[00:00:00] [00:00:00] Intro --- [00:00:00] Phil: What's up folks, welcome to the Humans of Martech podcast. My name is Phil Gamache and I'm on a mission to future proof the humans behind the tech so you can have a successful and happy career in the constantly expanding universe of marketing. What's [00:00:25] up everyone? Today we have the pleasure of sitting down with Erin Foxworthy, Industry Lead, Advertisers and Agencies at Snowflake. [00:00:33] About Erin --- [00:00:33] Phil: Erin is a former Category Development Lead at Microsoft Advertising, collaborating with product, marketing, and sales teams. She later became Executive VP of Partnerships and Innovation at Horizon Media, the popular New York City based ad agency. [00:00:47] She was focused on first to market creative and data opportunities for her clients. She's also a well traveled speaker and was awarded the Technology Leader of Synopsis Top Women in Media in 2020. Today, Erin serves as the Industry Principal for Media, Entertainment, and Advertising at Snowflake, focusing on advertisers and agencies. [00:01:06] Erin, thanks so much for your time today. I really pumped the chat. [00:01:08] Erin: Thanks. I'm excited to be here. [00:01:11] Phil: This episode is brought to you by our friends at Knack. Launching an email or landing page in your marketing automation platform shouldn't feel like assembling an airplane mid flight with no instructions, but too often, that's exactly how it feels. [00:01:24] Knack is like an instruction set for campaign creation, from establishing brand guardrails and streamlining your approval process, to Knack's no code drag and drop editor to help you build emails and landing pages. Knack No more having to stop midway through your campaign to fix something simple. Knack lets you work with your entire team in real time, and stops you having to fix things mid flight. [00:01:49] Check them out at knack. com, that's K N A K, and tell them we sent you. This episode is brought to you by our friends at Revenue Hero. I can't think of anything worse than finding out a lead waited a week for a response from sales. That's why we recommend RevenueHero, it's the easiest way to qualify leads based on form values or enriched data and route them to the right sales rep. [00:02:12] Their product is packed with a bunch of behind the scenes superpowers that ensures qualified leads are assigned to the right reps, following your custom round robin rules, and sending key data back to your CRM. That means more qualified meetings for your reps. We all know they want more of those, but more importantly, no more waiting time for your potential customers. [00:02:32] They back all of this up with the best product support out there, offering 24, five support on Slack connect for all customers, no matter your pricing plan. So if you want a three X, your conversions with the same traffic. Go to revenuehero. io and tell them we sent you. Your sales team will thank you for it. [00:02:51] We haven't talked too deeply about advertising on the show, so I'm excited to kind of switch gears just a little bit, um, and have an ad tech veteran like yourself on the show. [00:03:01] The shift in creative and media alignment in advertising --- [00:03:01] Phil: I wanted to start by asking you about. This tension that I find fascinating in advertising between the scientific data driven methods of ad tech and this more like non linear creative aspects of traditional advertising, like the Admin era, which are harder to measure, but obviously crucial for brand. [00:03:19] What are your thoughts on how this space has evolved over the past couple of years? [00:03:23] Erin: I was really like reflecting on this question when you brought this up, because I've been doing this a long time, and so what I think's really interesting is early in my career in advertising, media was such a second thought, right? [00:03:35] The time that a CMO spent in their commercial spot, you know, their direct mail, their magazine print ad, and all the attention that went into the fine details, I think was everything that the industry talked about. But what happened is, in ad tech, is that as you see consumers, right, come on in the digital age and the mobile age. [00:03:55] And that media became really, really fragmented and so much more types of creative came to market, right? Different types of ad units across all these platforms. It became specialized where I think the media persona had to become very specialized. And what happens is, is that growth happens. you kind of pull away a little bit from bandwidth to be as aligned to your creative teams. [00:04:20] And so you saw that in the agency world, which is where I was born, right? You started to see the proliferation of media only agencies. I started my career in a full service agency where I was sitting down next to the creative directors, right? And the copywriters kind of coming together. But when you start to think about the size of an agency and now, right, they're spending across hundreds of platforms. [00:04:38] It very much pulls you away from having a little bit of the joint discussions around creative, right? Because it's, it's a bandwidth and it's originally a structure issue. But what I've talked about, and I pontificate a little on this, but I think we're sitting at Snowflake at a, at a unique place to see this is that I think AI and the opportunity advancements of what's happened in the industry is going to pull that back together. [00:05:00] And I know we'll talk about this later, but I think that What's going to happen is you're already seeing it in, in kind of the walled garden platforms, right? The AI and the bidders and the way they're doing the algorithms, they're trying to make it almost like a turnkey button of let the platform, right? [00:05:13] Find your goals, do that, and will that give more time back into understanding more of the creative production and actually what works on those platforms, either organically or paid, right? Within that. And so, and right, do you start to allow. People who are strategic but may not understand how to build creative also the opportunity now to become creatives, right? [00:05:34] So it's going to be really interesting. I think that there you're going to see potentially and I've said this is that I think you're going to see a swing more towards, you know, marketers and agencies have the opportunity to bring that closer together because of the advancements in AI. [00:05:47] Phil: Super interesting. [00:05:48] Yeah. [00:05:48] The future of automation in creative marketing --- [00:05:48] Phil: Like we, we talked a lot about this topic specifically around email, like this idea of letting the machine take the wheel when it comes to the best email to send to the right person at the right time and all that stuff. And it's like a mixed bag of skepticism around still like fully letting the machine decide that. [00:06:08] And I'm curious your take for, for ads and creative, like if it's still the same, like at what point. Do humans like feel comfortable just letting the machine take that? I know that like the programmatic world of advertising is way more advanced than, than email. So maybe folks are a bit more willing to, to, to kind of like let the machine take the wheel there. [00:06:28] What do you think? [00:06:28] Erin: Yeah. I think that where the machine's going to happen is there's so much about marketing ops, the resizing of creative ad serving. Like I