Soundbytes: Acxiom + Snowflake

Kyle Hollaway:

Hello everyone. I'm Kyle Holloway and I'm joined today by Lorel Wilhelm.

Lorel Wilhelm:

Thank you, Kyle. It's lots of fun to be here.

Kyle Hollaway:

Awesome. So can you give a quick overview of your role here at Acxiom?

Lorel Wilhelm:

Yeah, happy to. So I look after our partner and services marketing for Acxiom.

Kyle Hollaway:

From Snowflake, we have Erin Foxworthy, global head of marketing and advertising. Why don't you give some background on you kind of how you got to Snowflake and a litle bit about your history in the industry?

Erin Foxworthy :

Sure. Love to. I won't say how many years I've been in it. Let's just say right out of college I landed in digital advertising, which was pre-Google. So I'm going to leave it there. Spent the early part of my career in the early agency world. Most of my career, almost all of my career has been in Los Angeles. And it was interesting time then because digital budgets were a tiny percentage of the fraction of a marketing organization. And in Los Angeles, I got the opportunity to work across a lot of different types of industries, but automotive and entertainment tend to be large ones there. So I spent a lot of my time in these large enterprises, one very, let's say more data rich, some data poor. And so it was really interesting to see how different industries approached their marketing services. So I spent a lot of time on a lot of different types of businesses, which I think was really helpful in my early career.

I had an interesting opportunity later after working in the agency side is to either go client side or to go technology side. And I loved the digital advertising/technology intersection that was happening at the time. And I got a really amazing opportunity to go work at Microsoft. And in that role, similar to the role I have now, it was a role called category development. And this is when Microsoft advertising was being born. So if you think about Jeff Green's adECN was there, they had the equant purchase. This is pre-Bing. And they're building a really large advertising division. And so my role was to kind of come in as a, let's just call it a marketing expert to help the field sell in some of the services across Microsoft portfolio. And so we did that for many years, rolled that out globally and then sat back after Microsoft was kind of unraveling a little bit of their footprint within the advertising world.

I tend to do this to myself. I get really curious about things I don't know, which I know they say is a good thing. Sometimes that's not necessarily was a good thing. And I was watching kind of the unfolding of programmatic. I was watching the unfolding of a lot of data driven marketing. We had just started that and Microsoft advertising was fascinated to buy that space. And so I did a little bit of time, very short at what was called Rubicon Project, which was now Magnite. So on the SSP side.

And that was really interesting, but right in the moment I was there, I had an opportunity from a very good friend to kind of come back agency side, which I swear I would never do. But she had this amazing opportunity that I just I couldn't pass up was, there was a brand new movie studio, had no legacy data

Lorel Wilhelm:

And

Erin Foxworthy :

She wanted to start to unify her own, her MarTech stack to her ad tech stack. It was our early vision and the promise was most studios had no data and they wanted first party data. They want a relationship with their consumer and how do we start to build that? And for me, coming from more of a media background, but wanting to be more first party rich was really curious about this time and that space. I got really lucky. So we built a team that was almost in- house and I was at Horizon Media at the time and we actually kind of took this company on the journey of the CDP deployment. So how do you build first party? What does that look like? What does CDPs mean? How do we start to think about email and loyalty and push notifications and actually build a relationship with our customers?

How do we even gamify a litle bit? What do we reward them with? So more loyalty, which I had never explored before. But what that was doing was also feeding our media. Our first party segments was also feeding into our media buying because any media buyer knows first party will always perform amazingly sometimes limited, but it works. And so that was kind of the impetus was like the more we build up our own channels, the more we have first party for our paid channels. And what was really interesting is that we were really struggling with the early CDPs. They weren't flexible. We couldn't see our data. The cookie loss hurt a lot of them. And so what we ended up doing was migrating off of CDPs and saying, okay, where do we get more transparency and visibility into our data and kind of avoiding to have a lock- And that brought us to Snowflake actually.

So the solution for us was a data warehouse at the time, which much more than that now, that plus an identity spine so that we could have much more control and the visibility of our audiences. And at the time, even activating out of a data warehouse was a very unknown thing to do. It was just more of like a BI tool. And so we were kind of pushing the boundaries of what that meant. We were also at the same time, because I had an amazing team doing really great data science work in a lot of the clean rooms. We were testing ADH, we were testing Meta's clean room, we were touching really early testers of Amazon's clean room. When I saw Snowflake roll out that they were going to have kind of agnostic clean room, I was like, "Oh gosh, my data's already here. My first part is here.

