The Future of MarTech Doesn't Have to Be Complex or Creepy

The relationship between artificial intelligence and marketing has reached a fascinating inflection point. Rather than sparking fear about job displacement, AI presents an unprecedented opportunity for collaboration—enhancing human capabilities while handling data-intensive tasks that previously consumed valuable time.

Tara DeZeo, Pega's product marketing leader for customer decision hub, frames this shift perfectly: "If we think about AI as a collaboration partner versus a replacement for marketers, that's more how it's being used in marketing organizations and that's how it should be used." This view resonates with forward-thinking marketers who recognize that automation of routine tasks creates space for more strategic, creative work.

The conversation delves into one-to-one marketing—an approach that personalizes experiences at scale using real-time data signals. Unlike traditional segmentation that places customers into predetermined buckets, this AI-powered approach delivers contextually relevant communications when they matter most. Consider the banking app that recognizes when you've entered a wildfire zone and offers emergency resources instead of credit card promotions. That's not just smart marketing; it's empathetic engagement that builds lasting trust.

As third-party cookies fade into obsolescence, marketers face a critical inflection point. The solution isn't to abandon personalization but to reimagine it through first-party and "zero-party" data—information willingly shared by customers. This shift demands transparency about how data will be used, creating a foundation for more meaningful relationships. As DeZeo notes, "We weren't very transparent about how we were using third-party cookies... we just obfuscated that from the consumer to the point where it became a problem."

Looking ahead, Pega's Customer Engagement Blueprint represents a significant advancement in visualizing AI-powered marketing journeys, helping even traditional marketers evolve their approaches while identifying gaps in current programs. The vision for tomorrow centers on "scaling personalization without complexity"—activated data, unified experiences, and genuine connections that feel helpful rather than intrusive. 

Try Blueprint for yourself at pega.com/blueprint and discover how AI can transform your marketing from merely transactional to truly transformational.

🌎 Watch Tara's interview on YouTube - https://youtu.be/pGg_S9h5mIk

Chapters

• 0:00 Introduction and AI Marketing Fears
• 2:53 One-to-One Marketing and Real Examples
• 4:30 Empathy in AI-Driven Customer Communications
• 7:38 Life After Third-Party Cookies
• 11:06 Blueprint: Visualizing AI-Powered Marketing
• 14:05 The Future of MarTech

Transcript

Speaker 1: 0:00

My name is Tara Dezeo. I'm the leader of product marketing for Pega's customer decision hub. I'm a subject matter expert in MarTech and AdTech and I've held a variety of positions in a variety of marketing organizations. So I landed at Pega because the job title that I applied to had the terms AdTech and MarTech in it and I had never seen that before and I was like this job was meant for me and you got it so.

Speaker 2: 0:30

I did get it, I did get it and I'm glad it's working out as well, yeah, my colleagues are so amazing.

Speaker 1: 0:36

I love working here. I hear that a lot.

Speaker 2: 0:37

I hear that a lot. So let's jump into the topic here. Yeah, marketing is complicated for some people, yes, and then you put AI, and then you put agentics in and you layer that on top and then it's more frightening for people, yeah. So bring it down to a level that I can understand, bring it home, decomplicate it and take away some of the fear.

Speaker 1: 1:01

Yeah, sure, I mean. I think there's fear in a couple of levels, right. There's the fear around uncertainty with what AI is capable of, and then there's the fear that marketers have of it replacing them, and I think that, if we think about AI as a collaboration partner versus a replacement for marketers, that's more how it's being used in marketing organizations and that's how it should be used, right. It shouldn't be a replacement for a marketer, so to speak. I mean, I'm sure there's roles that it may usurp eventually, but I would say it's more of a collaboration tool, right, that we have going. And then the fear around AI. I understand that because, I mean, I'm in the industry and sometimes I feel afraid when we hear what it's capable of, like, you heard Rob's keynote. The good news about that, though, is that there's a lot of really smart people that are trying to figure out how to use AI responsibly and ethically all the time, and there's a lot of people that care about using AI the right way.

Speaker 2: 2:02

Good, as do we as well.

Speaker 1: 2:04

Yes, yeah.

Speaker 2: 2:05

Do you know? This is the oddity. I actually don't mind AI replacing lots of things that I do. Sure, because when I sit here and say, do I really want to be doing the exact same things in the exact same way in five years' time? Heck, no, heck, no. So I'm actually happy and my friends of mine who going, they feel the same thing because there's so much of it could be automated, digitized, yeah, and everything else to free them up to do the stuff that is really significant and really really turns the dial. One of the things we talk about we've heard at the conference here is is one-to-one marketing and how AI is making that possible. Yes and Jenny, what, what does that even mean? And what our company's doing. Do we have any examples of hero companies here today?

Speaker 2: 2:45

that are really using AI to make things sing.

