Kyle Hollaway:

Wow, congratulations.

Heather Philpot:

Yeah.

Kyle Hollaway:

Yeah,

Heather Philpot:

It’s pretty cool. And as a side note to all of our listeners, I have actually worked on presidential campaigns on both sides of the aisle, and that’s because data is neither red nor blue, but it’s agnostic. So it is a fun, it’s fun to see how both sides are leveraging data and strategy within their campaigns.

Kyle Hollaway:

Wow, that’s awesome. And what a great background there, and I’m sure you’ve got some amazing stories to tell along the way of that, especially crossing the aisle and some of those efforts. But before we get into more specifically some of the stuff around the election and stuff, in the breadth of your time there, going back 15 plus years, talk a little bit about the role that data has played and how you’ve seen that morph over the past two decades.

Heather Philpot:

How much time do we have?

Kyle Hollaway:

Take as much as you need.

Heather Philpot:

Well, what’s so funny about that question is I feel, because I’d also love to hear your feedback just in how far it’s come within the industry and the different sectors that all of us have played in. And this is the question that gets to show how old we really are, if you will,

Heather Philpot:

For sure. Yes.

Heather Philpot:

But a few things definitely come top of mind just to when you consider just the seismic change that the role of data has really played within the last 15 to 20 years, and first of which is just the sheer volume and variety that’s available out there. And I feel like the amount of data generated has just exploded thanks to the proliferation of digital devices and the various social media platforms that are out there. So we’re dealing with large data sets, both structured and unstructured from a variety of different diverse sources that we’ve never really dealt with before. And that is something that’s obviously we didn’t see 15 years ago the use of data in analytics and just how far we’ve come. I remember when we used to build predictive models in a SaaS based environment, and really those would only kind of take into account anywhere between 30 and 40 data variables at a time.

Now that we have cloud-based infrastructure and these cloud computing solutions, we’re able to store data and analyze it, manipulate it in ways that we’ve never been able to do in a cloud-based environment using thousands of data variables. So now you’ve set your targeting on steroids basically. And I think number three is just the democratization of data compilers, very much like Acxiom and others out there are making data very accessible and user-friendly for organizations big and small. And I think that’s important. People are now able to cherry pick variables and become their own little mini data scientist based off of the audiences they’re looking to target. And there’s so much more, but I’d love to hear your perspective obviously as to where you’ve seen the change also within the sector.

Dustin Raney:

For us, I think also the different channels that people are engaging with media, it’s become much more one-to-one, right? It’s like you think about social media when Facebook and all these platforms came on the scene before that it was really kind of broadcast, so it was very much survey, almost like Nielsen type level information where you guys would probably have to depend on more of a cohort of surveys to get down to political sentiment maybe things like that. But with the onset of social media and big data, which is what we’re talking about and the algorithm and it’s like what propensities are people showing is even imagery. It’s like the level of detail specificity of data coming in at the person level is really the change that we’ve seen. And yeah, it’s taken cloud computing and all those scalable things for us to get to a point to where you could even one house the data, make any sense of it, and then use it in a compliant way. So there’s just a lot of things that have come together to get us to where we are today. And it’s like, I want to say back in, I would say the last two election cycles, it is the first time I started hearing, well, this campaign, the reason they won is because they leveraged a data strategy or it really impacted the results, whether it’s social media or whatever. So those are just some of the things that I’ve just observed.

Kyle Hollaway:

And just to layer onto that, it seems like the movement with that from more of a outbound messaging to more of a discourse, getting those realtime feedbacks. So we, Dustin was saying historically it was kind of batch data on the backend. You pull it in, it may be months old process it make some decisions, and then push outbound some messaging associated with the campaign. But now with the integration to social, leveraging a lot of these real time signals and the ability to crunch all of that in timeframes that in

Heather Philpot:

Real time almost

Kyle Hollaway:

Right, blow your mind, and now it’s like, oh no, yeah, we can do that. And literally whether it’s pivot or just certainly refine the messaging or the targeting for very specific geography or a very specific topic in real time back again at that people level really has changed the whole kind of strategic messaging component to a campaign. It seems

Heather Philpot:

Well, and you hit upon a critical point, especially as it applies to politics, Kyle, because really the entrance of predictive AI really entered the scene back in 2008 with President Obama’s campaign. And the tactics that that campaign was employing is really just standard fare now within how we are operating within the political sphere now. But back then it was so cutting edge, the implementation of the algorithms and really running very key strategic decisions through these very complex algorithms based off of voter turnout, voter engagement, where to position a ground game and all of AI and big data and analytics played a very front and center role in all of that.

