B (3:08)

Yeah, yeah.

A (3:09)

And he actually, I thought he put this so well. This was the early days of E Com, when a company's website was equally about their brand presence and their digital presence and engagement as much as it was about shopping and product promotion and transacting and all that. So that's where my early roles were. It was around email marketing, growth marketing, E commerce, Those are very much deep in like the tools, the systems, audience segmentation. It's where I learned all the mechanics of Martech and Marops. But I think because I came up in my marketing career during that, during that era of E commerce, I'm also very well versed in the digital storytelling, how to introduce a brand online, driving the consumer behavior, engagement outside of just pure shopping. And then from there I spent four years at Uber primarily focused on our safety portfolio. This experience really introduced me to that tension between growth, between trust. How are you balancing customer acquisition, engagement, aggressive growth targets, while ensuring transparency, building user confidence and brand favorability. And I think all that's kind of come together nicely in my work now at Transcend where we're helping these Fortune 500 companies and category leaders enable that growth and that innovation within frankly like a risk sensitive, a technical environment that is personal data collection, personal data storage, downstream activation, all the, you know, bits and bobs to make that plumbing happen and all the user preferences and choices that empower that data to flow through that layer. So I actually really like to say that, you know, within every modern growth initiative, whether that's a shopping journey, an ad experience, this relies on first party and zero party data, of course, and that personal data must be consented to, it must be ethically collected and then properly governed downstream in order to even make these really cool, sexy digital projects and growth initiatives possible. There is actually that, that, that middle layer. This is where Transcend plays. It's not easy, right? There's a lot that needs to happen to bring all that together seamlessly and accurately and ethically, whether that is stitching together identifiers across different tools, you know, ensuring that user choices are enforced, consistently collected in real time, activated across all the marketing, advertising, third party systems that, you know, any modern enterprise is plugged into. But I'm a marketer myself, I've always been a marketer and I like to kind of zoom out and even look at the layer before that, which is you need individuals to even a know your brand and then you know, have confidence in who you are, build a trust and relationship before they're even going to raise their hand and entertain the option of giving you access to, to their data and consenting to that. Right, so transcend plays on that middle layer of the data capture and permissioning and downstream activation. But really this is a marketers problem. You know, from brand awareness all the way through to the martech and the marops.

B (6:09)

Yeah, yeah.

C (6:10)

And so yeah, let's let, let's dive into that and really start with this. You know, it's, it's certainly a strategic imperative to say that, you know, we need to reconcile much to what you're just saying. Reconciling this need for very laser focused personalization as well as the need for data privacy and doing that. You know, there's lots of things going on in the background that you know, I know, you know, many listeners, if not all listeners are aware of but may not know what to do about necessarily, you know, shared cultural moments, you know, kind of disappearing or maybe being minimized in some ways. AI commoditizing content again, you know, with all of this really the, the answer is this, this really narrow and, and focused personalization. So from a strategic viewpoint, why is the, that old marketing playbook of broad stroke segmentation just not breaking through the noise and not, not effective?

A (7:13)

Yeah, I mean I think that's a lot of what you said. You know, we're increasingly in a digital world where we're looking at echo chambers of our algorithms and our, and our own content. There's fewer of those shared cultural moments to, to build personalization around. AI is really leveling the playing field on creative output. So differentiating is going to take more in terms of how a brand shows up, how they activate their data, the relationship they build with their customer. I was actually just at an event with a bunch of other B2B marketers this week and we were joking about how sad it was that we were all sold this very shallow version of personalization which was just like hi first name, nice to see that you work at company. Like that is not personalization. And people are, you know, today's consumers are digitally savvy and they want, and they expect a lot more of that. So I really, yeah, 100% agree with you. The future is going to be towards more and more laser focused and pinpoint personalization. But I do want to call out like this is very Much still like a crawl, walk, run thing. There's still a lot to be gained from the sort of broader strokes motions. We actually at Transcend did some research and put out a report earlier this year where we surveyed marketing, security and privacy professionals. In that research, only 42% of those respondents even told us that they were using preference data to do things like personalized campaigns, personalized offers. So there's still so much untapped opportunity here. But I think, you know, to put on the consumer hat this is where, this is where consumer expectations are going. This is where digital behavior is pointing to.