Speaker 1: 2:48

Yeah, so one-to-one marketing and customer engagement is exactly what it sounds like. It's being able to scale personalization to people individually, and AI makes that possible. So you know, we have various stages that marketers are in. We have traditional marketers that are still doing campaigns, all the way up to folks who are using self-optimizing AI in their marketing programs, and it's really about being able to ingest data signals in real time and then tailoring that interaction based on the signals that you just got. So, for example, I use a lot of examples that I've experienced my banking app. I live in seattle and I, once I drive over the border into portland, oregon, my banking app pops up a notification that, hey, you can use your banking app on public transit in portland, which that tells me that they know me because I use public transit a lot in Seattle. So they have a lot of first-party data and they're activating it in the right way and that's what we're trying to achieve.

Speaker 2: 3:53

I like that. That feels more like triggers, as opposed to using traditional AI that puts people into a bucket and then sends them messages because that isn't personal or doesn't feel personal.

Speaker 1: 4:05

No, that's more segmented, I would say for sure.

Speaker 2: 4:07

Okay, how do we get? Because if we're saying that we're going to get the AI to augment people in marketing, how do we get it to augment and not replace? So, in other words, how do we get employees in banks, in whatever company at all, to actually understand their role, their position, how they should use the AI to actually enhance the service? Because AI is one thing, data is another, but unless you actually operationalize it and make it work for the customer, then it's just data.

Speaker 1: 4:37

Yeah, and I think also two levels there, right, there's the way that brands use AI to talk to their own customers, and then there's using AI inside your own marketing department to make your job easier, right? So I feel like the the connection point there is essentially it's a. It's a slow drip, making your employees understand what AI can do for them. We do a really good job of that at Pega. We have workshops and our marketing team tries to educate all of us on how to use the tools that are available to us, and I think, as it relates to deploying AI in your customer engagement programs, I always say you don't have to rip and replace. It can be like a crawl, walk, run moment, right, we're not. You know, there's an adoption curve. You're not just going to wake up one day and be able to use AI in the exact way it's intended and have your models working amazingly instantly. It's a learning curve.

Speaker 2: 5:43

So the marketing's not real. It's not real yeah yeah, it's.

Speaker 1: 5:46

You know we're all. Clients are at different stages of maturity in many areas, and marketing is one of those areas, for sure.

Speaker 2: 5:58

So how do we put empathy into the actual communication? If a machine is deciding the campaigns, if a machine is triggering, where does it feel human? Where's that empathy in those communications that we would want to see or feel?

Speaker 1: 6:10

Yeah, I think it comes down to contextual data, right? So if I'm in an area that's impacted by wildfires, say, maybe that's not a great time during the wildfire to try to sell me a credit card, so it's thinking about using, maybe, location data to understand? Ok, let's not talk to this person right now. Or let's say, hey, are you separated from your wallet? Did you know you can use your app to access the ATM? If you need cash? There's, you know. I've seen banks actually put hurricane messaging up and saying here are the shelters and the centers and the Red Cross areas where you can access that. So if you still have a working phone and you log into the mobile app, that's the message that you're gonna get see that's useful.

Speaker 2: 7:04

Yes, that then. Do I want a relationship with my bank? I don't really, but do I want a bank that's purposeful, that's using AI and generative AI and agentics to deliver value to me in a moment that matters to me? Absolutely. That would get my loyalty. I noticed in the market a little while ago, we started hearing a lot of conversation around third party cookies being phased out and going away. So how are businesses actually going to get hold of the information and the context and everything else that they need without third-party cookies going to be available?

Speaker 1: 7:38

Yeah, I think it's a way of thinking about first-party data and how we can expand that definition. So, if you think about zero-party data, that's essentially consented data that the customer gives you that's not related to them being logged on, so to speak. So that's a form of first-party data. We call it zero-party data, but I always talk about Brooks Running. They're not a client of ours, but when you go to their website, they just ask you four questions about the way that you run, and that gives them contextual information that they wouldn't have otherwise about you, so that if you decide then to log in at that moment or create an account, they already know a little bit about you in a way.

Speaker 1: 8:25

That is not what we would say creepy right Marketing term. Yes, already know a little bit about you. In a way. That is not what we would say creepy right marketing. Yes, and third-party cookies in that world it was more oh my god, that ad is following me around everywhere that I go. I maybe already bought that product if there's no closed loop with third-party cookies. So, yeah, you could be potentially like stalked by an ad.

Speaker 2: 8:49

Which it often felt like, and then that lost the trust, that lost the empathy and that was using AI or scale communications in a way that really didn't feel in service of the customer. Yes, it felt in service of the brand, in service of the business, not in service of me.

Speaker 1: 9:05

Right, and I think, too, you know what you'll hear a lot of our clients talk about, or what you may have at the conference, is the value of transparency. So we weren't very transparent about how we were using third-party cookies and it was not, in most cases, very nefarious. You know, we're trying to help you buy products and shop and we just obfuscated that from the consumer to the point where it became a problem. And you know, here we are.

