Pod Insights MarTech Podcast ™ // Marketing + Technology = Business Growth Bridging The Gap Between Your Marketing & Data Teams About this episode CEO and Co-Founder of GrowthLoop, Chris Sell, delves into bridging the gap between marketing and data teams. GrowthLoop, a leading composable customer data platform (CDP), enables marketers to create dynamic audience segments, orchestrate cross-channel journeys, and assess campaign performance through its advanced data cloud. Seamlessly integrating with top data warehouses, GrowthLoop is revolutionizing the connection between data cloud and growth platforms. Show NotesConnect With: Chris Sell: Website // LinkedInThe MarTech Podcast: Email // LinkedIn // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
Transcript 0:00 Speaker 00 The Martech Podcast is a proud member of the I Hear Everything Podcast Network. Looking to launch or scale your podcast? I Hear Everything delivers podcast production, growth, and monetization solutions that transform your words into profit. Ready to give your brand a voice? Then visit iHereEverything.com.
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0:53 Speaker 00 Welcome to the Martech Podcast, a member of the I Hear Everything Podcast Network. In this podcast, you'll hear the stories of world-class marketers that use technology to drive business results and achieve career success. Here's the host of the Martech Podcast, Benjamin Shapiro.
1:15 Speaker 04 Welcome to the Martech Podcast. I'm Benjamin Shapiro, the executive producer of the Martech Podcast, and today we've got a special episode for you, which is going to be guest hosted by Juan Mendoza, the author of the Martech Weekly Newsletter. Juan is a recovering martech consultant turned creator who writes an amazing weekly newsletter about the martech industry, and I'm thrilled to invite him and some of his friends to take the mic and share their knowledge with you, our loyal Martech Podcast listeners. All right, here's a special episode of the Martech Podcast, guest hosted by Juan Mendoza, the author of the Martech Weekly Newsletter.
1:52 Speaker 05 Well, hello, hello, martechers. My name is Juan Mendoza. I am your guest host on the Martech Podcast and also I'm from the Martech Weekly. Joining me today is Chris Sell, who is the co-founder and chief product officer at Growth Loop. Growth Loop is an awesome company, which is empowering marketers to build dynamic audience segments, orchestrate cross-channel journeys, and really evaluate campaign performance through its advanced data cloud. Growth Loop seamlessly integrates with the leading data warehouses and are really sort of driving a lot of thought leadership around what does sort of composable marketing technology architecture look like? So today, Chris and I are going to discuss bridging that gap between marketing and data teams.
2:33 Speaker 05 Okay, so here's my conversation with Chris Sell, the co-founder and chief product officer at Growth Loop. Chris, great to see you.
2:41 Speaker 06 Great to see you too, Juan. Thanks for having me.
2:43 Speaker 05 Let's dive in, and I want you to start with your story. Where did Growth Loop come from? How long have you guys been in market for? And what kind of problems are you trying to solve?
2:52 Speaker 06 Growth Loop, as you were mentioning, we call ourselves today a composable CDP, but essentially that's fancy speak for if I'm a marketer, I want to create an audience once in one tool, and I want to be able to use it in any of my marketing channels. It'd be nice if I didn't have to do it 15 times. We've gone beyond that to do journey orchestration as well in one tool and then use it in any of your marketing. But really where we started was much more humble beginnings. I actually worked at Google in 2011 with my co-founder, David Yostin, and we were actually on the marketing side. So I know we're going to get into this a little bit, but we saw firsthand the marketer's experience in trying to get a single campaign
3:34 Speaker 06 live in an enterprise environment. And the short version is, it's not easy. We went through, you'd file a JIRA ticket and say, hey, I'd really like to target my churned customers. You'd have a few meetings with the analysts about what exactly did you mean by churned customers? And then they would go and put it in their roadmap, write some SQL, pull some data, send me a CSV. I'd load it into the email tool, realize they didn't give me the personalization fields I needed. Back to them, do it all again. And we were like, wow, marketers have no agency in using their own data for targeting in their marketing. So that was really the genesis. We started to see that problem a lot as we were doing marketing ourselves. And so we were like, hey,
4:16 Speaker 06 what if we started a company where a marketer could self-service, describe their audience, get the sequel, and actually use it in any channel they wanted to. And that was really the start of Growth Loop.
