A Podcast About Truth, Science, and the Future of Marketing

LF: It's a great question. I think when we start to consider the main challenges that advertisers are facing, we have to really think about what's happening in today's landscape, both from an industry perspective, as well as a macroeconomic perspective. From the industry perspective, obviously identity, which we're going to talk a lot about today, is one of the big changes and topics that advertisers are increasingly forced to navigate. Identity really affects everything at their organization and if it isn't already, it's going to force them to rethink everything from their audience definition, to their targeting, to their measurement. Other factors and challenges that advertisers face at the macroeconomic level, obviously this is a time when many are thinking about the performance of their campaigns, the cost of their campaigns. Truthfully, this is always one of the top challenges that advertisers face. How can they be successful and how can they do that in a very cost effective way? We just find ourselves in a situation where this is even more on their minds.

AD: You're absolutely right about the cost implications. And I think you're kind of referring to the recession or a potential recession that a lot of people are talking about. And in particular, an increased focus on performance measurement. Are there things that you're finding that advertisers are exploring? When it came to the pandemic, we found a lot of advertisers were starting to look at reduction in ad spend, for example. Are you hearing that there are certain things that advertisers are exploring as it relates to the cost implications and trying to manage that cost and their campaign performance?

LF: It depends on the type of advertiser as you might imagine. We do know that for a lot of advertisers, they are looking for the platforms that they know perform, and in some cases doubling down with them. This also presents a really great opportunity for specific verticals that may not be as impacted by some of the supply chain issues or rising inflation rates. To get into some of the channels and into some of the platforms that previously may have been very expensive and to capitalize on some of the openings that they see in the marketplace.

Brett House: Can you dig in a little bit to that topic? You say, because there's been a lot of talk about CPM inflation. And how that's impacting CPM rates across the board. Can you dig in a little bit about what you just mentioned?

LF: Sure. So when we're looking at channels in particular that advertisers may be looking to with more frequency, social media, search are common ones that will in many cases and in scenarios like this, be go-to channels for advertisers who are very performance driven, want the flexibility to be able to move their dollars quickly and efficiently. Connected TV as well, we continue to see momentum there. Granted, that can be from a CPM perspective, very costly. But if you have some categories and verticals that are at this point sitting on the sidelines, it does present the opportunity to get in there in a less competitive manner.

AD: So it's interesting because we talked a little bit about, I mentioned the pandemic and there were some reduction in ad spend in terms of people, some brands pulling out of certain placesand invested elsewhere. It's interesting that you mentioned that presents an opportunity because on the flip side you were talking about identity. And we're finding a lot of advertisers are concerned about things like scale and the rise of walled gardens in an environment where identity is changing and being able to identify your audience on the other side of that digital platform or screen, whatever that screen might be. How do you kind of reconcile those two concepts of this increase in CPM, this challenge of achieving scale? This rise of walled gardens or higher walls amongst the walled gardens and then also this opportunity that you're talking about.

LF: So I think ultimately it comes back to performance and what advertisers are capable of measuring. In some of the walled gardens, where some of those walls are getting higher, the reality is many of them still have scale. It may not necessarily be at the advertiser's first party data level. But if the scale is there and the performance is there, they're going to continue to go there. From an identity perspective, we know that with some of the challenges in the landscape, from a regulatory perspective, there's a massive emphasis placed on moving away from third party data toward first party data. That in theory is where the market's headed, but advertisers know it's very challenging to take their first party data, to collect enough of it, to then activate that across either the open web or the walled gardens in a way that scales. So that is one of the areas where there is a lot of opportunity, but also a lot of ongoing growth.

BH: Let's dig into that a little bit because people have been talking about first party data strategies for years. You and I have been in this, we talked 10 years ago when I was at Nielsen, have been in this space for a long time. And people have been saying first party data, first party data. One, not every advertiser has a lot of first party data. Especially if they're not involved in the DTC, direct to consumer industry, like a CPG player that doesn't play in the DTC space. Are there limitations to that from a scale and audience reach perspective, especially when your KPIs might be top of funnel, brand awareness to get more people interested or at least aware of your product or service. That you can then start to execute against your more customer acquisition based programs. With those challenges of first party data, from a scale perspective, how do you think advertisers and what are you hearing in the space around the use of second party data, partners, whether it's ecosystem data providers, or if it's other brand partners, if you're a brand.

