00:00
[Introductory slide displays: “The Secret to Unlocking Customer Lifetime Value – April 9th, 2025”]
Ryan Wooford: Well hello, and good afternoon. Welcome to today’s Adweek webinar. Customer Lifetime Value shapes the way a brand makes decisions. A CLV North Star informs marketing spend and platform goals; it provides space for customer segmentation and retention, and broadly provides data back to product development strategies. But what is the secret to unlocking Customer Lifetime Value? Today, we’re excited to be joined by friends from SheerID and Whirlpool to discuss permissioned data and why it is a critical part of their marketing strategy.
00:42
Ryan Wooford: I’m Ryan Wooford, the VP of the Branded Studio here at Adweek, and we want to thank today’s sponsor, SheerID, for making this discussion possible. Before we begin, let me do some housekeeping for our presentation today. Today’s webinar presentation will run approximately 30 to 35 minutes, after which we should have time for audience Q&A. So if at any point you have a question for one of our speakers, just use the Q&A tool beneath the video window on your screen, and we’ll get to as many questions as we can after the end of the presentation.
01:12
Ryan Wooford: Also, it’s not too late to invite your colleagues to join us today. About 15 minutes ago, you likely received a final reminder email from us. In there, there’s a link to the webinar registration page that you can share with your colleagues; there’s still plenty of time for them to join us. Uh, if they can’t, or if you’d like to revisit our discussion at a later date, today’s webinar is being recorded. The on-demand version will be available to all registrants via link, which will be provided later today in your email. And if you’d like a PDF of today’s slide deck, you’ll find that in the event resources area beneath the window on your screen.
01:47
Ryan Wooford: As always, if you enjoy today’s webinar, definitely check out our full slate of webinars at adweek.com/webinars. Now, uh, for today’s speakers. We’re happy to be joined by Rebecca Grimes, the Chief Revenue Officer at SheerID; Chris Oliviera, who’s Product Marketing Manager at SheerID; and Patrick Debkowski, the Senior Manager of D2C Merchandising at Whirlpool. I’m going to let them introduce themselves, so Chris, take it away.
02:17
Chris Oliviera: Sure. Thank you so much, Ryan, I appreciate it. Well, thank you everybody for joining us today. The topic of today is—kind of Ryan alluded to this already—is the power of permissioned data when it comes to this becoming a secret of unlocking Customer Lifetime Value, right? I think a lot of times we have these conversations that are very timely, and I don’t think this could be a—a more timely discussion. Literally today, right, we’re talking about, uh, the uncertainty when it comes to the macroeconomics of things and how important it is to create relationships—direct relationships—with consumers so they choose your brand time and time again. So let’s jump into a quick round of introductions uh, for—for us three, and then we’ll get into the topic today. Sound like—all right. So, my name is Chris Oliviera, uh, Senior Product Marketing Manager here at SheerID. Been here for about four years or so in sunny Fort Lauderdale, Florida. And I—and I love this topic. I love understanding, uh, the needs, challenges, and successes of our customers, and understanding our customers’ customers as well so we can serve our customers better. So, Rebecca, I’ll turn it over to you.
03:29
Rebecca Grimes: Hi everyone, Rebecca Grimes, I’m the Chief Revenue Officer at SheerID and I oversee all of our customer-facing teams. I have been here, um, a little under a year, and I’m really excited to talk about this topic today. This is one that is very near and dear to my heart. I’ve spent the last, um, 15-plus years working alongside some of the world’s most admired brands. This is my second time, um, working with Whirlpool and, uh, and really excited to—to start this discussion today.
04:01
Patrick Debkowski: Hey guys, I’ll jump in. Um, my name is Patrick Debkowski. I’m the Senior Merchandising Manager at Whirlpool Corporation for our D2C business. So, you may or may not know, Whirlpool owns, of course, the Whirlpool brand, KitchenAid, Maytag, Amana, JennAir, and others. Um, and so my responsibility is leading our D2C team, helping sell our products directly to our consumers. Um, with that, loyalty is one of the arms, uh, that I lead, and—and one of the focuses of today’s conversation.
04:30
Chris Oliviera: Awesome. Thank you guys for—for joining us today. So, before we jump into increasing lifetime value with data, we need to define a couple of things, right? You might have heard us say: “Permissioned Data.” What—what does that mean? Maybe a lot of you haven’t heard that term, so let’s define that before we go into some best practices of how to leverage this type of data. So, a quick definition here: Permissioned data is consumer data that brands collect and use with explicit consent, ensuring a transparent value exchange where consumers clearly understand how their data will be used and what they will receive in return. So let’s expand on that a little bit. Um, Rebecca, I’ll—I’ll turn the first question over to you. What is permissioned data besides beyond this definition, and how does it differ from other types of consumer data?
05:25
Rebecca Grimes: Thanks, Chris. Um, one of the things that permissioned data clearly differentiates itself is around—it emphasizes the importance of building those genuine connections with consumers. Because it’s more crucial than ever. Factors like increased privacy regulations and shifting consumer expectations and, as Chris just mentioned, economic uncertainty are all reshaping the marketing landscape. Consumers are seeking out these brands who share similar—similar values and are focused on building relationships and trust with their consumers. So now more than ever, brands have to do more to attract and retain customers. Which means that brands and industry leaders need to move beyond just first or zero-party data to emphasize the consumer consent and control, leading to the adoption of the term “permissioned data.” So, permissioned data is any data that a consumer willingly and knowingly shares with a brand. This—this consent can be given explicitly, such as through an opt-in form, or implicitly through continued engagement with the brand’s content and services. By focusing on building trust and transparency, brands can navigate the challenges that sit in front of them and create lasting relationships with their audience.
06:40
Chris Oliviera: Nice. Okay. Right. And so why—why do you think permissioned data is considered like the gold standard when it comes to consumer insights?
06:51
Rebecca Grimes: Yeah. So let’s start by breaking down these data types and then look at the pros and cons of each one. [Slide displays: Comparison chart of Third-Party, Traditional First-Party, and Permissioned Data] So this chart provides a clear overview and I’ll walk you through each category. First up, we have Third-Party Data. Third-party data is collected without direct consumer involvement and is less reliable due to privacy regulations. For example, purchasing a list of email addresses from an external provider based on specific attributes is acquiring third-party data. As you can see, the pros are that it is quick to acquire and scale and offers broad reach. And this might seem appealing initially, however the cons are significant. This marketing approach suffers from low accuracy and is heavily restricted due to increasing privacy regulations. And most importantly, it often reduces consumer trust. In today’s market where trust is paramount, relying heavily on third-party data can be detrimental. As a consumer, I am bombarded, as I’m sure many of you as marketers are, with emails daily from companies that I don’t have any relationship with. And that immediately leads me to not only unsubscribe but potentially avoid that brand altogether.
08:00
Rebecca Grimes: Next, we have Traditional First-Party Data. The pros here [are] that it is collected directly from consumers and it’s more reliable than third-party data. This is the data you’ve gathered from your own website or interactions. However, the cons are crucial to consider as well. This data is often passively collected without explicit consumer consent. This means customers might not be fully aware how their data is being used. Furthermore, it might not comply with future privacy regulations and, as regulations tighten, this type of data collecting is becoming increasingly risky.
08:36
Rebecca Grimes: Building consumer trust with first-party data happens when consumers opt in to its use. Prompting a consumer to accept cookies when visiting your website may appear to be consumer consent, but when somebody actively raises their hand by checking a box to receive content from your brand, they are then actively opting in and giving you permission for that data to be used for marketing purposes. And let’s keep in mind that consumers remember their very first interaction that they have with your brand. So leaning into creating a transparent and trusting relationship is critical from the moment they begin to engage and then reinforced through ongoing interactions that will drive increased Customer Lifetime Value and purchase frequency. The golden standard that we are all after.
09:24
Rebecca Grimes: So finally, and most importantly, we have Permissioned Data, which includes both zero-party data—which is proactively shared by consumers—and then that first-party data that is collected with explicit consent. The pros here are substantial. The data is highly accurate and consumer verified. It builds trust and strengthens brand relationships because consumers know and have agreed to share their information. It’s also compliant with privacy regulations like GDPR and CCPA, which is essential today. And it enables deeper personalization, which leads to higher Customer Lifetime Value. The cons are that it requires a strong value exchange to encourage that data sharing. You need to offer something in return to make it worthwhile. Something like points, discounts, early access, or exclusive content to encourage consumers to share that data with you. Permissioned data also takes time to collect and scale compared to third-party data, which means that you need to be thinking about it well in advance of activating on this data to build a strategy for how to collect and leverage that data. However, the long-term benefits of trust, compliance, and personalized experiences far outweigh these challenges. Think of it as building a strong foundation rather than a quick fix. And the good news is that you can start to collect the data in parallel while you’re building out that strategy for how to meaningfully use the data.
10:54
Chris Oliviera: Great. Thanks, uh, Rebecca for that. I want to ask you one more question, and—and I want to hear from Pat afterwards. How does permissioned data help brands build this type of trust with customers, with their customers?