I'm segmenting here and my identity here. If I can now collaborate in a privacy safe way, that's where this is going. " And so I got really lucky at that time of my interest, there was a position open, which is this role now. It's a very small team that kind of sits across Snowflake, but has this conversation with marketers. So that same journey I went through now, all marketers are going through across all enterprises, big, small, across the board. How are you joined and paid and owned? What's your first party data strategy? How does Snowflake help? And so I lead a team now that has those conversations across the organization.

Lorel Wilhelm:

Wow. As you were describing that. Yeah. I was thinking you could not have had a better foundation for where you are now. I mean, truly.

Kyle Hollaway:

Yeah. And I think it does seem like there's a convergence there of your story and Snowflake and where Snowflake's heading and what we're really seeing then work towards at this point, just a great convergence there. So that's really cool. So if we think about the big picture, you said it's a small team right now, but very impactful. I know you're having lots of conversations and a lot of influence there, but from kind of now the Snowflake perspective, what are these trends that you're really starting to see shape up around the future of media and advertising?

Erin Foxworthy :

Yeah, I think that this is probably no surprise to you. The first one is the, it's the identity imperative, which I put that in the first party world. How do we get better fidelity of our first party and understand our consumers? I'll put that in that bucket. I would say, and you guys know this too very much based on where regulation is headed, governance and privacy, right? That's forefront. We see those two just happening a lot there. We'll talk about how Snowflake answers some of those challenges. And then the third one now is just it's AI foundation. How are we setting ourselves up for the future of AI? Hard to predict, but there's some very key things that I think organization needs to do to be ready, which is you have to have your data ready for AI to be able to use it. So those are definitely the three paradigms I would say that we're seeing in market right now.

Lorel Wilhelm:

I'd like to take a deep dive for just a second in the first one that you mentioned, that importance of first party data. So can you talk to us a little bit about how Snowflake is helping brands really navigate that shift into first party strategies?

Erin Foxworthy :

So the interesting thing about when you think about cloud infrastructure, which a lot of times I know from marketers kind of lives in the world of their IT department, but the reason why it's so important, just take you from marketer's perspective and a consumer's perspective, what we know is how fragmented everything is now. So in our world, you'll help people talk about structured and unstructured data. Really, it's about consumers are on apps, they're on web, they're in your retail stores, right? They're in your call centers, they're looking at video messages, they're listening to audio. All of those consumer touchpoints are things that marketers want to use because what we do is we understand behavior. We understand consumer behavior better than anyone else. I love the way that marketers' brains think, but to be able to think about how to respond to those touchpoints, we have to have the data in a place that can handle it.

So a platform that can handle the speed the data comes in, the format the data comes in, the scalability of how to leverage that data that happens in the cloud. And so what Snowflake does is allow you to bring all those different elements in a way that you can transform it to make it something that can be usable by the business. And that's really what Snowflake does. It was built to do that the way that was architected really early was meant to be exceptionally fast and scalable platform. And so for consumer data, which is probably the fastest moving data set, I would argue, we really set ourselves up to be that foundation.

Kyle Hollaway:

Yeah. And as we've seen that shift to the first party data and especially with deprecation, as you mentioned of cookies and such that a lot of signals were lost in the third party space, but there's still a rich set of providers on the third party data aspect. Talk a little bit about how Snowflake is bringing those together. Yeah.

Erin Foxworthy :

So we work with a lot of some of the most amazing companies in the world around their datasets, Acxiom obviously being one of them. So Snowflake has a marketplace, similar to some other marketplaces. The interesting one about Snowflake's marketplace is that if you think about data coming instantly to an actionable database, that's what it does. It allows the organization to either bring a third party dataset. We work with many of the top leading third party data providers, geolocation data, social listening data, like name a lot. You can land that instantaneously into a Snowflake table. Now that's different because in the past when I was a media buyer, I would click a box in a platform and it would be my dataset and would activate it. The neat thing about when you buy and purchase data sets in Snowflake is it lands in a table, you physically see it.

You know what is standing right there and you actually physically see it and you work with it right away. And not only do we work with, this is a really interesting part and Acxiom plays a big role here, not only can you buy third party datasets, all kinds, you can actually buy applications. You can buy actual IP that comes directly instantaneously to your data. So this is where identity resolution would come in. So not that you're buying the actual function of identity resolution without having to send your data out. So that's what's amazing. You set that foundation and now there's a term we'll talk about called data gravity, which is that idea, these applications, these services, identity resolution can come to you, resolve right there and allow you to understand those signals of your consumers better, your household information, your mobile IDs and your email addresses as an example.