LF: So if we're thinking about the strategy long term, if we're seeing advertisers beginning to build what that new framework looks like. You have to think of it as building blocks and at the base is the first party data. That's what advertisers, as we've talked about, Brett, are really looking to collect. They're putting a lot of stock in the ability to utilize that, to still maintain one to one targeting, one-to-one measurement, that type of addressable capability. From there, because there are inherent limitations for the vast majority of companies in the amount of first party data they can collect.

You're right. Second party data plays an important role and that's the next layer of what they're looking to build. That would include anything that could be obtained through a publisher, accessing publishers’ first party data, which would inevitably be their second party data. Certainly this is where the walled gardens come into play and many advertisers look for that scale. And you also have any sort of data co-op or partnership that might be in play as well, whether it's with another advertiser or another party.

BH: . So, do you think one to one, cause I want to zero into that one point. That the notion of a one to one advertising world, individually addressable data, one to one targeting and measurement. Do you think that's a potential reality going forward? Considering, a lot of the privacy restrictions. The European Parliament just adopted the DMA and DSA, the Digital Markets Act, the Digital Services Act. Which is supposed to put some teeth in what was formally known as GDPR. Do you think that one to one is the future or is it going to be more cohort or segment based, where you really can't do one to one based advertising? Even though, it might be equally effective.

LF: I think it's going to be a mix of both. And when some of the restrictions to third party data first came into play, advertisers really pivoted to that idea of one to one and hence building the first party data layering in the second, then going to the third party data. The reality that we're now seeing, and we're seeing this as well reflected in our research is that advertisers increasingly acknowledge that's not going to give them enough scale. It may not necessarily be privacy compliant depending on the types of identifiers that they're using and how they're using them moving forward. So we are seeing a growing acknowledgement that cohort contextual based, more anonymized type targeting moving forward is absolutely going to have a role and an important role in the advertising framework.

AD: It comes back to your original point though, Lauren, around this need and this growing focus on performance based marketing. So yes, that's all true, but then they're also under enormous pressure to deliver an impact from that marketing. And really if you're spraying and praying, for lack of a better term, are you able to really have that same level of performance?

LF: I think some of the definitions of performance may change.

AD: I think you're right. And I think we've talked to others in the industry on this podcast actually. And I think it comes back to this idea of marketers really need to start trialing and testing some of these different audience based approaches so that they can understand and sort of reset the bar around what does performance look like in the future.

LF: We are seeing more savvy advertisers taking that approach. Certainly the larger the advertiser, the more resources they have to test those solutions. Agencies, as you can expect, tend to be a little bit more future forward with some of the strategies that they're testing. I think the challenge comes back to the culture that you have at your organization, the freedom that you have to do those types of tests. And of course, the ability you have to figure out what success is going to look like for those tests to begin with.

BH: And when you say success, that is how you're defining performance based marketing. Cause when I think of performance based initiatives, I think customer acquisition, I think deep funnel, you're targeting people that have shown some level of intent, hand raisers. And, and certain channels lend themselves, whether if you've got their email and contact information. It could be email, it could be direct mail, it could be search. Someone has been exposed to-

BH: ... mail. It could be search, someone has been exposed to something through CTV or otherwise. They end up doing a search to learn more about a particular product or service. It's that classic last-click play. But, to me, those seem to be your down-funnel performance channels, or when you define performance, are you thinking the entire funnel, whether it's a linear funnel or otherwise?

LF: It can be the full funnel.

BH: Performance could be brand awareness metrics, where just as long as you're measuring it in an accurate way to understand, "Hey, what are my KPIs when I'm running a television campaign to a large audience and a large percentage of those people not necessarily being in my target," so to speak.

LF: That's a good point of clarification, Brett. When I'm talking about it in this scenario, I am thinking about performance more broadly versus the typical performance marketing association. Performance just to mean the ability to get return on investment or meet the campaign objective that you had set forward, whether that was an upper-funnel KPI or a lower-funnel KPI.

AD: I think that's really fair, Lauren. I think that's one of the limitations I always have a concern around first-party data is Brett's talking about hand-raisers or people who've already indicated that they are engaged and interested in the brand, but that may not be part of the objective or it may be limiting an audience who actually would be intent on purchasing. They may not have raised their hand, but they just may not have been aware or considering. There is this benefit or this need to look beyond just first-party data, especially when it comes to customer acquisition and those KPIs that are a little bit more broad.

