The speed at which your customer data moves is critical to your success in shaping the customer experience, and the interoperability between your CDP and your other critical martech systems can make the difference between a good and great experience. Today, we’re diving deep into the fast-evolving world of first-party data and customer data platforms with Justin DeBrabant, Chief Product Officer at ActionIQ.
About Justin DeBrabant
Justin is Chief Product Officer at ActionIQ. He spent his formative years building large distributed systems to support data science and analytics and holds a Ph.D. in Databases from Brown University where he researched the forefront of modern data systems. For the last 10+ years, he has been passionate about building data-driven products that help realize the value of customer data by delivering truly customer-centric experiences.
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Show Overview
Justin Debravant, Chief Product Officer at ActionIQ, highlighted the importance of adopting a first-party data strategy to differentiate and thrive in today’s competitive landscape. Here are key takeaways from the episode that reinforce the significance of this strategy:
- Transition to First-Party Data: As third-party cookies face obsolescence, brands are shifting their focus towards first-party data as their primary asset. This shift is driven by the necessity to rely on data that they own and control, rather than on increasingly unreliable third-party sources.
- Ownership of Customer Lifecycle: Customer Data Platforms (CDPs) have evolved to encompass the entire customer journey, from acquisition to retention. Brands are now utilizing CDPs to manage all facets of customer data in a unified platform, enhancing their ability to engage customers effectively.
- Data as a Competitive Asset: In the modern business landscape, data has become a critical asset that can provide a competitive edge. Justin emphasized that brands must effectively leverage their first-party data to meet customer needs and drive business growth, as products and services alone are no longer sufficient for differentiation.
- Strategic Data Investment: Brands must invest in strategies to collect and utilize first-party data effectively. This involves leveraging technologies like CDPs and establishing organizational capabilities and processes centered around data management.
- Competitive Imperative: Brands that fail to embrace a first-party data strategy risk falling behind in a rapidly evolving digital environment. The ability to harness first-party data for personalized customer experiences, targeted marketing campaigns, and data-driven decision-making is essential for maintaining competitiveness.
The podcast episode underscores the importance of embracing a first-party data strategy as a key differentiator in today’s business landscape. By prioritizing the collection, management, and utilization of first-party data, brands can enhance customer experiences, drive growth, and sustain a competitive advantage in an increasingly data-driven world.
Transcript
Greg Kihlstrom:
The speed at which your customer data moves is critical to your success in shaping the customer experience, and the interoperability between your CDP and other critical MarTech systems can make the difference between a good and a great experience. Today, we’re diving deep into the fast-evolving world of first-party data and customer data platforms with Justin DeBrabant, Chief Product Officer at ActionIQ. Justin, welcome to the show. Hey, Greg. Thanks for having me. Yeah, looking forward to talking about this with you. Why don’t we get started with you giving us an overview of your role as Chief Product Officer and what ActionIQ focuses on within the market?
Justin DeBrabant: Yeah. So yeah, I’m chief product officer at ActionIQ. I’ve actually been at the company since the beginning. So it’s been almost 10 years now as our first employee. Nice. So for better or worse, I’ve seen all the ups and downs of 10 years at an early stage startup and in the roller coaster that has been the CDP space. I oversee our product design, influence our engineering initiatives, and also a bit of our partnership strategy as it relates to kind of other ISVs in our ecosystem. And ActionIQ, we are, as you said, a customer data platform. That means a lot of different things to a lot of different people. I’m sure if we asked the room of a couple of people from our tech, if we asked three people, we’d get five different answers. So I would say for us, we’ve always defined it broadly as really trying to allow large enterprises, and we are enterprise focused, really tap into their first party data and use that to power better customer experiences. So we’re really about helping enterprises democratize data throughout the organization. A lot of data exists within different IT, infrastructure, systems, silos, applications, et cetera. But the teams that drive revenue, marketing, sales, service, support, et cetera, often don’t have access to that. And so really the vision for us is democratizing that access, helping them make use of that data, and then ultimately use that data to drive better customer experiences.