Dustin Raney:

You also have these regional plays, right? The swing states. So I think data becomes a really critical factor now. It seems like way more than it used to on where you spend on your media. It’s like where does it matter? I know in some states people are like, where are the political campaign ads? It’s like we’re right in the middle of, and I can’t imagine what it’s like in some of those locations or states that it seems to be, there’s no statistical significance on who’s got the lead. It’s like that’s where people are really trying to focus, right?

Heather Philpot:

It is. And kind of going back to what we had touched on really earlier in the conversation is the type of data that is available is allowing targeting to be put on steroids. So I’ll go back once again to the 2008 election because it was the first time in a presidential election that the majority of the voting age population engaged in political dialogue and education discourse in the social media channels that had never taken place. We’d normally marketed to voters and engaged with them for both fundraising and GOTV within more traditional channels, your direct mail, telemarketing, and of course linear television, both cable and broadcast. And now you have the digital channels are now playing a very front and center role. And the type of data and the digital exhaust on the behavioral side that you are now able to gather and collect is able to really build more of a 360 degree complete picture as to who these voter audiences are that you are really targeting. And again, the President Obama’s campaign being able to capitalize on all of that and say, Hey, okay, how are we leveraging all of this data that’s coming in so now we can really produce true hyper-personalized one-to-one marketing via via email, via social channels and all of that. And again, that is something that really revolutionized the way that we market to folks politically.

Kyle Hollaway:

So this kind of brings about interesting thing, and honestly, I’m not super steeped in the inner workings of the political ecosystem.

Heather Philpot:

That’s good. Kyle, you don’t want to be,

Kyle Hollaway:

I’ll leave it to the experts, but the aspect that there’s really two primary functions going here, right? There’s fundraising, which is an aspect of getting investment from the general populace, your constituents, to help then drive some of these messaging strategies that you’re talking about. So you almost have a strategy within a strategy, right? Your fundraising strategy to drive the other strategy. Talk to me a little bit about the difference of those. Do you approach those differently at all? Is there a different mechanism by which you go about that? Or is it really just tuning your algorithms and particular targeting methodologies depending on which kind of path you’re going down?

Heather Philpot:

We absolutely target them differently. Anyone who is a donor has basically bought in with their wallet, you know what I’m saying? There’s no need to convince them. They’re also going to show up to the polls to vote for you. So you get a two for out of it. On the voter engagement side, what we’re looking to identify is who can become a likely donor? Who can we drive emotionally based off of the issues, and now get them to take the same action and make that conversion of the wallet, if you will. And so we’re absolutely communicating with them differently. Once a donor lands on a candidate’s house file, what we’re now looking with is propensity. How often now can you give and at what capacity can you give? So the metrics are much different once a conversion takes place. Yeah. And obviously you’re fostering a relationship, you’re engaging, you’re building community with a voter that has not yet become a donor, but we’re really hoping that that takes place.

Dustin Raney:

So to go back on something you talked about earlier in ai, it really doesn’t matter what industry you’re in, AI is absolutely a hot topic. We’ve all experienced AI already in social media, but talk about the way it’s making a difference in political decisioning and operating efficiency. So just AI specifically.

Heather Philpot:

Well, it’s a game changer, definitely. And it’s kind of interesting when we just take the pause and take a step back and we think about how gone are the days of campaign buttons and guessing about voter preferences and even passing out palm cards which outline a candidate’s platform. All of that’s gone with the, I can’t say it’s completely gone, but a lot of that has been dialed back due to how we are marketing. It’s no longer the mass billboard effect, it’s now we’re honing in and targeting at the individual level, truly. And so I’m going to approach this now from two different sides of the political spectrum, the policy side, how the role AI is on, how lawmakers are using it within Capitol Hill and on their staffs, but also on the campaign. And so what AI has done on the political campaign side is it’s leveled the playing field.

So typically you’d have to raise a lot of money and you still do because we read all of the articles on how this is going to be the largest amount of spending that’s taken place in political history and expenditures that have taken place. But in order for you to really play ball and have a campaign that would go toe to toe with an opponent, you would have to hire a really great agency that’s going to come and do creative and copywriting for you targeting messaging and offer all these services. Well, AI is the big leveler in all of that because people with or campaign operatives rather with little to no experience on how to create content or graphic design video, all of these different things are able to do them now with a simple platform like a chat GPT, like a copilot, I use it often when I’m even creating graphic design work for visualizations that I’m doing within more.