LF: Exactly. I think that's where a lot of the cohort and some of the more anonymized or aggregated data can come into play. Certainly you can see a scenario where that would be really useful to model off of known first-party data for lookalikes and really be able to broaden the scale and reach.

BH: Exactly. It gives you that broader reach in a slightly more targeted way than potentially just the age and demo categories.

LF: Exactly.

BH: If you know somebody's researching or looking at particular topics online, they're interested in cycling and your Trek. I say that, I'm a bit biased. I'm a Trek loyalist and ride an overly-expensive Trek bike. But point being, if you're reading a lot of information and you're targeting someone, you know their age and demo at a basic level, and then you're targeting the content that they're super engaged with, there's a greater likelihood than just a mass television ad in terms of the linear world, that they're going to be in your target from a contextual perspective, but you get broader scale than you would just targeting at the one-to-one level, for example.

LF: Exactly.

AD: We've been talking about contextual and ways to reach audiences beyond simply utilizing a cookie or an identifier. But let's go back to this idea of utilizing identifiers, and in particular, one of the things we love to do on our podcast is talk about hype-y terms. One of those being clean room. I think it'd be interesting to have you talk a little bit about clean room and the importance of having a centralized clean room data environment. How does that allow data to be shared and moved around? Why should a brand or a publisher consider a clean room? What are those criteria or use cases that are relevant for the clean room?

LF: I think the reality, as we're looking at a more regulated environment, is that clean rooms offer both the buy and sell side the ability to utilize some of that first-party data. The reality is a lot of that first-party data is customer data. There's some sensitivity. There are some compliance increasingly. The likelihood of there being compliance and regulation around the use of that customer data is in our future. Having a clean room capability, or being able to utilize a clean room, gives them that security that the information that they're taking and activating with a publisher or with a platform is going to be taken care of in a compliant manner.

BH: Do you think it's powering use cases that already existed, but just in a much more privacy-safe way? Back in early ad tech, you could do a private marketplace, a second-party data marketplace where you're sharing data. It could be two brands. It could be a brand and a publisher, but the notion that the clean room is not allowing any PII to be passed or moved and that it's in a central place so there's no files being exchanged across parties, I mean, do you think it's the same fundamental use cases, but just in a privacy-safe way?

LF: I think that's a fair way to describe it. Really thinking about where the clean room comes into play quite often for the media activation piece, this isn't any different than the process that would be required, or that advertisers already go through to take their data and upload it or transfer it to another partner. The difference here, as you said, Brett, is that there is that assurance that the PII is not making it from one party to the other.

BH: Then you get into advanced use cases, which I think were in early days where there's more federated machine learning happening, where data is actually not being uploaded to anything. It's all living behind firewalls for all of the partners involved. Then you basically have algorithms that are grabbing bits and bites in order to piece together an audience, for example.

LF: Listen, I think it's still early for clean rooms. Back to the comment about the hype, I think the phrase clean room to begin with can mean different things to different people. When we think about a clean room, you might think about Snowflake or something that's more independent. Whereas for an advertiser, it may be as simple as utilizing whatever is available to upload their first-party data into Facebook or using EDH and Google. There are many different iterations and forms of the clean room that I think make it difficult to sometimes have the conversation from the advertiser side as to why you need an independent clean room versus just utilizing one that's provided through your MarTech partner or an advertising partner.

BH: Or your cloud provider or otherwise.

LF: Exactly, exactly. We do see in our research, we surveyed advertisers back in May. We saw that the majority are accessing clean rooms today through the marketing cloud or through an ad platform that they're working with, like Facebook or Amazon or Google. There's only a small percentage, 16% that are actually using sort of an independent, standalone clean room.

AD: That's really interesting because I think we hear a lot advertisers saying, "Oh, I hear this term a clean room. Do I need a clean room?" If an advertiser were to come to you, Lauren, and say, "I think I need a clean room," what would you tell them?

LF: I would say that it's possible you are using clean room-like capabilities already. I think also sometimes we get very hung up on the terminology. Where we really need to be focused on is the why, the use cases, the activation. I really need a clean room. Why do you think you need a clean room? What are you trying to accomplish with a clean room that you aren't accomplishing today? Where does that fit into your entire process? I think those are the questions we need to always work through. With any new technology, any new platform, of course, you're going to look into it, you're going to investigate it, but the use case has to be very clear and the value needs to be very mapped out, which I think can always be a difficult assessment or decision to make.