So whether that's third party data or whether it's identity resolution, those are some examples that Snowflake allows.

Lorel Wilhelm:

Oh, that's awesome.You've mentioned Acxiom a few times, so I would love to take just a second to talk about our partnership if you don't mind. So why would Snowflake want to work with Acxiom? What makes us strategic partners? I know from our side, but I'd love for you to talk about Snowflake's perspective in this.

Erin Foxworthy :

Yeah. I mean, I don't know an organization I don't talk to that thinks about the fidelity of their data and world-class identity resolution is paramount to the industry and that's where Acxiom's lived for many, many, many years. So not only the long history and understanding consumer data, the reputation of governance and being privacy first has been really important too. So there's not that many organizations in the world that know that like Acxiom. And so I think that that was a natural progression of whether it's IDA resolution, whether it's hygiene, all kinds of different applications for that partnership to be there. I think what I appreciate is organizations. I think it's hard for some companies to see this where someone will say to you, "I'm not going to move my data." I'm a marketer staying. And so I think the organizations who realize that and take advantage of the fact that this dynamic shift is happening are the leaders and Acxiom was right on top of that.

They saw that, they see this, they work with someone who's governing privacy data in the world, they know that the best thing for everyone is that data not to move. And so I think that that just created a natural synergy for our companies to work together.

Lorel Wilhelm:

Yeah, couldn't agree more. I would love to hear your perspective on some of the outcomes that you've seen in some of our joint solutions or joint implementations.

Erin Foxworthy :

Yeah. The first one I don't want to understate, which is like time to value.

So in a marketing organization, it's speed, right? Your promotions are up or down, your consumers are moving and shifting. The damage are changing so quickly in a marketing organization. So the first part is just that. Standing up this identity resolution on a data set and a data foundation that's already established, the amount of speed we save just to kind of move to market is pretty massive. So I would say that's number one. The second one, and I know there's still a lot of organizations that struggle with this is really kind of increasing, especially in the paid ad space, like the fidelity of your match rate. So we still know these platforms don't have all the signals and for them to perform well, they need both from an activation perspective and also from a measurement, like from a conversion API perspective. They need this data to be able to do what the platforms do well, which is understand their audiences, but they don't have all the signals.

So I think marketers are like, "How do I continue to make sure I have high fidelity data where I'm enriching these audiences into downstream platforms that get me the best bang for the buck?" I definitely see an improvement of that type of signal as we work together.

Kyle Hollaway:

Yeah. And talking about working together, obviously we have a shared set of clients where we are approaching really the marketing and advertising arms of world's largest brands and such. But you mentioned earlier talking about cloud tends to be in the IT department, right? Execution and everything kind of lives in the marketing department and you're kind of sitting at the middle of that and certainly Acxiom's longtime role has been kind of bridging the gap between those two. And so it's really interesting where you are coming at it from a architectural, even a kind of fundamental level of how to enable technology for these purposes, but then communicating that to a more non-technical ... Certainly the marketing department has become much more technical over the last even five years in my experience. And so you're bringing that. And I love that Snowflake's really leaning in by bringing on practitioners like yourself to help with that.

So talk a little bit about how Snowflake is approaching this aspect of being a technology company and a core component, but how they're delivering that into the marketing departments.

Erin Foxworthy :

Yeah. It's not easy. That's what I'm going to start with.

Kyle Hollaway:

There you

Lorel Wilhelm:

Go.

Erin Foxworthy :

And the reason why, I mean-

Kyle Hollaway:

Good answer.

Erin Foxworthy :

Because I've been in the office of CMOs many times. They are under the gun, the pressure. We know the average life cycle of a CMO is very short. The amount that is sitting on them and then for them to sit back and understand, "Oh, I need to understand cloud," which is highly technical. And by the way, it's its own massive ecosystem. It's funny, it's like we have a lot of drama sitting in MarTech and AdTech. We have the same type of drama in cloud. It's just there's all kinds of competitors and things happening, moving all the time so you really kind of have to stay on top of it. But I think that that's what we're hoping to do and you guys, Accent does this so well is when we talk about Snowflake, I can talk about elasticity like I did in scale and structured unstructured, but what I'm really saying is like, do you want a faster event trigger for someone that's abandoned?

