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Customer Data Perspectives, Ep. 1: David Raab, The CDP Institute

What is a Customer Data Platform, and how does it help companies achieve their data goals? How does a CDP compare to CRMs? Data warehouses? DMPs? What do business leaders need to know today to find the right CDP for them? In this episode of Customer Data Perspectives, host Isaac Sacolick, of StarCIO, sits down with CDP Institute founder David Raab to answer all of your CDP questions.

Watch or listen to the full episode below. You can also tune in on Apple Podcasts, Spotify, YouTube, or wherever you choose to listen to your favorite shows.

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Read the Transcript

Sacolick: Hello, everyone, and welcome to this episode of the Customer Data Perspectives podcast and webinar. I am Isaac Sacolick, president of StarCIO. And in this podcast and webinar, we’re going to be talking through how different leaders think about, orchestrate, create demand, and deliver value from customer data platforms. Joining me today is David Raab. David is the founder of the CDP Institute. David, why don’t you tell us a little bit about yourself and a little bit about the Institute.

Raab: So the Institute is an organization whose mission is to educate the world about doing a better job with customer data. We were founded about five-and-a-half years ago, we deal primarily with customer data platforms, but really, our goal is to just help people do a better job because there’s so much to be done with customer data. We spend a lot of time on privacy, for example, which overlaps with CDPs, but it’s a separate issue. We spend a lot of time on international data. It’s just another complicated issue. So we just feel that there’s a great deal that people need to learn to serve their customers better, and customer data is the foundation of better customer experience.

Sacolick: That’s great. David, let’s start with a very basic one – I can’t think of anyone better to ask than yourself. What is a customer data platform? Why is it important? If you’re talking to a CEO, or to a board member – somebody who doesn’t understand all the bits and bites about how things connect: What is your elevator description of what these platforms aim to accomplish?

Raab: So it depends on the size of the elevator – how long the trip is. The three-word thing is that CDPs build profiles. And so we always say – it’s that CDPs build customer profiles, that’s what they do. They take the data from all of your systems that have customer data, and then a lot of systems that have customer data today. And they pull that data into one place into a unified profiles so you get a complete picture of each customer. Then they make that profile shareable by any system that needs it. So there’s a formal definition of CDP as packaged software that builds unified, persistent customer databases accessible to other systems. Now what about the 20th floor? So we can go through what all those things mean. But at the end of the day, it comes down to that they take that data from all the places and they put it in one place, and then they share it out to anybody who needs it. That’s what CDPs do.

Sacolick: Okay, so I have my CRM, I have my ERP, I have marketing systems, I’ve got a number of customer-facing applications – and CDPs are going to help me bring all the data into one place and create not just a profile, but kind of a living profile in terms of everything that they’re doing. And, all the interactions that are happening across these platforms. Do I have that right?

Raab: That’s right, the CDP will update itself as data flows in from the source systems. Some source systems will provide data as it occurs in real-time streams, some source systems themselves can only push the data into the CDP on a daily, or sometimes even less often, basis. But however frequently the data gets pushed, the CDP will update it. Again, sometimes absolutely, immediately. Sometimes, you might be lagging with minutes or hours, rarely more than a day. So you do have a current complete picture – and that’s not trivial. 

You know, people think, oh, it’s just a database. Well, getting that data and getting it updated, realizing that this email and that telephone and that computer are all the same person, as you unify the data – that’s not trivial. It’s just a lot of work that happens to build out those profiles. But then, the good news is that it’s there. It’s usable. So any other system that wants to use it doesn’t have to do the profile building for itself. Because the CDP has done that work. We talk about how the CDP is like a farmer, and the farmer does all the work to get the food, but it puts it on the shelf so the chef can just go into the store and grab the food that they need without worrying about how you grow it.

Sacolick: I love that analogy. Let’s maybe take it a step further, and maybe bring that elevator down a few levels and talk. I’m a technologist, I’m a data professional. I hear new platforms come and go every three to five years and now somebody is telling me about a customer data platform. What problems at the data level do CDPs address that they would relate to?

Raab: On a technical level, the main problem is that data integration problem. You have all these systems, all having a partial view of the customer. The CRM knows what happened in the CRM. The web personalization system knows what’s happened in web personalization. The call center knows what happened in the call center. But they’re all, you know, separate silos. So bringing that data together is really tricky. There’s that matching problem that I was just discussing, about recognizing that this is really the same customer regardless of whether they’re on the phone or on the app, or whatever. And then there’s also simply the data complexity problem that they all store data in different ways, and they may even have different terms for the same object.