And I’m not a graphic artist by any stretch of the imagination. And so these tools are incredibly user-friendly, and typically what you’d have to pay a lot of money for in an election cycle, people are being able to really take these tools and leverage them to really help offset cost. Now on the policy side, when we’re looking at how lawmakers are using it within Capitol Hill, AI is taking these large complex pieces of legislation that representatives are sponsoring on the Hill or their co-sponsoring with other members. And it’s making it understandable for people that don’t live, eat, breathe politics. And that’s huge because if you can understand what your representative is representing in Washington for your constituents, it’s a really big deal. And I would say that also policy simulations are really interesting. You can take these pieces of legislations and from a forecasting perspective, look at the impact it’s going to take place, not just fiscally, which is always where people’s heads go, what is this going to cost might through tax dollars, but also what are the other implications, environmental, socioeconomic, culturally, things of that nature. So AI is playing a really, really big role in all the best ways on how we’re implementing these both politically and from a policy standpoint.

Kyle Hollaway:

Wow, fascinating. Just to think about especially that aspect of the predictive modeling or the ability of the forecast out impacts, and then therefore consumer sentiment down the road about that. So you’re really even starting to look at not only this election cycle, but even downstream election cycles based off of if this person gets elected, these things are enacted, then what does that look like for future opportunities? So it’s pretty amazing that we’re at that level of complexity and the breadth of focus now. But with all technologies, there’s always kind of a dark side, right? We’ve got the deep fakes, we have a lot of misinformation, proliferation across platforms, the need to ensure accuracy of the data. How are you guys wrestling with those topics?

Heather Philpot:

I think that’s a moving target because, so I touched on the positive effect that AI is having in politics, but obviously there’s a lot of mistrust that exists, especially with the ads that we’re seeing that are put out where AI is able to now simulate an individual’s voice. You have voice simulation taking place, and people are wondering, was that really a robocall that President Biden just left on my cell phone? Just because it is so real, it is so authentic. And so I think that there is still a lot of work that has to be done to show that this isn’t the boogie ban by continuing to implement it in positive ways, but it is a moving target. It’s hard because public sentiment always, I think goes to a negative aspect on all of this with public mistrust and over implementation. I just saw a bill that was vetoed this morning by the governor of California, Gavin Newsom around ai, and he had vetoed a bill specifically around this, which is interesting because Silicon Valley does live in his backyard and am not going to claim to be an expert on what is in that bill and what it plans on, what its uses are and whatnot.

But it is fascinating that that was the knee jerk reaction was just to kill a bill on AI in its uses.

Dustin Raney:

Wow. Yeah, I mean there’s so many hot topics obviously that are front of mind for every American leading into November 5th, and inflation and the cost of living, things like that are definitely one of them. And I know when it comes to fundraising, that has to have some of an impact. But what are you seeing there on your side? Are you seeing some of the economic factors playing effect or people so concerned that they’re donating anyway?

Heather Philpot:

With the rise of inflation, obviously people have less disposable income, which is the key ingredient to donating to any cause, be it philanthropic or even political. But then every year we see giving and spending go up. Do you see what I’m saying? Yeah. Inflation is high, but this year is set to break record numbers of fundraising also, especially on the low dollar side. And I think that that’s really where we’re seeing a lot of the runway happen is within donors that are really giving a hundred dollars and less,

Heather Philpot:

If

Heather Philpot:

You will. That’s where we’re seeing the biggest penetration in terms of political giving. But I mean, it’s tough because you have scarcity of resources, costs are going up, the cost of doing business has gone up, so it is more expensive to run campaigns than it has been in years past because of inflation. But this is where we kind of bring it all back home with the use of data analytics and ai. Because if you can now cut waste by targeting the correct audience and putting your message and content in front of the right set of eyeballs, then that’s a win. And you can only do that by leveraging big data, modeling that into a variety of different data sets to really give you a true 360 degree picture of an individual. And then taking that and marketing to them on their channels of preference. And we live in an omni-channel world.

People used to build budgets, especially in political campaigns based off of channel and a lot of silos were in place and still are to this day. But now with the use of AI and big data, we’re seeing people shift from more of a channel focus to an audience driven focus because we live across channels. I live on multiple devices. I don’t just live in direct mail and I don’t just live on my tablet. And so being able to take that audience and market to them across multi-channels and where their eyeballs are living is very powerful. It’s also cutting a ton of campaign waste as well in spending.