So we try to get to that business level and we need a whole ecosystem of partners to get us there, but we are solutioning for that modern need of a marketer. A lot of its speed, a lot of its governance, a lot of its privacy, a lot of it's better measurement and visibility into their data. Every CMO can understand that it's a little bit of a translation. And so the other part that's really been then I think driving this too is that Snowflake, one of our key parts of our ecosystem is its collaboration, whether that's for second party data, whether that's collaboration to add platform endpoints or MarTech providers, Snowflake was built actually to be a collaborative platform. And so I think what you're starting to see is that when a marketer goes to say, "Hey, I want to collaborate with maybe a tangential sister agency or company and I want to think about maybe a really interesting co-promotion around data," I think what they're hearing is our IT department's going like, "Okay, that's great, but we're going to do it through data share or we're going to do it through data clean realm because we have governance concerns." And so I think they're hearing sometimes Snowflake come into the conversation around collaboration and sometimes that's where it's starting and then that's allowing us to come in and actually saying, "Well, actually your entire foundation's here and that's why it's important to you to care." So I think we come in sometimes with a conversation like that a lot, which is great.

If the way we come in and that's the way CMOs understand us is through collaboration, that's a great opportunity for us to educate as well.

Kyle Hollaway:

Yeah. I think that leads back to your original kind of three points, first party data regulation and then now AI on top of that. So adding one more level of complexity and challenge is bringing that and we're again, pulling those technical aspects and considerations and then placing them more into the hands of the marketer on how to leverage those in a way that still allows the IT department to do their thing and to still provide that governance and that oversight and everything that they want to do, but in a manner that allows the marketer to really take advantage of, like I said, landing it directly into an actionable table and being able to visualize that and be able to then decision off of that and execute without the historical baggage of, "Hey, we've got to move this data from one place over to a partner, then to maybe an execution platform and then so on and so forth." Yeah, exactly.

Yeah. Exactly. And it'll eventually get there. So talk a little bit about, because I know over the last period of time you've kind of repositioned a bit from just data cloud to AI data cloud and really leaning into that. And I think it's more than just a moniker. I mean, there's real meat behind why, but talk just a little about how you're integrating that AI specifically into media and advertising workflows.

Erin Foxworthy :

Yeah. It's really so exciting to watch. In the progression that we've seen marketers explore this, so going back to what we talked about first, the hardest part and the most important part, and I talked to a lot of marketers about we need to be control freaks. We need to think about our data and control it at all costs.That is your IP, that foundation of your data will be the future of your organization. And this is across enterprise, but really for the CMO, you need to guard it at all costs, right? Those are your consumers and setting up that foundation is hard. It's not easy to come in and get all of those API integrations, all those endpoints transformed and normalized in a way that can be leveraged for the business. And those that have done that, they're sprinting, we're watching them, they're sprinting to the industry.

What that did, that foundation, it set them up to basically build something what we call semantic layer. So just think about a business user layer that AI reads to tells you what to do and it has all your governance and all your controls and all the understanding of your consumer there. And once that's built, it allows the orchestration of AI and agents. And so that's something that Snowflake has naturally been able to build and bring to a lot of organizations. Now one of the things that we're doing, which I get really excited about, obviously Snowflake is a highly technical SQL based platform, but what we just released is an example of where I get excited where we're probably going to continue to head is to something called Snowflake Intelligence. So just went GA. Think about that as a natural language super agent that learns over time on all your data that's sitting in Snowflake that you can ask any questions to.

So I'll give you some examples of some early use cases we've seen. We've seen the questions of, "Hey, I want to understand." I have social sentiment data coming in. I have some from my APIs, I have things coming off of blog chatter, I have it coming off of some social platforms. I just want to understand what's a sentiment that's happening around my brand. Maybe I had a trailer drop, maybe I had a game release, maybe I had a Friday promotion. What's happening? Now we know that there's a lot of SaaS applications out there that kind of provide social listening, but now instantly in Snowflake, you can ask questions because that data's landed and it's structured and it's yours. And so you have that beautiful UI layer now to ask the questions to and learns over time. And so whatever data sources you want to feed that, it gives you kind of the understanding of that.