Greg Kihlstrom: Great, great. Well, yeah, let’s dive in here. We’re gonna definitely touch on that and a few things here. Wanted to start with one of the things I brought up in the intro, which is that critical need for speed with customer data and the importance there. And so why is merely fast processing of customer data not sufficient? Why is real time or maybe near real time data handling critical for things like personalization and better customer engagement?
Justin DeBrabant: I mean, I think it’s a balance. I would say that with all things data, it’s best to start at the use case and the value of the data within that context of that use case. Right. So think about it from a customer experience standpoint. If there is value in, you know, your own experience, let’s say you’re checking into a hotel brand or you just scanned into a concert. having kind of a real time interaction with the brand. Hey, welcome. You know, here’s some things you want to know. Here’s what your status gets you. Hey, we gave you this free upgrade. Here’s the lineup for the concert venue. All those things make a ton of sense in real time and having access to that kind of full holistic customer profile and then being able to activate it in real time is truly critical, right? But not every customer experience is that. I mean, I hear a lot of times the example of you know, a real-time experience being something like an abandoned cart or an abandoned browse real-time trigger, right? If you think about it truly in the context of real-time, imagine if you added something to your cart, you went to a different tab and then immediately got a text message to say, hey, come back, you forgot this in your cart and here’s 20% off. That’s not a great experience and the brand is giving away 20% for potentially nothing. Maybe they just got interrupted by an email. So, I think it’s best to think about what’s the right customer experience and then understand what are the data latency requirements that are necessary to drive that customer experience. And it’s not always about, you know, sub-second, millisecond, 200 millisecond processing. It’s about understanding what’s actually going to drive the right experience and then mapping that latency to that.
Greg Kihlstrom: Yeah. And so given that, I mean, you gave a few examples there of, you know, when it makes sense, as well as when it might not make sense. But, you know, do you think that brands are kind of held back in being able to deliver a great customer experience because they’re thinking real-time isn’t possible? In other words, how can real-time data unlock things that maybe they’re not thinking about yet?
Justin DeBrabant: Yeah, I think usually, so what happens is there’s so many internal hops and processes for data that when When marketers talk about the lack of real time data, what they really mean is that by the time they get access to the data, it’s 24 to 48 hours old. Right. Yeah. And that’s that’s for most use cases. Right. You’ve missed the mark at that point. You’ve missed that moment to drive a valuable customer experience. And why is that right? Because the data needs to be collected and needs to be governed, needs to be routed to internal systems and maybe needs to be cleansed. Maybe you need to do identity resolution. Maybe you need to kind of stitch it together with other data sources. Maybe there’s some batch job that runs to dump the data into the warehouse and then a view gets created and then marketing is able to access it from there. And that whole process, historically, that’s how data warehouses ran, right? It was like a 24 hour delay, a nightly batch process. And a lot of marketers are dealing with that reality. And then once the data is there within 48 hours, they can’t even access it, right? Like they don’t have the SQL skills to go and directly access it. So they file a ticket and their team pulls them a list. And at that point, more days have gone by. And the reality is when we talk to large enterprises, their latency is usually on the order of days to weeks by the time they’re able to execute on kind of new campaign ideas with the data that’s available. Right. And that’s completely insufficient. Right. So I think that when marketers talk about real time they don’t always mean kind of millisecond latency. Really what they mean is more direct access to data as it’s generated and the ability to do that themselves. Now sometimes it does require you know 200 milliseconds of latency because you’re trying to drive, you know, an in-person experience or a web experience. They clicked on this, make sure the next page that they view is personalized based on that. That makes a ton of sense and requires real time data. But for, you know, a lot of the rest of the marketing strategies, you don’t need that level of latency, but you do need access to data that is fresh, that is up to date and through interfaces and applications that give the non-technical marketer or revenue teams, the ability to ask questions directly, make use of that data, and then activate it.