So, you have to reconcile all that data and  pull it together in a format that’s consistent and usable and easy. And none of those other systems that are collecting the data are really designed to do that data unification — it’s a separate problem.

Now, if you’re an IT person, you’re saying, hey, let’s describe the data warehouse. Well, yeah, okay, it’s a lot like a data warehouse. Most data warehouses, however, traditionally are limited to structured data transactions, because they’re traditionally built for financial analysis at the end of the day. So the CDP is going to deal with unstructured and semi-structured data. Web behavior logs, in particular, is something that very few data warehouses are designed to support but native to a CDP because a lot of the data, of course, is web data today. So they’re gonna have a broader breadth of data than you would store in a traditional data warehouse, they’re also going to be more flexible, because they’re designed to bring in any kind of data.

And often, what you have is a new kind of data of pop up, either a new attribute that shows up on your website, because somebody added a feature and didn’t bother instrument it or to tell you about it, or a new data source. All of a sudden, we’re doing virtual reality or some crazy science fiction thing that turns out to be totally real, right? And now there’s an entire new source. Well, adding that stuff to a data warehouse, traditionally, is weeks, months of work that one attribute because they’re very carefully structured. Structured databases just take a lot of maintenance, and they’re great at what they do, but the CDP is designed to at least at least store all that data.

Now, there may still be some work to make it accessible to add it to the formal profiles that are available to the other system. But at least it’s there, it’s captured. And the CDP does have the capability to extract whatever bits and bytes it needs to be used by whoever needs that particular piece of information. So it’s a different sort of technical approach. And if we’re still talking to the imaginary IT person: Could they build it for themselves? Yeah, eventually, of course, they could. But it’s a lot easier to buy something that’s got all those things knit together than it is to buy the different pieces and do your own integration.

Sacolick: Yeah, David, that one thread I wanted to pull in with. You mentioned data warehouses, very structured, therefore, it’s got all the referential integrity, but, you know, a little bit more complex to update, a little bit more complex to store unstructured data. And you talk to a chief data officer or an architect, and they say, well, that’s why we have our data lake, or that’s why we have our data cloud, or our data fabric – all kinds of different technologies there. And I point this  – and I want to see if you have the same perspective –I point this to a build decision, right? I have my cloud platforms, I buy data management platforms, I have my data integration platforms, I have my master data platforms, I have all these tools. And you know, someone’s gonna say, Well, you know why shouldn’t I just build this – connect to all the systems, bring all the data together? That’s why I have all these systems. What’s your response to that? When is that a good idea, when is it not a good idea?

Raab: It may be a good idea if your systems are really doing most of what the CDP does, and we have this discussion in the industry a lot. And, obviously, the people who are selling the package software are saying, nobody should ever build anything. But you know, the reality is, I have seen situations where people have very robust, existing infrastructures, and adding what a CDP does was a relatively straightforward process. So there was a case to be made. But in most cases, there are very large gaps between what you have and what a CDP will do for you. 

So you have a data lake – we love data lakes. Data lakes are a great source of data for your CDP. It saves the developers having to go out and gather the data from all these systems because it’s already being dumped into the data lake. But that’s what data lakes are….they just take the data in the original format, and just puts it in a copy of it so the analysts can play with it without interrupting the operation of the original source system. 

Getting that data which is highly disorganized into that organized format other systems can use is a lot of work. Data lakes don’t do that work. Traditionally, data scientists go into the data lake, they dive around and scavenge and pick up the little bits that they need. And they come up to the surface, and then they go off into their little data scientist hut or boat, or wherever it is data scientists live. And they do the work to assemble that data and make it usable for that project. And the next guy dives in and [takes] different sets of data for his project. So they’re just diving around the data lake and pulling out the bits that they need for different projects. But they’re not creating an ongoing clean repository of data that other systems can use – that’s not what data lakes for. So the data lake is like a source. Many CDPs pull data out of a data lake, but it’s just the starting point for the CDP process of transforming that disorganized data lake data into these profiles that CDPs build that are then available. So it’s a very different kind of value.