11:12
Rebecca Grimes: The transparency of the collection of this data, consent-based actions like filling out a form or completing account profile settings with a clear understanding of the give-get for the customer, can instantly build trust compared to other marketing tactics. Consumers willingly share their data because they see a direct benefit. Furthermore, consumers know that they’re sharing, what they’re sharing, and why they’re sharing it. Confidence in that brand increases because they understand how it is mutually beneficial. This is especially important during times of economic uncertainty where people are more intentional with how and where they spend their money and with whom.
11:52
Chris Oliviera: Great. Pat, I want to hear from you. How important is consumer trust when collecting this type of permissioned data at Whirlpool?
12:01
Patrick Debkowski: Yeah, so coming from the perspective of a manufacturer who also sells our products directly to consumers, uh, we need to make sure that our customers have the same level of trust in sharing their personal information with us, um, to the same degree or even greater than the customer trust that we’re selling them a quality product. Um, maintaining this trust with their digital experience can extend to the impression on our physical products as well. So you can imagine how important that is to keep a positive perception in order to keep the—the customer loyalty to our brand. Um, you know, in a competitive environment like what we are in today, the trust of the manufacturer is crucial to the customer so that they know that we will use this data responsibly and reward them accordingly, uh, for sharing that information with us.
12:49
Chris Oliviera: Great. Awesome. So, uh, appreciate all all those answers. I think that helps really frame what permissioned data really is, and—and and we’re starting to get into kind of some of the benefits of that. But I want to talk about how we, uh, can collect this type of permissioned data, some of the strategies and best practices. So, Rebecca, I’ll turn it over to you and, uh, what are—what are some of the other ways brands are gathering permissioned data today?
13:21
Rebecca Grimes: Yeah, I think the most obvious one is obviously with exclusive offers, which, you know, consumers are willingly sharing data to access special pricing, exclusive offers, and even membership-based perks if you think about like a student, a military, or a senior discount. There are also other ways that aren’t necessarily offer-driven. So, in-brand experiences; so brands can collect data through customized quizzes, preference centers, interactive tools that tailor recommendations based on customer input. Uh, most, you [know]—obvious then is if you have a loyalty program or rewards program that you’re encouraging customers to share data in exchange for points or tiered benefits or early access to products and events. That’s just another way to incentivize the collection of this data without having to offer a discount. Gen Z in particular values first and early access to products or events. So if they’re in your target market, think about how to drive parallel strategies that might combine all of the above and best practices to maximize the collection of this permissioned data. The common theme here is that quality strategies include a clear value exchange.
14:34
Chris Oliviera: Yeah, uh, I love that. And so let’s—let’s spend some time digging a little deeper into this concept of value exchange. I put together this quick definition of—of value exchange here for us to take a look at. [Slide displays: “Clear Value Exchange – Consumers willingly share their data when they see a direct benefit…”] And then we’ll dive a little bit deeper into—into this. But, uh, what is clear value exchange as we talked about this, right? Consumers willingly share their data where they see a direct benefit. A strong value exchange provides tangible rewards (e.g., discounts, early access—all these things we’ve been talking about) and enhanced experiences (e.g., personalization, seamless interactions, that type of thing). Making data sharing feel like a fair trade. And that’s the key there. So, um, Rebecca, I’ll turn it over to you one more time. How can brands create a compelling value exchange to encourage this type of data sharing?
15:29
Rebecca Grimes: Yeah. So as we’ve outlined here on the slide, obviously start by making it clear. Consumers need to immediately understand what they gain—exclusive pricing, personalized offers, or a better shopping experience. The next is really make it authentic. Consumers are smart and they know when a brand truly cares about them as an individual and when their actions are superficial. Don’t be afraid to lean into your values when asking for data. Remember that consumers are drawn to brands that align with their values. Today more than ever when they have so many options on where to spend their money. Make it easy. The process of sharing data should be simple, fast, rewarding. No unnecessary steps or confusing terms. And make it worthwhile. Brands need to use that data to enhance the customer experience by providing personalized recommendations, those early access promotions, improving support. So reinforcing trust and long-term engagement means that you need to make sure that there is a strong compelling give-get. Every day I see brands that display a prompt to give your email in exchange for a 10% discount. An email address doesn’t tell you anything about that consumer, and you just gave away something valuable in exchange for one data point when you could have captured more and explained the why behind the ask. So think through the data elements that will enable you to drive that deeper engagement with your customers and then orchestrate a way to make that data exchange clear, authentic, easy, and worthwhile.
17:01
Chris Oliviera: Absolutely. So, uh, Pat, from your perspective now, uh, how does Whirlpool create this type of compelling value exchange that encourages consumers to share their data with you?
17:14
Patrick Debkowski: Yeah, so we have unique value props uh that incentivize our customers to share these additional permissioned data up front as part of our account creation process. Um, you know once—once we collect some of that data from our customers, we’re able to use it to tailor offers, unique experiences, um, to meet them wherever they’re at in the shopping journey. Uh, this includes things like professional affiliation uh to find the right moments to speak to their specific audience and engage in authentic ways. Um, in addition, we’re implementing ways for customers to share permissioned data to extend offers in their own communities through word of mouth to amplify the reach of our own authenticated audiences. Uh so this word of mouth would have unique benefits for both the person referring as well as the person who is receiving the referral.
18:05
Chris Oliviera: Yeah, and I want to follow up to that really quickly. Are—are there any unexpected or any surprising results that you might have seen uh from running these types of audience offers?
18:17
Patrick Debkowski: Yeah, there’s a few things that come to mind. One of the more surprising results uh we’ve seen is the way we’re attracting customers organically through these offers, without much of a paid media activation behind it. So, there are some audiences in particular that know to go out and look for these specific offers, um, and they’re able to find them on their own without us really screaming it from the rooftops. Um, you know, it’s clear that while promotions on price are impactful, what comes to permission-based data is also super important: serving up a personalized and authentic experience for these audiences. Connecting these audiences with some of the broader missions of our corporation can help further build that trust with the customer. You know, one example I could point you to uh that we have is um our “Care Counts” campaign, where Whirlpool Corporation has been working in collaboration with Teach For America to donate washers and dryers to schools that help provide broader access to clean clothes for those who are in need. Um, you know, communicating these initiatives with an audience like teachers can help build that trust uh that we support initiatives that hit really close to home for them specifically. Um, you know lastly, I think uh one more surprising thing is we do see a high conversion rate from some of the more traditional audiences who expect to be offered discounts. Think military, seniors, first responders. But what might be more surprising is the engagement we receive from audiences that are not accustomed to being rewarded for their permissioned based data. In this case, we target veterinarians, interior designers, recent movers, uh real estate agents. To these audiences, you know, finding out where they qualify for a unique offer can be the tipping point which really helps push them in the direction of purchasing from us.
20:06
Chris Oliviera: Awesome. Thanks for that insight, Pat. Appreciate it. I—I think now it’s a good time for us to talk about how we can now leverage this type of permissioned data to increase that lifetime value, right? So we—we defined what permissioned data is, we talked about some best practices of collecting that type of data. Now let’s get to the meat of it, right? How can we use the data to—to increase our lifetime value? So, um, Rebecca, I’ll start with you. You’ve spoken to a lot of innovative brands; I talk to them all the time, every day. What are some of the key business KPIs that they’re tracking to measure the impact of permissioned data on their overall business health?
20:55
Rebecca Grimes: Great question. Um, and I am so glad to be able to—to work alongside some of the—the Whirlpool’s admired brands and the ones that are very, very near and dear to my heart. I actually have a brand new Whirlpool dishwasher in my kitchen, um, um, that my husband loves. Um, um, he’s a—he’s the dishwasher. But, um, I think that, you know, there really has been a shift for marketers where every dollar spent is increasingly being scrutinized for ROI and impact. So, of course, those traditional engagement and conversion KPIs are still important. This includes things like opt-in rate, email open rate, and funnel conversion. These metrics tell us whether customers are seeing value in sharing their data. If opt-in rates are high, that means you’re offering a compelling reason for customers to share their information. And if email open rates and conversion rates are strong, it indicates that the personalized experiences you are delivering with that data are resonating. Identifying new customers or first-time customers is another critical KPI for brands, along with win-back KPIs to re-engage with customers who haven’t purchased from the brand in 18, 24 months. We are also seeing a lot of analysis on Customer Lifetime Value, the topic of today’s uh webinar. And that’s being broken down further by specific cohorts of channels of acquisition, audience attributes, and more. So understanding Customer Lifetime Value really involves looking at repeat purchases, average order value, frequency of purchase, and overall customer retention. Permissioned data enables you to lean on purpose-driven marketing by leveraging the data you collect to curate at scale content that will resonate with each individual consumer. And so when you get this right, you will find specific cohorts that are outperforming historical average levels. When you know what your customers want and need, you can provide them with much more value, which keeps them coming back. And when you get this wrong, it can actually turn customers away from you.