Kyle Hollaway:

That’s great. And it’s a really interesting observation on the penetration in the lower dollar sector, and it’ll be interesting to see how that plays out and what the real influences behind that are. But if we step back a little bit from maybe specifically talking about the election and strategies there that are very pertinent, you did have a really interesting article in the nonprofit times where you looked at political fundraising comparative to what was going on in just fundraising as a whole and really whether they were in sync with each other or if one drove the other one up or down. Talk a little bit about what you’ve seen there, how this impacts fundraising as a whole for nonprofits, because obviously there’s a lot of people sitting on the sides when there’s a political campaign going. It seems to overtake the airwaves and everything, but there’s a whole lot of other organizations that still have to meet their annual budgets. How’s

Heather Philpot:

That look? Well, it’s interesting, and again, it’s a bit of a moving target. If we take a look at what history has shown us political donors and donors that give to charitable causes have really stayed in their lanes, and there hasn’t really been a lot of crossover. I say that because every election is different, and this one will probably break the box right on the statement that I just made here. And it’s kind of interesting. I think nonprofits are in a prime position for where they sit because they get the benefit of taking advantage of the halo effect, I would call this, that the election provides because there is such a focus on issues, issues from all over the board. And so because of that, you’re going to have increased awareness to all of that. So depending on the platforms of each of the candidates, what is front and center with what they are talking about and what they’re communicating through content and with likely voters and even their donors, if that is in alignment with where a nonprofit is or where their mission sits, they get the benefit of that increased awareness at times.

There is increase overlap with donors that we do see, I’ll throw an interesting number at you, but what we tend to see on the giving side is that voters that engage in primary elections, and typically we would call these hard Republicans or hard Democrats, they don’t ever miss a primary and they never miss a general. They’re hyper engaged in their communities is what this behavior shows us. And when they show up, come rains, leaders shine to vote in primaries, there’s also a 60% crossover that they will also give to charitable causes specifically within their own backyards. And so there is that overlap that takes place within primary voters and donors that are also giving to philanthropic causes. And then of course, there’s the emotional engagement that comes rolled into all of this because we’re looking to move you emotionally, politically to get you to center around a particular candidate or to get you to go to the polls because of a particular issue. You have single issue voters all the time that go don’t necessarily like the candidates, but they care about the issues. And so that, again, that emotional engagement is moving a voter to the polls one way or the other. And nonprofits, again, if you happen to be in that particular lane, get to benefit from that halo effect that’s happening. So they’re in a unique position, I think to really capitalize on what is taking place within the election for good.

Kyle Hollaway:

Yeah, that’s really interesting. With certainly the rise of clean rooms within the ecosystem for data collaboration and stuff. Do you see collaboration between political fundraising events or strategies with those that are just in the nonprofit sector? I mean, is collaboration via cleanroom something that’s taken hold in that sector?

Heather Philpot:

I will say from a data perspective, Kyle, and I might have you even drill down a little deeper into your question because if you’re looking at the complete data sets, that one would take into account when we are modeling this data to figure out when a donor would be most likely to convert onto somebody’s house file. You’re using multiple data sets, you’re not just using one particular data set. And so when I think of collaboration and clean rooms, it’s really the bringing together of different types of data sets to make an informed decision or a prediction rather, on whether or not somebody is likely to give. And that’s the convergence of charitable donation data, transactional data coupled with political transactional data, behavioral data, attitudinal data, and then of course, obviously what all of you specialize in. Well, you specialize in everything, by the way, but I mean especially the demographic side, which serves as the spine to many proprietary data sets that so many people build out there. And so when I think of that, that’s where I think of is the coming together of all of these different data sets to really build a complete picture.

Kyle Hollaway:

Yeah, great. Okay. Yeah, and that answered basically my question that I had, so great job.

Dustin Raney:

So Heather, what are the biggest challenges you encounter with identity when trying to understand both individuals and households

Heather Philpot:

Data resolution and identity? It big issue to really wrap your arms around because it really ends up being the foundation for how you are marketing and whom you’re marketing to. When we’re looking at both the individual and the household level. So the first one that comes to mind is data quality, accuracy. Is the data you are sourcing, is it accurate? And the most dynamic piece of all of this is the household itself. Why? Because households are ever changing. People get married, they have kids, people get divorced. Sometimes the kids grow up and they move out of the house. And sometimes kids become caregivers to aging parents. And so the household is the most dynamic piece of the equation. And so being able to have accuracy, I believe in data quality is really going to be the key component. The other two I would also look at is making sure that your cultural and socioeconomic variables are also on target where you have a blended household.

My husband and I are of two different races. I am Hispanic and he’s not, but I get treated very differently based off of my last name, which usually is the big driver when trying to identify from a cultural perspective who you’re marketing to and where they fall into. And then of course, something we touched on earlier is the data integration piece because you are collecting data from so many different sources, you’re piecemealing them all together, and then you’re making sure that it all kind of makes sense. It jives with each other that the same Heather FILPO that graduated from the University of New Mexico and grew up in Albuquerque is the same Heather Filpo who now lives in downtown dc. And so being able to have that historical reference data as a touch point to look back at, but also to connect the pieces, I think is a huge, it’s a critical piece of all this. But I’d love to hear from all of you because you are the experts at Acxiom around all things identity resolution and really building 360 degree views of individuals in households. So I’d love to hear your experience also and how you guys are working with these challenges.