Greg Kihlstrom: So that access issue, and I work with plenty of enterprise orgs and access, and the delay of days, if not weeks, it’s real. I think a lot of people listening to this are probably living through that too. In addition to the speed at which the data is processed, you touched on this as well, but the concept of interoperability, just access to the data, whether that’s between systems or between systems and people and all of the above. From your perspective, could you define, you know, what do you mean by interoperability and, you know, how do you look at that in the context of customer data platforms?
Justin DeBrabant: Yeah, that’s a great question. So maybe take a step back and think about where a CDP sits in the stack and be a little bit more specific than that. At least kind of the original vision of the CDP was that the data exists within these infrastructure, these applications, but it was kind of all over the place, right? There wasn’t a consistent customer 360. So the CDP would be the kind of unifying infrastructure layer across those different sources of data, maybe augmenting with its own tag or SDK data as well, right? And then sit in an agnostic way across the different downstream customer experience channels, right? So being able to push to email, mobile, paid media, owned and non-owned channels, customer support, CRM systems, whatever it was, that full CX stack. Obviously, CDPs are not those systems. They’re not usually doing that last mile delivery, and they’re not necessarily owning or the source of truth of the data. So they kind of sit, if you think about it, really at the center of a complex data stack underneath and a complex channel stack above that, right? And, you know, there is a POV that the CDPs should really own the data, really pull it into their infrastructure, their data cloud, put it in their data model, and that they should also own the channels. And that’s the kind of full stack approach like an Adobe or a Salesforce would take. Right. You have to be all in on that stack. You’re not going to be able to support kind of channels outside of that ecosystem. It really exists inside that little bubble. The other approach is this best of breed stack which is we what we argue for where you know regardless of the data source whether we’re the tag or not whether it’s your you know, we’re managing the data or it’s in your cloud data warehouse, we need to complement kind of the existing investments that are there. And then same thing on the channel side. We don’t do that last mile delivery. We integrate with whatever ESP, whether it be the Adobe stack or Salesforce stack or independent, whether it be mobile push integrates across the paid media ecosystem. And then there’s nuances to that, right? Like what about identity? Are CDPs the source of truth for identity or are they stitching together kind of different identities, different assets, either from the first party data or also from third party data and augmenting with different forms of identity. And so usually, again, there’s no hard and fast definition. And if you ask different vendors in the space, they’d probably disagree. But for me, it’s really coming in. And I think also it’s a reflection of the fact that we work in the enterprises. We’re not going to be the all in stack for everybody. Right. So we need to come in. and really complement the existing investments that the brand has made. On the data side, that means if they have a centralized Cloud Data Warehouse, fantastic. We should be able to complement that. That’s this, quote-unquote, composable architecture, where we sit on top of their Cloud Data Warehouse, we federate queries down, we don’t need to copy or move the data into our ecosystem, we’re essentially leveraging exactly what they have. If they don’t have that, right, if they haven’t consolidated all the data, or some data is not consolidated, then we should be able to manage that portion of the data. And really, by interoperability across those different ecosystems, we can be kind of a stable interface to the business where they might be querying data across their cloud data warehouse, or data that lives in ActionIQ, and they’re building audiences in both, or journeys in both, and they don’t need to know or care where the data lives. For us, that’s really what data interoperability is. And then on the channel side, it’s integrating with any and all downstream channels, right? We integrate with 300 plus channels. You pick your own stack, you pick your favorite ESP, mobile, paid media, et cetera, and we’ll integrate down that, across that stack. So for us, that’s what interoperability means. It means really adapting what our deployment and our architecture is to where it adds the most value in the client’s existing stack, as opposed to kind of starting a clean sheet of white paper and drawing things from scratch.
Greg Kihlstrom: Yeah, yeah. So there’s a few things you touched on there that I want to get back to. But starting, I want to get back to kind of the internal operational part of things. But I wanted to first talk a little bit about, you mentioned the stitching customer identities together. And I do think that’s a big consideration for, you know, how customers are thinking about buying a CDP and implementing a CDP. So, you know, you mentioned there’s a few different ways of thinking with that. What are the considerations that an enterprise should be keeping in mind when they’re, I guess, when they’re thinking about, you know, what should be stitching those together? And, you know, I think you touched on some of it, but, you know, just to kind of double click on that a little bit.