22:56
Rebecca Grimes: And I’m going to share a bit of a story. I recall when I became a first-time mom. I had registered at several different retailers because of, uh, everything from my expected due date, the gender of my baby, and the brands I was likely using, and so much more. And I recall one of my first nights as a new mom scanning my phone in the middle of the night, probably with a screaming baby, um, and seeing a message from this retailer showcasing bicycles that were on sale. Um, by contrast, in my same email inbox at another retailer that I had registered with, and they had delivered this personalized message to me with helpful tips for first-time parents or ideas of full products that were not included in my registry, one of them being a swing that I immediately ordered from my phone at 3 AM in the middle of the night and had delivered to my house the next day. That made all the difference to me for how I felt connected to that brand over the other brand, and they became my go-to for all of my needs. So for marketers that are living in the data and looking for those headwinds and tailwinds, those are the ones that are going to scale well even in uncertain times by really using the data to inform how they’re leveraging not only permissioned data but also that purpose-driven marketing to combine that for the exact experience that’s going to connect with the consumer.
Part 3: Advanced Applications and Q&A
24:11
Chris Oliviera: Awesome. And so let’s—let’s talk about loyalty for just a second. You alluded to this already; I just want to expand this a little bit more. But beyond repeat purchases, how are these brands that—that you talk to uh defining loyalty beyond, like I said, the just repeat purchases? What does that look like?
24:29
Rebecca Grimes: Yeah. Obviously, the example I just shared was a great one. It’s more than just someone buying from you again and again because I still shop regularly with that retailer. Brands that are thriving are recognizing the importance of emotional connection. So those truly loyal customers are going to advocate for the brand, they’re going to engage with your content and refer others. They’re not just customers, they’re brand ambassadors. And that kind of emotional connection is really built on trust and personalized experience, which permissioned data—[Pat 2 compression starts here]—going back to the example that I just shared, I was talking to one of my friends who was soon-to-be parent about my overwhelmingly positive experience. And that influenced their decision on where to register and then eventually spend their money. Loyalty can also be measured in examining engagement and interaction. So metrics like time spent with the brand, participation in its loyalty programs, response to personalized offers, also show a much deeper level of commitment. It’s about the quality of the interaction, not just the transaction. When a customer spends time exploring your content, participates in your loyalty program, discovers new products that you recommend, it signifies a strong and engaged relationship.
25:42
Chris Oliviera: Got it. Cool, great. Rebecca, that’s a great answer. Uh, Pat, and what about you from your perspective at Whirlpool? How do you define loyalty beyond just repeat purchases from customers?
25:55
Patrick Debkowski: Yeah, you know, repeat purchase is great. Um, but in an industry like appliances where customers aren’t frequently in the market, you know, what is more important to us is that continued trust in the product, the brand, um, and engagement with us throughout their product ownership life cycle. Um, you know, you could think of it like a car. You don’t buy a car very often, but when you do buy a car, you’re doing deep research, uh, and likely you have a deep affinity already with a brand, uh, before you even go make that purchase. Um, as a result, you know, we’re tracking loyalty at a customer level as engagement throughout the life of the appliance, rewarding these customers for their needs in between purchases. Think of things like service, repairs, warranty, uh, product education. Um, you know, we also have the opportunity to cross-sell consumable products that are—that will help maintain and extend the life of their appliances. Things like water filters; um, you could have a subscription to that, um, where it’s delivered to your home every six months. Um, we sell appliance cleaners, accessories that go along with your appliance. Um, these are all ways to keep that customer engaged in between the major appliance purchases and ultimately maximize the Customer Lifetime Value.
27:08
Chris Oliviera: Great. Cool. And Rebecca, one more question for you. Uh, we’ve talked about the importance of permission data, the KPIs to track, how brands are defining, uh, loyalty. Now let’s—let’s talk about a crucial question: how can brands effectively leverage this data to maximize Customer Lifetime Value?
27:32
Rebecca Grimes: Yeah, that—that’s a great question. And, you know, first I think about personalization at scale. And so this isn’t just about sending an email with somebody’s name. It’s really about understanding individual experiences and behaviors and using that knowledge to deliver those tailored experiences. With permissioned data, you can offer exclusive offers, relevant product recommendations, content that speaks directly to each customer and actually do that at scale. Um, this leverage—this kind of level of personalization for me, uh, helps keep me engaged and makes me feel valued. And I think that that’s what consumers are actually seeking out in the brands that they’re spending their money with today. Um, you know, the next way to leverage data is really around proactive engagement and retention efforts. Permissioned data allows you to anticipate those customer needs before they even arise. By analyzing the data, you can identify anomalies that deviate from your purchase history and proactively engage with them to drive them back to your brand. So, for example, you know if a customer hasn’t made a purchase from you in a while, you could send them a special discount or personalized message reminding them of the value that you provide. And you could also use those similar insights to enhance your loyalty program and create targeted outreach campaigns that resonate with specific audiences. And, you know, finally—and I know that this is a buzzword, um—and this is where it really is exciting is that we’re seeing more and more brands feeding that data into AI models. And permissioned data is really gold for those AI models. It enhances that predictive analytics, the customer segmentation, and it really allows those brands to optimize cross-sell and up-sell and life cycle marketing strategies with incredible precision. And, you know, imagine being able to connect with a customer when they are most likely to buy next. Um, AI models, you know, powered with this permissioned data make that possible. Uh, you know, an AI model could analyze purchase history and browsing behavior and suggest complementary products or predict when a customer is ready, uh, for an upgrade or a new service. Uh, I realized we were out of dog food last night, and it would have been great if I proactively had been told, “It might be time for you to order dog food before we run out,” um, and then I had to go panic and have it, uh, prioritized for next-day delivery. So, you know, when you’re thinking about Customer Lifetime Value with this permissioned data, it’s all about understanding your customers at a deeper level and then using those insights to deliver those personalized, proactive, and intelligent interactions. By focusing on those three strategies I just mentioned, you not only increase CLV, but you also build those stronger, more meaningful relationships with your customers. This just is not about data; it’s about creating those experiences that truly resonate and differentiate you from your other brands.
31:18
Chris Oliviera: Absolutely. Absolutely. Uh, Pat, um, one last question for you and then we’ll throw—there’s a few questions in the—in the chat that, uh, I wanted to share and get to you. But, Pat, at Whirlpool, how are you thinking about permissioned data, uh, and how it’s going to support your growth this year?
31:38
Patrick Debkowski: Yeah, I mean, at the core of it, um, it’s focusing on unlocking the give-to-get nature of permission-based data with the right rewards, uh, value props for our customers, uh, that opt to create accounts with their permissioned data and ultimately transact with our brand. Um, this permissioned data, it gives us another lever to pull as a reason to talk to our customers. Um, for example, reaching out to teachers during our teacher appreciation week and giving them a unique offer for their audience to incentivize them to shop with us. Um, you know, we’re working on creating a full-funnel approach and maintaining the relationship through the customer’s stages of ownership. So, with the goal that we can stay top of mind and ease immediate price sensitivity by offering an ongoing but unique value prop across all stages of their ownership.
32:29
Chris Oliviera: Nice. Awesome. Well, thank you so much. I think that was super informative. We learned a little bit more about permissioned data and how it can help us build loyalty with our customers. We’ve defined what permissioned data is, we talked about how we can gather it, and how we can leverage it to increase lifetime value in general. So, I want to make sure we have—we have a few questions in the chat. I want to get to those quickly. Let me take a look here really quick. Let’s see. Uh, Rebecca, I’ll start with you. What are the biggest challenges that you see brands facing when it comes to using permissioned data?
33:14
Rebecca Grimes: Uh, great question. And, you know, I’m pretty regularly talking, you know, with customers today about, you know, they’re already gathering that permissioned data and how do they actually leverage that in new and different ways. Um, I—I think that once you get that strong value exchange—we talked about earlier—defined, it—it’s the first hurdle. So, how do you make sure that there is something compelling enough that allows for that data to be collected so that you can then action on it? And I think this is sometimes where folks are stumbling on, you know, trying to look at promotional activities across the organization and trying to design something new or different. And my recommendation is to look at programs that you were already delivering on. So think about a lot of folks who are in back-to-school planning—so students and educators are likely top of mind for you to gain their wallet share for the upcoming fall season. As you’re thinking about those programs, what are the ways that you can define strategies to collect permissioned data that authenticate an educator or a student in exchange for something with the program that you’re already running? So don’t reinvent the wheel; just analyze what you’re already delivering against and then build and augment that strategy accordingly. I think the next challenge that people get stuck on is, “I need to action on this data immediately,” and that means that I’ve got to get my IT resources involved and I’ve got to work collaboratively and get that done, and they’re on a backlog of six months and… all of that, um, is—is—is factual. However, um, my recommendation is to just start. Even if you end up taking that data and you are uploading that manually on a regular cadence and then using that for retargeting, that is okay. It doesn’t have to be, uh, perfect from day one. You can think about launching this in phases and then actioning on it, um, in an orchestrated way as a Phase 2 or Phase 3. And—and lastly the thing that I—that I often hear from our customers is, um, um, you know, how does this scale? And, you know, do I have to do in-store if I have brick-and-mortar as well as online at the same time? And again, my recommendation is to just start. Build on a foundation, test, learn, be agile, figure out what is the carrot that gets that permissioned data to feed into—into your marketing CRM or CDP, and then—and then build upon that and learn from it and figure out if you have to deliver an evergreen offer, so perpetual student discount that’s available year-round or even a pulse offer where we’re doing a handful of promotions throughout the year, um, you know, so just on a specific audience. All of those things, um, you can define today and then evolve over time.