Sacolick: Yeah, I think you actually introduced the concept earlier – what’s the size of your elevator, right? And you’ve probably can apply it to this question too. So if you have relatively clean data in your CRM, and maybe you’re only doing a limited amount of digital marketing on a couple of channels, and your e-commerce site has 100 SKUs to it – you know, relatively clean data. A few sources to pull it from, maybe you can pull it all together if you have a pretty good data engineering team to go do that. 

But the average enterprise has several CRMs acquisitions still trying to figure out how to pull ERPs. Together, they’re doing multi-channel marketing across different platforms, and they’re asking lots of questions about how to do cross sells, and upsells. Now we’re getting into that complexity factor.

But I also want to bring this question back to the business leader, who the CRM vendor, or the marketing automation vendor has sold them this concept that, “yeah, all your customer data should be in the CRM, or all your customer data should be in a marketing automation platform.” And now the CMO believes that and the CFO says: “Well, I already made an investment over here, why isn’t it just working in the platforms I already invested in?” So now maybe I’m trying to get a sponsorship going, and I have to answer to the CMO and the CFO around CRMs, and maybe marketing automation and maybe DMPs. What am I doing differently here to let them see there’s something different hat I’m focused on?

Raab: Actually, it’s funny. I was chatting with somebody the other day, who was talking about selling CRMs 20 years ago, and she was having the same debate we have now about CDPs: “Now, why do I need this thing?”  CRMs are built to do what CRMs are built to do, which is to put records in front of agents or salespeople so they can see what’s up with a customer. Very important function, very valuable function. They’re not built to pull in data from other systems, they’re able to capture call notes, basically, that’s what CRMs do. They don’t even usually have purchase transactions in the CRM. So CRMs aren’t built to unify data. Data management platforms are not built to pull in first-party data,  they’re built to manage cookies. Every one of those systems is very good at what it does, but what it was built for, it’s not what a CDP is built for. So there’s no reason to think that just because you invested in a DMP, or CRM – master data management doesn’t even claim that it’s gonna do what a CDP does. It’s like saying, Well, I have this great boat, I can’t fly it. But it’s not an airplane, it’s a boat, and why would you expect it to fly?

Sacolick: When you look at platforms, there’s three levels, right? There’s the level that the vendor is trying to sell you – the vision…Then there’s what it actually does well, and what it actually does well for the requirements that you’re throwing at it, which every company is a little bit different in that respect. And then there’s the reality – what you’re actually using it for, right? CRMs, account management, basic customer profiles in terms of who they are where they live, then how to contact them.Pipeline in terms of your sales pipeline. A lot of organizations splinter off of that quite a bit. And same thing with marketing automation, right? Certain channels, trying to reach prospects off of it. But again, this idea of a unified customer profile, and what’s happening on all these platforms, and how to start putting single panes of glass against that, I mean, these platforms were not originally designed to be able to do that. 

When we talked, you gave me a statement that I want to read off, that I was intrigued by. You ask executives, quote: “Is your data disconnected, and are there things you’d like to do, but you can’t because your data is disconnected? What are some of the problems and use cases these kinds of questions expose when you ask executives these questions?

Raab: Everybody has, of course, different pain points. So what you want to understand is what their pain points are. When we look at the classic CDP cases, one of them is letting the call center agent  see what somebody was just doing on the website. They were on the website, they were having a problem, and they called up and they said: “Hey, I have a question.” It’s really nice for the agent to see what they were just doing. So that means you’re getting data out of your website system into your call center system in real time – that’s not a natural connection. Those two systems have no natural reason to be connected. So, you could maybe link them up together. But it actually makes much more sense to throw that into a CDP. That’s a real-time requirement for the CDP. 

Sacolick: I mean, what’s the last three things I did before I engaged a chat bot or opened a ticket or called up? And that’s incredible context, right?

Raab: And, actually just being able to see what you know, the chat was. It’s not part of your CRM system, it’s a whole separate system. So how do you get the one to be available to the other? Is this a loyal customer, a gold-level customer? Are they a chronic complainer? All the stuff that’s probably not in the CRM,  should be in the CDP minutes. And actually, what often happens (just to get a little deeper in the weeds for those CIOs out there) is that because the CRM can’t support all the data, often, the integration opens a window within the CRM screen that pulls in the CDP data. It doesn’t actually take the data into the CRM database, it just shows that data on the screen so the agent can see it, because the CRM would blow up if you’re trying to throw all that data into it. So that’s one classic thing. 

