are, you know, gathered around the same campfire and rallying around their Objectives. So we had to be very, very close to their data, to what they were trying to accomplish. And, and we also wanted to be very transparent with them about how we were impacting their business.
- [03:24]
B
Oh, that's amazing. So what I'm hearing is you are being transparent with your clients about data where their campaigns are running. The days of black box agency life are kind of gone by the way side. I really hope so. But still driving outcomes, still very much focused on driving that business result for each customer, but in a transparent way. Is that correct?
- [03:50]
C
Yeah, absolutely.
- [03:52]
B
So in this age of AI, we just kind of watch the startup showcase, which is always so cool. I love that they, that market share does that. You know, when you start with all of this data that you all are kind of collecting as the agency for various clients and you have your clients bringing data and you're working with third party partners that are bringing data to the table, how do you distill all of this signal from good, bad, irrelevant? How do you actually form that foundation that enables, right, enables you to build an actual AI model that doesn't produce something obscure and you know, allows you to reach your consumer, allows you to drive that business outcome. How do you sort through all of that? And I'm glad that you're doing it, not me.
- [04:47]
C
But yeah, it's definitely a difficult challenge. We thrive on challenges. We have always been about data as the foundation of our platform and as you said, garbage in, garbage out when it comes to AI models. So absolutely it's critical that the foundation of the data is precise and validated. And actually the timing couldn't be better because in fact today there's. I brought a newspaper with me.
- [05:17]
B
The Wall Street Journal brought a newspaper to a tech conference.
- [05:19]
C
Yes. Print is not dead. We put a full page ad in the Wall Street Journal today about our position. Data is everything is everywhere, intelligence is not. And this is something that we truly believe in as a company and this is stating our position to the world that it's not just about aggregating the data, it's also about bringing insights into it. So we take a look at three different areas. We look at the strategy, the signals that we can get on it, and the decisioning that we can make from the data. So from a strategic standpoint, it's really about discovery. What trends can we pull from the data at a high level? How can we react quickly? And then we look at first party data. When you think about consumer data that our brands have, we use it more actually for insights than for direct activation. We look at how do we take this known user and expand into it and use third parties to really enhance that data and create an understanding around it. And then that gets baked into the decisioning that goes into the plans, that goes into the activations. And again, it's not always about being one to one precise. That does not exist anymore, not truly. It is about creating an understanding at a high level and then building our media activations around it. So I'm curious how Bliss does look at first party data.
- [06:54]
B
Oh man, we absolutely take kind of very similar approach that you do. Right. So we start with let's say the T mobile data set. We're going to validate it, we're going to ensure that the signal that we're getting off of our own devices is actually valid. And we're going to ensure that that starts as our kind of foundation, our seed population. Then we're going to project it locally and then roll that up nationally to create really kind of these full cohorts of folks that then we're going to look for across the programmatic ecosystem, not dissimilar to the way that you all are approaching it. We've kind of moved beyond this. I can't remember, I think it was Gareth kind of mentioned in the startup AI, but you know, I think this idea of looking for an individual ID and kind of chasing that around as a single point, we've moved beyond that. We now have a lot more information to use for decisioning. And taking that more cohorted, that more broad based approach to finding an impression, to finding a consumer is really, at least from our standpoint, where the market's going and it does it in a privacy safe way that puts consumers first. This idea of consumer control is something that we're talking about or consumer in control, which is something we're talking about at this conference. But it's this idea that as consumers, consumers are moving. They're choosing whether they opt in or opt out, they're choosing whether app not to track or app track. And you know, that's creating an interesting dichotomy between marketers, advertisers, publishers that I don't know, that we've seen and it seems feels like we're kind of hitting that inflection point. So as we have all of this data kind of historically, right. We would have taken all these attributes, appended them all together and targeted the three people that made sense there. So how do you take all of that data and make it scalable across the open web, make it work beyond kind of, you know, a very narrow perspective so that you can deliver reach, scale, relevancy and outcomes for PMG's customer base.
