[00:00:00] Scott Wolfe: All right, I think we can go ahead and get started. Thank you everyone so much for joining us today. We are here to talk about everything related to audience data and how it can help you unlock some new opportunities. Before we dive in though, just a few housekeeping notes: this session will indeed be recorded so you can access it later. Um, we’ll also send you a follow-up email with the slides and recordings, so no need to worry about taking any notes today. If you have any questions, go ahead and drop them into the bottom in the Q&A section. Uh, we’ll get to questions through—um, at the end of—of the session today. We want this to be interactive, so we definitely want to give you the chance to drop in questions.
[00:00:38] Scott Wolfe: My name is Scott Wolfe, I’m the Principal Product Marketing Manager here at SheerID. I’ve been with the company for, let’s see, about, uh, four years now. Uh, doing everything related to product marketing but also primarily focused on everything related to data. And so, really excited to announce my counterpart here, but before we get into that, um, when people think about SheerID and audience verification, it’s more about the—the—than the initial verification. You know, it’s about creating those authentic, genuine, emotional connections, but it goes beyond just that initial verification. It goes about the data that you get from that. So, with that, I want to introduce my exciting counterpart today, Scott Dylag. Scott?
[00:01:19] Scott Dylag: Yeah, thank you so much, Scott. Uh, yes, great names think alike after all. Um, and thank you to the SheerID leadership team for having me speak with y’all today. Um, my name is Scott Dylag. I’m currently the owner, principal consultant for my own independent retail consultancy, JSD Digital. But, uh, prior to that, however, I was—uh, I spent the last 20 years building and scaling Nike’s online business, both domestically, uh, and then across the globe. Um, and during my time at the swoosh, I held a—a number of leadership roles across technology, capability development, customer experience, operations, business leadership, a lot—a lot of different areas I got to experience, um, there at Nike. And—and really the breadth of those roles helped me gain a really deep understanding of—of how best to leverage, uh, that intersection between technology, data, and then the skills and talent of the team to deliver hyper-relevant customer experiences that—that Nike is known for. Um, and so today, you know, I’m really excited to share some of my journey in partnering with the SheerID team to leverage audience data and platforms to deliver campaigns that are designed to unlock new sources of business growth.
[00:02:27] Scott Wolfe: Today we’re—we’re dealing with a lot as marketers, right? It’s—it’s such a crowded marketplace out there. There’s more brands and more messages coming at you all the time. And acquisition costs are through the roof. We’re looking at 30% plus higher customer acquisition cost right now with paid media, etc. But beyond those first two points, it’s harder than ever to connect with relevance. And what I mean by that is there is so much noise out there. And so it’s so hard to create that emotional, authentic connection, uh, with consumers out there with everything going on in the marketplace. It’s absolutely—absolutely nuts right now, right Scott?
[00:03:00] Scott Dylag: Yeah, I mean, these are headwinds all of us as marketers face and, you know, there’s no sign that it’s letting up anytime soon. If anything, it’s probably going to get more competitive. And, uh, you know, acquisition is still a really important, um, piece of powering that flywheel, right? It’s a huge component. But the shift we’re really seeing in brands, uh, is focusing more energy, time, and frankly marketing dollars on the customers they already have. So, leaning into that economic volatility a little bit, uh, with greater relevance, you know, building deeper relationships with existing customers. So, you know, those could be active regular consumers you see all the time, uh, could be first-time or one-time buyers, lapsed buyers who haven’t, you know, you haven’t seen in a while, but really looking at the customers you’ve engaged with at some point across their lifecycle with your brand. Um, so, you know, this is something that we all see and feel, but this is our first opportunity: we want to hear from you. So, our first poll of the day is on screen. We want to know what your biggest challenges are as marketers, uh, reaching your audiences, reaching your customers.
[00:04:01] Scott Wolfe: If you could take a minute to participate and submit your question, that would be great. Give people a few moments here to submit their response. Very interested to see some of the results here.
[00:04:25] Scott Dylag: Hey Scott, we’re not able to vote. I want to vote on this one.
[00:04:28] Scott Wolfe: I do too! I feel—feel left out that we can’t vote. I want to—I want to weigh in. It’s all of the above from what I can see. And you can—there’s only a single choice of course, you know, so I’m very interested to see the results here. All right, we’ll wrap it up.
[00:04:53] Scott Wolfe: All right. So, it looks like a split vote there from the first one. Some interesting results. We’ll have—we’ll have the chance, uh, later on for some more people to submit their answers. Maybe we can get some more people to vote in the next one. But, uh, these—these are things we’re definitely hearing from all of our customers as well. I mean, Scott, I’m curious if you can share a little bit about some successful approaches you’ve—you’ve employed along the way to double down on engagement, retention, and some of these other levers—levers that you need to connect with to—to get things done.
[00:05:20] Scott Dylag: Yeah, I mean, just thinking about the poll there for a second, like data and analytics were the two that popped. It’s like, okay great, like we’re—we’re in the right place, right? Uh, but yeah, you—know, it starts with this insight right here. So, you know, when—when you’re thinking about a customer-centered, um, marketing program, it really comes down to like this overarching truth, right? So, the only way brands can really serve customers in—in a way that feels personal and relevant is to know them. And, you know, probably know them at a level deeper than maybe we have in the past, right? And—and that starts and ends with the customer data and how brands collect it, manage it, use it, etc. So, again, that’s—that’s really why we’re here today.
[00:05:57] Scott Wolfe: It’s all about the data, right? That’s why we’re here. Talking about data. We have data warehouses these days, big data, metadata, data lakes, even data moats. Um, and that’s the modern reality that we’re in today as marketers, right? Is that we are truly as much in the business of the data itself than we are in the business of—of actually trying to reach those customers.
[00:06:16] Scott Dylag: Yeah, and we’re going to go a little deep here, so—so bear with us. Um, but yeah, I mean, talking about data can lead you sort of down any number of rabbit holes. And so, in my experience, having some sort of framework or approach that’s simple, clear, and—and easy to understand up and down the organization is really important for building advocacy and support, i.e., you know, budget, for powering up a data-centric offering. So, this framework here, it’s intentionally oversimplified, um, but it’s—it’s one way to think about the pillars of—of the customer data landscape. So, starting from left to right, you know, bringing it together. So, you know, as the case of most brands, data is all over the place, right? It can be fragmented, in varying states of quality. It could be sitting in your point of sale, uh, your marketing databases, third-party campaign stores, email and marketing platforms, your customer service platforms, like it’s—it’s everywhere, right? And so, you know, being able to leverage that data is a challenge if you don’t have some sort of central store or warehouse. That’s—that’s just a key part of the piece of the architecture. And, you know, these are table stakes for any marketing program. I don’t think there’s any new insights here, um, that everyone here doesn’t already know. Um, but as you collate and centralize, you know, again we’ve probably all been through this, you know, you need to plan to normalize that data as much as possible for consistency and quality. So, uh, bringing it together, normalizing it across, you know, a host of attributes, gen—like demographic and behavioral. So, you know, gender, age, date of birth, city, state, postal, uh, where it came from, um, shopping preferences, uh, a lot of attributes, you know, either obtained implicitly or explicitly as you collect that data, having that normalized across the architecture. Uh, and then the third piece of this is really operationalizing that data. Um, so in that, it can be securely accessed by marketers or maybe your marketing operations team through some sort of an interface. You know, ideally self-service, uh, at least for some of your cohorts. And, you know, I think a litmus test here that I’ve experienced is—is if you as a marketer need to brief a data scientist for every campaign that you want to run, it’s—it’s probably a clear signal you have a little bit of work to do in the space of operationalizing your data.
[00:08:21] Scott Dylag: So, let’s move to the sort of the second pillar. Um, and that’s around establishing a data hierarchy within your brand. And the reality is not all data is created equal, especially when it comes to the idea of leveraging that data to deliver relevant customer experiences, right? So, working from the bottom up, inferred data, uh, is this notion of, you know, data that—um, is generalized about a customer using other data attributes. So, you know, an example might be assigning someone to a cohort because of a demographic representation. And, uh, you know, interestingly enough as—as Scott and I were preparing for today, like we learned a lot about each other where, uh, we actually went to the same high school. I—I went to the school many years before Scott Wolfe, but we did go to the same school at some point. Um, we went to the same college. Uh, but Scott Wolfe is a Dolphins fan and I am a Seahawks fan. Um, but with an inferred data model, um, you know, I might be grouped into a Dolphins fan cohort by, you know, a marketing team just—strictly because like a look-alike assignment, right? So, our profile looks similar, so Scott must be a Dolphins fan. So, that’s kind of the folly of purely an inferred data model.