Kyle Hollaway:

Yeah, and a great question. Thank you. And I totally agree with your aspect of having that longitudinal view of a consumer or constituent and your language, being able to track all those life changes, not for the purpose of necessarily understanding behaviors or what’s going on at those different life stages, but just that it’s the same person and being able to see that so you can look at a broader view and being able to tie more disparate data sets together. I think that is absolutely critical. And part of that is for a nonprofit, if they’re only on first party data, which first party data is rising in importance because of things we’ve already talked about around privacy and data use and such. But at that point, you only know what you know,

And that may be good, but there’s a lot that you don’t know. And being able to come up and say like, Hey, I only know what I know and I know that there’s others that know other things, and how do I connect those? And that’s really where you get to, as you’re saying, the accuracy of that connection and then the data associated with those connections. And so Acxiom, we’ve taken a very long journey in really mastering those capabilities, both on the referential side, which is our census scale ID resolution capability that says, yes, we understand Heather Filpo across those various life stages and events that we can still put the right identifier against that, as well as at a household level, not just individual, but household,

Announcer:

And

Kyle Hollaway:

Then all of our Acxiom data that’s associated with those individuals, the ability to accurately compile that and model that so that you have that sense of accuracy there. So I always view identity as being a team sport.

Heather Philpot:

That’s good.

Kyle Hollaway:

You know what? I know what I know. And then together, what we know is really what can be most effective because you’re not just dealing with the constituents that you have today. You’re always looking for new constituents, people that you can bring into your party or into your nonprofit sphere. And so you’ve got to be able to accurately identify even the Venn diagram of that. Where is there overlap where it’s someone that I already knew that I just didn’t know well enough, or it’s somebody brand new. So to me, that’s identity as a team sport is kind of where I land

Heather Philpot:

Avoiding that myopic view of data because you’re just hyper focused on your own first party data sets.

Kyle Hollaway:

Yep.

Heather Philpot:

Okay. Dustin, you have to say something because Kyle answered the question. So yes,

Dustin Raney:

I was just sitting there thinking as Kyle was talking and just thinking about the topic of the political side of things at the household level now, it feels like more than ever, you probably have a lot more of these kind split households, right? It’s like you can’t treat any household in one color. So it’s marketing to a household’s got to be interesting on how you guide and strategize with a party on what your message should be because you’re going to have potentially a lot of households where you got a differing of opinion on leading topics. Not to throw it back, but is that something that you guys really think about before you build a strategy out at the household level?

Heather Philpot:

You have to because you could put yourself in a situation where you could seriously anger a potential voter or donor because you have now treated it as a monolithic block, if you will, and that you just can’t do that. And there are so many split households nowadays, and you have to make sure that you’ve pieced each member of the household with their correct party affiliation in how they voted in years past. And that in politics is the most critical piece. And then even be able to track when people change parties. And I always say, we’re all entitled to change our minds. None of us are ever fixed in this game. And so being able to also track and identify when that change happens, but then also to start marketing to them very differently based off of that behavioral change, that attitudinal change, if you will. So yes,

Dustin Raney:

Totally. And yeah, based on what Kyle was just saying around identity, it’s like it’s easier said than done. It actually takes a lot of knowledge, customer intelligence to actually make that work to enable you to do that, to maybe even have compassion for a household. I think identity is kind of a core fundamental thing that really has to be in place and really has to be thought about before you go and just execute on your strategies.

Heather Philpot:

But that’s why we have people like you to always guide and direct us and show us the best path forward. So it’s great having resources like you and Kyle around to really help us navigate the ever-changing waters of this. Yeah,

Kyle Hollaway:

Thanks, Heather. I think another industry where we see some collaborations between a financial service provider and a travel company where there’s some overlap, obviously, of their customer sets or even of their target customer set. And so there’s a collaboration there where neither party really wants to share the details of the PI associated with their audiences, but they want to take advantage and say like, Hey, I have something that may be of value to you as you’re making your strategy to these consumers and vice versa. So just looking at the fundraising, is there, I mean, because not being a fundraiser as I am not one, it’s kind of like is there more co-option or is there cooperation between fundraising arms?

Heather Philpot:

Okay. So I think this brings up a really great example when we consider the commercial side of the house.