B (8:45)

Yeah, yeah. Well, yeah.

C (8:47)

And I think, you know, consumers, even if they don't know how marketing works from, you know, the, the detailed view, I think they can, they're savvy enough to know they, they know the. I call it substitute like first, you know, insert first name here. Like that's to your point, that's not personalization. That's like substitution of, of, you know, hello or whatever. And so, you know, I think they're, they're, they're savvy and they're getting savvy savior as well. You know, I think to, to point to the, the report that you recently put out as well. You know, one of the other things that I found interesting in there is most companies have massive amounts of what's referred to as shadow data. And just curious if you could talk a little bit more about that and just how does this undermine or affect that consumer trust that's so critical here as well?

A (9:44)

Yeah. And in situ. So shadow data, that's really data that's collected without awareness, or maybe it's ungoverned. Maybe it's, you know, it was collected ethically in this one use case, in this one channel, but it is living in a certain silo within the business or within the company's data ecosystem. So all that shadow data floating throughout an organization's tech stack that creates unseen risks, that erodes transparency. And as a marketer, as an operator, you don't always know what data is permissible to use. And then if you, we like to at transcend, we like to talk about this concept of like over permissioning and under permissioning, over permissioning means you're using data, you're using, you know, personal data where you probably shouldn't, or you're using it in a way where it wasn't consented to. And that is what, you know, leads to the, of course, the regulatory risks and just like overreaching, but also just erodes transparency because to your Point like customers are smart now. They like, they know when personalization is shallow and just like a dynamic field substitution. But they also can instinctively sense, you know, when brands overreach or they mishandle data and that leads to far graver consequences. Opt outs, people just like churning off of your, your brand or just completely blocking ads and that just kills personalization, like right out the source.

C (11:14)

And so, you know, building, building on this, this idea of, of building trust and this foundation of trust. Recent stats from Adobe found 71% of consumers see personalization as critical, but only 34% think that brands actually deliver. It kind of mirrors what you were saying earlier. You know, what do we do here? You know, what, what are maybe the first one or two things that a marketing leader should do to start closing this, this considerable gap?

A (11:42)

Yeah, yeah, because we can talk all we want about this is an issue like what are your steps? Right. So I think the first one really is to outline audit, architect the data touch points across your user experience. And that includes everything from third party partnerships to of course your own channels and own experiences. So just identify where user choices are being collected or where they're just being utilized to deliver a certain message or certain creative, a certain experience. And then really it's about operationalizing those user choices. So preference signals, when Greg, you say I consent to this, but I don't consent to this and I'm going to show you this, but only use my biometric data in context of X. All of those preference signals need to be deeply integrated within a Martech stack in this example. So your CRM, your ad platforms, anything else in that customer service, all those channels that then go out and touch those users, again, need to be able to operate on compliant and real time data. And this actually needs to be a fairly deep integration because I can't simply just say, hey, meta ads, don't advertise to Greg, there's an actual signal, I need to flip the flat. All of that is very robust. So that needs to be deeply connected. And that's, that's kind of the meat of it. And you know, that means like this is, I think a lot of companies, they have technology in place of course to market and advertise and collect data. But companies also, from what we've seen working with our customers is that they rely on process and people to fill some of those technology gaps that of course, you know, results in just human error, some inefficiencies and frankly like way too many CSV files that's saved on an individual desktop Somewhere else.

C (13:34)

I've seen some of those. Yeah, yeah.

A (13:36)

Oh yeah, yeah. I've been guilty in a past life too, for sure.

C (13:40)

Yeah. Yeah. And, and you know, I mean, of course from the, from the consumer perspective, it's like to get someone to consent to that, you know, brands can't take that for granted anymore of just, you know, the consumers are just going to blanket accept that things. And so this brings us to this, this value exchange which, you know, the consumers need to feel like if I give something to this hotel company that I'm going to get the room that I want when I, when I, you know, first time I check in or, or whatever, you know, there's, there's got to be that, that value exchange. So, you know, beyond simply just saying we're going to give you a better experience, you know, quote unquote, whatever that means.

A (14:24)

Yeah.

C (14:25)

What are like tangible examples that, you know, could convince that, that savvy consumer to, to willingly trust a brand with their data?