think that piece is so right for disruption and the need for automation, which is where I think that's going to go. I, I have not seen or been convinced that AI is going to replace any type of human touch. [00:06:48] In the experience of like maybe an email form, right? Cause that's obviously maybe some written text, but when you start getting into some of these really creative ad units, right? Where you're trying to build a brand message to a consumer, I, I, I'm going to be very skeptical that AI is going to do that anytime soon. [00:07:03] Phil: Yeah, yeah, totally agree. [00:07:04] Understanding the convergence of Martech and AdTech --- [00:07:04] Phil: What do you think is the difference between MarTech and AdTech? Like, where's that line for you? If I like research, a couple of different folks answers to this before I asked this to you and like. To me, like even before I dived into the research, it was just a question of like the umbrella, like terminology, nomenclature, Martech is technology used by marketing teams and AdTech is technology used by performance or demand gen teams who work in marketing under that marketing umbrella. [00:07:34] But I get that maybe this is a simplified take, uh, especially in like enterprise teams. Where, where do you kind of draw that line? [00:07:41] Erin: Yeah, I think that some people divide it into the own paid, I think that's such a simplification though of kind of where the world is going. And it's interesting because I think some people are like marketing is for the MarTech is for the marketer. [00:07:56] It's the platform that the marketer controls and ad tech is the platform control base. But if you think about it, the marketer really at the end of the day, they're not creating the technology. A company is creating the technology and the underlying technology, right, and the infrastructure of that. Is technology, whether it's for the marketer or for, right, the advertiser. [00:08:17] And so as the business user, you're just the customer of those technologies in most cases. And so the hardest part, I think, about our industry is understanding which technology is right for you based on your enterprise needs. And so what's interesting about Martech and AdTech, at least from a Snowflake perspective, is that as we start to see this world of personalization need to continue, we start to see that one to one conversation actually pays out from a business perspective. [00:08:46] That's happening, obviously always has in the own channels, but very much also happening within your paid and organic and social and linear and all the parts of advertising. And so if you start to think about that's all based on understanding your consumer and having the data to feed those applications of technology, that's what we start to see is that it's going to be where you can understand, right? [00:09:10] If I message someone in a text message or an email deployment. And I understand my open rights and I understand what I'm sending that message there. What am I also sending them in a social ad? What am I also sending them in a broader marketing, right, persona that I'm actually spending within even my CTV by? [00:09:25] And we've never done that as an industry. It has never been something that we've considered how to really unify that. And so you start to see that convergence. I think like a lot of the, you know, applications in this space that are building on that, it's all about unifying that on top of, right, a scalable platform. [00:09:40] And so, The convergence of that, I think is huge. But to your point, I think that the paid and owned is such a interesting take. Like we, it's just an easy way to describe it, but the complexity of that is much deeper than just kind of that topic. So exciting times. [00:09:54] Phil: Yeah, definitely. Um, [00:09:56] The uncertainty of Google's cookie deprecation rollback --- [00:09:56] Phil: we're, we're recording this at the end of July. [00:09:58] Uh, by the time this launch is going to be kind of like September ish. Um, but we're only a few days, uh, after the major Google announcement that, uh, they're rolling back their decision five years ago to deprecate third party cookies on Chrome browsers. Pretty wild that Safari and Firefox deprecated cookies like several years ago now. [00:10:18] And Google is like, Yeah, we decided we won't remove cookies after blown smoke for the last five years. What a waste of effort on their part, but all the other industry partners and advertisers and CMOs who like had signal loss. What was this a surprise to you or did you always kind of suspect that naturally Google's money making cookies would never actually be deprecated? [00:10:42] Erin: I was always 50 50. I'll have to say, like, my own personal take was always 50 50. And I think what they did that is very interesting is that they basically, the conversation now, it's, there's maybe no deprecation. But there's going to be potential deprecation by consent, right? [00:10:57] So [00:10:57] Erin: they're rolling it back to the consumer to say, right, there's precedent here, right? [00:11:01] Apple did it right with ATT. Let's let it put it back on the consumer to decide. And so what we don't know as an industry yet is how aggressive is that opt out going to be. And so I think people, you know, maybe want to make this assumption that, Oh, I'm still going to have, you know, some of my desktop data coming back and through pixels, but are you really, right? [00:11:19] The question's really going to be what's the, it's kind of just push back to the consumer, which they actually just did with GA4 too, right? So they made some decisions now to kind of put the onus and liability back on the users of it. And so it makes sense, right? There's precedent there, right? Apple. So I think that. [00:11:35] It's not out of the woods, it's just a different type of conversation. [00:11:39] Phil: Yeah, it's going to be interesting times. [00:11:41] The convergence of AdTech and Martech driven by first-party data --- [00:11:41] Phil: Uh, I feel like I've always heard that the cookie deprecation was kind of responsible for the convergence of AdTech and, and Martech. Most of these like post cookie solutions rely on first party data. [00:11:55] Like first party data was always like painted as the solution to the cookie deprecation. Um, which is primarily managed by Martech. So we had a lot of conversations about that with different folks. But do you think that like this convergence is less proactive and more of a reaction initially at least to Google discontinuing third party cookies? [00:12:13] What are your thoughts on this? Like, am I missing anything in this convergence? Is it the kind of end of third party cookies that's the main driver? [00:12:20] Erin: I think it's, it depends on the enterprise and I'll speak on this from experience. I think that when you have like a really strong, let's say paid media, or like, say it's like a DDC advertiser, someone that was like really granularly getting into the belly of understanding what works from an ad perspective, what you saw early, even before cookie deprecation was at first party to this works, you know, it's your consumer, you have a one to one relationship. [00:12:47] Even as a seed, right, building that into a lookalike model in some of these platforms performs better than a lot of the third party data that sits on those platforms themselves, right? So when Facebook and Google decided, hey, I'm going to kick