[00:09:27] Scott Dylag: And then the next one is acquired data. You know, these—this is data you might get from any number of third-party sources. And, you know, while that data may be permissioned or authorized at the time it was collected through, you know, the terms of use or whatever, you know, uh, it’s—it’s hard to fully understand the context in which it was collected. So, you know, this when it comes to relevant customer journeys, this is good data but maybe not great. Which kind of segues us to the top of the pyramid, which is that permission data. You know, this is first-party data, uh, that customers explicitly provided to your brand—your brand in a context that’s clear and understood from the usage standpoint.
[00:10:02] Scott Wolfe: Yeah, and permission data is really the place where SheerID is playing exclusively, in that when a consumer provides that data, it’s a value exchange, right? Where they’re providing that data to the brand in exchange for something of value. Uh, and it’s the most reliable category of data that you can really leverage to build all of these marketing campaigns that we’re going to get into and—and customize those customer journeys. It’s truly about the value exchange of that data, so the action that is being taken, and it’s why it’s so powerful.
[00:10:29] Scott Dylag: Yeah. Okay, great. So, we’ve got centralized, normalized data that’s at our fingertips. Um, you know, the next step is identifying your specific customer groups. So, segments, cohorts, whatever you want to call them, and really at as finite level of detail as your team’s own resourcing will allow, frankly. And, you know, I’ve personally seen like core brand cohorts that, you know, number in six to eight mega-segments. And then I’ve seen individual segmentation that could be in the hundreds, right? And those cohorts are typically a combination of a bunch of filtered attributes across, you know, some of the demographic data we talked about, um, and other pieces. So, let’s—let’s actually run through an example. So, let’s take Sophia. Sophia is a—a female, age 18 to 25, lives in Tampa, Florida, and, uh, she’s a student at the University of Florida. Um, I actually had to look up to see where—what universities were in Tampa, uh, to finish my example. USF is there, um, true. So, uh—and then you overlay that demographic data with lifecycle data. So, in terms of where that customer exists in their relationship with, uh, the brand. So, Sophia is a former repeat buyer, uh, but she’s lapsed in a 90-day cycle, which is a cycle we as marketers for our brand track, um, with regularity. So, uh, and then the third piece is the behavioral. So, you know, further slicing that based upon either observed or logged—logged actions that Sophia has taken. So, she’s previously purchased running footwear and apparel, but during sale events only. Um, and then finally, the last piece of this is—is factoring in the ICP or that ideal customer profile. So, the example above is a good illustration of a—what we call a positive ICP. Like, we feel good that customers identified in this way have a pretty high likelihood to be—you know, connect with a campaign that’s, you know, it’s delivered with relevance and find it interesting. And then on the flip side, you also want to be intentional in identifying those that might be within a negative ICP. So, while they may fit the cohort, they’ve proven through maybe a recorded history of non-responsiveness that they probably have a low propensity. So, it’s not just about finding, you know, the folks in your cohort that you feel good that are going to respond, it’s also identifying potentially excluding those that like, “We know that this—this group isn’t going to be as—as interested or respond like we want.”
[00:12:40] Scott Dylag: Okay, so let’s finish out this slide and finish on the last rung here, and that’s really now thinking about how you take that data, those cohorts, and then building campaigns around them. And this is when you bring it all together, um, really through a clear and very specific objective tied to one or maybe even multiple cohorts. So, just to follow our example all the way through, uh, you know, the data may tell us there’s a lot of other Sophias out there. And—and we need a campaign geared specifically to re-engage our community of lapsed female runners, uh, who are also students and potentially, right? That might be part of that cohort. But, uh, but also motivated by sale and deals. And so as a marketer, you know, when you brief a campaign that way, you can start to visualize what, you know, the language and that creative, and, you know, might look like in that campaign, right? Because it’s very targeted and very specific to an outcome you’re trying to achieve. Um, and so the final, you know, piece of this is that, you know, air traffic control or frequency management as it’s more commonly referred to. So, this really tracking when and how you’re connecting with your individual consumers. Uh, they can show up in many different cohorts, and this helps regulate, you know, potential over-communication, uh, and burning through a customer, um, but also help identify those who may be falling through the cracks who you haven’t communicated to in a while and you need to. So, uh—okay, that’s a lot for one slide, but it’s an important level set.
[00:14:02] Scott Dylag: Um, I think this is a time we want to hear from our audience again, let’s get some more participation from the audience. We want to hear from you, like: what’s the state of your data, specifically your customer data? We’ll give this one a minute.
[00:14:14] Scott Wolfe: Yeah, I’m excited for this one. This—this should be inter—I can’t wait to see some of these responses. Please vote if you have a second. Really appreciate your participation. We’ll give people more time here to get—some votes.
[00:14:31] Scott Dylag: I’m hoping we don’t see any votes for the last one. But hey, you never know. Some people are just starting out, so…
[00:14:45] Scott Dylag: We need the Jeopardy music. We forgot the—forgot that.
[00:14:48] Scott Wolfe: We did. We forgot that, yeah. All right, give people a couple more moments here. Please take a chance to vote if you have a second.
[00:15:33] Scott Wolfe: Interesting. Okay.
[00:15:38] Scott Dylag: Yeah. Looks like everyone’s at least those who responded have some data, there’s work to do. No surprise, right?
[00:15:52] Scott Wolfe: Yeah, that’s fine. I mean, when everyone is in a different place with their data, right? And when it comes to data with SheerID, we really want to make it easy for all brands. And I think it’s paramount to us that the data is owned by you. So, just a quick four-step process for how it works for SheerID. Step one is of course creating that exclusive audience offer. Whether you want to reach out to students, military, young adults, etc., you need to create that offer first. And then step two of course is you need to promote it. You need to get it out in the world, right? Um, and step three is some in-brand verification process over, you know, 200,000 data sources. It’s an in-brand experience. But we’re here today primarily to talk about step four. And that’s what’s so important to us is that you own your data, uh, and you really choose your path on how you want to leverage it by enriching your CRM, your DMP, or your CDP, etc. Uh, so those are the four steps. Um, now I’m curious Scott, if—we’ve covered a little bit of the “what” so far, we’ve covered a little bit of the “why”, but I’m curious if we can talk a little bit about the “how” now in terms of: how do you go about building some of this momentum at the very start of your data journey?
[00:16:53] Scott Dylag: Yeah, so this is a little bit of a left turn from our conversation because this gets into like the organizational change management, which is super important, right? So if you have any big—any big initiative, you know, you have to have a—an approach for how you’re going to get that over the top within your organization. So, you know, with—and with any big change, you know, it starts with having the vision, right? You got to help paint the picture of what the desired end state, uh, needs to look like. Um, it’s got to be bold, uh, but also attainable for your brand, uh, and then connects to a clear “why”. Um, you know, why should your brand care about getting after this initiative, prioritizing it, funding it? Um, and then as much as possible, like how you connect that vision and that “why” as an enabler to the strategy and future vision that your company already has, right? So your company’s already charging in a certain direction, just connecting how the vision for this program can help, um, drive more momentum into that existing strategy. Um, and then, you know, it’s building a story around it to help that—that vision create momentum and give it maybe some virality. So, you know, you want others pitching the idea. And, you know, in some cases I’ve—you may see people pitching it as their own. You know, that—that never happens. But, uh, you know, I actually feel in—in my experience, that’s a good thing to an extent. You want that, you know? It can’t just be when you’re trying to push something big and bold and new, it can’t just be your hill to climb, right? And if you have a clear, compelling vision combined with a great story, uh, something that colleagues believe—believe in, the vision spreads in a number of ways.