35:59
Chris Oliviera: Great, I love that. Um, Pat, I have one that I think would be great to hear from you is: how do you see the role of permissioned data evolving, let’s say in the next two to three years?
36:12
Patrick Debkowski: Yeah, I think, um, as more regulation around gathering personal information online goes into effect, um, I expect more efforts across online retailers to explicitly seek out more personalized data. Um, you know, as a result, customers will likely become increasingly more willing to provide that permission-based data, uh, as long as they get something out of it. So over the next few years, brands and retailers that use this data in the most responsible, authentic, and creative ways, while providing customers meaningful value in return, ultimately they will become the preferred shopping destination for these customers.
36:55
Chris Oliviera: Great. Um, thanks Pat. Let’s see. Let me pick another one here. There’s—there’s a bunch coming in. So if we don’t get to all the questions, uh, today, we’ll make sure to answer them afterwards so we get to—to the answer for that. There’s—there’s a ton coming in. So, um, let’s see. Rebecca, what—we talked a little bit about—and I’ll ask this question—but the value exchange, right? What are some of the incentives that you found uh to be the most effective for different types of audiences? Even Pat mentioned a few audiences that they—uh, that they make these offers available to. How do you—what—what are some of those value exchanges that—that work best for them?
37:41
Rebecca Grimes: Yeah, we touched on this a little bit earlier, but obviously discounts are the—you know, the most obvious. You know, an “I’d like a relationship” in—in order to capture that initial set of permissioned data. So most popular incentives, um, are, you know, 10% off a purchase, a BOGO, free shipping, occasional, you know, spiking up to 20% off if you’re trying to use that to leverage, you know, smoothing out potentially a rough month; you can, you know, toggle things on and off as needed, uh, to engage with specific audiences. And, you know, beyond those discounts we’re seeing a lot of brands get creative with exclusive early access to new product launches and double loyalty points. Um, something where, you know, in—in those consumers feel special in exchange for giving you that information. Um, one—one other interesting, um, strategy that we’re seeing—and we just, you know, talked about this earlier today in a press release—is an increased prioritization on low-income audience engagement. And brands are leaning into these new incentives to attract consumers. Um, that Pat actually mentioned. You know, we—we recently launched a program with Albertsons, and they, um—they—they prioritized obviously engaging with, you know, programs like the Supplemental Nutrition Assistance Program, the SNAP program, where recipients, uh, receive a 50% off discount on their Fresh Pass program. And so they get a range of benefits and exclusive perks in exchange for shopping there. And, you know, they—they, you know, shared that information to qualify in a very simple and secure online process, and then that data is used by Albertsons to really deliver on that purpose-driven marketing that we talked about earlier.
39:26
Chris Oliviera: Awesome. Uh, this next one could be for—for either one, so feel free to jump in and—uh, feel free to answer this. But, uh, another question: How do you balance the need for personalization and targeted communication without coming off as too intrusive? Even though people willingly share their information, not everybody wants to be constantly reminded or targeted. It can sometimes feel like “my phone is listening” (in quotation marks). It’s always a slippery situation to make customers—consumers uneasy.
40:00
Patrick Debkowski: I’ll jump in first. Um, yeah, I think, you know, what comes to mind for me is um, when you’re soliciting this data from the customers, only get the depth of data that you really need as a marketer to provide the right level of personalized experience for the customer. So, you know, it’s great if I can learn about professional affiliation; I don’t need to know what their favorite color is. Um, so just finding that right balance of—of information that you are gathering in the first place. I think if you’re able to keep that amount of information acquired limited and focused on what is truly important, you know, ultimately it will help reduce privacy concerns that might come from collecting irrelevant information.
40:42
Rebecca Grimes: Yeah, uh, great—great answer Pat. And, you know, what comes to mind is that you can also progressively capture data. It doesn’t all have to be on your very first interaction with that brand. And so when—when I’m interacting with a—with a brand and they, um—they communicate the why and I feel seen, I’m more willing to align myself and share data and information with them, um, as—as my journey goes with them. So again, be authentic, make it clear what that value exchange is and remind them early and often what they get in exchange for that. Again, anticipating needs, um, makes people’s lives easier. So how to use that data to anticipate the next step, going back to the swing that I didn’t have on my registry that, you know, I had delivered the next day. Like, that was that brand engaging with me and being helpful, and so I’m willing to continue to give them more and more information when it makes my life easier. And or saves me money.
41:42
Chris Oliviera: Absolutely. Um, again, another one for—for—for either one. But, um, how do you tie and then we talked a little bit about this, but maybe you can expand this a little bit more—how do you tie ROI to permissioned data?
41:59
Patrick Debkowski: For me, it’s pretty easy. I mean, the data speaks for itself. Um, when we look at these audiences uh that provide the permissioned data versus those who do not, um, you know, the metrics are very clear. Um, these audiences outpace all the other audiences in metrics like conversion rate, in AOV. Um, so we—we’re able to quantify that, actually, with the data we have, um, and the investment is well worth it, uh, at least from our side.
42:32
Chris Oliviera: Great. Um, and I want to get to one more question here, especially when it comes to ROI, KPIs, like getting that cross-functional buy-in. How—so how do you—the question is—how do you approach educating leadership or a cross-functional team about the value of permissioned data? Getting people’s buy-in to see that this is really valuable and we should be investing in something like this.
43:01
Patrick Debkowski: Yeah, like I said about data, I mean, it is really clear when you look at it. Um, when we have our business performance reviews over a given time period, you know, we drill down to the audience level. Um, we’re able to delineate between those who have given us permissioned data and those who have not. Um, and the data is dramatic enough where it’s—it’s really hard to ignore the value. So having those data points for our senior leadership in those business reviews, uh, it’s—it’s super clear and and they’re able to see the value immediately. Um, working with cross-functional partners, you know, we did a kickoff earlier this year uh to educate our broader D2C team on all of our loyalty initiatives. Um, you know, for those people who are seeing the data for the first time, uh, it was pretty eye-opening. Um, we’re able to get some additional support coming out of that kickoff that really wasn’t there before, um, by simply demonstrating the value of these customers and framing it in the context of how it can help some of our cross-functional partners in their work streams, and ultimately make their life easier. Uh, so yeah, I mean, those are the two ways how we kind of communicate with leadership and how I—I’ve worked with cross-functional partners to—to see the value here.
44:10
Chris Oliviera: Great. All right, let’s do one more question, and then we’ll—we’ll throw it back to Adweek. Can you share some strategies—maybe Rebecca if you could—if you could answer this from the conversations that you have with—with brands—is can you share some strategies where the main aim is to drive consumers back to the brand when a consumer has been lost to the competitor, but was a prior customer? How deep should the effort be given, uh, consumers’ preferences are hard to pivot? Given that consumer preferences are hard to pivot? Maybe, uh, how—how can we do that with—by using the data, right?
44:57
Rebecca Grimes: Yeah. Uh, you know, I—I think—I think this is something that a lot of brands are trying to figure out right now. There is so much consumer choice in how and—and where they spend their dollars. And so, you know, re-engagement or win-back strategies, especially, um, you know, when you had a highly engaged consumer and they left, um, you know, my—my recommendation is to go build look-alike models to look at what permissioned data that you have on that consumer, compare that to the buying habits of other, uh, of other similar consumers that are behaving as a cohort similar to you, uh, to what you want, you know, this—this other consumer to behave like, and figure out again that, you know, that very compelling value exchange that pulls them back into your funnel. And for, you know, different consumer segments it’s—it’s going to look different. And that’s where, you know, really mining the data and building out audience-driven, purpose-driven marketing activities based on what outcome you’re trying to deliver. So you define, “This is what my strategy is going to be for,” you know, “to deploy against. I want to get returning customers who haven’t shopped with us in the last 18, 20, 24 months. What is the offer or the message or the reinforced value or the ‘I know who you are’ um ‘and these are our values and we align’? How do you pull them back into your funnel?” Those are all very bespoke strategies that while they might have similarities, you have other consumers that are behaving that way that you want this other cohort to behave. So leverage that intelligence and that data and deploy it and test and learn and be agile. Um, and I—I’m confident that the data resides—uh, you know, the answer resides somewhere in your data on—on how to pull those levers.
47:41
Chris Oliviera: I love that answer, Rebecca, because it actually answers another question I saw on the chat regarding how can we use permissioned data to improve the pre-purchase experience. So I think creating these look-alike models using good data is one of the best ways that you can improve that, uh, pre-purchase experience or—or get more people at the top of—of the funnel. So thank you so much for that, I appreciate it.
48:05
Ryan Wooford: Absolutely. Well, thank you to our speakers and to our sponsor SheerID for this. This was a wonderful conversation. To everyone who asked a question, Chris noted this, but if we didn’t get to one of your questions, uh, those will be provided back to the people here on this call so that they can respond directly, uh, to you. Some final reminders from Adweek before we go: Make sure you download the slides from the event resources tab and check your email for the on-demand recording later today. As always, if you enjoyed today’s webinar, make sure you check out our full slate of webinars at adweek.com/webinars. And lastly, just again, a big thank you Chris, Rebecca, Pat. Thank you to our audience for joining today. We—we appreciate your engagement with us and the learning that you do uh on a week-to-week basis. So we look forward to seeing everyone at an upcoming Adweek webinar soon. Thank you.