And also, so comparing that in the philanthropic side, and I think about the ads I get served both on linear television but also on streaming connected TV and OTT. And I look at, I’m going to pick a brand out of the sky, but say McDonald’s. McDonald’s, no matter doesn’t really market to me and talk to me about their Big Macs anymore or how great, whatever it is their chicken nuggets are. What they do like to tell me is that the Ronald McDonald House has helped over a million families this year that were in need of room and board because their child was going through an intensive surgery within their community. And more and more brands, I feel, are marketing to us to not necessarily tell us anymore what their widgets can do as much as they are contributing and giving back to the community. And so when we talk about a crossover effect happening, I feel like there is a natural synergy and affinity between that and the nonprofit space, obviously, because more and more big brands, I believe are shifting to more what they’re calling or revamping themselves is more purpose-driven, if you will. And so I think that when we think about a collaborative effort taking place, I feel like that is a very natural synergy or a place to start, especially when you’re looking at commercial and the charitable side.

Dustin Raney:

Cool. So Heather, we talked a lot about outbound sending out campaigns, whether it’s through OTT or programmatic or social. Let’s talk about inbound. When people are going maybe to a political campaign, site landing page, are you seeing and are you guys helping some of those campaigns with personalization efforts when somebody comes on taking data-driven approach and maybe focusing on key areas, even imagery on certain hot topics that you feel like that person who’s coming in has

Heather Philpot:

Would love? Okay. And I would also love to hear your perspective on this because Well, yeah, because so much of the tracking that we do when we’re pixelating various websites and we’re dropping cookies into folks is cache so that we can retarget them, also learn more about their own online behavior to better more smartly market to them. I know a lot of these things are disappearing, and so third party cookies, things of that nature, it’s again, these are all moving targets. What are you guys seeing on your side? Because you are the data experts, you’re also experts in identity, and so how are you guys dealing with all of that? Because to answer your question, we are, we always encourage the pixelation and the tracking of certain websites in particular, especially donation pages. Obviously the most relevant when it comes to fundraising organizations based off of their privacy will and will not do it will watch their results tank if they don’t want to. But you’re not tracking critical behavior, by the way. But these are all tactics that people are using to either co-target, or re-target a very specific individual based off their device id. So what are you guys seeing within that front, especially with data privacy laws ever changing?

Dustin Raney:

Yeah, I mean, we’re definitely seeing a shift to first party data becoming way more important. So having mechanisms in place for, say, a party that should collect its own first party data whenever they’re engaging with an owned media site, for instance, across any landing page, making sure that you’re making use of every engagement and then persisting that over time with consent being very transparent. A lot of the, I think we’re up to what 18 states now, where there is consumer privacy regulations in place on what you can and can’t do with consumer data and how much transparency they have to show. But I think first party, we’re definitely seeing a shift in first party. And then Kyle and I like to say, even though Google didn’t deprecate third party cookies, the industry’s kind of moved on. So there are these kind of cookie list capabilities to get back to insights that can be done in a secure, privacy centric way that doesn’t put the consumer at risk, who’s engaging, but gives them a better experience and doesn’t put the brand at risk of doing something with data that they shouldn’t. And I think clean rooms are absolutely a part of that. You’re seeing places like Trade Desk, and our listeners have probably heard this from us a thousand times, but again, it’s relevant to this industry and you’re bringing it up. It’s like this isn’t just for profit, this is nonprofit, we’re all people, we engage in different things. I love my McDonald’s, but I also love to areas where I love a cause, right? My heart melts when for puppies or whatever that is.

Heather Philpot:

Do you love chicken nuggets though? This is what I want to know if we can continue to be friends.

Dustin Raney:

Yes, I do, to be honest.

Heather Philpot:

Okay, great. Kyle, you pass.

Dustin Raney:

It depends on the chicken so much more. I’m a quarter pounder guy myself. I mean, I’ve done it for years. Yeah. And yeah, I don’t know what that says about me. I’m the loyal quarter pounder eater.

Heather Philpot:

We’re going to run it through copilot to see later.

Dustin Raney:

Totally. But yeah, we’re seeing all these different technologies in place, and I would find it interesting to see if the same that for profit companies are leveraging, if nonprofits maybe using some of those same things on inbound real time personalization and leveraging some of these new capabilities that don’t depend on a cookie.

Heather Philpot:

There is so much that we can learn from the commercial space. And historically, the nonprofit space and even political space has always really been about eight to 10 years behind where the commercial space is. It’s so fascinating. When we were just at that conference in Boston and we were describing customer journeys and how customer journeys have really been around and the creation of them for the last 10 years in the nonprofit space, what we are calling donor journeys are just now emerging and really becoming more front and center over the last few years. And this is a tactic, cultivation tactic that’s been in existence in the commercial space, like I said, for the last eight to 10 years. And so the nonprofit space is always behind, and that’s why being able to learn from different sectors, be it commercial publishing, B2B, all of these things on how their marketing and the strategies that they’re leveraging to really communicate with their customers is definitely something the nonprofit and the political industry can really learn from.