[00:18:21] Scott Dylag: Okay, so you’ve got the vision and now it’s really about, uh, you know, knowing your stakeholders. Um, you know, as you plan to—you know, as you plan to—to roadshow your vision, like all good stories, you got to know your audience. Uh, you know, who are your key stakeholders in this, who holds the decision rights? Uh, the purse strings, um, you know, what do they uniquely care about, and, you know, what are their hot buttons? You know, what, you know, what do you need to anticipate and hit proactively when you’re speaking with them and sharing your vision? Um, and then you bring it all together in building that advocacy. You hit the road, you bring together your stakeholders, align them to the vision, hit their hot buttons, anticipate their counters, uh, and then you let the—you let the momentum—you let the momentum build. And so, you know, when it comes to knowing your stakeholder, we’ll—we’ll double-click on that just for a second for illustration purposes. So, uh, you know, these could vary, uh, but we’ve taken sort of three slices of leadership across a typical organization. And, you know, the responsibilities here can vary.
[00:19:18] Scott Dylag: But if you think about like a CMO for example, and you’re speaking to—to them and their team, you know: how can this program—thinking about how to share—how can this program drive incrementality at acquisition, you know, engagement or re-engagement, retention, um, and, you know, speed to value? Um, likewise for the CFO, you know, if you’re speaking to the financial community: how is this—demonstrate how these programs are accretive to the P&L up and down? Um, you know, it could be at the top of funnel pocket—tapping into new pockets of demand, uh, maybe larger order sizes, uh, creating leverage, uh, in customer acquisition costs that we talked about earlier, your ROAS, uh, or even lower in the—the P&L, you know, releasing some margin pressure through more targeted promotional offers. Uh, and then finally, you know, speaking with the technological—technical community and your CTO, you know: proactively hitting things about like technical lift or LOE required to get various phases of a program live. Uh, and then likewise, you know, proactively hitting concerns around security and—and privacy that’s always present when you’re talking about customer data. Um, and then finally the ROI piece, right? So, um—within your technology team, there’s—there’s always a roadmap that’s—that’s overly full. And, you know, if you can generate a demonstrated ROI that’s, you know, at parity or even better than other items—items that are in competition on that roadmap, you’ll be in a good spot when—in working with the technology team.
[00:20:40] Scott Wolfe: We know that brands are at many different stages in—that their modes of their data in terms of where they are in the maturity of their data. And I’m curious Scott, um, can you speak a little bit about your experience on this line graph here in terms of how you get to the different stages and how other brands might be able to think about it?
[00:20:56] Scott Dylag: Yeah, you know, I mean, kind of like the last set of slides, it’s all about, you know, having a plan and—and a thoughtful process for how to approach it. That can be a multi-year, you know, multi-year journey. And, you know, when you start those sorts of journeys, I—you know, there’s lots of different conventions. I’ve used the crawl-walk-run convention in—in my background. And so we’ll just use that to illustrate a similar progression here. So first in the crawl is sort of the “get in the game” phase, right? So this is how you get started. We talked about aligning the org, uh, and then once you have that, you know, it’s about designing and activating the right offer and verification flow for your brand. Uh, getting that established and then starting to drive some traffic through it to see some of those early returns and the learnings about how you might be able to extend this. Um, and then so—uh, once you’re in the game, then it’s like, okay, um, next phase is that walk phase. And it’s just about driving more and more awareness into the programs that you know are already working at small scale. Um, and this kind of starts with really looking at your marketing calendar, right? So maybe you’re—you’re driving some evergreen traffic, but now you can start looking in your marketing calendar like: what are those moments we can start programming against to make use of some of this permission data through customer segments, uh, to deliver relevance? Um, and then looking across your marketing mix of—of other areas you can promote this program and these offers. Whether it’s, you know, in paid channels, affiliates, your—your email strategies, etc. Um, and then looking like: how can we make both the data and the customer experience more—more integrated and more seamless, uh, and starting to test, uh—maybe with permission data within your own marketing stack. That—that might require a little bit of manual lift as you’re sort of in this walk phase. Um, but that kind of segues into, you know, what a run might look like, which is a little bit more about like automation, uh, of your data, uh, of the experiences, and then really getting into like bespoke programming, highly targeted offers, and understanding how well those work and then how you can drive more of that. Um, but, you know, in any convention like this, it’s—it’s super important to call out: like, it’s—it’s one, it’s not linear, even though the visual makes it look like that, and it’s, you know, not one size fits all. So any—every brand’s path could be a little bit different, you know? For some, starting small and simple and—and mastering the basics can be perfectly fine. Um, you know, and for others, maybe you have resourcing early on who are getting after, you know, customer data and—and personalized, you know, marketing. Uh, and then, you know, going after fully integrated customer experiences and data automation and plugging directly into your ad-tech/mar-tech platforms. You’re ready to go day one. That’s great, too. So, not one size fits all, but more like a menu of options depending on the state of your brand and investment and resourcing and all that fun stuff, uh, of, you know, to choose what to take on and when.
[00:23:38] Scott Wolfe: Scott, I’m—I’m a little biased, um, as a fellow Oregon Duck and—and a huge fan of Nike. Um, but this was truly one of SheerID’s favorite campaigns that we worked on with you and I’m curious if you can tell us a little bit more about how this came to life.
[00:23:51] Scott Dylag: Yeah, you know, this is one, uh, I still have a lot of personal pride in, especially, you know, given the circumstances we were living in at the time. So, just for context: like, we were four to five months into COVID, um, and, you know, the toll that COVID was having on our entire medical community, you know, that was in the news cycle pretty much daily, right? We all—we all saw that and lived through it, and—and some folks here may have family members or friends who lived through that personally. And, you know, as luck would have it, you know, Nike had already been working on a new SKU of footwear explicitly designed for those in the medical community: nurses, doctors, med-techs, ER, people on their feet all day long and in that environment. Called the Nike Zoom Pulse. And, you know, this was a clear opportunity, you know, to honor one of Nike’s longest-standing company values. It’s—it’s maxim to “do the right thing”. Um, and so the charge to us, you know, as a digital team was to find a way to use our digital capabilities to give away 30,000 pairs of the Zoom Pulse to deserving Nike members. Verified members that were part of our medical community, um, and using the data that we had. So, so using our permission data via our evergreen, uh, medical program, medical discount program, uh, an offer was enabled that invited the community in to opt in for the free pair and we—we set an offering window. Uh, and then once that—all the pairs had been claimed in an offering window, uh, an automatic 100% discount was applied to the member profiles. They were able to seamlessly add to cart, check out, and then within, you know, without any charges and within a few days their free pairs arrived. Um, was pretty—was pretty epic moment for me executing this campaign. But, uh—you know, I think, you know, while this offer was 100% initiated through a sense of duty to—duty to the community, um, you know, and to be able to serve Nike’s members in a way that only Nike could. Um, but, you know, we were living in a time when good news was at a serious premium, you know? And the goodwill that stemmed from that campaign was pretty—pretty massive. Uh, you know, but—but for me, you know, more valuable than the media coverage was the connection that—that Nike was able to deepen with those members on the other end of that offer. So, if you imagine you’re in that environment, you’re living through that and you receive this offer from Nike, it’s a pretty, you know, it’s a pretty palpable thing, right? So, you know, in the grand scheme, the giveaway, you know, relatively small gesture for a multi-billion dollar brand, but, you know, that’s an investment in a customer connection. It’s really hard to measure, like, even through traditional LTV metrics, right?
[00:26:22] Scott Wolfe: Yeah, totally. I mean, this is such an amazing example of doing something for the greater good and truly having that opportunity to create that authentic emotional connection with an individual. I’m curious if we can dive a little bit deeper and you can share some of this, uh, success, um, that stemmed from this amazing campaign.