Justin DeBrabant: Yeah, so I would say one is understand what the use cases are for the identity you’re trying to create or define. So, you know, if it’s a direct mail or email based use case, then you need to take, you know, one approach to identity. If it’s paid media and you’re trying to do kind of anonymous retargeting or reactivation of users to your site who didn’t authenticate, then it’s a completely different form of identity because you’re activating that across different channels. Now, I’m not saying they can’t all be stitched together into one kind of ecosystem profile. But the reality is, is identity is not a singularity. You need to have different notions of identity. They’re going to be activated across different use cases in different channels. So one is, again, start with the understanding around that use case. And then from there, I think you need to work your way back and understand, OK, do I have the data that I need to support that notion of identity? And if not, do I need to augment that with different sources of identity or create kind of a more probabilistic view of identity based on the data that I do have? So as an example, if you’re trying to do authenticated user email-based targeting, and you’re integrating data from multiple CRM systems that hasn’t been integrated before, which is a very common use case, then you need to probably do some form of probabilistic identity resolution. Take the first name, last name, physical address, phone number, email address, assign some weight, do some clustering, create a golden profile, and define that authenticated identity from there. CDPs did not invent this. This has been part of MDM solutions for decades now. I think CDPs put a lot of fancy marketing material on customer 360 and identity resolution, but the reality is nothing has really changed there in the last 15 years. They’ve probably done it more specific to customer data and a use case than MDMs have historically. And there was a niche market for that. But, you know, it’s really kind of standard probabilistic identity resolution. The kind of other angle is on the paid media side, right? So let’s say you’re at anonymous data, you have devices, you have maids that you’re collecting from your users on your site or maybe your mobile app. There, the goal is maximizing addressability and reach for the campaigns that you’re going to run across different paid media systems. To do that, you might need to augment with third party data, right? Be able to append, you know, different device IDs into kind of a singular identity based on some third party graph that you’re integrating into your ecosystem or augmenting kind of the the ID that you have with different IDs that can be activated across the different paid media ecosystems. So you might need to think about augmenting what you have in your first party data if your goal is activation across a digital ecosystem where you’re trying to maximize for reach and addressability. And the reality is you probably have to do both of these things, right? It’s not either or, it’s just understanding what the use cases are and then backing into the capabilities that you would need to support them.
Greg Kihlstrom: Yeah, and I think all the more reason for the argument to have something that’s a bit more flexible and and able to adapt. And I mean, that kind of brings me to the next thing I wanted to talk about, which was the interoperability. I mean, is it safe to say, is composability and interoperability, are there nuances to those definitions? Are we talking about the same thing here? How do you look at that?
Justin DeBrabant: Yeah, I think interoperability is probably a little bit broader, but they’re the same flavor, same idea, right? When we talk about composable, what we mean primarily is around the storage and the compute. Like, where does the data live, right? is the data in the cloud data warehouse and we’re essentially pushing queries down to one or more cloud data warehouses and never copying the data back. Or does it live within the CDP and you know there’s a copy of the data and that customer 360 is defined within the CDP. Which was the original you know architecture for a CDP. I think in part because nobody had mature cloud data warehouses right. Ten years ago when the category started There wasn’t, hey, we have all our data in Snowflake or BigQuery or Redshift. That just didn’t exist. And now there’s a critical massive adoption of those systems where you go into a large enterprise and say, yeah, we’ve already defined our customer 360. It’s all sitting here in this cloud data warehouse. why would I want to copy it into your infrastructure? And I think that’s a good question to ask. So for us, composability, and I think generally speaking in the CDP space, composability is really around kind of the data and the storage and is starting to become about the identity as well and being able to plug in different identity spines or third party data into that kind of customer 360 versus kind of having something out of the box yourself. And interoperability, I would say, is a much broader kind of architectural principle about working seamlessly across the stack. And I think interoperability applies into how we integrate with the channel ecosystem downstream, right? Like we’re interoperable across an Adobe, a Salesforce, and an Oracle stack. And for a lot of our clients, we actually are integrating with some channels from each of them, and we’re interoperable across them.