[Introductory slide displays: “The Secret to Unlocking Customer Lifetime Value – April 9th, 2025”]
Ryan Wooford: Well hello, and good afternoon. Welcome to today’s Adweek webinar. Customer Lifetime Value shapes the way a brand makes decisions. A CLV North Star informs marketing spend and platform goals; it provides space for customer segmentation and retention, and broadly provides data back to product development strategies. But what is the secret to unlocking Customer Lifetime Value? Today, we’re excited to be joined by friends from SheerID and Whirlpool to discuss permissioned data and why it is a critical part of their marketing strategy.
00:42
Ryan Wooford: I’m Ryan Wooford, the VP of the Branded Studio here at Adweek, and we want to thank today’s sponsor, SheerID, for making this discussion possible. Before we begin, let me do some housekeeping for our presentation today. Today’s webinar presentation will run approximately 30 to 35 minutes, after which we should have time for audience Q&A. So if at any point you have a question for one of our speakers, just use the Q&A tool beneath the video window on your screen, and we’ll get to as many questions as we can after the end of the presentation.
01:12
Ryan Wooford: Also, it’s not too late to invite your colleagues to join us today. About 15 minutes ago, you likely received a final reminder email from us. In there, there’s a link to the webinar registration page that you can share with your colleagues; there’s still plenty of time for them to join us. Uh, if they can’t, or if you’d like to revisit our discussion at a later date, today’s webinar is being recorded. The on-demand version will be available to all registrants via link, which will be provided later today in your email. And if you’d like a PDF of today’s slide deck, you’ll find that in the event resources area beneath the window on your screen.
01:47
Ryan Wooford: As always, if you enjoy today’s webinar, definitely check out our full slate of webinars at adweek.com/webinars. Now, uh, for today’s speakers. We’re happy to be joined by Rebecca Grimes, the Chief Revenue Officer at SheerID; Chris Oliviera, who’s Product Marketing Manager at SheerID; and Patrick Debkowski, the Senior Manager of D2C Merchandising at Whirlpool. I’m going to let them introduce themselves, so Chris, take it away.
02:17
Chris Oliviera: Sure. Thank you so much, Ryan, I appreciate it. Well, thank you everybody for joining us today. The topic of today is—kind of Ryan alluded to this already—is the power of permissioned data when it comes to this becoming a secret of unlocking Customer Lifetime Value, right? I think a lot of times we have these conversations that are very timely, and I don’t think this could be a—a more timely discussion. Literally today, right, we’re talking about, uh, the uncertainty when it comes to the macroeconomics of things and how important it is to create relationships—direct relationships—with consumers so they choose your brand time and time again. So let’s jump into a quick round of introductions uh, for—for us three, and then we’ll get into the topic today. Sound like—all right. So, my name is Chris Oliviera, uh, Senior Product Marketing Manager here at SheerID. Been here for about four years or so in sunny Fort Lauderdale, Florida. And I—and I love this topic. I love understanding, uh, the needs, challenges, and successes of our customers, and understanding our customers’ customers as well so we can serve our customers better. So, Rebecca, I’ll turn it over to you.
03:29
Rebecca Grimes: Hi everyone, Rebecca Grimes, I’m the Chief Revenue Officer at SheerID and I oversee all of our customer-facing teams. I have been here, um, a little under a year, and I’m really excited to talk about this topic today. This is one that is very near and dear to my heart. I’ve spent the last, um, 15-plus years working alongside some of the world’s most admired brands. This is my second time, um, working with Whirlpool and, uh, and really excited to—to start this discussion today.
04:01
Patrick Debkowski: Hey guys, I’ll jump in. Um, my name is Patrick Debkowski. I’m the Senior Merchandising Manager at Whirlpool Corporation for our D2C business. So, you may or may not know, Whirlpool owns, of course, the Whirlpool brand, KitchenAid, Maytag, Amana, JennAir, and others. Um, and so my responsibility is leading our D2C team, helping sell our products directly to our consumers. Um, with that, loyalty is one of the arms, uh, that I lead, and—and one of the focuses of today’s conversation.
04:30
Chris Oliviera: Awesome. Thank you guys for—for joining us today. So, before we jump into increasing lifetime value with data, we need to define a couple of things, right? You might have heard us say: “Permissioned Data.” What—what does that mean? Maybe a lot of you haven’t heard that term, so let’s define that before we go into some best practices of how to leverage this type of data. So, a quick definition here: Permissioned data is consumer data that brands collect and use with explicit consent, ensuring a transparent value exchange where consumers clearly understand how their data will be used and what they will receive in return. So let’s expand on that a little bit. Um, Rebecca, I’ll—I’ll turn the first question over to you. What is permissioned data besides beyond this definition, and how does it differ from other types of consumer data?
05:25
Rebecca Grimes: Thanks, Chris. Um, one of the things that permissioned data clearly differentiates itself is around—it emphasizes the importance of building those genuine connections with consumers. Because it’s more crucial than ever. Factors like increased privacy regulations and shifting consumer expectations and, as Chris just mentioned, economic uncertainty are all reshaping the marketing landscape. Consumers are seeking out these brands who share similar—similar values and are focused on building relationships and trust with their consumers. So now more than ever, brands have to do more to attract and retain customers. Which means that brands and industry leaders need to move beyond just first or zero-party data to emphasize the consumer consent and control, leading to the adoption of the term “permissioned data.” So, permissioned data is any data that a consumer willingly and knowingly shares with a brand. This—this consent can be given explicitly, such as through an opt-in form, or implicitly through continued engagement with the brand’s content and services. By focusing on building trust and transparency, brands can navigate the challenges that sit in front of them and create lasting relationships with their audience.
06:40
Chris Oliviera: Nice. Okay. Right. And so why—why do you think permissioned data is considered like the gold standard when it comes to consumer insights?
06:51
Rebecca Grimes: Yeah. So let’s start by breaking down these data types and then look at the pros and cons of each one. [Slide displays: Comparison chart of Third-Party, Traditional First-Party, and Permissioned Data] So this chart provides a clear overview and I’ll walk you through each category. First up, we have Third-Party Data. Third-party data is collected without direct consumer involvement and is less reliable due to privacy regulations. For example, purchasing a list of email addresses from an external provider based on specific attributes is acquiring third-party data. As you can see, the pros are that it is quick to acquire and scale and offers broad reach. And this might seem appealing initially, however the cons are significant. This marketing approach suffers from low accuracy and is heavily restricted due to increasing privacy regulations. And most importantly, it often reduces consumer trust. In today’s market where trust is paramount, relying heavily on third-party data can be detrimental. As a consumer, I am bombarded, as I’m sure many of you as marketers are, with emails daily from companies that I don’t have any relationship with. And that immediately leads me to not only unsubscribe but potentially avoid that brand altogether.
08:00
Rebecca Grimes: Next, we have Traditional First-Party Data. The pros here [are] that it is collected directly from consumers and it’s more reliable than third-party data. This is the data you’ve gathered from your own website or interactions. However, the cons are crucial to consider as well. This data is often passively collected without explicit consumer consent. This means customers might not be fully aware how their data is being used. Furthermore, it might not comply with future privacy regulations and, as regulations tighten, this type of data collecting is becoming increasingly risky.
08:36
Rebecca Grimes: Building consumer trust with first-party data happens when consumers opt in to its use. Prompting a consumer to accept cookies when visiting your website may appear to be consumer consent, but when somebody actively raises their hand by checking a box to receive content from your brand, they are then actively opting in and giving you permission for that data to be used for marketing purposes. And let’s keep in mind that consumers remember their very first interaction that they have with your brand. So leaning into creating a transparent and trusting relationship is critical from the moment they begin to engage and then reinforced through ongoing interactions that will drive increased Customer Lifetime Value and purchase frequency. The golden standard that we are all after.
09:24
Rebecca Grimes: So finally, and most importantly, we have Permissioned Data, which includes both zero-party data—which is proactively shared by consumers—and then that first-party data that is collected with explicit consent. The pros here are substantial. The data is highly accurate and consumer verified. It builds trust and strengthens brand relationships because consumers know and have agreed to share their information. It’s also compliant with privacy regulations like GDPR and CCPA, which is essential today. And it enables deeper personalization, which leads to higher Customer Lifetime Value. The cons are that it requires a strong value exchange to encourage that data sharing. You need to offer something in return to make it worthwhile. Something like points, discounts, early access, or exclusive content to encourage consumers to share that data with you. Permissioned data also takes time to collect and scale compared to third-party data, which means that you need to be thinking about it well in advance of activating on this data to build a strategy for how to collect and leverage that data. However, the long-term benefits of trust, compliance, and personalized experiences far outweigh these challenges. Think of it as building a strong foundation rather than a quick fix. And the good news is that you can start to collect the data in parallel while you’re building out that strategy for how to meaningfully use the data.
10:54
Chris Oliviera: Great. Thanks, uh, Rebecca for that. I want to ask you one more question, and—and I want to hear from Pat afterwards. How does permissioned data help brands build this type of trust with customers, with their customers?
