Transcript

You're gonna probably irritate or alienate your potential customers because you've showed them the same ad so many times. They say, I just want this to go away. And so frequency capping is a really important part of a marketer strategy that you can't do without proper identity resolution.

Hi, everyone. And welcome to The Big Question where we tackle the topics shaping the future of marketing, data, and AI. I'm Jeff Dubois from LiveRamp. With me today are Daniella Harkins, SVP of go to market at LiveRamp, and Aaron Balkans who is the vice president of product strategy and identity at LiveRamp. Today's big question is, is identity resolution still relevant in the age of AI? You know, AI can now understand behavior, predict intent, and make decisions at incredible speed.

So one might argue that maybe marketers don't need to know exactly who someone is anymore because AI can connect the dots for us. Daniella, let's start with you. Is identity resolution still necessary in the age of AI?

So Jeff, not only would I say that it's necessary, I'd argue that it's more important than it's ever been. If you think about the opportunity and what's happening with AI as it becomes more and more adopted across the ecosystem, is that it's creating more data, more signals, and sometimes more silos than we've had in the past. And so really having a strong data foundation and being able to connect that data foundation becomes paramount. And like I said, it's more critical, I believe, than than it's ever been.

Erin, what about you? What do you think?

Yeah. I completely agree with Daniella. To say that a marketer may not need to know who they're contacting is a whole foreign concept to us. Like, know we want the brands and the advertisers to know who we are and what we like.

We want them to tailor their campaigns to us so we get ads that are relevant to us. And without knowing the identity of an individual and being able to connect all the different ways that they interact with your company, you really don't know the person. And so like your interactions with that person become like less genuine or less complete and holistic. They won't always have the context of an individual across all the different touch points and all the different interactions throughout the ecosystem.

And so identity to tie all those interactions together is is still as critical, you would even argue more critical than it's ever been.

Do the clients when you speak to LiveRamp clients, do you hear them asking this question specifically? Is this is identity something we still need to invest in?

Yeah. Our our clients do ask about this and like, how is identity changing in the face of AI? And we say we you still need to build that foundational understanding of your clients and your prospects. And they really care about making sure that we do it in a privacy forward way. And as we continue to build out this identity and make it more available for AI use, we ensure that we build upon the things our customers care a lot about, which is ensuring that their customers' data isn't compromised.

The questions aren't coming about whether or not it's important, but to Erin's point, it's how it's changing and how I, as a brand, think about it differently. What is the application? What are the use cases? Where is good enough versus not good enough? Where is it that we can rely on AI to make the connections versus really being able to leverage this kind of richer, identity strategy that connects all the data together?

You touched on the counterargument I wanted to bring up. If AI can understand context and intent and behavior and recognize patterns better than ever and well enough to predict what someone wants in the moment, maybe the future of marketing is less about identifying people and more about understanding all those signals that come in. What do you say to that argument?

It's not a question of, do I need an identity strategy or do I need to leverage all of the signals and the context and the connections that AI brings you? It's a question of and. And I think that's really the critical component. I think where Aaron and I sometimes don't necessarily see eye to eye is some of the use cases today, like targeting as an example.

A lot of folks will say, hey, listen, I can get good enough without needing to invest or needing to spend so much time around identity, leveraging all that AI now brings with us. Right? And so like there are use cases where someone might say this is good enough for the use case that I'm that I'm using like targeting. But then when you start thinking about optimization, thinking about measurement, knowing who that consumer is or being able to connect all those different data points together become really critical.

I think that there is is an argument to be made for good enough. However, we've all been inundated with like the same ad that is shown on our mobile device and then our TV and then in our email over and over and over again. And how advertisers keep that from happening is it's a it's a process called frequency capping. And if you don't know who you're targeting, then you don't know how many times you've targeted them.

And therefore you're gonna probably irritate or alienate your potential customers because you've showed them the same ad so many times. They say, I just want this to go away. And so frequency capping is a really important part of a marketer strategy that you can't do without proper identity resolution. And then to add on to Daniella's point about measurement, like you don't know how your campaigns are performing if you're not able to say I targeted Daniella so many times and I know the optimal amount of ads to show her is six times.

Without knowing how many times you target her, you won't know what the optimal amount of ads to show her is to get that conversion or to win her as a customer.

And it's also, if you think about like your own behaviors, think about all the different devices that you're engaging with to Erin's point. And so like the ability to not just connect data to a consumer, but be able to understand devices and behaviors across those devices becomes super critical. And you can't optimize effectively because you might be able to optimize within a, within a platform or within a channel. But the reality is that as consumers, we're engaging across all of these channels, across devices, even within a single channel. And so you need identity to be able to connect all of those things together and then not just maximize your marketing results and your media results, but really optimize the consumer experience.

Absolutely. And it's really important to be able to do this at the individual level, but also really important to do it at the household level. And so if you're Let's say you're using a CTV ad, you're not really gonna know who's on the other side of that television, whether it's me or my spouse. But if one of us makes the purchase, then that ad worked and you got your conversion. And so the ability to measure your campaign effectiveness will also rely not only on identifying the person, but being able to identify the other potential buyers in the household.

All right. So it sounds like identity resolution is still critical in the age of AI.

That is our take on The Big Question. Be sure to check out LiveRamp's website and YouTube channel for future episodes. And join us next time as we tackle another Big Question, shaping the future of marketing.