Think about that on top of measurement data instantaneously asking questions over what's my highest lifetime value, what's my best performing segment. When you start to combine that across what's happening across my call center, give me a cohort of users that are unhappy by their last experience that I can think about segmenting. So it's powerful because there's a lot of chatbots, there's many of them, but ours comes with the intelligence of all the data within the enterprise and the learnings. And so it's really exciting for us to watch that and see us as being the place of democratizing all the data that the marketer has never been able to access. I love that. As a business user, it's so fun to be able to see the ability for Snowflake to really democratize the data that they've never had before. I'm even processing this a lot as a marketer.

What does that mean for images? What does that mean for audio? What does it mean for all this data I've never had, this unstructured data that's coming in now? I'm excited to see some of those use cases too.

Lorel Wilhelm:

What have some early reactions been as you've demoed Snowflake Intelligence? I got to see it this morning and it is amazing. It is amazing. It's really

Erin Foxworthy :

Amazing. I mean, marketers are, we like UIs, we're visual. And so thankfully we can talk. I can talk all day about a semantic data layer and then I can say, look at what it can do to answer questions you've never seen before. We walk into a gaming company, we've talked to a movie studio and it's all of a sudden it's like, do you want to do box office predictions, ticketing data and also tie that to your measurement of all your ad spend all in one UI layer? And they're like, yes. Yes, please. Yes, please. So I couldn't demo that. We've been pulling up SQL and we'd be showing them code and then hopefully attaching it to a beautiful BI tool, but now we can just do that instantaneously with natural language. So really it's fun because as marketers, we know the questions and now what we just have to do is make sure you have the data in a format that can be answered.

Kyle Hollaway:

Yeah, I love that. And that kind of leads to the enabling component, which is your native apps. You kind of touched on

Lorel Wilhelm:

Those

Kyle Hollaway:

Earlier and certainly that's been a place where Acxiom has really leaned in because from an enterprise perspective, as you've noted, having the data all there and then being able to have Snowflake intelligence, the AI agent on top of that is awesome. But then that aspect of how do we bring one data hygiene into that, bring in the aspect of, as you said, identity resolution to really know who the individuals are within that ecosystem and start to stitch all those disparate components together. Because one thing to just have all the data there, that's another to effectively stitch it together and then augment it or enrich it with those third party assets like we talked about all while not leaving your own ecosystem, bringing those capabilities to the data. And that's really been a great strategy for us at Acxiom in conjunction with your native applications is being able to take what has historically been send your data to us and then we'll return it of us being able to bring our capabilities still in a very privacy conscious because we've always been at the very forefront of privacy legislation and ensuring compliance.

And so allowing us in a privacy conscious manner to bring our capabilities to the data in a privacy conscious ecosystem has really been a game changer and one that I'm really excited to see continue to grow out over time. And so that native application framework that you guys have brought to the table, I think has just been a very strategic component.

Erin Foxworthy :

It's really interesting you say that because I'm processing ... Native apps have been around for a litle while, you guys were leading this space there. And when I think about identity resolution, I think about hygiene and I think about a better customer review, we talked to us earlier a lot of times to test and understand if that was helping was a downstream activation to a match rate and then maybe there's some measurement and then you understood like, oh, this is really helping get a better view of my data because I can see it in my match rates and kind of my media as an example. But if you think about now if I can ask natural language questions of my audiences, you're going to see immediately the value of it because you're going to know through the questions the accuracy of the data, which is exciting.

It's going to make, I think that investment of identity resolution and hygiene and something like Acxiom even more important because it's going to immediately give the marketers the visibility into the data, not even necessarily for activation, but just for understanding of audiences. So I think that's going to be an interesting value that Acxiom's going to bring to Snowflake intelligence for sure.

Lorel Wilhelm:

Yeah. So in all of the conversations that you have with marketers across the industry, Erin, are there any common threads that you're hearing common challenges you're seeing, especially on the media side that leaders are facing? And talk to us a little bit about those and how Snowflake helps address them.

Erin Foxworthy :

Yeah, there's a couple. I mean, some of the challenges, they've been consistent. How do I make sure I get full visibility of my data, specifically in the traditional walled garden space That's obviously difficult, right? Those are walled gardens to begin with. So I think that that challenge is something that we see, but we are seeing, I would say a lot in the measurement space, that question come up of, and you guys are probably hearing this quite a bit too, the measurement space is shifting really quickly because I think that we're hearing a lot of the conversation around triangulation of measurement, which I think is really interesting. It's you can go in platform, you can do your holdouts, you can do your optimization, you can use the tools and the platform.