4:27 Speaker 05 That's amazing. And that situation you just described is a situation that happens millions of times, which is marketers going to a data team and then asking for certain things so they can deliver on their growth plan. Obviously, they're trying to grow their company and they've got strategies to do that. But when the data team comes to them, they give them a flat file or a CSV, they go load it up. Man, that's like the worst probably situation that you could be in is loading up personalization fields from a CSV file. But it happens. It is crazy that in 2024, it still happens, but it does. And it happens a lot because those two worlds, they don't sync up. The incentives are different, the business teams are different, a lot of misalignment there. But I guess how does a CDP fit into that picture? And would Growth Loop, would you call yourself a CDP these days?
5:11 Speaker 05 Or how do you sort of frame the technology and how it's actually used in the business?
5:15 Speaker 06 Overall, we frame ourselves as really, our job is to be the bridge between the data team and the marketing team. If you take the situation you and I were just describing, where a marketing team goes and asks for a certain audience of customers, like churned customers, and gets a SQL query back in a flat file. Like, one, the marketer doesn't want to have five conversations about this, gives them no agency in doing their job. On the other side of it, the analyst, they didn't become an analyst so they could run SQL queries for flat files for email campaigns. They became an analyst to build out a data model that all the marketers could use in the company. That's what they want to do. They want to do data models, they want to do machine learning predictions, and they want to experiment with AI, not pull SQL queries for marketing.
5:57 Speaker 06 So you have two unhappy customers in that situation. So as a CDP, we do call ourselves a composable CDP. But the really, I think the job of a CDP and the job of Growth Loop is to say, look, data and Engineer, you create the data model once. You think about how do you want to model information about your customers? What do you want to predict about your customers? It's our job to make that all accessible and understandable for marketing so they self-serve. Because one, you don't want to be bothered by marketing. And two, marketing doesn't want to have to actually go to you every single time. They want to run and hit their growth targets. So our job is to be that UI bridge in between the two to allow the marketer to self-serve and on top of that data model.
6:42 Speaker 05 That makes sense. And increasingly, I think that the composable CDP trend is, I think, is trying to solve this. Like fundamentally, I think what it's trying to do is solve this problem, which is, how do you get the marketing and the data teams working way better? I think often your point is that manually sending files back and forth from each other, that ain't scalable. That does not work.
7:04 Speaker 06 Yeah.
7:04 Speaker 05 And there's so many assumptions in that. But having a platform where they can actually collaborate, where all of their core customer data and all the valuable data that they need is sort of in one place, but both parts of the business can have input into it. That is obviously a very clear thing that needs to happen in business. But it is interesting because I think when you take a step back and you think about composability, a lot of the discussions are about, yeah, let's just get data out of your data warehouse. Oh, cool. We can pull data out of AWS or Snowflake or BigQuery or whatever. And actually, I don't think that's the value. If you talk to a brand, I think they're like, yeah, that's fine. I mean, we can build an API into a CDP. No worries. It's not about that. It's actually about the harmony of data and marketing. It's actually how do you build the technology building blocks in your business or buy them
7:49 Speaker 05 in order to have that harmony so you don't have all these disjointed interactions with each team? So yeah, it's interesting, right? That's kind of, it might be that's what's going on, but I'm interested in how you think about the sort of role of composability in business right now.
8:02 Speaker 06 I think that's spot on. I think composability as a concept has talked way too much about the technical architecture of it, which the business doesn't care about. I think they much more care about what you're speaking about, which is the harmony between the teams. So why does composability matter to the business teams? On the data side, if I want my job not to be pulling SQL queries for a marketer, I want it to be defining a data model. Well, in my career, where do I want to be working? And where do I want to do that? I want to do it in AWS, Google Cloud, or Azure. I'm going to do it in the data clouds. That's where my career skillset wants to go. That's what I want to study. So that's the toolset I'd like to use to define that data model. And on the marketer's side, they're like, look, in order for me to get promoted,
8:45 Speaker 06 I need to hit growth targets, which means I need to take a number of shots on goal at this problem. I have a 20% LTV lift I got to hit next quarter in this category. I need to now run 20 experiments. Enable me to do that. And so all composability does is say, well, data team, stay in the data cloud. Keep using the tools you like. It just so happens it's Google Cloud AWS. Marketing team, you just use the data and use it in any marketing tool you want. And so it kind of creates harmony. And yes, the underlying technical architecture is somewhat interesting if you're a nerd about it, but most people don't care about that.