off third party data a long time ago, even before cookie deprecation, You are kind of forced to say, okay, I'm going to either use their broad interest buckets, or my other option is to bring in first party and scale that. [00:13:09] And if you were testing that years ago, you were already seeing it works. It works better than a lot of what's already out there. And so with the idea of cookie deprecation, I think that just continued to force that narrative, at least from the paid side. And so for the, when, in my background, what happened is, is, okay, well, first party works. [00:13:25] Now I have to go upstream into MarTech to get that first party data. Now we needed, so it's, it was probably a rare, but this is how it happened for us. It was okay. And well, now I need to take my first party data. Now I need, this was, this was DMP days. So this was crux. So this was way, this is when I first started in MarTech, but it was driven by the fact that actually first party data was working in paid media. [00:13:46] Right. [00:13:47] Erin: It usually kind of goes the other way. But for us, we saw like, wait a second, we need to start to segment these users. And now let's get into more of the own channels and you start to unify that. And that was years ago, and we were really lucky to be ahead, my team that I was running at the time to be ahead of that. [00:14:00] But I think that it, there, so cookie deprecation, yes, it's the reaction. But I think if you're, if you also spend a lot of time using that data across all of your channels within Pave, you also realize that it works. [00:14:12] Phil: That's a cool way to think about it. Using first party data as a seed for lookalike audiences. [00:14:18] I feel like that Answers like [00:14:20] Leveraging first-party data for predictive personalization --- [00:14:20] Phil: one thing that I was going to ask you about, like the, the common hypothesis is that first party data can replace third party cookies. And this idea kind of stems from like all these rich insights that you're getting from first party data, email, transactional behavior, but even like zero party data, like people willingly sharing, uh, information, all this data can strengthen, um, your personalization, but it is a lot more sensitive and personal when you're dealing with PHI and PII. [00:14:49] But first party data is about known audiences and like people that you've reached already and it can't really match that volume of third party cookies and that unknown audiences that you could reach. But you just mentioned this idea of using first party data as a seed to open that box a little bit and find people that you could reach. [00:15:08] Um, yeah, I would love to unpack that a bit. [00:15:11] Erin: Yeah. So how we see this unfolding. And kind of the first party to what you said, the richness of own personalization. And that's obviously amazing when you have a lot of data to do that. Where it's interesting, I think, in the landscape that's happening is that your first party data, even not at high scale, is going to be the signal that you build upon. [00:15:31] So to your point, the seed and the platforms tied to, let's call it the first party of the platforms. And this isn't just the walled garden. So if you think about publisher data. The richness of Disney's data, the richness of NBCU's data, the richness of, right, a lot of these publishers data, they know their consumers. [00:15:48] On their opposite side, often on Snowflake, they're doing the same thing. They're unifying that customer data so they have a better understanding of who they are. So if your seed now informs their data sets, and then on the other end, you're bringing that seed and conversion data back in to help them optimize against their first party data, that's kind of, I think, where we start the industry going. [00:16:07] It's the tail ends, right? Right. So you're coming in and informing the algorithms and the data that these companies have collected about their consumers, and then you're also feeding in the loop back in, right, with that data coming in on the endpoint to help the optimization, right, to find the conversions or the lift or the metrics that you're, the KPIs that you're kind of going towards. [00:16:26] So I don't necessarily think it's all about, now, listen, if you have massive first party and you can use it, great, but. I think even those seed predictions are going to be really important. Now, the question is, what's the right seed, right? And how do you make sure that's the right seed going into the platform? [00:16:40] And that's where we start to see really interesting use of AI, even just seed prediction. [00:16:45] Phil: Yeah, no, I think you're well positioned to be able to, to talk to a lot of this stuff, like not just from the Microsoft and all your, your ad experience, but. Obviously, like being at one of the top data warehouse companies, um, [00:17:00] The shift from APIs to data sharing in cloud environments --- [00:17:00] Phil: I want to ask you about like the role of the data warehouse in this convergence of AdTech and, and Martech. [00:17:06] Talk to us about, um, how companies are transitioning from APIs, kind of like old school APIs is where like I, I grew up in marketing automation too, like bugging developers to. Hey, this is the REST API for Marketo. How can we get that hooked up to the product? Talk to us about how companies are transitioning to like leveraging data sharing. [00:17:27] Maybe unpack that for the audience and activation within cloud environments. [00:17:32] Erin: This is the, this is one of my favorite topics. It's like, it's like the gem. It's like the [00:17:37] Phil: gem. Nice. [00:17:37] Erin: Veiling. That's like really, it's amazing because this is the whole point of cloud infrastructure, right? This is what cloud infrastructure does the best. [00:17:46] So you may think about data sharing for, for your listeners that might not know. It's the ability within Snowflake to actually just expose a view of a table. So you think about you're exposing a view of data, finding controls on what you expose within that view, and then the other party able to query and ask questions of that data. [00:18:04] And so if you think about that, right, which can be real time, it's actually never sending a copy of your data. It's just sending a view, right? So you, sometimes we explain it a little bit to business users, because how I would think about it early in early days is if you think about like a Google doc, right, you're able to both share on the day without the data moving. [00:18:20] It's kind of a similar concept. And so what's amazing is if you talk to any data engineer in the industry that sits on Snowflake. The last thing they want to do is maintain APIs, right? You can get that data, right, in a quality view and instantaneously, real time, cross cloud, right, read that data, right, into your database. [00:18:41] Like that's phenomenal. And so what you start to see is really, and I think we're going to get to this later, is like, what does that mean? Right? So we think about the data that can come between you and a partner like Salesforce. So we announced it. So by the way, this is also called zero copy. You'll hear that term a lot. [00:18:56] Snowflake doesn't call it that. We call it data sharing. Okay. It's the ability for you to instantaneously share data bidirectionally between you and a platform like Salesforce, or between you and the ad logs coming