[00:26:41] Scott Dylag: Yeah, I mean, you know, a couple learnings actually came from it. Um, like first was we could execute, you know? Frankly, you—know, we weren’t in, you know, thinking back to the maturity curve, we weren’t in a space where like all of our, you know, permission data with SheerID was automated and integrated and piped in. And so there was some lift, um, but, you know, now that lift was a known quantity. Like, we’d executed, we knew like what it would take to build some SOP around, you know, replicating doing more of this. And then in thinking about that, it—it, you know, exposed an opportunity to us to say, “Hey, there’s probably other data segments that were underutilized, um, on our part that we could also be—be looking at.” Um, and so, you know, I think the other—that’s the ability to understand like what it takes to execute is—is often like an overlooked part of a test and learn offense. Um, you know, being able to establish a repeatable process for execution is a super valuable byproduct. Um, so, you know, reality is, you know, no marketing offense or technology platforms are ever done or perfect. I think we saw that in the poll, you know? Most brands here, you know, they’ve got data but they got more work to do. But, you know, moments like these provide brands great opportunities to get scrappy, um, you know, illustrate, you know, what delivering with some hyper-relevance might look like and then—you know, then you know because you’ve done it what it might take to move the ball forward and advance the vision, uh, to the next level.
[00:27:58] Scott Wolfe: Thank you so much for diving a little bit deeper on that. It’s such a great example of, um, the impact you can have with partnering with SheerID and having a—a great partner like yourself. Are you ready to go on the hot seat? We have some questions for you.
[00:28:11] Scott Dylag: Yeah, let’s do it.
[00:28:13] Scott Wolfe: Okay. All right, so the first question we have here is: many brands feel the pressure to level out the seasonality of the business, the peaks and the valleys. Can you share how you’ve seen brands do this effectively through targeted campaigns?
[00:28:27] Scott Dylag: Yeah, I mean—I mean, this is one of my favorite topics. I—I mean, I lived in this space for so many years. Uh, so Scott you may have to cut me off at some point. I know we’re—we’re hitting 30 minutes. Hopefully folks can stick with us. Um, you know, for brands in that seasonal cycle, you know, retail e-commerce focused brands, it—it can be a feast or famine roller coaster, um, when you get into these really peaky sale moments. And, you know, and it’s not just for marketers, you know, or teams who live on that demand gen side. Um, when you think about those peak retail moments of back-to-school, holiday, Black Friday, um, etc., like huge spikes in demand take a toll on the operational teams as well. So, fulfillment and supply chain teams, customer service, stores, uh, you know, and staffing the levels to meet the demands of those—those massive peaks is—is usually not possible financially and it usually comes in some sort of service degradation in some way. So—so like if you look at—if you look at back-to-school, um, we could talk about holiday but let’s look at back-to-school. Um, you know, I’ve seen success in campaigns that were specifically geared, um, around, you know, messaging that was—uh, like shop—you know, shop early exclusively for students. And, you know, this provides a couple benefits in that moment. Like, first it gives that cohort, you know, something that’s unique just for them, you know, at least for a period of time and, you know, it’s time-bound. Um, nice thing too is like when you have these shop early campaigns, your assortment’s typically the most full, you know? You—you have fewer broken size runs, you’re out of stock, etc. So, a little side benefit there too for the shopping cohorts that are given an offer at that moment. But—but it does, I mean secondary, it does pull forward some of that demand, you know? That limited time only, that FOMO of—of hitting that deal in the moment, you know, triggers that buy now. And it doesn’t fully mitigate the peaks that are going to happen, um, but it does help make the peaks less peaky. So, like getting into some really technical business jargon here, but—but it, you know, it does work, you know, to help level that out a little bit. And, um, you know, finally, and this is for the finance team, you know, a lot of brands are wary about stacking promos, you know, just from a margin dilution side. And, you know, when you get into like a back-to-school or other shopping events, like—that can be par for the course sometimes. So, if you think about it—going a little deep there from like a financial perspective—but if you think about it in those terms, you know, your evergreen discount programs are usually 10 and 15%, somewhere in that range. But—and then these—these moments where you’re giving an offer gives you a chance to raise those, you know, uh, 15, 20%, increase that offer. Um, and depending on the retailer, you know, your effective aggregate discount rate across your entire assortment for a season may sit anywhere from like 10 to sometimes up to 25%, maybe less for premium brands etc. Um, but if you can target your campaigns to sit at or just below that sort of effective aggregate discount rate, uh, it gives the customer something, um, but it also, um—it gives your finance team something as well, it keeps them happy. So, um—sorry, you said these were rapid fire. Um, went a little deep there but like I said, I’ve lived in this moment for so much that there’s—there’s a lot to it and it’s—it’s super important, right? These programs can do so much to help level those curves a little bit, those peaks.
[00:31:37] Scott Wolfe: No, that was—that was great. It’s really interesting to hear about the different ranges of the discounts and—and it’s so important to keep that finance team happy, right? Um, so let’s go into the second question here. You talked about integrating with the marketing calendar as a key strategy. Can you share some examples of the role community offers can play on those 365 calendars?
[00:31:56] Scott Dylag: Yeah, um, you know, with marketers, um, you know, we’re always looking for timely, relevant reasons to connect with customers. You know, if you’re doing full file sends weekly, you know, sometimes those can feel a little arbitrary or forced to be honest, like we’ve all seen them. Um, but, you know, when you look at the range of customer segments that SheerID supports, that—like there are a lot of options to go and deliver something that’s more relevant and timely to individual—individual customer. And so, like again kind of playing that student, um, population again, like we talked about back-to-school but you’ve got spring break gear-up season, um, and then specifically like within collegiate students, like you get into all the college sport moments, right? So you get, um, college football kickoff and the playoffs that—that follow, March Madness. And so like, you know, even brands that aren’t typically marketing in the sporty—sports space, like if you’re supporting students, like now you have a reason to—to communicate with these—these students, right? So, um, these moments are happening in their lives and—and you need to be a part of that as a marketer. Um, and then similarly, you know, with some of the other segments I have experienced with, the military, the medical, which we talked about, first responder, I mean there’s—there’s annual moments, days, weeks, entire months, like the entire month of May is Military Appreciation Month. Um, you know, honored to—you know, those are designed to honor those who serve the community. So, Memorial Day, Veterans Day, um, there’s—there’s days and weeks that honor doctors and nurses, uh, there’s September Remembrance, you know, for first responder. Like, it just kind of goes on and on. And so when you open up your 365 calendar, it really starts to light up with all these moments to think about as a marketer: like, “How can I be—how could and should I be leveraging these to connect with my consumers in a really deep, meaningful way?”
[00:33:42] Scott Wolfe: Absolutely. Okay, one more question here for you. How does a brand know—this is a good one—how does a brand know or recognize when it’s ready to make investments in the marketing tech stack?
[00:33:53] Scott Dylag: Yeah, uh, I mean, anytime you talk about making another investment in the—in the tech stack, you know, it’s—there’s a truth in tech and that’s there’s always going to be more asks than—than on the roadmap than what can be done through capacity. And so what I’ve found is, uh, you know, too often the gravitational pull goes to, you know, the shiny objects, right? The—the slick features, um, pro—you know, promising to drive clicks or conversion or customers or whatever it may be. But, you know, when it comes to like assessing readiness, um, you know, it comes back to where we started, you know? The—you know, having that strong, uh, audience data MVP. Um, I mean, it’s really difficult to create authentic communicate—connections with customers, you know, regardless of what feature you have on the front end, if you don’t have that data story in order. Uh, so when it comes to like, “Are we ready?”, it—it’s got to start there first. Uh, you know, and we saw in our poll, um, you know, brands, you know, at least the folks here, you know, brands have some work to do. So having that, you know, crawl-walk-run approach even to the data, you know, can help, you know, get your brand more ready. Um, so yeah.
[00:35:01] Scott Wolfe: All right, Scott, you are officially off the hot seat. Thank you for being a good sport.
[00:35:05] Scott Dylag: Yeah, yeah, I appreciate it and—and I know we’re going a little bit over but, uh, hopefully folks are finding this a valuable conversation.
[00:35:13] Scott Wolfe: Yeah, absolutely. Uh, thank you everyone for investing your time with us today. I just want to close it out, uh, by reiterating that no matter where you’re at in your journey, um, with data, whether you’re crawling, you’re walking, or you’re running, SheerID has a solution for you. Um, and we can support you with where you are on that journey, whether you’re a current customer or a future customer. Uh, we really enable you to leverage that data to build some of these crawl, walk, and run strategies that Scott alluded to. Um, I want to thank everyone for investing their time with us today, we really appreciate you. And I—I want to give a special thank you to my partner in crime today, Scott Dylag. Scott, it was, uh, a pleasure to host this with you and thank you, uh, very much for joining us today.