11:12
Rebecca Grimes: The transparency of the collection of this data, consent-based actions like filling out a form or completing account profile settings with a clear understanding of the give-get for the customer, can instantly build trust compared to other marketing tactics. Consumers willingly share their data because they see a direct benefit. Furthermore, consumers know that they’re sharing, what they’re sharing, and why they’re sharing it. Confidence in that brand increases because they understand how it is mutually beneficial. This is especially important during times of economic uncertainty where people are more intentional with how and where they spend their money and with whom.
11:52
Chris Oliviera: Great. Pat, I want to hear from you. How important is consumer trust when collecting this type of permissioned data at Whirlpool?
12:01
Patrick Debkowski: Yeah, so coming from the perspective of a manufacturer who also sells our products directly to consumers, uh, we need to make sure that our customers have the same level of trust in sharing their personal information with us, um, to the same degree or even greater than the customer trust that we’re selling them a quality product. Um, maintaining this trust with their digital experience can extend to the impression on our physical products as well. So you can imagine how important that is to keep a positive perception in order to keep the—the customer loyalty to our brand. Um, you know, in a competitive environment like what we are in today, the trust of the manufacturer is crucial to the customer so that they know that we will use this data responsibly and reward them accordingly, uh, for sharing that information with us.
12:49
Chris Oliviera: Great. Awesome. So, uh, appreciate all all those answers. I think that helps really frame what permissioned data really is, and—and and we’re starting to get into kind of some of the benefits of that. But I want to talk about how we, uh, can collect this type of permissioned data, some of the strategies and best practices. So, Rebecca, I’ll turn it over to you and, uh, what are—what are some of the other ways brands are gathering permissioned data today?
13:21
Rebecca Grimes: Yeah, I think the most obvious one is obviously with exclusive offers, which, you know, consumers are willingly sharing data to access special pricing, exclusive offers, and even membership-based perks if you think about like a student, a military, or a senior discount. There are also other ways that aren’t necessarily offer-driven. So, in-brand experiences; so brands can collect data through customized quizzes, preference centers, interactive tools that tailor recommendations based on customer input. Uh, most, you [know]—obvious then is if you have a loyalty program or rewards program that you’re encouraging customers to share data in exchange for points or tiered benefits or early access to products and events. That’s just another way to incentivize the collection of this data without having to offer a discount. Gen Z in particular values first and early access to products or events. So if they’re in your target market, think about how to drive parallel strategies that might combine all of the above and best practices to maximize the collection of this permissioned data. The common theme here is that quality strategies include a clear value exchange.
14:34
Chris Oliviera: Yeah, uh, I love that. And so let’s—let’s spend some time digging a little deeper into this concept of value exchange. I put together this quick definition of—of value exchange here for us to take a look at. [Slide displays: “Clear Value Exchange – Consumers willingly share their data when they see a direct benefit…”] And then we’ll dive a little bit deeper into—into this. But, uh, what is clear value exchange as we talked about this, right? Consumers willingly share their data where they see a direct benefit. A strong value exchange provides tangible rewards (e.g., discounts, early access—all these things we’ve been talking about) and enhanced experiences (e.g., personalization, seamless interactions, that type of thing). Making data sharing feel like a fair trade. And that’s the key there. So, um, Rebecca, I’ll turn it over to you one more time. How can brands create a compelling value exchange to encourage this type of data sharing?
15:29
Rebecca Grimes: Yeah. So as we’ve outlined here on the slide, obviously start by making it clear. Consumers need to immediately understand what they gain—exclusive pricing, personalized offers, or a better shopping experience. The next is really make it authentic. Consumers are smart and they know when a brand truly cares about them as an individual and when their actions are superficial. Don’t be afraid to lean into your values when asking for data. Remember that consumers are drawn to brands that align with their values. Today more than ever when they have so many options on where to spend their money. Make it easy. The process of sharing data should be simple, fast, rewarding. No unnecessary steps or confusing terms. And make it worthwhile. Brands need to use that data to enhance the customer experience by providing personalized recommendations, those early access promotions, improving support. So reinforcing trust and long-term engagement means that you need to make sure that there is a strong compelling give-get. Every day I see brands that display a prompt to give your email in exchange for a 10% discount. An email address doesn’t tell you anything about that consumer, and you just gave away something valuable in exchange for one data point when you could have captured more and explained the why behind the ask. So think through the data elements that will enable you to drive that deeper engagement with your customers and then orchestrate a way to make that data exchange clear, authentic, easy, and worthwhile.
17:01
Chris Oliviera: Absolutely. So, uh, Pat, from your perspective now, uh, how does Whirlpool create this type of compelling value exchange that encourages consumers to share their data with you?
17:14
Patrick Debkowski: Yeah, so we have unique value props uh that incentivize our customers to share these additional permissioned data up front as part of our account creation process. Um, you know once—once we collect some of that data from our customers, we’re able to use it to tailor offers, unique experiences, um, to meet them wherever they’re at in the shopping journey. Uh, this includes things like professional affiliation uh to find the right moments to speak to their specific audience and engage in authentic ways. Um, in addition, we’re implementing ways for customers to share permissioned data to extend offers in their own communities through word of mouth to amplify the reach of our own authenticated audiences. Uh so this word of mouth would have unique benefits for both the person referring as well as the person who is receiving the referral.
18:05
Chris Oliviera: Yeah, and I want to follow up to that really quickly. Are—are there any unexpected or any surprising results that you might have seen uh from running these types of audience offers?
18:17
Patrick Debkowski: Yeah, there’s a few things that come to mind. One of the more surprising results uh we’ve seen is the way we’re attracting customers organically through these offers, without much of a paid media activation behind it. So, there are some audiences in particular that know to go out and look for these specific offers, um, and they’re able to find them on their own without us really screaming it from the rooftops. Um, you know, it’s clear that while promotions on price are impactful, what comes to permission-based data is also super important: serving up a personalized and authentic experience for these audiences. Connecting these audiences with some of the broader missions of our corporation can help further build that trust with the customer. You know, one example I could point you to uh that we have is um our “Care Counts” campaign, where Whirlpool Corporation has been working in collaboration with Teach For America to donate washers and dryers to schools that help provide broader access to clean clothes for those who are in need. Um, you know, communicating these initiatives with an audience like teachers can help build that trust uh that we support initiatives that hit really close to home for them specifically. Um, you know lastly, I think uh one more surprising thing is we do see a high conversion rate from some of the more traditional audiences who expect to be offered discounts. Think military, seniors, first responders. But what might be more surprising is the engagement we receive from audiences that are not accustomed to being rewarded for their permissioned based data. In this case, we target veterinarians, interior designers, recent movers, uh real estate agents. To these audiences, you know, finding out where they qualify for a unique offer can be the tipping point which really helps push them in the direction of purchasing from us.
20:06
Chris Oliviera: Awesome. Thanks for that insight, Pat. Appreciate it. I—I think now it’s a good time for us to talk about how we can now leverage this type of permissioned data to increase that lifetime value, right? So we—we defined what permissioned data is, we talked about some best practices of collecting that type of data. Now let’s get to the meat of it, right? How can we use the data to—to increase our lifetime value? So, um, Rebecca, I’ll start with you. You’ve spoken to a lot of innovative brands; I talk to them all the time, every day. What are some of the key business KPIs that they’re tracking to measure the impact of permissioned data on their overall business health?
20:55
Rebecca Grimes: Great question. Um, and I am so glad to be able to—to work alongside some of the—the Whirlpool’s admired brands and the ones that are very, very near and dear to my heart. I actually have a brand new Whirlpool dishwasher in my kitchen, um, um, that my husband loves. Um, um, he’s a—he’s the dishwasher. But, um, I think that, you know, there really has been a shift for marketers where every dollar spent is increasingly being scrutinized for ROI and impact. So, of course, those traditional engagement and conversion KPIs are still important. This includes things like opt-in rate, email open rate, and funnel conversion. These metrics tell us whether customers are seeing value in sharing their data. If opt-in rates are high, that means you’re offering a compelling reason for customers to share their information. And if email open rates and conversion rates are strong, it indicates that the personalized experiences you are delivering with that data are resonating. Identifying new customers or first-time customers is another critical KPI for brands, along with win-back KPIs to re-engage with customers who haven’t purchased from the brand in 18, 24 months. We are also seeing a lot of analysis on Customer Lifetime Value, the topic of today’s uh webinar. And that’s being broken down further by specific cohorts of channels of acquisition, audience attributes, and more. So understanding Customer Lifetime Value really involves looking at repeat purchases, average order value, frequency of purchase, and overall customer retention. Permissioned data enables you to lean on purpose-driven marketing by leveraging the data you collect to curate at scale content that will resonate with each individual consumer. And so when you get this right, you will find specific cohorts that are outperforming historical average levels. When you know what your customers want and need, you can provide them with much more value, which keeps them coming back. And when you get this wrong, it can actually turn customers away from you.