Speaker 2: 9:34

Yeah, which felt more like marketed at as opposed to marketed for which was never an attractive moment. So how do we bring forward scalable, high-powered marketing when the cookies are disappearing and we still need to deliver empathy? And how will agentics play a role in that mix?

Speaker 1: 9:55

Yeah, you know, I think, if you think about the operations of marketing, agentic is going to help with that a lot, right? So you know I was talking to someone yesterday about I know that brands are creating creative centers within their organization where an agent you might upload your brand guidelines and the agent then can you know, check to make sure that your creatives are all on brand. They're creating, maybe predictors out of data and the agent to funnel into the whole lifecycle of their marketing. I think that you know for outbound marketers, what they're sometimes missing is that link to you know what's happening on the inbound channel and if you can use your data from inbound to power agents, say on outbound, that's gonna make customer experiences way better because it's a more informed interaction yeah, so you have the full picture.

Speaker 2: 10:58

They're not half of the picture. One of the things that is featured really prominently this week at PegaWorld has been blueprint. Yes, would you mind giving us a little bit more detail around blueprint and how that can help with marketing?

Speaker 1: 11:12

yes, I'm so excited about Blueprint, so we launched Customer Engagement Blueprint in February and it's a tool that helps you ideate what your marketing programs could look like, what your customer journeys could look like with AI powered decisioning, and it helps folks who maybe are traditional marketers move into the next phase of their marketing.

Speaker 1: 11:36

It helps people that are just implementing CDH really understand what they could do, what channels are going to be best, and it's an aspirational view of what your customer is going to see with your marketing.

Speaker 1: 11:51

And then, lastly, for the folks that are already bought in on AI-powered decisioning, it's a way to expand your use cases and your product lines. And one of the things that we talk about a lot is when you're first moving from traditional marketing to a next best action AI-powered marketing. It's the marketer's job to educate the stakeholders that aren't inside of marketing, and with Blueprint, you can actually export your Blueprint and share it with your org. People in your org can collaborate and say hey, I know I've been talking about customer journeys, but I haven't really been able to show you this. Here's what it looks like. Or you can see in real time why an interaction might change mid-journey, which is an abstract concept, right, that we're not able to show, we're able to tell. So this is more of a way to visualize aspirational customer journeys and marketing in a way that we haven't seen before.

Speaker 2: 12:52

Which is really exciting, because that's always been the challenge. You have people in technology or more tech, who know what they want to do, they know what the outcome is going to be, but they can't quite explain it in a way that's visual, and the last stat I saw was 60% to 70% of the population is visual. So if you show me it all of a sudden, now I'm part of the narrative, and then with Blueprint as well, and folks, if you haven't tried it, go to peggacom forward, slash Blueprint Now I'm able to see what's happening in real time. Now, if I'm part of the business, I can be engaged in that design and I can see what's happening at that moment in time and it seems so simple. And it's this tool I wish I had 30 years ago, when I started out in tech 30 years ago when I started out in tech.

Speaker 2: 13:33

I know, I know, but it's there and it's available and it works, and we've heard that this week as well.

Speaker 1: 13:36

Absolutely, and you know we've had clients too, understand what gaps they have in their program. So what they aren't saying by using Blueprint.

Speaker 2: 13:47

Wow, Wow. That's powerful in itself. So then, close some of the gaps and we're good. So look, if we finish off here, what is the future of MarTech and what is the future that PEG is trying to build to put AI, Gen AI and agentic AI into place to meet that future.

Speaker 1: 14:05

Yeah, I think it's really about scaling personalization without complexity, because MarTech stacks are so complex and they're disconnected, they create data silos, they create wasted impressions, they erode consumer attention, and what we're trying to do is use AI to create connected experiences where the data is activated in the right channel at the right moment, so that you're being able to scale personalization in an environment that's fully unified which I'll make, which I'll feel a lot better, not only for the business, yes, but for the consumer.

Speaker 2: 14:40

If we're sitting here in 12 months time, what are you going to be talking about then? What are you going to say? Has happened? What has pega delivered?

Speaker 1: 14:46

yeah, I think we're gonna have, uh, more folks moving away from traditional marketing approaches to transformative marketing approaches. We're gonna see the promise of agentic AI instead of the you know aspirational. We're gonna start seeing it pay off. We're gonna see the early adopters of agentic start to like realize the fruits of their you know early investment. So the next 12 months are going to be very, very interesting, for sure okay, so we've got tyra's predictions there.

Speaker 2: 15:20

We will come back in 12 months time. Yes, we'll hold you accountable for every single one of those and we'll see what happens can't wait I wish you every success thank you.

Speaker 1: 15:28

I tend to be right most of the time, so I'm not going to argue with that brilliant thank you.

Speaker 2: 15:33

So much indeed, thank you.