BH: Oftentimes, it's a technology looking for use cases. We've looked at dozens of clean rooms in the space. Some of these are literally just protected data lakes that allow basic use cases like audience overlap analysis. I'm like, well, if that is your goal to do an overlap analysis, which is the 101 of use cases, is it worth the investment? If you do a cost-benefit analysis, to your point around cloud platforms or other partners, do you really need to make this investment in the shiny, new object if your use case is so narrow. I think there's a role that identity plays. I think this might be a good shift into that topic because it seems like a room, a vault, a protected data lake environment is nothing without data. How do you think identity, identity resolution, connecting all of these data fragments that represent people and devices and households plays kind of in this privacy-forward future?

LF: It's critical. Identity is really the backbone of advertising. It's the backbone certainly of digital advertising and being able to figure out how to make it work in a privacy-compliant way is the major question of the future. That's critical for every publisher, every advertiser, every ad tech provider to be able to figure out. Identity is what's required to effectively gauge performance in some form or another. If we're talking about measurement, if we're talking about reach, if we're talking about scale, behind that is always this assumption that there will be some sort of identity resolution available to enable and power that.

AD: We talk about identity a lot as a foundation, a foundational capability, a foundational source, so that you can build this cohesive omnichannel view of the consumer, whether that's for audience activation, audience building, or for measurement, to your point, Lauren. What do you see as the main things that marketers expect and really just demand from identity as part of our ad ecosystem?

LF: I think there's an expectation that whatever solution or framework they use moving forward will be capable of providing them comparable performance results, value to what they have today. That may or may not be realistic when we're thinking about how they're currently targeting and measuring, but I think the expectation and the hope is that we're going to figure something out where, for them, it's business as usual, just with a different layer or backbone to power all of the functions that they do today.

BH: On that topic,

BH: It's harder and harder to piece the data together. Because the data lives in all of these, we'll call it, independent clean rooms. Facebook's got a clean room, Google's got a clean room, Amazon's got a clean room. So my question is, with this fragmentation, which only seems to be increasing, to me identity is when you can actually connect the dots, you can pull together all these data fragments, you can connect them with a certain confidence level to a device, to an individual, to a household.. What's the role of data science in all of this? The data science function within brands, are you hearing brands saying, hey, we're doubling down on the investment in data science capabilities and people because it's becoming way too complex and we need a PhD in house to be able to solve this data connectivity problem? I mean are you hearing that a lot? And do you think that role of data science is going to be something that's only going to grow and expand going forward?

LF: I don't see a scenario where it doesn't grow. And for many of the reasons that you mentioned, for many of the reasons that we already spoke about, we see in our research, for example and we talked about, we're increasingly looking at first party data which contains PII, which is customer data, and there are rules and regulations at most organizations. The marketer isn't necessarily going to be able to go into all of the organization systems and just take what they want. It's the data scientists, the data practitioners who are the gatekeepers. They are the ones that are responsible for creating the framework for how that data gets stored. They have the permission to go in and pull that data and transform that data. And they're really critical for packaging that in a way that marketers can then take and activate. Brett, you're right. It's becoming increasingly fragmented, increasingly complicated, which means we have more and more sets of data that somebody needs to put together. That's not a function that the majority of your traditional marketing roles can do on their own.

AD: What you're describing is these walled gardens that are occurring even within an organization that you have to sort of overcome, and that brands need ways to be able to share safely our own customer data across the organization. Is that accurate?

LF: Yeah, that's right. Think about GDPR for example, this is one of the requirements of GDPR is that you have sort of a really good understanding of who at your organization is touching which data and that there is some sort of...

BH: Governance.

LF: Governance as to how that data is being stored and being shared.

BH: Yeah. And it seems like it's becoming increasingly cross-functional too. It's no longer okay to just have a data scientist in a room as Joanna O'Connell, I love that quote from last year's Brave New Worlds, she said, "You can't just have a person that is assigned to handling the cookie problem." It's one person off at a cubicle somewhere handling the cookie problem. That you've got this get your data house and order data governance, obviously data strategy which powers advertising and targeting and measurement. But, it seems like to my point earlier, it's cross-functional because you have to get the privacy teams involved, legal by extension. You've got to get, obviously, the marketing organization and the data science and analytics organization if it's different. I mean, are you seeing that clients are preparing for that sort of task force, that cross functional task force that needs to sit in war rooms and plan for their data future from both a privacy and regulatory perspective, but also from just a, we need to be able to reach people. If we're going have as much data available and it's behind all of these walled gardens and we can't measure it or otherwise. I mean, do you find that's happening right now or is it still nascent it in terms of how brands are adapting to this?