off of something like the trade desk, right? So amazing insights coming in from, you know, your MarTech and AdTech ecosystem for you to instantaneously starts to find results upon. [00:19:17] And so, The use cases that come off of that are tremendous and it's really exciting. Like there's one very large holding company, I can't name their names. They're going out to the market saying we will only take data now through a data share if possible. And they're leveraging their buying power to kind of force that, like, use case. [00:19:32] Because the amount of time you think about that it also saves, right, from a talent perspective. For your engineers to do really more important work than maintain APIs, it's, it's really, it's amazing to watch it. [00:19:43] Phil: Yeah, super fascinating and exciting times in the data world. [00:19:47] Composability and zero-copy data in modern CDPs --- [00:19:47] Phil: We, uh, I don't know if listeners, uh, checked out, uh, the deep dive that we did last year on the whole battle between packaged and composable CDPs, but we touched a lot on zero copy data because it's like one of the cornerstone arguments of why would you go the package route? [00:20:06] Because they are essentially recreating a big copy of your data warehouse. And you're having this chat with your engineering team and trying to pitch them on having a CDP just for marketing. And they're just like, so you're basically trying to pitch recreating all the work that we just did and snowflake. [00:20:24] Just like in a new third party, just so it can be closer to marketing data. So yeah, zero copy data is what I'm a bit more familiar with as, as a term, but I like the concept of data sharing. Like it's a bit more, uh, explainable in, in the term, but yeah, the Google Doc analogy is, is making it pretty clear. [00:20:43] Like, um, we, we talked also about like warehouse native tech, like tech that sits on top of, The data warehouse. And so it's kind of the same lending, the same terms, right? [00:20:56] Erin: That's right. It is. And that's, you, you've talked about it. Like I've, I've heard a lot of your podcasts about this, but you're spot on, right, from the composable perspective, it's. [00:21:04] If you've done the work to build your marketing foundation in Snowflake, the whole world of applications is now coming to that data. And the whole point is not only from a cost perspective, but a security perspective, right? Like you don't want that data to move. [00:21:16] Yes. [00:21:16] Erin: So how do we collaborate as an ecosystem, right, across our consumer sets, but move the data as little as possible? [00:21:23] And that's exactly why I think you see the composability conversation coming. And, and again, you know, a platform like Snowflake probably wasn't, you know, years ago. First of all, it wasn't around. Second of all, you have to have the scalability of performance to handle that vast amount of data. And the technology is there now, right? [00:21:37] And so, like, that's why you start to see this amazing kind of conversation of, like, how do you now build applications and bring those applications, like MarTech and Antech, to the data? And so, yeah, it's a really similar, right, concept of data sharing, to your point. [00:21:49] Phil: Mm hmm. And maybe unpack that a bit more. [00:21:51] Like, how, [00:21:52] The evolving role of the cloud data warehouse --- [00:21:52] Phil: how do you see the role of the cloud data warehouse evolving in the next, like, five, ten years, like, maybe speculative future, you don't have to look too far in advance there. Especially like considering, um, this idea of democratizing data and technology and obviously like, um, data sharing kind of falls into that bucket. [00:22:10] Erin: Yeah, I'll say this is more of like an Aaron Fox review, or at least my hope. Um, and I'll preface it that way. I think what's interesting is that, because you, I mean, you can kind of see it too, it's, One of the hardest things in the industry as a marketer to do is to wrangle all the data coming off of all the different platforms, right? [00:22:26] To unify it, to create the right data layer, to transform that data, that's exactly what Snowflake is meant to do when we do it in really unique ways. We're going to continue to make that easier, right? That is foundational to what our company does and to what data platforms do, right? Is bring that data in and unify it. [00:22:43] And I think after that, you're setting this foundation for all these things to happen really, like many things to happen. And so I see it and we start to, we're starting to see this. And if you, you know, if you're watching Snowflake closely, it's the idea is that you're a marketing foundation with an interoperation of applications. [00:23:00] And those applications can do all kinds of different things, right? If you think about the robustness right? We talk about with all these Martek and Antec platforms. The inauguration of that needs to come to the data, the customer data, where the data is living. Now, what I think is really interesting is that right now, you know, you have to be a data engineer, data science, you need a lot of technical resources to do something like that on Snowflake. [00:23:22] The interesting thing is with the proliferation of AI, does that become something that more of a business user could potentially do? Right, and I think that that gets really interesting because now you're walking into a world of, Right. Like, how do we just make this easier for the ecosystem? So as someone that comes with a business user, right, I get, I get excited when I see the opportunity, right. [00:23:39] And think about what that could mean to the ecosystem, but that first piece, right, that marketing data foundation and that wrangling of data is number one, right. And that will always be where Snowflake lands and is. And so as these applications start to come to that data, right, you start to think about what does that future look like? [00:23:56] And the other part I love about Snowflake, and this is coming from the ad tech space, this is really important, is that. There's so many black boxes, right? There's so many of right ways that data gets locked in silos, right? For business reasons and being neutral agnostic to that space, I think is a wonderful place also to be because then, right, there's opportunity where you're not saying, you know, these applications are going to do things to potentially lock in your data because that's not what we do, right? [00:24:24] We don't sell advertising, right? We're never, you know, we're not a marketer, right? So I think that that's what's amazing about the platform is that we sit really neutral to the ecosystem. [00:24:34] Phil: This episode was brought to you by our friends at Customer. io. Oversold on a legacy marketing automation platform that is still struggling to update its user interface, I've done a tour of duty with all the major marketing automation platforms and many are definitely similar, but Customer. [00:24:48] io is the most intuitive and beautiful platform. 