Greg Kihlstrom: So I wanted to talk a little bit about what’s coming down, some future trends and stuff. But first I wanted to mention, it’s interesting, Gartner just released its first quadrant on CDPs. As you mentioned, CDPs have been around for a bit, a little over a decade here. So nothing like taking the time to get it right, right? But it took them a while and probably for some of the reasons you mentioned earlier, which is the definition can be a little nebulous depending on who you ask. But I do have to say, by the way, congrats on your placement as a visionary on that quadrant. So that’s a huge achievement. We’re very excited about that. Yeah, yeah. And it’s great to be able to see you know, how the different players are, you know, are stacking up, so to speak, in that, in that framework, you know, from your perspective, and, you know, having been doing this for a bit, a little over a decade here, is the CDP market too fragmented to have a quadrant? You know, is that one of the reasons why it took so long? Or, you know, do you see is further consolidation coming down the pike or either even, you know, further fragmentation?
Justin DeBrabant: Yeah. So I think there’s kind of a chicken or the egg situation here. Like is the category defined and Gartner and Forrester come like defined in practice, then Gartner and Forrester come and kind of put their rubber stamp on it. Or should they be the ones really helping define the category and shaping it? And, you know, I think that for a long time, the lack of you know, magic quadrants or waves or kind of real strong opinions on the CDP space from those vendors, from those analysts, I think did the space a disservice. I think there were a couple of reasons for that. I could take a more pessimistic view to this, but I’ll take kind of a, I’ll take, you know, a more practical view where I think this was a tricky space because it was between data and infrastructure and kind of IT systems and the marketing stack. Right. And traditionally, the big analysts have had kind of focus in one or the other, but it’s tricky to have kind of a POV across both of those. Right. And so it kind of created this kind of who owns this situation and even in the market. Right. Like our buyers were CMOs for the first five or six years exclusively. And increasingly, most of the most of our new logos, our new pipeline is being driven by CIOs. in collaboration with CMOs, but CEOs are increasingly the buyer. So we’ve seen a shift in the market. I think that kind of confusion probably prolonged the uncertainty with the analysts. The other thing I’d say is this has been a hot space for a while, and there were some unique, shall we say, macro conditions that I think prolonged some of that confusion. I mean, you had things were really starting to heat up going into 2019 and 2020, and then you had the pandemic. What did that do? It created a surge in investments in digital, right? Like a lot of has been written about how that probably accelerated the shift to digital for these brick and mortar brands, especially by at least a decade. Yeah. So you saw a ton of money rushing into this space, which was great. But then because of that, you saw a lot of companies that were in, you know, dead or shrinking categories kind of pivoting over to the CDP space and trying to claim a portion of that. Most of these companies are VC backed. There was a ton of loose money in 2021. You know, people were fundraising at ridiculous revenue multiples that were never sustainable. These were never going to be real businesses, but they raised a ton of money. What did they do with that money? They pumped a bunch of money into go to market, you know, paid for marketing, paid for sales teams that created confusion, even around products that were never going to last or that were only solving a kind of a small niche problem within the space. And now I think you’re seeing the reconciliation of all that, right? The money is much tighter. You really need to be there. There’s also a lot of efforts within brands to kind of consolidate costs consolidate and reconcile their their tech stack. So if you were a point solution CDP you’re often now getting replaced by a much broader solution which we’re doing more and more of. And so you’re starting to see kind of that the market I think consolidates after that expansion period and now You know, it’s great. Gardner and Forrester are on board saying this is the market. I wish it had happened a little bit sooner. But I do think that we’re at the point now where things are going to become a lot less fragmented. I think a number of companies that are even in the quadrant now are companies that won’t last another year or two. And you’re going to see, you know, in two, three years, a much cleaner picture of the space.