- [09:13]
C
So I think the perspective that we've developed over time is precision can actually be at different levels, at different stages in the campaign life cycle. So when you think about something like creating those insights that I'm talking about, taking their first party data, extracting it, understanding insights, pulling that into an audience. For strategy, we have a feature called Audience Planner which effectively allows our teams to build a digital twin of the consumer that they're trying to reach and that uses billions of points of data. It's talking about, you know, how do we find them in different media mix, what media are they consuming, what are they shopping for? How do they map to Amazon DSP? How do we find them in TikTok and Snapchat? What influencers are they following? And this changes week by week, month by month. So having a live version of this digital twin as a proxy helps us. Even though we are creating, I guess, an amalgamation of a person, it actually keeps us a little bit more on top and reactive to where these consumer populations are instead of being super prescriptive about the one to one relationship. In fact, actually I read a study recently that the number of devices in households have gone up from 7 to 17 in the last 10 years. So the ability for someone, a brand who is not in this business to figure out what 17 devices map to the single person that they're trying to reach is impossible. So it's not really about that in depth precision at the brand level. It's about enabling them to work with third parties who know those consumers better than they do and who can find them across those devices.
- [11:13]
B
Yeah, no, that makes sense. 17 devices feels like a lot, but I guess, you know, my kids I think have half of them, so I don't want to count. It's just terrible. You know, when I think about all of those different aspects and tying that all out. Right. You need to differentiate kind of at that household level. Right. You need to know the folks that are in the household, which devices are tied to which Personas and then you have to go and decide, oh, do I want to reach them or do I not want to reach them? That is not an easy task. So let's say I believe everything that you are saying, Edge. Of course I do. You know, how do you then prove this outcome? Right. When I think back and you know, I have the gray hair to prove it, but when I think back on the way that we used to Measure results in digital marketing was dropped a cookie, it was cool. And then it was like, oh, they went to this website, then they went to that website, then they went to this website and then they checked out. And that is great. I have the attribution, thank you very much. Those digital breadcrumbs are declining. They don't really exist anymore. So how are you validating results now?
- [12:23]
C
Yeah. And we have to ask ourselves honestly, did they ever exist? I think we ourselves, yeah, that cookies were working, but I do, I do think so. We are very used to as marketers attributed, measurable. You know, what is the channel? What is it driving on one end and then incrementality and lift. I know they were just talking about that on the other end, which often takes a long time to measure and is not as directly correlated. I believe that we need to identify proxies in the middle. And what we are doing at PMG is building a brand equity model that looks at other signals that are mid level, mid funnel. So we can actually start to connect the dots between the top and the bottom. Things like brand sentiment. Everyone's measuring social sentiment, everybody's looking at kind of social conversations. But building a measurable proxy around how your brand is indexing against your competitive brands and how those are moving over time. We're looking at what we call brand curiosity. How are consumers looking for you? Where are they engaging with you? How are they searching for you? How are they coming onto your owned and earned properties? We're looking at market indicators like economic power. How does Wall street vote for your brand? Investors really are putting their confidence in your company when your stock price goes up. So how does that actually impact your brand equity? And then fourth is pricing power. How much can you charge and keep volume up compared to your competitive set? So you might be a Nike who can charge a lot of money and sell a lot of shoes, or you might be a Chinese brand who is on the other side of that. Yeah, you're not wearing Nike.
- [14:18]
B
I know, I made a mistake.
- [14:19]
C
Yeah, poor choice. You might be on the other side of the spectrum with low brand power and you can't charge very much. So those kinds of factors we can track over time. We are doing a study now of the last two years of data and looking these correlative metrics and how they predict outcomes at the end of the day, how they predict your revenue and moving channel budgets according to those measures.