A (14:34)

Yeah, well, this is like, this is where it gets fun, right? This is where you're able to build really valuable, meaningful and personalized experiences. And that, that definition of, you know, value and a tangible experience can mean so many different things. Personalized loyalty or rewards that visibly reflect those data choices. So I think a lot of retailers do this. Well, Sephora's like rewards program is a great example. They're asking for, you know, your eye color, your skin tone and being able to then take those preferences once a consumer has opted in and turn that around to personalized recommendations. A lot of financial services apps will do this with credit insights or budgeting tips in exchange for seeing a user's transaction data. Right. That just makes the experience more valuable and personal. And I think we can't forget real utility by way of convenience, by way of time savings, continuity. So cross device experiences when a user is opted in that persist across different devices or browsers, wish lists, transactions, that kind of stuff, that's real utility. And it's not just like being marketed to in a better way.

B (15:45)

Yeah, yeah.

C (15:46)

I mean, I think. And maybe that's underrated, I would say, you know, in, you know, but. And yet as a consumer, because we're all also, you know, we're marketers, but we're also consumers in real life. I mean, some of those, the utility stuff is what I value the most and.

A (16:03)

Yeah, yeah, yeah, totally, totally. And it's, you're right, it is undervalued from the organization, the operator's perspective, because it's not, it's Part of like our. It's table stakes now in our digital world. Right. But it's not the flip of a switch. Like, there's actually a lot of data and plumbing and user choices and all that needs to line up to even be able to deliver that baseline digital experience seamlessly.

C (16:28)

Yeah. And I think, you know, I was just doing an interview a little while ago of just on how simple things are. Often, you know, making something simple for a consumer is often very complex from a technical perspective. And so, you know, it's why companies like Apple, you know, like the design. From that design perspective, it's like, yes, a lot of thought goes into these very seemingly simple things.

A (16:54)

So, yeah, the same with copy. The fewer the words, the more time it took to capture.

C (16:58)

Totally, totally. Yeah, yeah, yeah. So I want to talk now about, you know, a lot of, let's say, data privacy conversations often start with this idea of, you know, risk mitigation, you know, avoiding fines, you know, GDPR and all that kind of stuff. And certainly that's. That stuff is very important and needed. But there's lots of components. I mean, we've already talked about several components of this and the importance of data privacy. You know, how can marketing leaders kind of reframe this as not just risk mitigation and avoiding the negative part, but really the positive business impact of strong privacy practices?

A (17:45)

Yeah, yeah. I think this is such a great question because so oftentimes marketers are thinking about privacy as a, like last mile, check the box before I hit deploy. But really a lot of this needs to be thought about so much further upstream. And we're just not used to thinking that way because privacy as a term, as a department, it just feels removed from our day to day. But just coming back to this theme of over permissioning versus under permissioning user data, I think this is actually a good analogy for that privacy marketing tension. So traditionally, when we think about avoiding fines or being audited or even grand backlash if there's a breach or something bad happens, the way that people try to solve that and the way organizations try to solve that right now is through under permissioning. We're just going to do less. We'll just sit with our hand, you know, sit on top of our hands and only do like whatever we feel comfortable with, with whatever risk appetite or the flip side to that is some companies will just say, you know, a fine is a risk, like cost of doing business, and we're just going to keep pushing forward with it because the upside is greater. Really, like the way I would tell marketers just to, to start to think about this reframe is that we need to be able to show that trustworthy data pipeline is expandable, use usable data. So that expands your overall audience size and under permissioning is actually leading to a huge opportunity cost. You're not able to market to an additional audience or perhaps you need to actually just do more generalized marketing to everyone even if parts of your audience are irrelevant. That's wasted ad spend, that's higher route. Like, you know, that's also not great. And so I think that's, that's the area. Whereas marketers, you know, we're good at this. We can chase those metrics downstream into the KPIs that we want that we need to tell, you know, specific stories. Whether that is translating across, you know, opt outs to our overall kind of marketable audience to how that impacts like customer LTV or engagement rates or even basket size. By being able to show the right recommendations. I would really think about it as opportunity costs and being able to like how large is your available audience to market to and how much do you know about them such that you can do it in a very strategic and resource and ad spend efficient way.

B (20:07)

Yeah, yeah.