The second phase up from that is your holdouts, your controls, your incrementality measurement. So how do you get that back even in aggregate and then do your holdout and controls and do incrementality testing? We have a lot of marketers using our clean room as a way to access into that incrementality, into these ecosystems where the publisher doesn't have to avail their entire log set, protect their IP and you can still bring incrementality to those audiences and those platforms. And then the nice part about that is that if you're using the same incrementality model and holdout across all of your different endpoints, now you're getting a true sense of incrementality, right? It's not the model, the holdout of the platform, it's yours. And so you get to bring that across. And then the last one, so that piece that's giving you kind of like channel level incrementality, maybe not at a bidded level or like a granular optimization level, but enough to know the channels, bringing incremental audiences and then that is feeding into MM models, which is also something you can run in Snowpark.

And there's a lot of open source ones now and we have people kind of building their own using a lot of our ML libraries. So now you can run that same data that's feeding the incrementality, the data that's coming off the platforms and all the enterprise data. So if you have your POS data coming in and sitting and you have some call center data, you have other data sets in Snowflake, that all can now start to feed kind of a faster churn MM. MM models have been hard because I remember specifically in a fast churn business, if I have to know I have an up and down very fast sales cycle, an MM model comes back to me in nine months, that's not going to help me.

Lorel Wilhelm:

The

Erin Foxworthy :

Reason why that modeling's so hard, it's the aggregation of the data.

So it makes sense that a platform like Snowflake's going to allow you now to bring in faster MMM. So I think I think it's that piece. It's like, how do I continue to optimize the platform? How do I know that the channels are working and then how do I think about the big picture of allocation? We talk a lot about that, that measurement framework with marketers. I think that whole industry's changing a litle bit on how people are doing that. That's definitely a big one we're hearing in market. I would say we talked about the very tip of this, Kyle, a little bit is and this is organizational. It's the convergence of ad tech and market. It's like that you're first party coming between your owned and paid. It's the same audiences and they should be respected the same way. You should understand how you're hitting them and downstream media channels and advertising as much as you are thinking about them like we do with an email and SMS.

Yes, this is more personal and it's one-to-one, but how you think about even suppression, what's

Lorel Wilhelm:

Working

Erin Foxworthy :

Between those channels and how do I say, okay, I've hit you over the head with six emails you haven't opened it. Maybe I need to suppres that and think about finding you in another channel. That sounds basic. That's very hard for a modern organization to do that. It

Kyle Hollaway:

Is.

Erin Foxworthy :

So I think we see that conversions kind of happening quite a bit on Snowflake as well, which is exciting. A lot of that though is org design. We have these disparate orgs in a marketing organization. So it's not all technology. There's a lot of humans that has to happen too.

Kyle Hollaway:

Absolutely. So I'll be maybe a little provocative in such in this. So that was a great little segue there where you were talking about the media mix modeling and the platforms and measurement and all this. There may be some aspect of someone say like, "Hey, because of the focus on first party data and especially at the publisher side, we're seeing kind of a proliferation of many walled gardens where they're kind of saying, Oh no, this is mine. I now have this first party data that is more accurate than what traditionally was available and I want to monetize it. So now we're kind of ... And certainly Snowflake is a key component to their architecture. So do you see within the industry more fragmentation? Do you see that there is still a collaborative layer there where people are actually buying into this aspect of, because measurement's going to have to take place across multiple mini walled gardens and plus the open internet.

So the complexity is increasing. Notwithstanding the technical aspect of Snowflake that could enable that, do you think industry-wise, do you think we're going to get there where people will actually embrace that?

Erin Foxworthy :

I mean, you're probably teeing this up.This is where an Acxiom really makes the difference. There has to be universal stitching of this complexity back to a single source for the buy side because I see the fragmentation. You're right. Snowflake sits on both sides. We enable some of that fragmentation. I do think data cleaner rooms try to help with that. I do think that level of transparency of like, "Hey, I want to run an incrementality model. I'm a marketer. I'm spending a lot of money on your platform. I have the right to come in and create measurement with restrictions of privacy to know how my ads are performing." I think that does help a little bit, but it's a lot of work. A data cleaner room, we're all making it easier. We're continuing to make it easier, but it's not as simple as an API or a floodlight tag.