A second classic thing is retargeting. Somebody goes to the website, you look at the famous pair of red shoes but don’t buy the famous pair of red shoes, and now you want to retarget them and that’s great. Retargeting is very nice and you push it out to whatever social media platform you’re going to advertise on whatever web advertisement you’re retargeting through, and then by golly, they come back and they do buy those red shoes. But of course, the retargeting system doesn’t know that. So it keeps pestering them about the damn shoes they already bought. Or, maybe they bought it in the store even. So the CDP captures that purchase. And then it can update the retargeting list again in near real time to get that person off of it so you don’t annoy them by trying to sell them something they’ve already been sold. 

And then the third classic use case is to combine my retail purchase history with my e-commerce purchase history, so I get a complete purchase history…so when I send out my email messages with offers, I can target the offers based on a complete customer’s use. In every one of those use cases, what they have in common is that they’re sharing data across systems. That’s really the point. That’s really the core use case for the CDP. Any place where you’re going to share data across systems. That’s something that does not happen yet. And that’s something that a CDP really helps you to do.

Sacolick: I mean, the two things that drive me nuts is, when I open a ticket with a SaaS platform, and I get the canned response – go clear your cache, or upgrade your browser – maybe they should know that I’m an ex CIO and a little bit more technical and probably need to go direct to level two. In their environment, maybe I’m telling them something that they don’t know. But you also gave the other classic use case. I did my 20 minutes of shopping, I bought the red shoes, and I don’t need to see more advertisements around it, and it was probably a gift. Right? And you know, maybe you should put that into the entire context by what you’re showing to me. So you see examples of companies doing it really, really well. And you see examples of companies doing brute force, very simple, heuristic ways of doing things like retargeting or doing simple presentations of data back to customer service. And it’s because you’re not bringing the data in real time, and letting people make some better decisions – people, or in some cases, algorithms – we’ll talk about algorithms too as a follow up. 

Let’s dive into industries a little bit. When I think about platforms, it could be CRM platforms, it could be content management, can even be e-commerce – there’s a spectrum of how they’re being used, and when they became mature in different industries. So what industries are ahead of the curve and using CDPs and how are they using them? And what are some of the laggard ones? What are their opportunities if they start using these platforms over the next few years?

Raab: A very interesting pattern of adoption. The first CDPs by and large were used in retail, and in  online media, so the Netflix and Amazons of the world where they were picking what news article, what book, or movie should I say should I recommend to you –  that kind of media. And in both of those industries, we have a large number of transactions where the transaction happens pretty much immediately; you buy it, or you don’t buy, click on it, you don’t click on it. And tickets are relatively small. So those are in industries where even a little improvement in targeting will immediately show investment returns…they also happen to be industries that tend to be relatively immature, and technically, not a lot of old stuff kicking around it. 

Then there was a second wave, which is things like telcos, and financial services, and transportation, the classic data-driven industries. We always used to talk about those guys, in addition to retail as being the ones that were most mature. And those are all industries where there’s a lot of customer data, where they spent a lot of investment over years in their customer bases. They had a better environment to begin with, so they weren’t quite feeling the same pain as retail in terms of not having any capabilities. We think that’s part of the reason that they were a little slower to develop that, again, just wasn’t quite as pressing a need. They also are industries  where you have larger ticket, fewer purchases, longer consideration cycles. So it’s a little harder to see the immediate impact of the CDP targeting than it whereas in retail, you can see that almost immediately. 

Now we’re seeing the third wave of industries, which are things like education, health care, even slower purchase cycles, bigger tickets, less frequent purchases, but they still have customers. They don’t usually call them customers, their constituents, their students or their patients. But whatever they are… they still want to give them a good experience. So there’s still things that they can do better if they have a CDP and have customer data all in one place. So those guys are sort of the current cutting edge, because even those guys were doing it for a couple of years now. But it’s been interesting to see just how that happened. And we think that it had to do with the purchase dynamics of the industry.

Sacolick: I’m really intrigued with the hospitals that are going to go from the last two years of what they’ve had to go through to, now recognizing the importance of technology, they’ve all accelerated putting telemedicine out there, they have to find different more configurable, customizable ways to work with patients. And that use case is screaming at me as like, put a CDP and start bringing your health records and start bringing in the device data that you can capture from from Apple’s from Google’s – bring that data in and make the patient smarter, make the doctor smarter in terms of what they’re prescribing to different types of people. It sounds like a perfect use case.