C (20:07)

I mean, yeah, I've been, you know, outside of podcasting, I do consulting for enterprise orgs and I've been in those conversations where we are literally letting money sit on the table, so to speak, because it's a, it's a lowest common denominator approach. And some of these, these orgs at least it's like, you know, and, and again, totally, I respect the risk aversion, but at the same time, to your point, there's so much opportunity there to do it and, and there's tools to, to allow us to do it well. Right.

A (20:40)

So yeah, definitely not saying just like throw your risk gene out the door and go wild, but yeah, there are tools to do this stuff more surgically such that you don't need to just do lowest common denominator marketing or strategy and you can, you know, reach across brand audience or reach a different segment that you otherwise wouldn't have been able to tap into.

B (21:00)

Yeah, yeah.

C (21:01)

And so, you know, a lot of companies are, you know, some are way further ahead on the, on the AI adoption scale, some a little further behind. But certainly, you know, personalization powered by AI is something, I mean I, I love the promise of that because I think, you know, we've been talking about personalization for years and I think some of the recent, you know, generative AI stuff is helping us unlock some of that stuff. But certainly it also brings some, you know, additional concerns of, you know, personalization powered by AI. How can teams be confident that the data that they're using still, you know, kind of reflects that, that customer intent that we're talking about.

A (21:45)

Yeah, yeah, for sure. And I agree with you. It's an exciting, it's an exciting time to be a marketer. But this is very much still, you know, I think we're all still working through this, even the companies that are out ahead and adopting this. The one thing I can say though is that as we do more and more AI powered personalization campaigns and outreach, the data inputs and how data like lives within an enterprise ecosystem is only going to get messier and more circuitous in the sense that like, you'll be, you'll be further more degrees removed from that point in time where a user gave consent or told you their preferences or gave you that, you know, first or zero party data. The data is going to start to train on itself. It's going to get circuitous and messy. All of this is going to increase in its importance. One of the main data actions that we had been seeing customers pull across into their world and into their user experiences is the do not train action. So you, Greg, could say, hey, I'm, I'm trying, I want to engage with this AI product or I want this AI powered experience. But I don't want you to train on the data that I'm giving back to you or the data that you're using. And being able to honor that signal, of course is, is technically going to get more and more complex with these circuitous data cycles. But that is where this is going to go. It's going to be less around like, oh, I accept cookies to understanding if your data is being used to train either your own experience, maybe that's okay from a consumer standpoint, or if your data is being used to train a larger model. Again, maybe some consumers are fine with that in certain instances or not, but this is where it's going to get increasingly more granular. And I think we're certainly, you know, we're certainly at the early stages of this and it's going to be fun to, to watch this all unfold.

C (23:33)

Yeah, yeah, definitely. So, yeah, and kind of to that point talking about, you know, kind of what's next as kind of wrap up here. Yeah, you know, getting, getting all of this.

B (23:44)

Right.

C (23:45)

It's not just about the, the marketers and the cmo, but it's about, you Know, cmo, cio, you know, ciso, you know, all, all of the, all of the acronyms. Right. Like kind of get it getting together. Right. So, you know, how do you, how do you see the responsibilities of these roles converging, diverging, you know, how, you know, how do you see this kind of playing out over the, over the next few years?

A (24:08)

Yeah, it's a great question. And I think the companies that do this well will have leaders that are able to speak each other's languages and also ensure that collaboration not only starts at the very top, but it happens in tight partnerships throughout the organization. Because like we were talking about earlier, the guy with the CSV is on his desktop, needs to be able to then go back and talk to his counterparts in different organizations. But around those different functions, I think it really is going to be about the CIO and the IT department ensuring that the data that the enterprise has is discoverable. So, you know where it is. There's none of that shadow data governable. It's interoperable between systems. The ciso, and oftentimes the privacy leader here is also going to ensure that it's ethically collected. It's secure access controls following regulatory requirements. The CMO and their org, it's their job to really take that data foundation and translate that into customer value, into loyalty, into engagement. And I think the part that we need to really make sure as marketers that we're keeping our pulse on is that it's also the marketer's role to go back up and advocate for the data foundation that they need to drive those initiatives and growth goals. I think this is a little bit to marketing's detriment. We're so oftentimes we're on the receiving end of the data that comes out and we're just like, well, this is what we can do. Or this is like, that's that.