LF: In some organizations it's happening, it really depends on the culture and how that culture's trickling from the top down. In organizations where you have people at that C-level who get it, who understand how important that cross organizational collaboration is, who can both see the regulatory and governance and compliance side, as well as the journey that data is going to take to get them results from advertising and drive revenue, that's the critical vision that needs to be there. And when you have that view, then you do have organizations that are starting to put the right people in place, and more importantly, bringing those people together so that they really understand how their function within that chain can feed the entire process.

AD: So we've been talking a lot about key stakeholders that exist within an advertiser's organization. So you were talking a lot about leadership from the top and then sort of building this cross functional culture, this team. What about external partners? So what are some of the criteria that advertisers, particularly those who are successful in preparing for this sort of inevitable ecosystem change, what are those successful advertisers doing? What are the criteria that they are considering when they're looking to partner or to bring in additional partners to the table to help them and to enable that journey?

LF: Yeah, I mean, I would say this is where the legal team for better or for worse comes into play for some organizations. The organizations that are taking this very seriously have some sort of auditing process or some sort of review in place for some of their major partners. And that really allows them to put in front of potential partners, some requirements and rules to get a better sense of how they're handling their data, how they will handle their data and trying to check off the list some of those major regulatory and compliance concerns, whether they are mandated now or anticipated in the future.

BH: I mean, we haven't really talked about trust as a key term, another hype term that we oftentimes hear, but a lot of what we're talking about here is stemming from a lack of trust, of requiring brands, advertisers, publishers, part platforms to put in place all of this legal jargon to protect themselves because there is this lack of trust. And I think the machine learning and the AI capabilities that we're talking about, the data science capabilities that we're talking about, those are also trying to address the same topic, which is to enable data sharing, data collaboration in a world where there is limited trust. In the near term, I think we're going to see both play a role, both the data science capabilities and the legal capabilities and it sounds like you agree with that, right Lauren?

LF: I do. And I think a lot of companies will in the short term lean on the legal while they're figuring out what everything is. This is complicated stuff and I think the reality is there's a lot of education that needs to happen at all levels of the industry, all levels of the organization. It'll be interesting in a few years time to see if we're still having this type of conversation, talking about these dynamics. Is it the data science people who are only allowed to do that, has those sort of capabilities and has that knowledge transferred into the marketing side of the organization? Again, going back to just how fluid and ever changing our industry is, I think we are literally at one of those points in time where we're watching the tide change with how well we understand certain technologies and the application that they have for our companies.

BH: But at the end of the day, what is this all about? And does it come back to consumer trust and is a brand fundamentally responsible for abiding by the needs and concerns of consumers who do not want to share their personal information for more relevant advertising?

AD: BH: it goes back to trust and a brand has to... We have to... And this is a big topic that we talked about at Cannes this year was people have to be able to trust that the brands they're working with or the brands they're buying from are... If you're going to give your information, if I give my information to Trek, I have to trust that they're going to use my information in a responsible way. They're not going to sell it to third parties.

I'm not going to start getting direct mail from people that I don't want direct mail from. Right? So I think that's an important value that brands that are increasingly showing that they have, but need to show. What do you value? Do you value the people that buy your product? And if you do, this is what consumer expectations are demanding in this day and age.

LF: Yeah. I mean, listen, it is. It's a chain of trust. The further you get from the consumer, the more hops where you're sharing, the more concern there is, right? The brands who are asking their ad tech partners to go through an audit or fill out paperwork or getting legal involved, they want to protect themselves when they're taking the customer data that their customers trusted them with and using that in specific ways. And that continues down the line. Right? And you would hope it would. I think is really critical to understand for both consumers and advertisers as we're thinking about these topics and it's the interplay between trust and awareness, and education.

BH: Yep.

LF: Consumers have a lack of trust because they don't fully understand what that data is being used for. As an industry, we haven't clearly articulated to them how we're using it. We think we are, but we're not really, right? They don't really understand.

AD: No one does. I feel like it has to go somewhere between the thousands of words that you get when you agree to something and the ask not to track. It's got to go somewhere in between those two things. And I think we haven't quite solved that problem yet.