22:56
Rebecca Grimes: And I’m going to share a bit of a story. I recall when I became a first-time mom. I had registered at several different retailers because of, uh, everything from my expected due date, the gender of my baby, and the brands I was likely using, and so much more. And I recall one of my first nights as a new mom scanning my phone in the middle of the night, probably with a screaming baby, um, and seeing a message from this retailer showcasing bicycles that were on sale. Um, by contrast, in my same email inbox at another retailer that I had registered with, and they had delivered this personalized message to me with helpful tips for first-time parents or ideas of full products that were not included in my registry, one of them being a swing that I immediately ordered from my phone at 3 AM in the middle of the night and had delivered to my house the next day. That made all the difference to me for how I felt connected to that brand over the other brand, and they became my go-to for all of my needs. So for marketers that are living in the data and looking for those headwinds and tailwinds, those are the ones that are going to scale well even in uncertain times by really using the data to inform how they’re leveraging not only permissioned data but also that purpose-driven marketing to combine that for the exact experience that’s going to connect with the consumer.
Part 3: Advanced Applications and Q&A
24:11
Chris Oliviera: Awesome. And so let’s—let’s talk about loyalty for just a second. You alluded to this already; I just want to expand this a little bit more. But beyond repeat purchases, how are these brands that—that you talk to uh defining loyalty beyond, like I said, the just repeat purchases? What does that look like?
24:29
Rebecca Grimes: Yeah. Obviously, the example I just shared was a great one. It’s more than just someone buying from you again and again because I still shop regularly with that retailer. Brands that are thriving are recognizing the importance of emotional connection. So those truly loyal customers are going to advocate for the brand, they’re going to engage with your content and refer others. They’re not just customers, they’re brand ambassadors. And that kind of emotional connection is really built on trust and personalized experience, which permissioned data—[Pat 2 compression starts here]—going back to the example that I just shared, I was talking to one of my friends who was soon-to-be parent about my overwhelmingly positive experience. And that influenced their decision on where to register and then eventually spend their money. Loyalty can also be measured in examining engagement and interaction. So metrics like time spent with the brand, participation in its loyalty programs, response to personalized offers, also show a much deeper level of commitment. It’s about the quality of the interaction, not just the transaction. When a customer spends time exploring your content, participates in your loyalty program, discovers new products that you recommend, it signifies a strong and engaged relationship.
25:42
Chris Oliviera: Got it. Cool, great. Rebecca, that’s a great answer. Uh, Pat, and what about you from your perspective at Whirlpool? How do you define loyalty beyond just repeat purchases from customers?
25:55
Patrick Debkowski: Yeah, you know, repeat purchase is great. Um, but in an industry like appliances where customers aren’t frequently in the market, you know, what is more important to us is that continued trust in the product, the brand, um, and engagement with us throughout their product ownership life cycle. Um, you know, you could think of it like a car. You don’t buy a car very often, but when you do buy a car, you’re doing deep research, uh, and likely you have a deep affinity already with a brand, uh, before you even go make that purchase. Um, as a result, you know, we’re tracking loyalty at a customer level as engagement throughout the life of the appliance, rewarding these customers for their needs in between purchases. Think of things like service, repairs, warranty, uh, product education. Um, you know, we also have the opportunity to cross-sell consumable products that are—that will help maintain and extend the life of their appliances. Things like water filters; um, you could have a subscription to that, um, where it’s delivered to your home every six months. Um, we sell appliance cleaners, accessories that go along with your appliance. Um, these are all ways to keep that customer engaged in between the major appliance purchases and ultimately maximize the Customer Lifetime Value.
27:08
Chris Oliviera: Great. Cool. And Rebecca, one more question for you. Uh, we’ve talked about the importance of permission data, the KPIs to track, how brands are defining, uh, loyalty. Now let’s—let’s talk about a crucial question: how can brands effectively leverage this data to maximize Customer Lifetime Value?
27:32
Rebecca Grimes: Yeah, that—that’s a great question. And, you know, first I think about personalization at scale. And so this isn’t just about sending an email with somebody’s name. It’s really about understanding individual experiences and behaviors and using that knowledge to deliver those tailored experiences. With permissioned data, you can offer exclusive offers, relevant product recommendations, content that speaks directly to each customer and actually do that at scale. Um, this leverage—this kind of level of personalization for me, uh, helps keep me engaged and makes me feel valued. And I think that that’s what consumers are actually seeking out in the brands that they’re spending their money with today. Um, you know, the next way to leverage data is really around proactive engagement and retention efforts. Permissioned data allows you to anticipate those customer needs before they even arise. By analyzing the data, you can identify anomalies that deviate from your purchase history and proactively engage with them to drive them back to your brand. So, for example, you know if a customer hasn’t made a purchase from you in a while, you could send them a special discount or personalized message reminding them of the value that you provide. And you could also use those similar insights to enhance your loyalty program and create targeted outreach campaigns that resonate with specific audiences. And, you know, finally—and I know that this is a buzzword, um—and this is where it really is exciting is that we’re seeing more and more brands feeding that data into AI models. And permissioned data is really gold for those AI models. It enhances that predictive analytics, the customer segmentation, and it really allows those brands to optimize cross-sell and up-sell and life cycle marketing strategies with incredible precision. And, you know, imagine being able to connect with a customer when they are most likely to buy next. Um, AI models, you know, powered with this permissioned data make that possible. Uh, you know, an AI model could analyze purchase history and browsing behavior and suggest complementary products or predict when a customer is ready, uh, for an upgrade or a new service. Uh, I realized we were out of dog food last night, and it would have been great if I proactively had been told, “It might be time for you to order dog food before we run out,” um, and then I had to go panic and have it, uh, prioritized for next-day delivery. So, you know, when you’re thinking about Customer Lifetime Value with this permissioned data, it’s all about understanding your customers at a deeper level and then using those insights to deliver those personalized, proactive, and intelligent interactions. By focusing on those three strategies I just mentioned, you not only increase CLV, but you also build those stronger, more meaningful relationships with your customers. This just is not about data; it’s about creating those experiences that truly resonate and differentiate you from your other brands.
31:18
Chris Oliviera: Absolutely. Absolutely. Uh, Pat, um, one last question for you and then we’ll throw—there’s a few questions in the—in the chat that, uh, I wanted to share and get to you. But, Pat, at Whirlpool, how are you thinking about permissioned data, uh, and how it’s going to support your growth this year?
31:38
Patrick Debkowski: Yeah, I mean, at the core of it, um, it’s focusing on unlocking the give-to-get nature of permission-based data with the right rewards, uh, value props for our customers, uh, that opt to create accounts with their permissioned data and ultimately transact with our brand. Um, this permissioned data, it gives us another lever to pull as a reason to talk to our customers. Um, for example, reaching out to teachers during our teacher appreciation week and giving them a unique offer for their audience to incentivize them to shop with us. Um, you know, we’re working on creating a full-funnel approach and maintaining the relationship through the customer’s stages of ownership. So, with the goal that we can stay top of mind and ease immediate price sensitivity by offering an ongoing but unique value prop across all stages of their ownership.
32:29
Chris Oliviera: Nice. Awesome. Well, thank you so much. I think that was super informative. We learned a little bit more about permissioned data and how it can help us build loyalty with our customers. We’ve defined what permissioned data is, we talked about how we can gather it, and how we can leverage it to increase lifetime value in general. So, I want to make sure we have—we have a few questions in the chat. I want to get to those quickly. Let me take a look here really quick. Let’s see. Uh, Rebecca, I’ll start with you. What are the biggest challenges that you see brands facing when it comes to using permissioned data?
33:14
Rebecca Grimes: Uh, great question. And, you know, I’m pretty regularly talking, you know, with customers today about, you know, they’re already gathering that permissioned data and how do they actually leverage that in new and different ways. Um, I—I think that once you get that strong value exchange—we talked about earlier—defined, it—it’s the first hurdle. So, how do you make sure that there is something compelling enough that allows for that data to be collected so that you can then action on it? And I think this is sometimes where folks are stumbling on, you know, trying to look at promotional activities across the organization and trying to design something new or different. And my recommendation is to look at programs that you were already delivering on. So think about a lot of folks who are in back-to-school planning—so students and educators are likely top of mind for you to gain their wallet share for the upcoming fall season. As you’re thinking about those programs, what are the ways that you can define strategies to collect permissioned data that authenticate an educator or a student in exchange for something with the program that you’re already running? So don’t reinvent the wheel; just analyze what you’re already delivering against and then build and augment that strategy accordingly. I think the next challenge that people get stuck on is, “I need to action on this data immediately,” and that means that I’ve got to get my IT resources involved and I’ve got to work collaboratively and get that done, and they’re on a backlog of six months and… all of that, um, is—is—is factual. However, um, my recommendation is to just start. Even if you end up taking that data and you are uploading that manually on a regular cadence and then using that for retargeting, that is okay. It doesn’t have to be, uh, perfect from day one. You can think about launching this in phases and then actioning on it, um, in an orchestrated way as a Phase 2 or Phase 3. And—and lastly the thing that I—that I often hear from our customers is, um, um, you know, how does this scale? And, you know, do I have to do in-store if I have brick-and-mortar as well as online at the same time? And again, my recommendation is to just start. Build on a foundation, test, learn, be agile, figure out what is the carrot that gets that permissioned data to feed into—into your marketing CRM or CDP, and then—and then build upon that and learn from it and figure out if you have to deliver an evergreen offer, so perpetual student discount that’s available year-round or even a pulse offer where we’re doing a handful of promotions throughout the year, um, you know, so just on a specific audience. All of those things, um, you can define today and then evolve over time.