9:21 Speaker 05 So have you got a story, Chris, of say, a customer or a brand that you've worked with in the past that's really kind of nailed this picture where it's really they've been able to harmonize marketing and data teams under this sort of banner of composability and modern data and technology management?
9:35 Speaker 06 One of my favorites is we work closely with NASCAR. And the reason I love the example is they began their journey about four and a half years ago on the snowflake. That's what they chose as their data cloud. And they had a variety of data because as a fan of NASCAR, you purchase tickets. That comes through Ticketmaster. You buy apparel that comes through Fanatics and you buy concessions. You also have apps and online interactions with them. So they started thinking about consolidating all that data in the snowflake to get all the fan interaction data in one spot. And of course, then they get a BI tool to start to visualize that, understand the business. Better than they did before, but really their vision for it was to say like, great.
10:17 Speaker 06 If we're going to do this first party data strategy, how do I hook in not only marketing, but they actually went so far as to say, can we bring it to sales as well? One of the biggest things in sports is to say, can I sell ticket packages? That's what drives dollars. So when they started, they brought in not only their marketing teams, they brought in their, so essentially you had the data team on the one side deciding the data model. They actually have marketing teams for each of the 13 tracks around the United States. They have 13 different tracks and so they do marketing to get fans to come to the races at those tracks. And then they have sales reps that are selling tickets and ticket packages at those tracks. They brought each of the three stakeholders together and essentially what they did was they said, okay, I have Snowflake, I have my BI tool.
11:01 Speaker 06 They layered on Growth Loop as the composable CDP and our expressed purpose was to be the window for marketing and sales. So, marketing and sales started to use it for self-service to do ticket package sales. So, think about email, SMS, push notifications as communications and marketing. But as fans interact with those different marketing communications, you can develop a lead score and when the lead score hits a certain point, you actually start shooting opportunities into the CRM so sales is reaching out. So that was one of the first times where I saw an organization actually go from like, hey, first party data strategy and Snowflake is cool, but can we actually string it through the entire business organization to sell ticket
11:43 Speaker 06 packages and express business outcome and actually get them hovering off of the same data platform?
11:48 Speaker 05 That story, I think now is something I think is actually quite important for our audience to learn about, which is starting with use cases, like starting with really valuable use cases and the ones that make a lot of sense to your business. And then from there, you can go get your ask, you can get your funding for the tech you need and then the additional time that it takes to set it up and the line of the teams and everything. But it's really like, as you told that story, they were really trying to tackle one thing there and they actually did that and then that got them started into this, into this journey, which is interesting because you mentioned in that story also the data model. And what's quite interesting is that often the data science and often data engineering, these folks are the ones that are deciding the data models, like how the schemas are set out in like.
12:28 Speaker 06 And that's the pattern I see happen a ton is they do that for like six months and they miss the use case because they didn't bring in marketing and sales.
12:37 Speaker 05 Exactly. Yeah, we haven't got a data point for that, or it's sitting in some other table, or there's no golden key between these two different tables. So what are your thoughts on that? Like, how can the data analytics team bring marketing into those conversations when they're setting out their scheme and their data models?
12:51 Speaker 06 It is difficult. Like, a lot of people would say just bring marketing and sales in early. And that's not it, because I think where data teams get frustrated with marketing is they don't think marketing's specific enough about their needs. So, marketing will talk about different campaigns they want to run, but they don't know what data points actually go to those. So like, hey, I want to run a campaign to sell this new product. Okay, well, what data do you need to do that? That's where the conversation falls apart, because the data analyst knows the data, the marketer doesn't. You usually need somebody, it's usually a marketing analyst that can bridge the gap, that's hovering between the two worlds. So you'll have a data engineering team that's doing the hardcore stuff. You'll have the marketing team that's actually running the campaigns. And then you have the mediator,
13:34 Speaker 06 who is this marketing analyst that understands, because they actually measure the campaigns. Typically, this is the person measuring the outcome. So are we actually achieving our goal? That person, I have found, can be the interpreter between the groups. So you set up the session where, of course, you do bring in marketing early. You have a conversation about these use cases. Okay, you want to sell ticket packages. That's a key goal. Now let's talk about with the marketing analyst. He has the schema that's been given to him by data engineering. How do we interpret the two to tie them together to say, these five data points are what we need to run that first campaign? And that's, I call them threads. If you can make that thread, then you got value. And I think that marketing analyst plays that key role. One of my mentors and advisors, Brian Hempstead, he's the CIO
14:18 Speaker 06 at the Kansas City Royals, the Major League Baseball team.