Kyle Hollaway:

Yeah, I think that’s interesting. As you’re saying, the nonprofit sector maybe behind in certain strategies, and a lot of times early adopting takes money and it takes investment to get there, and nonprofits usually tend to have a tighter focus on how they’re spending money really trying to maximize that. Whereas on the commercial side, you may have a little more flexibility, but as that become democratized and those capabilities become more widespread at a lower cost and certainly the ability to pick those up and run with them within the sector totally makes sense. It is interesting though that on the flip though, I feel like some of the modeling and some of the targeting along with the AI use, it feels like in some, at least in the political and maybe in some of the nonprofit space, they’re actually kind of more forward thinking than you’ve seen necessarily within just a brand because there’s maybe more at stake or it is a more person-based kind of interaction. What do you think?

Heather Philpot:

Well, we like to say that in politics, we’re the first to love you and we’re the first to leave you because it has to work billions of dollars at stake and also the trajectory of the country. It’s becoming commonplace now here that this election is going to be the most important election in history. I mean, how many times have we heard that over the last 10 years? And that seems to be the catchphrase for every election that now takes place. And there’s some truth to that. However, when you are dealing with electing the leader of the free world and all of the consequences that come with that, you better make sure whatever you’re employing is going to work. So the idea of testing has become shorter and shorter, and then rollouts becoming longer and longer. We used to have a gap in off cycle elections where people would kind of take their foot off the gas, allow people to breathe a little bit, stop the amount of fundraising peels that would go out. And that doesn’t stop anymore. You don’t have breaks in elections. And so I feel that voters and donors are always being bombarded with a lot of different content that is out there. But yes, in politics, they are the first to test, to experiment. And if it works, they’ll roll into it big time. And so I will say that that’s how they differ. The nonprofit sector is much more slow, much more measured, and it’s, I think because of lack of resources, to your point, Kyle, they don’t really have the same level of investment.

Dustin Raney:

I would throw in that with especially this coming election, you have all these other countries outside of the US that are looking at this way more than they would look at a quarter pounder at McDonald’s. This really matters to them

Heather Philpot:

Maybe.

Dustin Raney:

So yeah, it’s like you have different countries looking at and saying, well, maybe one candidate is going to benefit us over another. So there’s these thoughts of, well, how much are they investing in some of these ads everyone’s seeing and they’re trying to throw the election? How do you guys handle things like that? And are there things in place to know where the money’s coming from?

Heather Philpot:

Wow. I’m also going to turn this question back at you

Again, I get to sit here and hang out with the experts today, but being able to put guardrails in place around the individuals that you’re targeting. I mean, we’ve seen the creation of bots within the last few cycles generating content that’s very, very questionable. And again, misleading voters from how they’re consuming their news, where they’re getting news based off of questionable websites. It’s tough. It’s tough because how do you regulate the worldwide web, which is where much of this really lives and exists. I will say that what you can do, but you do have control over what you do have in your own backyard. I will say that I think that that’s probably where the biggest influence takes place is the data sets that you are leveraging. Where are they coming from? How are they being sourced? How are they being managed, scrubbed all of these different things. I feel that where you are getting that intelligence means something.

We’re more as strategic partners with Acxiom in our own cooperative database solution. And I know that there are safeguards in place that whenever we come to you with data that you’re not sending us individuals that are 18 years and younger, say people that are ex-cons that have gone to jail. There’s a number of different things that you guys do before it gets to us as the end user to make sure that we’re in compliance and we’re doing what we need to do from a marketing standpoint. And so I guess I turn that back on all of you as to how are you all managing your large data sets? Because I’ve always seen you as the 800 pound gorilla in all things consumer fault data. And so how do you guys go about all of that?

Kyle Hollaway:

Yeah, well, great call out. And certainly ethical data use is right at the heart of Acxiom, and we’ve always taken a very thoughtful and wide ranging view of how to manage our data sourcing into our data products. And we don’t just partner for the sake of partnering. We ensure we vet all of our partners. We do a deep analysis on their sourcing mechanisms. Where’s their data coming from? Is it consented? Is it actually reliable? And so that comes into play when we start to look at our multi-sourcing strategies also where we’ll look for corroboration of data signals and be able to compile that obviously across our whole historical breadth of our data. So all of that comes into play. Where’s the data coming from as well? We don’t have a lot of direct to consumer sourcing. We do it through a wide partner network, but we ensure that those partners are meeting the bar to say on their privacy standards, their consent mechanisms, the data use agreements that we have with them, and the ability to bring that in and create data sets, like I said, that are ones that our customers can have confidence in, can understand that those are ethically sourced in a way.