LF: But also it's complicated. Right?

AD: Totally.

LF: It's not as simple to explain to a consumer how their information might be shared. You might have to explain how programmatic advertising works. Sometimes it's hard to explain programmatic advertising to someone in the industry.

BH: We started with the performance marketing. So if brands are just doing this for their own interest and aren't altruistic, so we'll start with that theme. But they're noticing that consumer performance of their marketing is going downhill because they've been following people around in a totally untargeted, unregulated way, right? You're getting that retargeted ad that follows you around every device to the point where they actually drive people away. That stuff is trackable.

You can see abandonment rates, lack of engagement. And I think that it kills customer experience with the brand. And if you start to see that even if you're not thinking about the consumer need, if you're thinking just from a performance goal KPI perspective, maybe your performance just goes on the toilet when all you do is follow people around and deliver pretty poor experiences. It affects conversion rates.

LF: It does. Although, if you're measuring off of last click, it could still look really good, right? Even though you're hitting them over and over and over again. I think this is a conversation in itself, but the measurement piece cannot be understated here. And I think one of the challenges that the industry is going to have to wrestle with is the fact that we're moving to a more complex world from an identity perspective. We're getting new ways of defining our universe, but we're still as an industry, in many cases, really struggling with measurement at a foundational level.

We still don't have great cross or omnichannel measurement. Many companies are still not even anywhere scratching the surface with attribution and more accurate ways of truly measuring their performance of their campaigns. I think that inevitably will catch up to a lot of organizations.

AD: Yeah. I mean, I think it comes back to this idea of having sort of a unified identity based foundation. Right? I think you can only do that well if you do have identity at the foundation so that you can see across these different devices, see across these different channels and platforms. And it's not going to be easy to make that connection. But it is, I think identity does play a role and does allow us to... It opens up the opportunity to see a future where that is possible. It just is going to require a little bit more privacy based data collaboration than it has in the past.

LF: Yeah. And again, thinking about what's the opportunity here, right, in some of the challenges that we're discussing. I love the fact that the entire identity conversation is forcing organizations whether that's brand buy side or sell side to really rethink everything about how they define audiences, how they target audiences, how they measure. Right? This is a good thing. It's a good thing that everyone is really thinking through these processes and given the opportunity potentially to free themselves of some of the practices that they've been following in the past that aren't ultimately going to get them where they need to be.

BH: And what kind of practices are those? I mean, are we thinking the classic sort of age and demo, basic measurement, which obviously is not at a one to one level. It's very generalized.

LF: It doesn't even have to be from that perspective moving toward one to one or off of very basic age and demo targeting. I think it's more about for me on the measurement side. Are you even putting together a cohesive measurement practice or are you still measuring at the channel level and then not looking to go higher with those insights to really understand what impact that had on your business?

AD: And a cross channel perspective.

LF: Exactly.

BH: And you inevitably over credit, whether it's last click. You over credit one or the other and completely inaccurately because you can't connect those dots of like, "Hey, consumer A has been exposed six times over these six channels or four channels." What is really the determining factor. Is it one channel or is it the combination? And then how do you understand the synergies between those channels and where to allocate more budget or where to optimize your program a bit. Right? LF: Yeah. And those are the types of insights that I think more and more organizations will start to come across and realize. So I think it's, again, an exciting time. Not without its frustrations, but nonetheless, the opportunity is immense.

BH: Yeah. And it just seems like we've got the barbarians at the gate, right? There's just threats from all sides, from all angles, whether it's privacy or pandemic or war, and yet it still evolves. That's what's so interesting about this space is that we continue to make progress.

LF: And quickly, right? It's just rapidly evolving all the time. I think to the people or the credit of the people in our industry, you get used to it. You are used to having things thrown at you having to learn about new things, having to pivot. I think that's a great skillset and really benefits organizations well in the long-term especially as we are wrestling with some big issues and challenges like regulation or some of the macroeconomic issues today.

AD: Right. I mean, the only thing that's constant is change and it's kind of forcing us to get scrappy and become more innovative. So I think you're right about that. And that's what our industry is really good at.

BH: Yeah. Necessity is the mother of invention, right?

LF: That's right.

AD: Lauren, thank you so much for joining us. I think it's been a really fun discussion and we hit on some really great topics. So thank you so much for spending time with us.

LF: It was my pleasure. This was very fun. Thank you.