14:22 Speaker 05 Who would have thought that Kansas City Royals would have a CIO managing their data architecture? It's pretty cool, eh?
14:28 Speaker 06 Moneyball has really sped things up in baseball. He basically always says, I don't want a customer three sixty. I want a customer seventy two and it better be the seventy two degrees that drive the most value. And I was like, that's pretty much it.
14:40 Speaker 05 And that's right. What we're seeing right now in industry is this rise of like the marketing operations, revenue operations professional, which has the skill set to have the technical discussions around schemas. They understand them. Whereas you talk to a marketing team like five years ago and they're like, what the hell's a schema? What are you even talking about? I just need email address and first name, last name. So I think that increasingly technical proficiency in these marketing operation roles is allowing that dialogue to happen in business. I think it's really exciting. I think we're kind of turning a corner here where we're finding these roles, which are technical marketers that can have the business discussion about ROI and the growth measures and the specific tactics they want to tackle, but it also can interface with the data and technology teams and talk and code. And like they know SQL, right? Like they can actually write SQL, pull their own queries. That's really exciting.
15:26 Speaker 05 Recently I did a pre keynote on this topic of the rise of marketing ops. And it's like, if you ever tried to make hollandaise sauce, beautiful eggs Benedict, have it for breakfast. You have the butter and you have the lemon juice. And if you try and mix those two together, you don't have a sauce. It just splits, right? It does, it's just, it's not, you don't even eat it, right? It's just disgusting. But the bit in the middle that you need is egg yolk, which emulsifies. It's a emulsifier that brings those two elements together. And I kind of use it as an analogy for thinking about data and marketing teams. And the bit in between, I think that emulsification, which is it brings those two together in harmony is that marketing ops role. And it's really fascinating to see that growth and trajectory of the profession.
16:02 Speaker 06 I love that metaphor, by the way, the emulsifier.
16:05 Speaker 05 The emulsifier, yeah. I used to work as a chef, so of course I'm going to think in food analogies and it makes people hungry too. I highly recommend not doing a keynote just before lunch and then having food analogies. It doesn't work. Okay, folks, so that wraps up this episode of the Martech Podcast. Thank you so much to Chris Sell. He's a co-founder and chief product officer of Growth Loop for joining us. We're going to have a lot of fun because tomorrow Chris is coming back to talk about something a bit different, which is transitioning to a first party data plan. So if you can't wait until our next episode, you'd like to learn more about Chris, you can find a link to his LinkedIn profile in our show notes, or you can visit his company website at growthloop.com.
16:45 Speaker 04 Okay, that wraps up this episode of the Martech Podcast. Thanks to our guest host, Juan Mendoza, the author of the Martech Weekly Newsletter. If you'd like to get in touch with Juan, you can find a link to his LinkedIn profile in our show notes, or you can contact him on Twitter. His handle is JuanMendoza, but it's spelled crazy pants. It's J U four N M E N D zero Z four, or it's a little easier to just visit his company's website, which is themartechweekly.com. Just one more link in our show notes I'd like to tell you about. If you didn't have a chance to take notes while you were listening to this podcast, head over to martechpod.com where we have summaries of all of our episodes and contact information for our guests. You can also subscribe to our weekly newsletters, and you can even send us your topic suggestions or your marketing questions, which we'll
17:29 Speaker 04 answer live on our show. Of course, you can always reach out on social media. Our handle is martechpod, M A R T E C H P O D, on LinkedIn, Twitter, Instagram, and Facebook, or you can contact me directly. My handle is Ben J. Shap, B E N J S H A P. And if you haven't subscribed yet, and you want a daily stream of marketing and technology knowledge in your podcast feed, we're going to publish an episode every day this year. So hit the subscribe button in your podcast app, and we'll be back in your feed tomorrow morning. All right, that's it for today. But until next time, my advice is to just focus on keeping your customers happy.
18:28 Speaker 00 Thanks for listening to the Martech Podcast, an I Hear Everything production. Looking to launch or scale a podcast like this one for your brand? Then visit iHearEverything.com.
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