- [14:46]
B
I think that, look, when you think about where you all are taking this as opposed to where we've been right in A very last touch world and kind of chasing that final impression, that final cookie, that final device id, whatever it may be to actually claim attribution for that. And then you're kind of layering brand sentiment. But it's a soft metric, right? You're like, okay, this is good, but how are we actually making this a true quantitative measure of this campaign and, and moving the needle? I love how you all are tying that out and tying it out not on a one to one basis, but you're looking at an aggregate population and you're trying to determine kind of are we moving this population as opposed to just all right, did we move these three people? Which I think, you know, for me at least, you know, as a consumer, right, this is much more relevant. This is actually the way that I buy. It's more than just kind of, you know, meeting me right before I got to the checkout counter. It's actually influencing that purchase along the way and influencing that purchase decision. So what I've heard you say is, okay, we're not targeting one to one. We're taking more of a cohort based approach. We're not measuring one to one. We are actually measuring an aggregate and looking at if we're moving populations and brand metrics. So is one to one identity dead? Are we over that now at these ad tech conferences or are we.
- [16:16]
C
I'd like to be spicy and say yes, I really would, but I do think it's evolving. I don't think it's quite dead. What I love about what you said earlier about consumer control is if you let's sit on the other side of the table, we're all also consumers. We're also buying things. We're also volunteering our information and giving it to brands. We're giving it to media publishers, we're giving it to Google. We are engaging with these brands in a way that we choose. And I love that for us, but I also love that for us as brands and agencies, because that means is you have a special relationship with your consumer. You know, where are they engaging with you? What are they buying for from you? Who are they buying it for? What are they saying about you? You can own that relationship and your consumers are leaning into that. They want to engage with you there, but they may not want to tell you what they're doing next week, or that they're planning a vacation to Rome, or that their kids are 5 and 12. What you do know about them is actually special to your relationship. And lean into that as you build then additional strategies and you want to understand them and where they're traveling to and how old their kids are, then rely on the partners that they are engaging with on that. So I might not tell, you know, Ralph Lauren that I am, that I have kids, but I will tell, you know, other kinds. You know, I'll tell my credit card company or my, my cell phone company because I have to buy them a line.
- [17:52]
B
Yes, please tell your cell phone company.
- [17:53]
C
Yes. So those kinds of relationships where we can really help each other build a true graph across the industry, it is really about that. Data is everywhere. Intelligence is not. Actually, if you want to put that up on the screen so you guys can get a bigger view of the little article, you can go to the next slide, guys. But this is really where I think we can lean in as an industry. And don't shy away from the fact that the consumers are taking back their data. Lean into it with them.
- [18:26]
B
This is so old school, this ad. I love it. It's absolutely love it. I'm like going back to old roots. Yeah. So with all of that going on, you know, it does feel like there's this value exchange between consumers, advertisers, marketers, publishers. And I think, you know, for me, where I sit at T Mobile, right, that's part of our ethos, right? We want to be returning value to our members. We want to make sure that every member as part of the T mobile family, right, we're returning value back to them. We have all programs launched associated to this. And as an advertiser, as a marketer, we want to make sure that that value exchange exists for our partners as well. And to that point, how do we actually begin to address that value gap? How do we run campaigns that are more meaningful? How do we bring that together as really kind of that value return to the consumer? If you were to go back in time, you said two years, but maybe five, we go five years. How would you re engineer this relationship with consumers? I think it's not just consumers like us, but your clients as a consumer too, right? So you're returning value to them, you're returning value to individual consumers. How would you re engage that relationship? How would you rebuild thinking back from the ground up, going back years?
- [20:01]
C
I mean, I do think that we're getting to the point where the relationships between consumers and brands are going to be much more durable. And if we could have done that five, 10 years ago, if we could have gotten away from cookie tracking and pixels and blockers and ad blockers and all this stuff that we had to deal with as a contend with as an industry. If we could have started that journey earlier, I think we'd be in a much better place now, a less painful transition. And I think we would all have been happier, actually, on the consumer side as well.
- [20:35]
B
Yeah, I love it. I think, you know, that makes complete sense to me. And so, Chrissy, in summation, we are moving on one to one, both targeting and from measurement standpoint. We're in a new era of consumer control and we need to meet that through this value exchange that we all provide. So thank you.
- [21:00]
C
Thank you. Thanks for having us.