It's a little bit more complicated than that. I do think that the fragmentation is continuing and I think that we need organizations like IPG and Acxiom to continue to push to say, "Wait a second, we need to have an identifier we collaborate on that can bring everything back and we need that transparency to push the ecosystem from fragmenting too much." I actually, Snowflake helps technology wise, of course,

But we don't have necessarily the industry, what's the right word? Demand. We're not an ad spender. You know what I mean? We're not representing any type of transactional demand in conversation. So I think about it a lot as a marketer. It is a lot more complex and I do think that we need companies specifically like Acxiom to help continue to be that stitching of everything. It's really important.

Kyle Hollaway:

Yeah. That's great. Appreciate that perspective because I think that is kind of the reality of it. There's the art of the possible, which there's a lot being enabled in the possibility space. And then it's the behavioral reality of who we are. And I was just reading an article earlier today

Just around, it was actually some IP to him analysis that was done and there was a statement in there that was like, it's hard when people are paid to not understand because they're focused on reach and then there's precision and they understand the challenges with precision. So kind of not understanding how it all works allows us to keep going. They're paid on reach. So there are some behaviorals, like you're saying, it's not just technology that it's organizational, it's behavioral, it's just industry expectation and breaking some old habits where we were measuring off of things that were not necessarily things we need to measure off of going forward. So very dynamic time and very interesting. If you were to give a piece of advice to CMO and media leaders who you're, and you're probably doing this every day, give me a device because this is who you're talking to, what would be that one piece around modernizing of their infrastructure that you'd really give to them?

Erin Foxworthy :

I think that when I talk a lot to marketers, I want them to understand that there's technology now that can help them that they didn't really know existed. Meaning I think when I'm a marketer in the past and I'm moving so fast, what I wasn't thinking about is that every time I send a copy to an API or anytime I send data out, I was kind of losing the relationship with that consumer and I didn't have to. I don't think I would've known that there was options now. There's options to protect your data and still have the orchestration of it without moving it and having full control. You don't have to hand over how your data is structured or your consumer data to have a relationship with endpoints. I think that that's what cloud now does and that reducing your silos and choosing a foundational platform that allows you to do that.

Again, that's the IP of not only marketing, but your enterprise and lean into that. I think that we've seen a lot of what the industry calls it a lot like shadow IT. They kind of went off and kind of, "I need this and I'm moving fast and I'm going to break away and I'm going to do my thing." Which I think we had to move fast at the time, but I think it's different now. I think that a lot of the organizations are catching up. My favorite conversation is when I come to a meeting and it's the CTO or CIO and the CMO in the room and they're working and orchestrating together. It's just magic. It's magic to watch it because here's what I need, here's what I can do, here's what I need, this is what we can do. And then the organization just accelerates.

So it's reach out and ask the questions because the technology's there, the information's there. So control freak CMO, be controlling of your data. You don't have to give away the keys to the kingdom. You are in control of your customer data and it's your IP. So I coach a lot around that.

Lorel Wilhelm:

I think if you walk in a room and all of those leaders are there, like you just described, it really is the blending of the art of the possible and reality, kind of bringing it to fruition.

Kyle Hollaway:

Well, we are about out of time, which it always goes way faster than everything it does. So I'm going to actually ask this to both of you. So if all the data about Erin and Laurel were in the Snowflake intelligence, and I asked the question of, give me three words that describe you, what would come back? What would Snowflake intelligence tell me about you?

Erin Foxworthy :

Lorel, you go first because I have to think

Lorel Wilhelm:

About it. Oh, man. You saw me writing down as soon as you said I'm going to ask. Man. Okay. So this is like a hot take because I didn't know you were going to ask that.

Kyle Hollaway:

Exactly.

Lorel Wilhelm:

So I think if AI were to describe me in three words, it would probably be quirky. My kids would agree with that for sure. I hope it would say kind and curious.

Erin Foxworthy :

Ooh, we have kind of similar. I was thinking genuine and kind. Those are kind of two together. Curious was my definite number two. And it's funny, I don't know if you are, but I'm an aquarian and so that has a little ... So maybe not quirky, but a little bit of aloof. I try work, but I'm a thinker. I'm a dream.That's kind of my nature. So I get a litle bit of aloofness too. So it's really similar.That's kind of funny. I had the same three kind of ideas. That is funny.

Kyle Hollaway:

That is awesome. Well, great. Well, it has been a pleasure having both of you here and certainly Erin gave me a lot to think about. I mean, I love your insights and certainly your expertise both in the industry at large and then what you're bringing specifically to Snowflake, I think is hugely valuable.