[00:35:54] Scott Dylag: Yeah, thank you so much for having me today. Um, take care everybody.
[00:35:58] Scott Wolfe: All right everyone, take care. Thank you again. Bye.
[00:00:38] Scott Wolfe: My name is Scott Wolfe, I’m the Principal Product Marketing Manager here at SheerID. I’ve been with the company for, let’s see, about, uh, four years now. Uh, doing everything related to product marketing but also primarily focused on everything related to data. And so, really excited to announce my counterpart here, but before we get into that, um, when people think about SheerID and audience verification, it’s more about the—the—than the initial verification. You know, it’s about creating those authentic, genuine, emotional connections, but it goes beyond just that initial verification. It goes about the data that you get from that. So, with that, I want to introduce my exciting counterpart today, Scott Dylag. Scott?
[00:01:19] Scott Dylag: Yeah, thank you so much, Scott. Uh, yes, great names think alike after all. Um, and thank you to the SheerID leadership team for having me speak with y’all today. Um, my name is Scott Dylag. I’m currently the owner, principal consultant for my own independent retail consultancy, JSD Digital. But, uh, prior to that, however, I was—uh, I spent the last 20 years building and scaling Nike’s online business, both domestically, uh, and then across the globe. Um, and during my time at the swoosh, I held a—a number of leadership roles across technology, capability development, customer experience, operations, business leadership, a lot—a lot of different areas I got to experience, um, there at Nike. And—and really the breadth of those roles helped me gain a really deep understanding of—of how best to leverage, uh, that intersection between technology, data, and then the skills and talent of the team to deliver hyper-relevant customer experiences that—that Nike is known for. Um, and so today, you know, I’m really excited to share some of my journey in partnering with the SheerID team to leverage audience data and platforms to deliver campaigns that are designed to unlock new sources of business growth.
[00:02:27] Scott Wolfe: Today we’re—we’re dealing with a lot as marketers, right? It’s—it’s such a crowded marketplace out there. There’s more brands and more messages coming at you all the time. And acquisition costs are through the roof. We’re looking at 30% plus higher customer acquisition cost right now with paid media, etc. But beyond those first two points, it’s harder than ever to connect with relevance. And what I mean by that is there is so much noise out there. And so it’s so hard to create that emotional, authentic connection, uh, with consumers out there with everything going on in the marketplace. It’s absolutely—absolutely nuts right now, right Scott?
[00:03:00] Scott Dylag: Yeah, I mean, these are headwinds all of us as marketers face and, you know, there’s no sign that it’s letting up anytime soon. If anything, it’s probably going to get more competitive. And, uh, you know, acquisition is still a really important, um, piece of powering that flywheel, right? It’s a huge component. But the shift we’re really seeing in brands, uh, is focusing more energy, time, and frankly marketing dollars on the customers they already have. So, leaning into that economic volatility a little bit, uh, with greater relevance, you know, building deeper relationships with existing customers. So, you know, those could be active regular consumers you see all the time, uh, could be first-time or one-time buyers, lapsed buyers who haven’t, you know, you haven’t seen in a while, but really looking at the customers you’ve engaged with at some point across their lifecycle with your brand. Um, so, you know, this is something that we all see and feel, but this is our first opportunity: we want to hear from you. So, our first poll of the day is on screen. We want to know what your biggest challenges are as marketers, uh, reaching your audiences, reaching your customers.
[00:04:01] Scott Wolfe: If you could take a minute to participate and submit your question, that would be great. Give people a few moments here to submit their response. Very interested to see some of the results here.
[00:04:25] Scott Dylag: Hey Scott, we’re not able to vote. I want to vote on this one.
[00:04:28] Scott Wolfe: I do too! I feel—feel left out that we can’t vote. I want to—I want to weigh in. It’s all of the above from what I can see. And you can—there’s only a single choice of course, you know, so I’m very interested to see the results here. All right, we’ll wrap it up.
[00:04:53] Scott Wolfe: All right. So, it looks like a split vote there from the first one. Some interesting results. We’ll have—we’ll have the chance, uh, later on for some more people to submit their answers. Maybe we can get some more people to vote in the next one. But, uh, these—these are things we’re definitely hearing from all of our customers as well. I mean, Scott, I’m curious if you can share a little bit about some successful approaches you’ve—you’ve employed along the way to double down on engagement, retention, and some of these other levers—levers that you need to connect with to—to get things done.
[00:05:20] Scott Dylag: Yeah, I mean, just thinking about the poll there for a second, like data and analytics were the two that popped. It’s like, okay great, like we’re—we’re in the right place, right? Uh, but yeah, you—know, it starts with this insight right here. So, you know, when—when you’re thinking about a customer-centered, um, marketing program, it really comes down to like this overarching truth, right? So, the only way brands can really serve customers in—in a way that feels personal and relevant is to know them. And, you know, probably know them at a level deeper than maybe we have in the past, right? And—and that starts and ends with the customer data and how brands collect it, manage it, use it, etc. So, again, that’s—that’s really why we’re here today.
[00:05:57] Scott Wolfe: It’s all about the data, right? That’s why we’re here. Talking about data. We have data warehouses these days, big data, metadata, data lakes, even data moats. Um, and that’s the modern reality that we’re in today as marketers, right? Is that we are truly as much in the business of the data itself than we are in the business of—of actually trying to reach those customers.
[00:06:16] Scott Dylag: Yeah, and we’re going to go a little deep here, so—so bear with us. Um, but yeah, I mean, talking about data can lead you sort of down any number of rabbit holes. And so, in my experience, having some sort of framework or approach that’s simple, clear, and—and easy to understand up and down the organization is really important for building advocacy and support, i.e., you know, budget, for powering up a data-centric offering. So, this framework here, it’s intentionally oversimplified, um, but it’s—it’s one way to think about the pillars of—of the customer data landscape. So, starting from left to right, you know, bringing it together. So, you know, as the case of most brands, data is all over the place, right? It can be fragmented, in varying states of quality. It could be sitting in your point of sale, uh, your marketing databases, third-party campaign stores, email and marketing platforms, your customer service platforms, like it’s—it’s everywhere, right? And so, you know, being able to leverage that data is a challenge if you don’t have some sort of central store or warehouse. That’s—that’s just a key part of the piece of the architecture. And, you know, these are table stakes for any marketing program. I don’t think there’s any new insights here, um, that everyone here doesn’t already know. Um, but as you collate and centralize, you know, again we’ve probably all been through this, you know, you need to plan to normalize that data as much as possible for consistency and quality. So, uh, bringing it together, normalizing it across, you know, a host of attributes, gen—like demographic and behavioral. So, you know, gender, age, date of birth, city, state, postal, uh, where it came from, um, shopping preferences, uh, a lot of attributes, you know, either obtained implicitly or explicitly as you collect that data, having that normalized across the architecture. Uh, and then the third piece of this is really operationalizing that data. Um, so in that, it can be securely accessed by marketers or maybe your marketing operations team through some sort of an interface. You know, ideally self-service, uh, at least for some of your cohorts. And, you know, I think a litmus test here that I’ve experienced is—is if you as a marketer need to brief a data scientist for every campaign that you want to run, it’s—it’s probably a clear signal you have a little bit of work to do in the space of operationalizing your data.
[00:08:21] Scott Dylag: So, let’s move to the sort of the second pillar. Um, and that’s around establishing a data hierarchy within your brand. And the reality is not all data is created equal, especially when it comes to the idea of leveraging that data to deliver relevant customer experiences, right? So, working from the bottom up, inferred data, uh, is this notion of, you know, data that—um, is generalized about a customer using other data attributes. So, you know, an example might be assigning someone to a cohort because of a demographic representation. And, uh, you know, interestingly enough as—as Scott and I were preparing for today, like we learned a lot about each other where, uh, we actually went to the same high school. I—I went to the school many years before Scott Wolfe, but we did go to the same school at some point. Um, we went to the same college. Uh, but Scott Wolfe is a Dolphins fan and I am a Seahawks fan. Um, but with an inferred data model, um, you know, I might be grouped into a Dolphins fan cohort by, you know, a marketing team just—strictly because like a look-alike assignment, right? So, our profile looks similar, so Scott must be a Dolphins fan. So, that’s kind of the folly of purely an inferred data model.