B (25:37)

Right.

A (25:37)

And really, I think it's up to the marketers to really understand the upstream data collection, data piping points and advocate for what they need.

B (25:46)

Yeah, yeah.

C (25:47)

And then, you know, kind of from the consumer standpoint, you know, kind of looking out a bit, you know, there's kind of. There's kind of two extremes, and I don't think either of them will be 100% true. But, you know, there's this, this world where, you know, AI just kind of does all personalization and, you know, kind of, I get maybe it runs amok, let's say, because we're talking extremes or, you know, there's. There's this Other extreme where consumers hold their data so tightly that the AI doesn't have enough information to work off of. You know, where, you know, where do you see things kind of netting out after? You know, admittedly we, I think we all have some things to work out as an industry probably, but.

A (26:28)

But yeah, yeah, yeah. It's, it's definitely going to be a dual reality like the AI automating personalization that trains out the station. But I think consumers are, you know, increasingly demanding more controls, more transparency around their data and how it's being used. And eventually, hopefully I'm, I'm very optimistic and hopeful here that consumers will advocate for a world where they can gate access to their data through whether it's layers of consent or certain touch points or certain ecosystems. And then it'll be on the enterprises and the companies to make sure those worlds and those journeys and those specific touch points are clearly communicated and surface as choices. And then of course, honored on the back end.

B (27:08)

Yeah, yeah. Love it.

C (27:10)

Well, Phyllis, thanks so much for joining today. Really, really enjoyed talking about this with you. One last question before we wrap up. What do you do to stay agile in your role and how do you find a way to do it consistently?

A (27:21)

It's a great question. There's so much great content and expert voices out there. I think, like, like I said earlier, it's a really fun time to be in marketing. So there. But there's a lot to consume and learn from. Right. And I've really found for myself that you need the fallow time to, to borrow the term from agriculture, to really just let it percolate and crystallize into actual projects or original thoughts. For me, that's making sure I'm able to go take a walk. I, for better or for worse, live near some cell phone dead sims. So sometimes I'm just like, well, I don't have service. I guess I'm, I'm gonna just think about things. So it's walking or maybe I'm just like doodling on my sketchpad, but getting out of digital and just like moving my body in some way to really let that kind of marinate in order to stay agile.

B (28:06)

Yeah.

A (28:07)

Love it.

C (28:08)

Well, again, I'd like to thank Phyllis Fang, head of marketing at Transcend, for joining the show. You can learn more about Phyllis and.

B (28:14)

Transcend by following the links in the show notes. This show is brought to you by Transcend, the privacy infrastructure company that unleashes growth for the world's leading brands. Unlike legacy tools which create manual bottlenecks, Transcend embeds data and consumer preference governance directly into business systems so teams can confidently and quickly activate data for AI personalized experiences, customer engagement and growth at scale and with reduced risk. Learn more at www.transcend.IO. thanks again for listening to the Agile Brand. If you enjoyed the show, please take a minute to subscribe and leave us a rating so that others can find the show as well. You can access more episodes of the show@theagilebrand.com that's the agile brand.com and contact me. If you're interested in consulting or advisory services or are looking for a speaker for your next event, go to www.gregkilstrom.com that's G R E G K I H L S t r o m.com the Agile brand is produced by Missing Link, a Latina owned, strategy driven, creatively fueled producer production co op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. Until next time, stay curious and stay agile.

A (29:43)

The Agile Brand.

B (29:48)

Before we continue, I wanted to share a key strategic resource that a majority of the Fortune 500 are already aware of. Finding the best technology, business and talent solutions is not easy. With business demands and competitive pressures mounting, you need to be able to design, deploy and optimize your technology to provide leading customer experiences while driving business growth. Those of you that have been listening to this show for a while know that this podcast is brought to you by Tech Systems, a global provider of technology, business and talent solutions for more than 80% of the Fortune 500. Tech Systems accelerates business transformation for their customers. Whether you're looking to maximize your technology roi, drive business growth, or elevate customer experiences, Tech Systems enables enterprises to capitalize on change. Learn more@techsystems.com that's T E K systems.com now let's get back to the show.