Raab: It’s a horribly complex environment, as you know. Obviously, of course, privacy issues, just electronic medical records have been a nightmare. So it’s not a trivial problem to sell. But as they get more customer oriented, more concerned about the patient experience and also the provider experience, they do begin to be much more interested in using a CDP. I think honestly as the other systems get better, the systems that collect the data in the first place get better, that the CDP has more input to work with. So it can do better things. Because of course, if you’re not capturing the data, originally, then the CDP does not need to work with. But now they are getting much better at capturing that with their portals, and that lets them take advantage of what a CDP can do.

Sacolick: Yeah, I think we’re, I agree, there’s a lot of complexity there. But what I’m saying is, it’s also a piqued interest on their radar – this is not something that’s we just gotta go back to the way we’re doing…before COVID. And they’re asking questions about how to be smarter with patients, they’re getting smarter about how they think about using data and analytics and how they’re using data that they don’t have access to – directly through mobile devices, and watches, and so forth. So I think it’s gonna be a very interesting time around that.

My next question for you is really, you know, to tap your consulting background, in terms of platforms, and, you know, now I’m at that stage where I’m, you know, doing a little bit of investigation, you know, I’m looking at what these different platforms can do, and want to understand time to value, ROI, ease of use privacy regulations. What are some of the things I should be looking for, when looking at these different platforms? 

Raab: The most important thing with any system, and this is tapping into my consulting background, is what do you want to do with it? That’s the biggest mistake that people make, is they don’t understand their requirements before they go off and they start looking at systems. And then of course, if you don’t know what your requirements are, then you’re gonna make a choice that’s based on something else. And that’s not going to be the right choice. Or if it is, it’s just dumb luck. 

So start with understanding what your use cases are, what shape your data is in, because it may be that your data is simply not clean enough or available enough to get any value from a CDP. So, what am I trying to do? What’s stopping you from doing it? And what’s the best way to close those gaps? Those are the three big questions that…I asked to my clients. And, if the answer to “why can I do it,” is I can’t connect data between systems, that’s what stopped me from achieving what I want to achieve…you probably need to see what kind of CDP you need. 

Well, industry experience is really important. Some CDPs, or general-purpose CDPs can do anything, and that’s great. They can legitimately do that. Other CDPs are specialized in particular industries and have lots of advantages in terms of data structures that are tailored to the industry and connectors to the standard industry, operational systems and so on. So, in the more complicated industries, like transportation, like telco, we actually do see more specialist CDPs, because those industries are so complicated. And they have such special requirements and the data volumes, and those two in particular are so huge that it makes sense to work with a specialist. 

But again, the big, major CDP vendors, typically the ones who focus on data management can handle those industries. But then I still go in and I look well, do you have people who understand the industry? You know, have you built out a custom data model for this industry, just using your technology, other things like that. So that kind of experience is certainly one of the critical things. Scalability is important, and scalability in terms of data volume, but also in terms of speed of processing, particularly as you get into real-time use cases – the ability to handle large volumes of simultaneous real-time transactions is something that everybody can do this specific technical requirements. You want to look at identity resolution, we don’t consider that to be something that a CDP must do, because there’s a lot of third-party resolution capability systems out there. So we’re perfectly happy for you to go out and integrate a third-party identity resolution solution, in part because those require third-party. In most cases, most companies don’t have enough data to do it properly, then the resolution is their own data. So how are they going to solve that problem? And they’re going to solve the chance to know about dealing with a lot of anonymous online visitors and you have a burning desire to identify them and that’s a very specialized capability. Some vendors have tools to do that. Make sure the vendor you have has the right tools to deal with the kinds of data that you’re dealing with.

Sacolick: So a lot of things to do discovery on, but I really liked where you started from. Because if I talk to the technologist or the data specialists, they’re gonna go forward and say, “well, you know, we need to figure out all the data sources, we got to figure out all the data quality issues, we’ve got to figure out how we’re going to join all this stuff.” But they start down that journey without asking, “what do you want to do with this thing once it’s there?” They don’t know the answer to that question. And if I start that discovery with the CMO, or, a head of strategy, or somebody who’s doing acquisitions, they’re gonna have a grand vision that hopefully gives me those requirements – what do you really want to do with this thing? They need to be educated on all the complexity it takes to get there, and how platforms and skills and processes get you there. And so you bring those two together, and you start looking right-left from benefit, and then left-right from where you’re starting from – and then you start looking at what your platform needs to do for you. So it’s a journey. 