[00:09:27] Scott Dylag: And then the next one is acquired data. You know, these—this is data you might get from any number of third-party sources. And, you know, while that data may be permissioned or authorized at the time it was collected through, you know, the terms of use or whatever, you know, uh, it’s—it’s hard to fully understand the context in which it was collected. So, you know, this when it comes to relevant customer journeys, this is good data but maybe not great. Which kind of segues us to the top of the pyramid, which is that permission data. You know, this is first-party data, uh, that customers explicitly provided to your brand—your brand in a context that’s clear and understood from the usage standpoint.
[00:10:02] Scott Wolfe: Yeah, and permission data is really the place where SheerID is playing exclusively, in that when a consumer provides that data, it’s a value exchange, right? Where they’re providing that data to the brand in exchange for something of value. Uh, and it’s the most reliable category of data that you can really leverage to build all of these marketing campaigns that we’re going to get into and—and customize those customer journeys. It’s truly about the value exchange of that data, so the action that is being taken, and it’s why it’s so powerful.
[00:10:29] Scott Dylag: Yeah. Okay, great. So, we’ve got centralized, normalized data that’s at our fingertips. Um, you know, the next step is identifying your specific customer groups. So, segments, cohorts, whatever you want to call them, and really at as finite level of detail as your team’s own resourcing will allow, frankly. And, you know, I’ve personally seen like core brand cohorts that, you know, number in six to eight mega-segments. And then I’ve seen individual segmentation that could be in the hundreds, right? And those cohorts are typically a combination of a bunch of filtered attributes across, you know, some of the demographic data we talked about, um, and other pieces. So, let’s—let’s actually run through an example. So, let’s take Sophia. Sophia is a—a female, age 18 to 25, lives in Tampa, Florida, and, uh, she’s a student at the University of Florida. Um, I actually had to look up to see where—what universities were in Tampa, uh, to finish my example. USF is there, um, true. So, uh—and then you overlay that demographic data with lifecycle data. So, in terms of where that customer exists in their relationship with, uh, the brand. So, Sophia is a former repeat buyer, uh, but she’s lapsed in a 90-day cycle, which is a cycle we as marketers for our brand track, um, with regularity. So, uh, and then the third piece is the behavioral. So, you know, further slicing that based upon either observed or logged—logged actions that Sophia has taken. So, she’s previously purchased running footwear and apparel, but during sale events only. Um, and then finally, the last piece of this is—is factoring in the ICP or that ideal customer profile. So, the example above is a good illustration of a—what we call a positive ICP. Like, we feel good that customers identified in this way have a pretty high likelihood to be—you know, connect with a campaign that’s, you know, it’s delivered with relevance and find it interesting. And then on the flip side, you also want to be intentional in identifying those that might be within a negative ICP. So, while they may fit the cohort, they’ve proven through maybe a recorded history of non-responsiveness that they probably have a low propensity. So, it’s not just about finding, you know, the folks in your cohort that you feel good that are going to respond, it’s also identifying potentially excluding those that like, “We know that this—this group isn’t going to be as—as interested or respond like we want.”
[00:12:40] Scott Dylag: Okay, so let’s finish out this slide and finish on the last rung here, and that’s really now thinking about how you take that data, those cohorts, and then building campaigns around them. And this is when you bring it all together, um, really through a clear and very specific objective tied to one or maybe even multiple cohorts. So, just to follow our example all the way through, uh, you know, the data may tell us there’s a lot of other Sophias out there. And—and we need a campaign geared specifically to re-engage our community of lapsed female runners, uh, who are also students and potentially, right? That might be part of that cohort. But, uh, but also motivated by sale and deals. And so as a marketer, you know, when you brief a campaign that way, you can start to visualize what, you know, the language and that creative, and, you know, might look like in that campaign, right? Because it’s very targeted and very specific to an outcome you’re trying to achieve. Um, and so the final, you know, piece of this is that, you know, air traffic control or frequency management as it’s more commonly referred to. So, this really tracking when and how you’re connecting with your individual consumers. Uh, they can show up in many different cohorts, and this helps regulate, you know, potential over-communication, uh, and burning through a customer, um, but also help identify those who may be falling through the cracks who you haven’t communicated to in a while and you need to. So, uh—okay, that’s a lot for one slide, but it’s an important level set.
[00:14:02] Scott Dylag: Um, I think this is a time we want to hear from our audience again, let’s get some more participation from the audience. We want to hear from you, like: what’s the state of your data, specifically your customer data? We’ll give this one a minute.
[00:14:14] Scott Wolfe: Yeah, I’m excited for this one. This—this should be inter—I can’t wait to see some of these responses. Please vote if you have a second. Really appreciate your participation. We’ll give people more time here to get—some votes.
[00:14:31] Scott Dylag: I’m hoping we don’t see any votes for the last one. But hey, you never know. Some people are just starting out, so…
[00:14:45] Scott Dylag: We need the Jeopardy music. We forgot the—forgot that.
[00:14:48] Scott Wolfe: We did. We forgot that, yeah. All right, give people a couple more moments here. Please take a chance to vote if you have a second.
[00:15:33] Scott Wolfe: Interesting. Okay.
[00:15:38] Scott Dylag: Yeah. Looks like everyone’s at least those who responded have some data, there’s work to do. No surprise, right?
[00:15:52] Scott Wolfe: Yeah, that’s fine. I mean, when everyone is in a different place with their data, right? And when it comes to data with SheerID, we really want to make it easy for all brands. And I think it’s paramount to us that the data is owned by you. So, just a quick four-step process for how it works for SheerID. Step one is of course creating that exclusive audience offer. Whether you want to reach out to students, military, young adults, etc., you need to create that offer first. And then step two of course is you need to promote it. You need to get it out in the world, right? Um, and step three is some in-brand verification process over, you know, 200,000 data sources. It’s an in-brand experience. But we’re here today primarily to talk about step four. And that’s what’s so important to us is that you own your data, uh, and you really choose your path on how you want to leverage it by enriching your CRM, your DMP, or your CDP, etc. Uh, so those are the four steps. Um, now I’m curious Scott, if—we’ve covered a little bit of the “what” so far, we’ve covered a little bit of the “why”, but I’m curious if we can talk a little bit about the “how” now in terms of: how do you go about building some of this momentum at the very start of your data journey?
[00:16:53] Scott Dylag: Yeah, so this is a little bit of a left turn from our conversation because this gets into like the organizational change management, which is super important, right? So if you have any big—any big initiative, you know, you have to have a—an approach for how you’re going to get that over the top within your organization. So, you know, with—and with any big change, you know, it starts with having the vision, right? You got to help paint the picture of what the desired end state, uh, needs to look like. Um, it’s got to be bold, uh, but also attainable for your brand, uh, and then connects to a clear “why”. Um, you know, why should your brand care about getting after this initiative, prioritizing it, funding it? Um, and then as much as possible, like how you connect that vision and that “why” as an enabler to the strategy and future vision that your company already has, right? So your company’s already charging in a certain direction, just connecting how the vision for this program can help, um, drive more momentum into that existing strategy. Um, and then, you know, it’s building a story around it to help that—that vision create momentum and give it maybe some virality. So, you know, you want others pitching the idea. And, you know, in some cases I’ve—you may see people pitching it as their own. You know, that—that never happens. But, uh, you know, I actually feel in—in my experience, that’s a good thing to an extent. You want that, you know? It can’t just be when you’re trying to push something big and bold and new, it can’t just be your hill to climb, right? And if you have a clear, compelling vision combined with a great story, uh, something that colleagues believe—believe in, the vision spreads in a number of ways.