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This episode is also brought to you by our friends at Census, the number one data activation and reverse ETL platform. Loved by Activision, Canva, Sonos, Notion, and more. Learn more As you might know, I'm pretty opinionated that the future of Martech is composable, and that the single source of truth for your marketing data should be your data warehouse. [00:26:00] Census helps marketers solve an age old marketing problem, getting real time, complete access to your customer data without needing to write a line of code. Also, if you want your own face as a humans of Martek style image, we're doing a fun monthly raffle with census for a personalized t shirt. Enter to win at get census. [00:26:19] com slash humans. We talked a lot about AI democratizing, like understanding of data and accessing data and even being able to like connect it to an LLM to be able to chat with your data and like ask for the questions and analyze it more. And I think a lot of folks are building. Around that, more in like the B. [00:26:41] I. spaced. But I totally agree with you. I think that like this wrangling problem, like the, the pipelining of all the data and joining it and then transforming it and standardizing it, that's like the part where I have a hard time, um, like grasping it today, but I'm really excited about the future where I don't have to depend on a team of 15 data engineers who are servicing the entire company when it comes to pipeline projects. [00:27:09] Like being able to automate at least pieces of that work. [00:27:12] Bridging the gap between data engineers and marketers --- [00:27:12] Phil: Do you think that marketers today are proficient enough in like their understanding of data to be able to leverage AI to, to, to do some of that stuff? Like, is there, is there a knowledge gap between the data engineers and the marketers that marketers just need to level up today? [00:27:30] So that in three, five years when this like wrangling Potential is automated. Marketers are able to like leverage it without like, all right, now that we can do this, I need to spend like a bunch of time figuring out all of like my tables and how can I join this stuff? Like maybe touch on that a bit curious. [00:27:48] Erin: Yeah, it's an interesting question. I think that right now, and, um, and my hope is that it changes is that marketers like marketer marketer, like the true marketer that comes from kind of like the traditional space is so far away from understanding a lot of this. And I think that that's the paradigm shift that probably needs to happen. [00:28:08] And I know it can happen because I'm starting to see it right within certain organizations where they have to get closer to some of the technology conversations and spend some time there. And frankly, that's also on, you know, companies like Snowflake to make that bridge and that educational gap, um, come together. [00:28:23] But I do think that for the future state of like, and I think we're talking about this, even in CMO suite, like it's going to be absolutely necessary to understand, you know, at least in broad. you know, strokes, the work your data engineers have to do to bring that data together. I think you have to. Um, and I think vice versa, right? [00:28:43] I think what you're starting to see is that A lot of the data engineers and technologists sit within the marketing organization now have to understand what's happening with that data downstream. So I, you start to see kind of this perfect convergence and I know there's a few, you know, there's probably a handful of them, but I, I mean, there's unicorns, right? [00:28:59] There's unicorns that came from one side and became the other, came from one side and became the other. And they sit in this amazing sweet spot of understanding, like, what can a data warehouse do to really make me a performant marketer and vice versa? And I think that that's where the industry is going. [00:29:13] Um, and I think that that's the bridge that the industry is going through. And I have a lot of people asking me that all the time. Aaron, how'd you go from like a business user and advertising to understand and work at something like Snowflake? And listen, it's constant curiosity and learning and understanding. [00:29:28] And I think that also what people miss a lot, it's, it's what is the use case unlock? [00:29:33] Like [00:29:33] Erin: we're talking about like pipelines and data engineering and data sharing and that's amazing. And you have to understand that. What does that unlock for you? Right. Like what's the use case, like more real time, deeper transparency and a measurement. [00:29:45] Like there's so many amazing use cases that come off of knowing that you need to know those things right on the marketing side. Right. To say like, if this happens, I get these new use cases unlocked for me. Right. And that's where I think that's really interesting. So if you just think about zero copy data between, you know, a CDP or an ad platform with ad logs. [00:30:05] What is that I want for you? [00:30:08] Phil: Yeah. Use cases is definitely where I think that like, you kind of talked about this idea of like both sides, state engineers and your traditional marketer, like learning a bit more from each other. And I think that's where like the, the marketing technologist, the marketing operations person, Kind of steps in the middle of this. [00:30:25] And I've been at companies where, um, sometimes the title is like a data product manager or like a MarTech product manager, and they're essentially translators within the company. And they spend time educating data folks about marketing use cases. Like here is what lifecycle marketing is. This is the value of personalizing our emails and how we can send different types of SMS based on where someone is in the funnel. [00:30:50] This is the funnel. This is the marketing breakdown of where people are in the journey. And then likewise to marketers, it's, it's a whole different conversation about like, here is how our data tables are set up and how there's different structure and there's different columns and they all come from different places. [00:31:08] We're using ETL to bring it all into snowflake. And we're using senses to push that into different tools. So like, I feel like the martech person is well positioned to continue to be curious in that space. And I talked to a lot of listeners that are fascinated about this space. [00:31:24] The importance of a unified data layer in marketing operations --- [00:31:24] Phil: And we had, uh, we had Scott Brinker on the show, um, last year and it was like a momentous event for, for us on the show. [00:31:31] He fans of, uh, Scott Brinker and like probably one of the archetypes who like got me into marketing ops in the first place. And, um, one topic that he's talked a lot about recently that you just mentioned a couple of times is the data layer. And how do you, um, I wanted to ask you, like, how do you kind of envisioned this data layer with the integration of the data warehouse or data lakes? [00:31:56] He calls it a lot of the times data lakes. Um, but like transforming this idea of like how effective and efficient marketing operations teams can be. What's the true business value that you foresee the data layer bring in to the entire marketing organization, especially when we talk about like AI and copilots coming into play. [00:32:18] Erin: There are many, many. So let's talk, before we talk about AI, we can talk about some other things. Let's just talk about time to value, right? So if you think about standing up an investment like a marketing data cloud and how long that potentially takes an organization, where if you have a data layer, right, that's, we just talked about that, right? [00:32:35] Prep stores organized, right? The data is in, you