35:59
Chris Oliviera: Great, I love that. Um, Pat, I have one that I think would be great to hear from you is: how do you see the role of permissioned data evolving, let’s say in the next two to three years?
36:12
Patrick Debkowski: Yeah, I think, um, as more regulation around gathering personal information online goes into effect, um, I expect more efforts across online retailers to explicitly seek out more personalized data. Um, you know, as a result, customers will likely become increasingly more willing to provide that permission-based data, uh, as long as they get something out of it. So over the next few years, brands and retailers that use this data in the most responsible, authentic, and creative ways, while providing customers meaningful value in return, ultimately they will become the preferred shopping destination for these customers.
36:55
Chris Oliviera: Great. Um, thanks Pat. Let’s see. Let me pick another one here. There’s—there’s a bunch coming in. So if we don’t get to all the questions, uh, today, we’ll make sure to answer them afterwards so we get to—to the answer for that. There’s—there’s a ton coming in. So, um, let’s see. Rebecca, what—we talked a little bit about—and I’ll ask this question—but the value exchange, right? What are some of the incentives that you found uh to be the most effective for different types of audiences? Even Pat mentioned a few audiences that they—uh, that they make these offers available to. How do you—what—what are some of those value exchanges that—that work best for them?
37:41
Rebecca Grimes: Yeah, we touched on this a little bit earlier, but obviously discounts are the—you know, the most obvious. You know, an “I’d like a relationship” in—in order to capture that initial set of permissioned data. So most popular incentives, um, are, you know, 10% off a purchase, a BOGO, free shipping, occasional, you know, spiking up to 20% off if you’re trying to use that to leverage, you know, smoothing out potentially a rough month; you can, you know, toggle things on and off as needed, uh, to engage with specific audiences. And, you know, beyond those discounts we’re seeing a lot of brands get creative with exclusive early access to new product launches and double loyalty points. Um, something where, you know, in—in those consumers feel special in exchange for giving you that information. Um, one—one other interesting, um, strategy that we’re seeing—and we just, you know, talked about this earlier today in a press release—is an increased prioritization on low-income audience engagement. And brands are leaning into these new incentives to attract consumers. Um, that Pat actually mentioned. You know, we—we recently launched a program with Albertsons, and they, um—they—they prioritized obviously engaging with, you know, programs like the Supplemental Nutrition Assistance Program, the SNAP program, where recipients, uh, receive a 50% off discount on their Fresh Pass program. And so they get a range of benefits and exclusive perks in exchange for shopping there. And, you know, they—they, you know, shared that information to qualify in a very simple and secure online process, and then that data is used by Albertsons to really deliver on that purpose-driven marketing that we talked about earlier.
39:26
Chris Oliviera: Awesome. Uh, this next one could be for—for either one, so feel free to jump in and—uh, feel free to answer this. But, uh, another question: How do you balance the need for personalization and targeted communication without coming off as too intrusive? Even though people willingly share their information, not everybody wants to be constantly reminded or targeted. It can sometimes feel like “my phone is listening” (in quotation marks). It’s always a slippery situation to make customers—consumers uneasy.
40:00
Patrick Debkowski: I’ll jump in first. Um, yeah, I think, you know, what comes to mind for me is um, when you’re soliciting this data from the customers, only get the depth of data that you really need as a marketer to provide the right level of personalized experience for the customer. So, you know, it’s great if I can learn about professional affiliation; I don’t need to know what their favorite color is. Um, so just finding that right balance of—of information that you are gathering in the first place. I think if you’re able to keep that amount of information acquired limited and focused on what is truly important, you know, ultimately it will help reduce privacy concerns that might come from collecting irrelevant information.
40:42
Rebecca Grimes: Yeah, uh, great—great answer Pat. And, you know, what comes to mind is that you can also progressively capture data. It doesn’t all have to be on your very first interaction with that brand. And so when—when I’m interacting with a—with a brand and they, um—they communicate the why and I feel seen, I’m more willing to align myself and share data and information with them, um, as—as my journey goes with them. So again, be authentic, make it clear what that value exchange is and remind them early and often what they get in exchange for that. Again, anticipating needs, um, makes people’s lives easier. So how to use that data to anticipate the next step, going back to the swing that I didn’t have on my registry that, you know, I had delivered the next day. Like, that was that brand engaging with me and being helpful, and so I’m willing to continue to give them more and more information when it makes my life easier. And or saves me money.
41:42
Chris Oliviera: Absolutely. Um, again, another one for—for—for either one. But, um, how do you tie and then we talked a little bit about this, but maybe you can expand this a little bit more—how do you tie ROI to permissioned data?
41:59
Patrick Debkowski: For me, it’s pretty easy. I mean, the data speaks for itself. Um, when we look at these audiences uh that provide the permissioned data versus those who do not, um, you know, the metrics are very clear. Um, these audiences outpace all the other audiences in metrics like conversion rate, in AOV. Um, so we—we’re able to quantify that, actually, with the data we have, um, and the investment is well worth it, uh, at least from our side.
42:32
Chris Oliviera: Great. Um, and I want to get to one more question here, especially when it comes to ROI, KPIs, like getting that cross-functional buy-in. How—so how do you—the question is—how do you approach educating leadership or a cross-functional team about the value of permissioned data? Getting people’s buy-in to see that this is really valuable and we should be investing in something like this.
43:01
Patrick Debkowski: Yeah, like I said about data, I mean, it is really clear when you look at it. Um, when we have our business performance reviews over a given time period, you know, we drill down to the audience level. Um, we’re able to delineate between those who have given us permissioned data and those who have not. Um, and the data is dramatic enough where it’s—it’s really hard to ignore the value. So having those data points for our senior leadership in those business reviews, uh, it’s—it’s super clear and and they’re able to see the value immediately. Um, working with cross-functional partners, you know, we did a kickoff earlier this year uh to educate our broader D2C team on all of our loyalty initiatives. Um, you know, for those people who are seeing the data for the first time, uh, it was pretty eye-opening. Um, we’re able to get some additional support coming out of that kickoff that really wasn’t there before, um, by simply demonstrating the value of these customers and framing it in the context of how it can help some of our cross-functional partners in their work streams, and ultimately make their life easier. Uh, so yeah, I mean, those are the two ways how we kind of communicate with leadership and how I—I’ve worked with cross-functional partners to—to see the value here.
44:10
Chris Oliviera: Great. All right, let’s do one more question, and then we’ll—we’ll throw it back to Adweek. Can you share some strategies—maybe Rebecca if you could—if you could answer this from the conversations that you have with—with brands—is can you share some strategies where the main aim is to drive consumers back to the brand when a consumer has been lost to the competitor, but was a prior customer? How deep should the effort be given, uh, consumers’ preferences are hard to pivot? Given that consumer preferences are hard to pivot? Maybe, uh, how—how can we do that with—by using the data, right?
44:57
Rebecca Grimes: Yeah. Uh, you know, I—I think—I think this is something that a lot of brands are trying to figure out right now. There is so much consumer choice in how and—and where they spend their dollars. And so, you know, re-engagement or win-back strategies, especially, um, you know, when you had a highly engaged consumer and they left, um, you know, my—my recommendation is to go build look-alike models to look at what permissioned data that you have on that consumer, compare that to the buying habits of other, uh, of other similar consumers that are behaving as a cohort similar to you, uh, to what you want, you know, this—this other consumer to behave like, and figure out again that, you know, that very compelling value exchange that pulls them back into your funnel. And for, you know, different consumer segments it’s—it’s going to look different. And that’s where, you know, really mining the data and building out audience-driven, purpose-driven marketing activities based on what outcome you’re trying to deliver. So you define, “This is what my strategy is going to be for,” you know, “to deploy against. I want to get returning customers who haven’t shopped with us in the last 18, 20, 24 months. What is the offer or the message or the reinforced value or the ‘I know who you are’ um ‘and these are our values and we align’? How do you pull them back into your funnel?” Those are all very bespoke strategies that while they might have similarities, you have other consumers that are behaving that way that you want this other cohort to behave. So leverage that intelligence and that data and deploy it and test and learn and be agile. Um, and I—I’m confident that the data resides—uh, you know, the answer resides somewhere in your data on—on how to pull those levers.
47:41
Chris Oliviera: I love that answer, Rebecca, because it actually answers another question I saw on the chat regarding how can we use permissioned data to improve the pre-purchase experience. So I think creating these look-alike models using good data is one of the best ways that you can improve that, uh, pre-purchase experience or—or get more people at the top of—of the funnel. So thank you so much for that, I appreciate it.
48:05
Ryan Wooford: Absolutely. Well, thank you to our speakers and to our sponsor SheerID for this. This was a wonderful conversation. To everyone who asked a question, Chris noted this, but if we didn’t get to one of your questions, uh, those will be provided back to the people here on this call so that they can respond directly, uh, to you. Some final reminders from Adweek before we go: Make sure you download the slides from the event resources tab and check your email for the on-demand recording later today. As always, if you enjoyed today’s webinar, make sure you check out our full slate of webinars at adweek.com/webinars. And lastly, just again, a big thank you Chris, Rebecca, Pat. Thank you to our audience for joining today. We—we appreciate your engagement with us and the learning that you do uh on a week-to-week basis. So we look forward to seeing everyone at an upcoming Adweek webinar soon. Thank you.
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