[00:18:21] Scott Dylag: Okay, so you’ve got the vision and now it’s really about, uh, you know, knowing your stakeholders. Um, you know, as you plan to—you know, as you plan to—to roadshow your vision, like all good stories, you got to know your audience. Uh, you know, who are your key stakeholders in this, who holds the decision rights? Uh, the purse strings, um, you know, what do they uniquely care about, and, you know, what are their hot buttons? You know, what, you know, what do you need to anticipate and hit proactively when you’re speaking with them and sharing your vision? Um, and then you bring it all together in building that advocacy. You hit the road, you bring together your stakeholders, align them to the vision, hit their hot buttons, anticipate their counters, uh, and then you let the—you let the momentum—you let the momentum build. And so, you know, when it comes to knowing your stakeholder, we’ll—we’ll double-click on that just for a second for illustration purposes. So, uh, you know, these could vary, uh, but we’ve taken sort of three slices of leadership across a typical organization. And, you know, the responsibilities here can vary.
[00:19:18] Scott Dylag: But if you think about like a CMO for example, and you’re speaking to—to them and their team, you know: how can this program—thinking about how to share—how can this program drive incrementality at acquisition, you know, engagement or re-engagement, retention, um, and, you know, speed to value? Um, likewise for the CFO, you know, if you’re speaking to the financial community: how is this—demonstrate how these programs are accretive to the P&L up and down? Um, you know, it could be at the top of funnel pocket—tapping into new pockets of demand, uh, maybe larger order sizes, uh, creating leverage, uh, in customer acquisition costs that we talked about earlier, your ROAS, uh, or even lower in the—the P&L, you know, releasing some margin pressure through more targeted promotional offers. Uh, and then finally, you know, speaking with the technological—technical community and your CTO, you know: proactively hitting things about like technical lift or LOE required to get various phases of a program live. Uh, and then likewise, you know, proactively hitting concerns around security and—and privacy that’s always present when you’re talking about customer data. Um, and then finally the ROI piece, right? So, um—within your technology team, there’s—there’s always a roadmap that’s—that’s overly full. And, you know, if you can generate a demonstrated ROI that’s, you know, at parity or even better than other items—items that are in competition on that roadmap, you’ll be in a good spot when—in working with the technology team.
[00:20:40] Scott Wolfe: We know that brands are at many different stages in—that their modes of their data in terms of where they are in the maturity of their data. And I’m curious Scott, um, can you speak a little bit about your experience on this line graph here in terms of how you get to the different stages and how other brands might be able to think about it?
[00:20:56] Scott Dylag: Yeah, you know, I mean, kind of like the last set of slides, it’s all about, you know, having a plan and—and a thoughtful process for how to approach it. That can be a multi-year, you know, multi-year journey. And, you know, when you start those sorts of journeys, I—you know, there’s lots of different conventions. I’ve used the crawl-walk-run convention in—in my background. And so we’ll just use that to illustrate a similar progression here. So first in the crawl is sort of the “get in the game” phase, right? So this is how you get started. We talked about aligning the org, uh, and then once you have that, you know, it’s about designing and activating the right offer and verification flow for your brand. Uh, getting that established and then starting to drive some traffic through it to see some of those early returns and the learnings about how you might be able to extend this. Um, and then so—uh, once you’re in the game, then it’s like, okay, um, next phase is that walk phase. And it’s just about driving more and more awareness into the programs that you know are already working at small scale. Um, and this kind of starts with really looking at your marketing calendar, right? So maybe you’re—you’re driving some evergreen traffic, but now you can start looking in your marketing calendar like: what are those moments we can start programming against to make use of some of this permission data through customer segments, uh, to deliver relevance? Um, and then looking across your marketing mix of—of other areas you can promote this program and these offers. Whether it’s, you know, in paid channels, affiliates, your—your email strategies, etc. Um, and then looking like: how can we make both the data and the customer experience more—more integrated and more seamless, uh, and starting to test, uh—maybe with permission data within your own marketing stack. That—that might require a little bit of manual lift as you’re sort of in this walk phase. Um, but that kind of segues into, you know, what a run might look like, which is a little bit more about like automation, uh, of your data, uh, of the experiences, and then really getting into like bespoke programming, highly targeted offers, and understanding how well those work and then how you can drive more of that. Um, but, you know, in any convention like this, it’s—it’s super important to call out: like, it’s—it’s one, it’s not linear, even though the visual makes it look like that, and it’s, you know, not one size fits all. So any—every brand’s path could be a little bit different, you know? For some, starting small and simple and—and mastering the basics can be perfectly fine. Um, you know, and for others, maybe you have resourcing early on who are getting after, you know, customer data and—and personalized, you know, marketing. Uh, and then, you know, going after fully integrated customer experiences and data automation and plugging directly into your ad-tech/mar-tech platforms. You’re ready to go day one. That’s great, too. So, not one size fits all, but more like a menu of options depending on the state of your brand and investment and resourcing and all that fun stuff, uh, of, you know, to choose what to take on and when.
[00:23:38] Scott Wolfe: Scott, I’m—I’m a little biased, um, as a fellow Oregon Duck and—and a huge fan of Nike. Um, but this was truly one of SheerID’s favorite campaigns that we worked on with you and I’m curious if you can tell us a little bit more about how this came to life.
[00:23:51] Scott Dylag: Yeah, you know, this is one, uh, I still have a lot of personal pride in, especially, you know, given the circumstances we were living in at the time. So, just for context: like, we were four to five months into COVID, um, and, you know, the toll that COVID was having on our entire medical community, you know, that was in the news cycle pretty much daily, right? We all—we all saw that and lived through it, and—and some folks here may have family members or friends who lived through that personally. And, you know, as luck would have it, you know, Nike had already been working on a new SKU of footwear explicitly designed for those in the medical community: nurses, doctors, med-techs, ER, people on their feet all day long and in that environment. Called the Nike Zoom Pulse. And, you know, this was a clear opportunity, you know, to honor one of Nike’s longest-standing company values. It’s—it’s maxim to “do the right thing”. Um, and so the charge to us, you know, as a digital team was to find a way to use our digital capabilities to give away 30,000 pairs of the Zoom Pulse to deserving Nike members. Verified members that were part of our medical community, um, and using the data that we had. So, so using our permission data via our evergreen, uh, medical program, medical discount program, uh, an offer was enabled that invited the community in to opt in for the free pair and we—we set an offering window. Uh, and then once that—all the pairs had been claimed in an offering window, uh, an automatic 100% discount was applied to the member profiles. They were able to seamlessly add to cart, check out, and then within, you know, without any charges and within a few days their free pairs arrived. Um, was pretty—was pretty epic moment for me executing this campaign. But, uh—you know, I think, you know, while this offer was 100% initiated through a sense of duty to—duty to the community, um, you know, and to be able to serve Nike’s members in a way that only Nike could. Um, but, you know, we were living in a time when good news was at a serious premium, you know? And the goodwill that stemmed from that campaign was pretty—pretty massive. Uh, you know, but—but for me, you know, more valuable than the media coverage was the connection that—that Nike was able to deepen with those members on the other end of that offer. So, if you imagine you’re in that environment, you’re living through that and you receive this offer from Nike, it’s a pretty, you know, it’s a pretty palpable thing, right? So, you know, in the grand scheme, the giveaway, you know, relatively small gesture for a multi-billion dollar brand, but, you know, that’s an investment in a customer connection. It’s really hard to measure, like, even through traditional LTV metrics, right?
[00:26:22] Scott Wolfe: Yeah, totally. I mean, this is such an amazing example of doing something for the greater good and truly having that opportunity to create that authentic emotional connection with an individual. I’m curious if we can dive a little bit deeper and you can share some of this, uh, success, um, that stemmed from this amazing campaign.
[00:26:41] Scott Dylag: Yeah, I mean, you know, a couple learnings actually came from it. Um, like first was we could execute, you know? Frankly, you—know, we weren’t in, you know, thinking back to the maturity curve, we weren’t in a space where like all of our, you know, permission data with SheerID was automated and integrated and piped in. And so there was some lift, um, but, you know, now that lift was a known quantity. Like, we’d executed, we knew like what it would take to build some SOP around, you know, replicating doing more of this. And then in thinking about that, it—it, you know, exposed an opportunity to us to say, “Hey, there’s probably other data segments that were underutilized, um, on our part that we could also be—be looking at.” Um, and so, you know, I think the other—that’s the ability to understand like what it takes to execute is—is often like an overlooked part of a test and learn offense. Um, you know, being able to establish a repeatable process for execution is a super valuable byproduct. Um, so, you know, reality is, you know, no marketing offense or technology platforms are ever done or perfect. I think we saw that in the poll, you know? Most brands here, you know, they’ve got data but they got more work to do. But, you know, moments like these provide brands great opportunities to get scrappy, um, you know, illustrate, you know, what delivering with some hyper-relevance might look like and then—you know, then you know because you’ve done it what it might take to move the ball forward and advance the vision, uh, to the next level.