know, a data model that's unified across all your brands and all your channels. Right. Once that's set up right now, you're talking your time to value to your marketing team, right? It can be days to weeks, first of all, right there versus like six months to years to potentially stand up right at a very large, large platform. [00:32:54] So there's first ones there. The one we talk about too, it's, it's think about consent and privacy, right? So I think the future, if you're looking, if you're watching really closely at privacy legislation, which I actually love to watch very closely. Is that there's going to be a need for fine grained controls and how we can sense customer data. [00:33:13] Well, if it's sitting in data silos and you haven't unified that customer data, how are you going to do that downstream, right? So like there's pieces like that. Now to what you just said, and this is, you know, you'll hear Snowflake kind of talk about this constantly. There is no AI strategy without a data strategy, right? [00:33:28] AI has to sit on top of organized data where it can't do what it's meant to do. You can't find, you can't build a model, you can't do any of that, right? So I think that, that there, we miss that in a lot of these conversations. And then we're seeing that in use cases, right? You'll have a great idea on AI and we'll get a customer coming to us and say, I have this great idea. [00:33:44] They're like, great. Well, your data's not in any place that we can actually, You know, build the models to do that. So I think that that's really important to think about the future is that, you know, there's really real time, really important use cases now to having that data layer. That un silos the data across the organization, and then there is the future state. [00:34:01] So, I have to say I love when Scott talks about that, because I fully agree. [00:34:04] Phil: Yeah, yeah. How, [00:34:05] Preparing marketers for the future of AI-driven data --- [00:34:05] Phil: what advice do you have for marketers to, like, prepare for this? Like, this future of marketing AI, where the data layer is influencing a lot of, like, the capabilities. We talked about, like, being more, uh, literate in terms of, like, data literacy and, like, uh, Like being more curious and, and, and trying to learn more a bit on the data engineering side of the world. [00:34:28] But what else, what else comes to mind if you're like giving advice to marketers that are listening, that are just like, I want to be well positioned to be someone To land senior level gigs to know that, like, this is where the industry is shifting. Like what advice do you have? [00:34:44] Erin: It's a great question. Um, it's hard because marketers are really, really busy. [00:34:49] Right. And you have a, a day job, right, to do whole time. I mean, and it's one of the most, you know, it argues busy, busy jobs within an enterprise. Um, I would say that the nice part is, is that a lot of the material that's coming out, listening to, obviously you, Phil, and others are like, I spend a lot of time. [00:35:07] Listening to Thought Leaders and podcasts and reading about People who are sitting on the front line see the vision going. So I think like you have those type of resources in the industry to listen to. I think that's exceptionally important. There's also to your point, this kind of new marketing operations person that's kind of coming to settle being the translator. [00:35:26] I think knowing those people or hiring those people is really important. unicorns and have them in your organization to start to educate both sides, exceptionally important. It's also a very ripe time right now for SIs. Consultancies are very happy right now in this very complicated landscape. Right. So, um, and I, in my background, right, SIs were never a part of like a media marketing organization, and obviously it's much more proliferate and maybe the MarTech space, but there's some amazing companies that are just coming in just to do this, like, let me consult you, you know, CMO on what the future of this looks like. [00:36:03] And I think that that's, There's some very good ones out there too. So there's resources, right? And I think that if I'm any type of CMO right now, I'm hiring those resources. And it's what's going to put you ahead of the game. And it's also what's going to teach you, right? In the little amount of time that you have actually to learn a lot of these things. [00:36:19] Phil: Yeah. Great advice. Let's, [00:36:21] The evolving role of the CMO in a fragmented marketing landscape --- [00:36:21] Phil: let's unpack the, the, the new demands of, uh, the CMO office. Like I, uh, we can circle back to like the transition away from third party cookies, I feel like has caused a lot of, not just marketers, CMOs, but a lot of like privacy folks, like you just mentioned, who have relied on addressable media for a lot of years and they need to like address signal loss essentially. [00:36:44] And over the past decade, plus marketing has grown and. A bunch of different stages like programmatic advertising and AI driven personalization talk a lot about that stuff. Um, this has led to, like you kind of said, fragmented systems where different parts of marketing don't communicate very well, especially in enterprise, CMOs now see this need to obviously unify a lot of that data. [00:37:07] And the issues they face is like, there's too many, too many agencies, there's too much scattered data, like isolated teams and silos. Talk to us about like the new demands of the CMO office and how leaders should tackle this. [00:37:20] Erin: Yeah, I think that's a great question. It's interesting because when we get into a CMO office, usually what happens is, and this is just my personal experience, we've talked to quite a few CMOs in the last few years, is they usually lean in a specific space or come from a specific background. [00:37:37] Yeah, and so what happens is, is that you get kind of, A lean into an enterprise based on that background, right? So maybe it was, I was a traditional marketer, right? And so I really understand kind of that space. And I'm trying to learn from a media perspective, right? How do I actually broaden my understanding and into areas, you know, like PR or promotions or write other areas of the marketing organization, right? [00:38:02] And so then you start to kind of see a push, but there's a lean towards understanding the specific piece of the marketing world. And I think that's really hard. Because I think now if you're not in a seat of a background of understanding how technology is going to actually influence all of those things, that's tough, right? [00:38:19] And so it goes back to I think everything you and I just talked about in this entire, you know, conversation is that a CMO has to flex and find the resources and the experts. to help them in those specific areas is they cannot do everything. But what they need to do is put the right people in the right places of their enterprise to drive that. [00:38:38] Right. And I also think the biggest part right now it's and it's been there for a long time. This is this is not new. It's the, you know, CTO, CMO battle shake, right? So if you have an order and that to me, that goes into the CEO, right? So like I would, I, what I think the hardest part right now, it's the battle between those two things versus the collaborative handshake. [00:38:58] And I'll tell you right now, cause we sit