Now, I’m going to tap the other side of what you do. You said, you don’t do consulting anymore. But you founded the CDP Institute. Why did you find it? What’s your goal with the Institute? How do you help companies through the Institute?

Raab: The origin story of the Institute is that I named the CDP category back in 2013. And there’s a blog post out there that I can point you to. And developed the concept, writing as an analyst and so on, over many years. And then by 2016, for some unknown reason, the CDP industry takes off, we don’t get out what was magical about 2016. In general, it was not that great a year, but CDPs. So then at that point, a couple of the vendors in the space came to me. So you know, we want to do something to promote the category.. So you want to work for a vendor, but happy to be vendor neutral and build the Institute. So that’s what the institute is – is we are a vendor neutral resource. And as I said earlier, it’s really just designed to help people do a better job educating the world about customer data. And often enough, that leads somebody to buy a CDP that, you know, the vendors are still willing to fund the Institute. So we are vendor funded to be perfectly clear about that is that we don’t have to charge for membership. So anybody can go to And use a vast library of resources that we have assembled for them that will make their CDP journey or their customer data journey that much easier.

Sacolick: I have a theory for you, I think 2016 is really the year digital transformation really started to pique people’s interest. And the heart of that is really around customer experience and more around growth at the end of the day than just changing your model, your operating model around technology. So digital transformation, changing the business model focusing on customer experience in digital products – all those things kind of point to, well, what are you doing with customer data? You got to start there. And so it doesn’t surprise me that that was an inflection year, but I’m talking to the expert, which is great. You’re listening and watching to Customer Data Perspectives. And, David, I have one final question for you before we close out your you are the expert, What’s your wish list easier button when it comes to gaining a competitive advantage with customer data? What’s still hard that you think needs to get easier for everybody?

Raab:I think that pulling together different channels is still hard. That data unification, identity resolution thing – it’s not a problem that goes away. Now with the loss of third party cookies on the advertising front, it becomes even harder not just to target people, which is what we think about when we hear about loss of third-party cookies, but also to measure results. This person saw the ad and this person made a purchase over here, are they the same person that we relied on cookies to tell us that, and now we’re not gonna have that? So dealing with that issue and CDPs are not a magic bullet for that problem or for any other problem for that matter. 

Of course, it’s easy to get excited about them in many ways, but they don’t solve all your problems. That problem in particular, it’s just a fundamental data problem and sometimes the signal is just not there. In which case there’s nothing you can do. But there are lots of things that you can do, so maybe if I had a second wish it’s not so much an easy button, but a reality button. Marketers…know the right way to measure the impact of their activity is to do a proper test where you send have set aside a control group and you send some people that treatment and you don’t send the other people that treatment, then you see how those two groups or behavior, and  hate to do it, it’s really hard. CDPs make that easier, I will say, to their credit, but you still have to do it, you still have to set up those tests. So I wish marketers would really just sort of bite the bullet on that stuff, use the technology, which makes that a lot easier than it used to be, to do those kinds of tests. Everything is online. So you can actually track who’s in which group and sort of control their experience to some extent. And take advantage. It’s the only way you’re really going to learn all the other metrics that we look at, open rates and things like that, they’re just vanity metrics, they don’t really tell you what you need to know. So I think, if I had a wish, I wish the marketers just sort of accept that and kind of do it right, which in the heart of hearts they know they need to do. And because they wouldn’t really learn, if they don’t do that they’re going to be chasing a lot of bad information and make a lot of bad decisions.

Sacolick: That’s a great answer. I mean, identity – we’ve been wrestling with this from a data and technology perspective for decades. You know, what’s your address? What’s the right zip code? What’s the right email address to reach people? Now, cookies are disappearing, the mobile platforms are locking things down. And the truth is, I have multiple identities, I have different ways that I navigate. And then we have this new thing coming down with Web3 with the Metaverse and what that’s going to bring to this equation. So hard problems are probably going to get harder. And your answer to that is, you know, marketers should, go back to the basics of doing A/B tests, doing experiments, learning from what you’re doing, put the extra effort in. And that’s a good way to use a platform like a CDP. 

David, thank you for joining me today on customer data perspectives. And thank you all for joining us for this episode. And looking forward to seeing you in future ones. Have a great day.

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