Greg Kihlstrom: Yeah, got it. And so, you know, there’s many reasons to adopt a CDP, but one of the big reasons that kind of prompts the conversation is just this need for the first-party data strategy, deprecation of third-party cookies. Eventually, it’s actually going to happen. We’ve been talking about it for, it feels like a decade, but we’ve been talking about it for at least a few years now, and it will eventually happen. But, you know, what other changes do you see that are impacting, whether it’s investment decisions in a CDP, in the enterprise, or just that are affecting some of the challenges that CDPs can help solve.
Justin DeBrabant: Yeah, and you know what’s crazy about the third-party cookie thing is that in the early years of the CDP space, CDPs didn’t really do any of that. I mean, you had authenticated data and, you know, hashed emails you could activate to the paid media channels, but you always kind of had a DMP on one side for the acquisition, you know, use cases fueled entirely by cheap cookies and third party data. And then you had the CDP for the kind of retention focus use cases. And we used to describe these kind of as two pillars of that customer experience stack. And then, you know, the rug got ripped out of the DNP side. All those products are dead. I don’t think people have realized how quick of a shift that was from how critical those were. You know, they’re all dead or deprecated. And now CDPs have really transitioned to owning that full customer lifecycle in the last two or three years. I think we were, you know, one of the early kind of people realizing that a CDP should do more than just the retention side of things. Yeah. So it’s funny, because that really wasn’t even on the radar five or six years ago. I mean, it was discussed, but it didn’t seem practical. And now it’s just become a given that CDPs inherit all the use cases from DMPs. And it makes sense, though, right? DMPs were about third party data. CDPs are about first party data. What’s really happening with the death of the cookie is brands need to focus on first party data. That’s what they have. Right. Third party data is not as plentiful. It’s not as cheap. You can augment it in very specific places. But without cookies it’s a massive reduction. Right. And so you need to focus on your first party data strategy and CDPs are that. So it makes a ton of sense. It’s just it happened very quickly. You know and back to the question what are maybe some of the other trends that we’re seeing. You know, the investments in the cloud data warehouses is a big one, right? I think that this whole composable architecture creates the opportunity to start to deploy CDPs in a much more nimble and agile way. You know, you can very quickly set up a CDP on top of your cloud data warehouse, connect to a few tables. and provide the business with an interface, we’re doing these deployments within a day, honestly. And so, you know, being able to test and iterate and POC these new technologies that quickly, get the marketing teams excited, get the creative juices flowing, generate new use cases, you get that flywheel turning a lot easier than, you know, a three-month deployment that costs hundreds of thousands and kind of data ETL work you know stitching together all these different assets etc. So I think it’s creating opportunities to accelerate that as well.
Greg Kihlstrom: Yeah. Well, Justin, thanks so much for joining today. One last question before we wrap up. You’ve given a lot of great advice and insights already, but you know, if there’s one thing kind of touching on the last point you were making, you know, if there’s one thing that our listeners could do to kind of try to navigate this, this limbo state pre third party cookie deprecation, you know, what, what should they be thinking about doing today?
Justin DeBrabant: And they just need to embrace the first party data strategy. You know it’s everybody’s a data company whether they want to realize it or not. Products and services are good but not sufficient to really differentiate in the modern world. Right. You need data. Data is going to be your asset and you need to build up the not only the systems and processes, but also the organizational muscle around making use of that data. And the CDP is, you know, a technology enabler to that, but it’s not the only thing that needs to happen. So again, like, you know, I’ve sat in conversations where people just throw up their hands and they say, well, we don’t have good first party data, so we can’t do that. And it’s like, well, you need to start with what you have, but you also need to invest in strategies to collecting better first party data and investing in that data strategy because I truly believe that brands that aren’t now are going to be quickly left behind.