[00:27:58] Scott Wolfe: Thank you so much for diving a little bit deeper on that. It’s such a great example of, um, the impact you can have with partnering with SheerID and having a—a great partner like yourself. Are you ready to go on the hot seat? We have some questions for you.
[00:28:11] Scott Dylag: Yeah, let’s do it.
[00:28:13] Scott Wolfe: Okay. All right, so the first question we have here is: many brands feel the pressure to level out the seasonality of the business, the peaks and the valleys. Can you share how you’ve seen brands do this effectively through targeted campaigns?
[00:28:27] Scott Dylag: Yeah, I mean—I mean, this is one of my favorite topics. I—I mean, I lived in this space for so many years. Uh, so Scott you may have to cut me off at some point. I know we’re—we’re hitting 30 minutes. Hopefully folks can stick with us. Um, you know, for brands in that seasonal cycle, you know, retail e-commerce focused brands, it—it can be a feast or famine roller coaster, um, when you get into these really peaky sale moments. And, you know, and it’s not just for marketers, you know, or teams who live on that demand gen side. Um, when you think about those peak retail moments of back-to-school, holiday, Black Friday, um, etc., like huge spikes in demand take a toll on the operational teams as well. So, fulfillment and supply chain teams, customer service, stores, uh, you know, and staffing the levels to meet the demands of those—those massive peaks is—is usually not possible financially and it usually comes in some sort of service degradation in some way. So—so like if you look at—if you look at back-to-school, um, we could talk about holiday but let’s look at back-to-school. Um, you know, I’ve seen success in campaigns that were specifically geared, um, around, you know, messaging that was—uh, like shop—you know, shop early exclusively for students. And, you know, this provides a couple benefits in that moment. Like, first it gives that cohort, you know, something that’s unique just for them, you know, at least for a period of time and, you know, it’s time-bound. Um, nice thing too is like when you have these shop early campaigns, your assortment’s typically the most full, you know? You—you have fewer broken size runs, you’re out of stock, etc. So, a little side benefit there too for the shopping cohorts that are given an offer at that moment. But—but it does, I mean secondary, it does pull forward some of that demand, you know? That limited time only, that FOMO of—of hitting that deal in the moment, you know, triggers that buy now. And it doesn’t fully mitigate the peaks that are going to happen, um, but it does help make the peaks less peaky. So, like getting into some really technical business jargon here, but—but it, you know, it does work, you know, to help level that out a little bit. And, um, you know, finally, and this is for the finance team, you know, a lot of brands are wary about stacking promos, you know, just from a margin dilution side. And, you know, when you get into like a back-to-school or other shopping events, like—that can be par for the course sometimes. So, if you think about it—going a little deep there from like a financial perspective—but if you think about it in those terms, you know, your evergreen discount programs are usually 10 and 15%, somewhere in that range. But—and then these—these moments where you’re giving an offer gives you a chance to raise those, you know, uh, 15, 20%, increase that offer. Um, and depending on the retailer, you know, your effective aggregate discount rate across your entire assortment for a season may sit anywhere from like 10 to sometimes up to 25%, maybe less for premium brands etc. Um, but if you can target your campaigns to sit at or just below that sort of effective aggregate discount rate, uh, it gives the customer something, um, but it also, um—it gives your finance team something as well, it keeps them happy. So, um—sorry, you said these were rapid fire. Um, went a little deep there but like I said, I’ve lived in this moment for so much that there’s—there’s a lot to it and it’s—it’s super important, right? These programs can do so much to help level those curves a little bit, those peaks.
[00:31:37] Scott Wolfe: No, that was—that was great. It’s really interesting to hear about the different ranges of the discounts and—and it’s so important to keep that finance team happy, right? Um, so let’s go into the second question here. You talked about integrating with the marketing calendar as a key strategy. Can you share some examples of the role community offers can play on those 365 calendars?
[00:31:56] Scott Dylag: Yeah, um, you know, with marketers, um, you know, we’re always looking for timely, relevant reasons to connect with customers. You know, if you’re doing full file sends weekly, you know, sometimes those can feel a little arbitrary or forced to be honest, like we’ve all seen them. Um, but, you know, when you look at the range of customer segments that SheerID supports, that—like there are a lot of options to go and deliver something that’s more relevant and timely to individual—individual customer. And so, like again kind of playing that student, um, population again, like we talked about back-to-school but you’ve got spring break gear-up season, um, and then specifically like within collegiate students, like you get into all the college sport moments, right? So you get, um, college football kickoff and the playoffs that—that follow, March Madness. And so like, you know, even brands that aren’t typically marketing in the sporty—sports space, like if you’re supporting students, like now you have a reason to—to communicate with these—these students, right? So, um, these moments are happening in their lives and—and you need to be a part of that as a marketer. Um, and then similarly, you know, with some of the other segments I have experienced with, the military, the medical, which we talked about, first responder, I mean there’s—there’s annual moments, days, weeks, entire months, like the entire month of May is Military Appreciation Month. Um, you know, honored to—you know, those are designed to honor those who serve the community. So, Memorial Day, Veterans Day, um, there’s—there’s days and weeks that honor doctors and nurses, uh, there’s September Remembrance, you know, for first responder. Like, it just kind of goes on and on. And so when you open up your 365 calendar, it really starts to light up with all these moments to think about as a marketer: like, “How can I be—how could and should I be leveraging these to connect with my consumers in a really deep, meaningful way?”
[00:33:42] Scott Wolfe: Absolutely. Okay, one more question here for you. How does a brand know—this is a good one—how does a brand know or recognize when it’s ready to make investments in the marketing tech stack?
[00:33:53] Scott Dylag: Yeah, uh, I mean, anytime you talk about making another investment in the—in the tech stack, you know, it’s—there’s a truth in tech and that’s there’s always going to be more asks than—than on the roadmap than what can be done through capacity. And so what I’ve found is, uh, you know, too often the gravitational pull goes to, you know, the shiny objects, right? The—the slick features, um, pro—you know, promising to drive clicks or conversion or customers or whatever it may be. But, you know, when it comes to like assessing readiness, um, you know, it comes back to where we started, you know? The—you know, having that strong, uh, audience data MVP. Um, I mean, it’s really difficult to create authentic communicate—connections with customers, you know, regardless of what feature you have on the front end, if you don’t have that data story in order. Uh, so when it comes to like, “Are we ready?”, it—it’s got to start there first. Uh, you know, and we saw in our poll, um, you know, brands, you know, at least the folks here, you know, brands have some work to do. So having that, you know, crawl-walk-run approach even to the data, you know, can help, you know, get your brand more ready. Um, so yeah.
[00:35:01] Scott Wolfe: All right, Scott, you are officially off the hot seat. Thank you for being a good sport.
[00:35:05] Scott Dylag: Yeah, yeah, I appreciate it and—and I know we’re going a little bit over but, uh, hopefully folks are finding this a valuable conversation.
[00:35:13] Scott Wolfe: Yeah, absolutely. Uh, thank you everyone for investing your time with us today. I just want to close it out, uh, by reiterating that no matter where you’re at in your journey, um, with data, whether you’re crawling, you’re walking, or you’re running, SheerID has a solution for you. Um, and we can support you with where you are on that journey, whether you’re a current customer or a future customer. Uh, we really enable you to leverage that data to build some of these crawl, walk, and run strategies that Scott alluded to. Um, I want to thank everyone for investing their time with us today, we really appreciate you. And I—I want to give a special thank you to my partner in crime today, Scott Dylag. Scott, it was, uh, a pleasure to host this with you and thank you, uh, very much for joining us today.
[00:35:54] Scott Dylag: Yeah, thank you so much for having me today. Um, take care everybody.
[00:35:58] Scott Wolfe: All right everyone, take care. Thank you again. Bye.
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