as an enterprise, right? Software platform. We come a lot of times through the IT organization, right? We come through the CEO's office. And this, the marketers are sprinting down the line right now is where that collaboration has been formed. And I think that that, that is something that's cultural to an organization. [00:39:18] And I think it also has to stem from the CMO. You know, CMO at the end of the day has to walk in to their CFO and say, these are like the technology things that I made. This is every dollar is actually paying out to the bottom line, right? That's what they're in charge of. And that's what their jobs are hanging on. [00:39:32] And so if technology is going to underpin that, guess what? You better have a really strong relationship, right? With your technology team to drive that. So I think that, that if you don't come from a traditional technology background, MarTech, media, anything that's a little more data driven, really important to start to lean into those type of. [00:39:49] Executives, hiring, and then collaboration, I think, with the right folks in the enterprise. Um, cause the difference is, is a sounding right in, in the organizations that we see. [00:39:58] Phil: Yeah. I, I like that you mentioned that like most of the time Snowflake, like a cloud warehouse will be brought into a company by the IT team, by the CTO. [00:40:09] Um, and what might surprise some folks by looking at Snowflake's site is that a lot of the marketing material, at least of recent days is geared also to marketing personas and that's CMO. [00:40:23] The shift towards CMOs engaging with data platforms --- [00:40:23] Phil: What was that like shift that happened where the company, um, maybe you can like speak to snowflake or, or just like your, your personal perspective, like what was. [00:40:34] This like lightbulb moment where it's like we can't just talk to the CTO, the CMO needs to also know that we exist and be part of that conversation. [00:40:44] Erin: I think it's just the maturation of what we just said of the CMO office, right? So if you start, it goes back to, yes, do I think that cookie deprecation was a part of that, right? [00:40:55] So we backed that out, right? So [00:40:56] it's, [00:40:57] Erin: I want to be a more addressable marketer. I've learned that now, right? I want to use first party data to drive into optimize, not just social, but my linear campaigns, like across the board. Now I'm getting to be a more advanced marketer. I need data to do that. Now I'm a data driven marketer. [00:41:12] Well, where does my data live? Oh, my data actually now lives in. Right. Something like a snowflake. What is snowflake? So it's this kind of natural kind of conversation. I think what also happened is that you have parts of our platform that got kind of pushed into the front of the dialogue, like data clean rooms, right? [00:41:29] So data clean room lobby. So there's a lot of times I get off call with a marketer and they're like, Oh, snowflakes, a data clean room. Right. And so that's, that's just their education point of where they actually learned about snowflake. Right. And so then you're going to have to unpack. It's like, there's a much bigger picture to what that is. [00:41:43] We're not just data clean room. But a lot of that's happening too, where. I think the one thing I will say about, you know, Google's announcement on cookie deprecation is that the train has moved towards data collaboration, was already moving towards addressable media. And so what's been amazing in the last few years is that the CML had to realize, how do I collaborate that protect my consumer data in this shifting ecosystem? [00:42:06] And a lot of that started, you know, Google started a clean room 70 years ago. Amazon, right, followed, Facebook followed, Meta followed, now you have Disney, NBC, and all these others. They don't have a choice because they want to measure, right, a lot of what they're doing. There's things like data cleanrooms that are coming up and now they have to understand that. [00:42:24] So, I think the forcing function from the industry based on the security protection of data kind of brought us to the CMO, like, level. And all those applications started to come, right? So now you have all these partners who are building applications saying this is the value to a composable model. And there's talking about right now to the CMO as well. [00:42:42] So there's a lot, right? There's a lot of factors. I mean, even identity providers, right? You look at the largest identity providers in the world, which are in every single office. They're like, Oh, now we have native applications that are run on Snowflake. Right. So it's, it's just, it's this maturation of the industry and kind of the snowball effect that's happening. [00:42:59] That's bringing kind of the CMO office staff to understand these platforms. And so it's exciting. I mean, I've only been at Snowflake for two and a half years, but right. The speed and the cadence of these conversations are just, you know, amazing. [00:43:11] Phil: Your, your passion is definitely shining through and, uh, your knowledge in this space. [00:43:15] And I definitely appreciate the insights you, you brought today. Myself, I think one of my favorite parts to do in the podcast is obviously like I get to sit down for an hour with, um, industry experts. And yeah. It's hard sometimes to always grasp like all the insights that come out of conversations right now, like real time. [00:43:32] And so I convert all the audio episodes and so long and long form blog posts for folks that just want to like read key takeaways. But part of that editing process is also reliving the podcast and like re listening. And I feel like I'm definitely going to enjoy that that part of our conversation as well. [00:43:50] So I thank you for, For sure. And all that, I got two more, um, kind of bit more fun questions for you. [00:43:56] Promoting diversity and combating bias in Martech leadership --- [00:43:56] Phil: Obviously humans in Martech, we, we cover the human side of, of Martech as well. And so one of the other things that CMOs and other leaders in, in enterprise and companies is, um, diversity and unconscious bias remains this significant challenge in promoting, uh, diversity within teams. [00:44:16] What strategies or training have you found effective in your career so far in combating this and ensuring a fair and supportive environment for women specifically? [00:44:26] Erin: I love that question. It was a really interesting transition for me to Snowflake specifically, I think when you, in the media world, you know, I never really struggled with finding that there was a lot of women around me in supportive roles or at least role models for me to look up to. [00:44:40] I find the closer you get to technology, which is not a super surprise in the industry, you just see it in the numbers, there is definitely a lack of women, especially in leadership roles. And so I think what to counter some of those things that I've seen be successful, right, is just the supporting of women and their career development within an organization. [00:44:59] So a lot of times, like, I think what's really important is like mentoring programs. So women helping women inside the organization or men mentoring women inside the organization as they grow. Like, I think that I've seen that be very successful in organizations. Um, I think even in states like California, you start to