And that term, it’s kind of interesting. You see that in other areas, just like in products like our diamonds or our beans or whatever it may be. You love diamonds, love Kyle.

Yes. And you like them to be ethically sourced. Exactly. And we take that same kind of mentality into data, even though it’s something that’s more digitally oriented, it still has the same, where’s the provenance of that data? How’s it being handled? Is it meeting all of our requirements? And then ourselves ensuring that we’re managing to that. We’ve got very strong opt-out strategies so that consumers can engage with us and ensure that their data’s being handled effectively and the ability to opt out of that where needed, but also multi-sourcing so that we can meet those needs that you have, being able to carve out certain populations that don’t meet your criteria. So yeah.

Heather Philpot:

So is there going to be a collaboration at some point in the future between DeBeers and Acxiom? Happy to.

Kyle Hollaway:

That might be a fun one, right?

Heather Philpot:

Quality of diamonds with the quality of data. I mean,

Kyle Hollaway:

There you go.

Dustin Raney:

I I’ll leave the charge on

Heather Philpot:

That.

Dustin Raney:

There you go. There is a backstory. Our listeners don’t know about My love for Little House in the Prairie. This is the perfect time to bring it in to the podcast. There’s just something about that show that I’ve grown to love, and I think it does come around honestly about ethics, about people doing the right thing. And when we talk about ethical data, that’s great, but having ethical people that manage that data and manage the processes and stuff, I think is absolutely, if not more critical, because they’re the ones that are kind of enabling some of these use cases. And I think at the end of the day, people want the truth, right? That’s what they want to make decisions based on the truth. They don’t want to be manipulated authenticity. They want authenticity. And I think that’s what we’re saying at the end of the day, it’s like let people make a decision for themselves on what they believe based on the facts. And I think having practitioners that are managing that process to get information in front of people is absolutely critical, more critical than ever.

Heather Philpot:

Okay. What was your greatest lesson learned from Michael Landon in Little House on the Prairie? Because you brought it up, so now we got to lean into this a bit. Now. See, Dustin, we just opened Pandora’s Box. We did it.

Dustin Raney:

I mean, I will say you’ll notice when you watch the show, there’s pretty much a funeral by the end of every episode, so it can be quite depressing, but there’s always a lesson learned. Usually teaching his kids, let them go through pain, feel the experience, but he is always there for them. After that, the fact givethemthat hug and tellthemit’s going to be okay, and it’s like, move on better the next time. So I think that’s my one little nugget from Little House from Michael Landon. I’ll give to my listeners. That’s really,

Kyle Hollaway:

That’s good. That’s a good one. I’d say mine, having watched it the past as well, would be just the humility of a father, because that was one thing. He was always willing to come back, and he’s very passionate, very strong sometimes in his strategies within managing the house and life. But then he would come back when he was wrong, and he would admit that I always took that as a real strong father figure there. Sorry.

Heather Philpot:

For me, it’s like learning how to chop wood.

Kyle Hollaway:

Yeah.

Heather Philpot:

I always feel like those greatest lessons were done.

Kyle Hollaway:

That may be a critical skill. I don’t know,

Heather Philpot:

Michael Landon swinging an ax while chopping wood, explaining the facts of life. So as a chicken,

Kyle Hollaway:

Global warming and all, you may need that

Heather Philpot:

Chopping wood. I can go back to Little House on the Prairie, watch some reruns on that. Yeah,

Kyle Hollaway:

There

Dustin Raney:

You go. Well, we might we’ll see a little spike in little house after this episode.

Heather Philpot:

You guys should be tracking that behavior. By the way, I may want to buy those, that particular audience. There’s got to be a nugget in there somewhere for political voters, if you will. There may be.

Kyle Hollaway:

Yeah, for sure. For sure. Well, we are coming up to the end of our time. This has been a fascinating conversation. Again, it’s on the edge of my area where I tend to play most of the time. So thank you so much, Heather, for your insights. It’s obvious that you’ve got so much knowledge and experience in this space, and I know our listeners will be equally enthralled by all the discussion and some of the topics we have been talking about AI. So we like to have kind of our final wrap up question, which is, if we fed all the data about Heather, including whether or not she watches Little House on the Prairie into ai, what are the three words it would produce to describe you?

Heather Philpot:

Ooh, that’s a really good question. That’s a scary thought, by the way. Yeah. Running all the data about Heather into AI and what would it come up with, I guess? All right. You’re putting me on the spot. I guess if there were three things that would come back with about what would best define Heather, I would say strategic, inquisitive, and the third fearless tenacious.

Dustin Raney:

Love that.

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