see a push of more women's on boards and leadership roles, right, to see if they can have obviously a stake at the highest levels of the organization. [00:45:21] I think that's exceptionally important because Especially when you've seen this, you know, and this has been talked about, but especially in the world of AI, right? When you're thinking about the biases that AI could potentially have on the people that are building the actual platform, that's very nerve wracking to think that there aren't diversity right in the build of those models. [00:45:40] And that's what's actually, that's what consumers are actually facing. And so I think it's an exceptionally important conversation to have, and especially in big tech. that we continue to support women to be able to do that. And that it can be in technical roles, very important, but also in managerial roles, right? [00:45:56] When there's big decisions to be made, like, is there right diversity sitting at the table when those decisions are being made? And so I'm really passionate about that. Um, and I think it's something that the industry needs to continue to think about. [00:46:07] Phil: Yeah. Such an important topic. Um, one of my favorite episodes this year was with Brittany Muller, uh, former, uh, SEO scientist at Moz, who's now all in on just like educating marketers about the world of AI and how LLMs are built. [00:46:23] Like she calls it like what's in the hot dog and it's really dirty and bad. And, um, yeah, all these biases and like the, the training data sets, it's, uh, It's a whole world to unpack that a lot of folks just kind of take for granted. Like, yeah, I've used chat GPT, like no big deal. Like, do you know what this is built on top of that? [00:46:42] Not enough folks do, [00:46:43] Erin: right. It's like, it's like, it's like, well, quickly. Yeah. [00:46:47] Finding blanace as a leader, mother and creative --- [00:46:47] Phil: Last question for you, Erin, uh, you're a senior leader at Snowflake and ad tag veteran. You're also a mother of three. Three, an avid gardener and a quilter. One question we ask everyone on the show is how do you remain happy and successful in your career and how do you find that balance between all the things you're working on while staying happy? [00:47:05] Erin: Yeah, I think that those things are, I was, you know, mentioning when I said quilting and gardening, I'm in my grandma era, the young kids these days, I'm in my grandma era, which is, you know, it's just like grounding outside of work, right? It's finding time where my brain is completely turned off. And I'm either in nature or I'm concentrating on a creative endeavor. [00:47:26] Those two things like feed my soul, feed my brain. And they actually, it's like a switch, right? I can't think about anything else. And it allows me, I think, to, to remain happy. And then, you know, when you're a mom of three kids, every other second, like the nice part about, you know, your kids, I could be doing a podcast, I'd be walking off a stage, I could have come off from weeks of travel, I walk in and I'm just mom, you don't have a choice, you're mom, right? [00:47:48] And it doesn't matter. And so all of a sudden you're in a whole different persona. And they demand your ultimate attention and they should have that, right? So I think I've been really strict about that in my career is that I'm always first, right? And if you have that ethos, it's a little bit easier to kind of turn off and like remain happy because you have these different pieces, right? [00:48:08] You're feeding the creative brain. You're feeding the mom brain and then obviously, right, that's helping you be who you are at work. So that's it. It's a balance, which we all talk about, but that's, that's what helps me. [00:48:18] Phil: Such a cool perspective. Yeah, definitely good advice for me too. I'm a first time dad this year and, uh, she just turned one actually. [00:48:26] And like, we're just now starting to see. sleep a bit more and, uh, but yeah, like definitely, uh, echo this sentiment of like wearing that dad hat first and being mindful of like why we're doing the things that we do. And yeah, it is, it is so cool to see them change and like, you're, you're still that like parent hat to them. [00:48:47] It doesn't matter what you just did during the day. [00:48:49] Erin: That's a total reminder, right? Constantly. Yeah. [00:48:52] Phil: A hundred percent. Aaron, thanks so much for your time. This has been super fun. I really appreciate it. [00:48:56] Erin: Same. Thanks for having me, Finn. [00:49:08] Outro --- [00:49:08] Phil: Folks, thank you so much for listening this far, I really appreciate you being here. Just wanted to call out a couple quick things before you go and give a shout out to other Martek creators that you should check out. The best way to support the Humans of Martek is by signing up for our newsletter on humansofmartek. [00:49:24] com. I send you a quick email every Tuesday morning letting you know what episode just dropped. I include my favorite key takeaways so if you don't have time to listen to that full episode I've got you covered with some learnings anyway. Proceeds from sponsors this year have allowed me to venture into video. [00:49:41] I recently launched a YouTube channel at the start of this year where I publish full length episodes as well as clips from, uh, all the episodes, so if you want to see my radio face, check that out. And if you can't get enough of MarTech content, check Wanted to give a couple quick shoutouts to some of my friends and awesome creators in the space. [00:49:58] We featured Mike Rizzo in episode 75 and we chatted about Mopspalooza, the first community led conference for marketing and revenue ops professionals. [00:50:20] 120 people a month are joining this Slack channel. And over time, we've really blossomed into something pretty incredible. [00:50:26] Erin: We have a few great days planned, and we cannot wait to dive in. [00:50:30] Phil: The conference is back again this year for the second time, on November 4th in sunny Anaheim, California. There's a few final tickets left if you haven't made use of your professional development budget yet, this is the perfect opportunity. [00:50:44] The conference is tech agnostic, so there's no vendor Kool Aid that you have to drink. Sessions are super practical and you walk away with the, uh, ideas and strategies instead theoretical concepts. And topics are super wide ranging. There's definitely something that you'll want to check out. You get to connect, learn, and grow among the best in the industry. [00:51:03] And you won't want to miss this incredible gathering right next to Disneyland. If you can't join in person, there's also a few virtual passes left if you're hearing this at the end of the podcast. So the entire event is going to be live streamed as well. So again, this November 4th. Go to marketingops. [00:51:18] com to secure your ticket. We also featured Justin Norris in episode 107 this year. And if you haven't checked out his podcast and newsletter, revops. fm, you won't be disappointed. Justin is a technology hipster with a polished voice of reason, and he's interviewed big names like Wes Coe, Jill Rowley, and John Miller, but he's also got a solo deep dive episodes, like how to create a knowledge base for marketing ops and how to use AI, a guide for marketers. [00:51:46] So, check out his show at rabops. fm. That's it for now folks, we'll catch you next week.