#100 ROI positive MarTech: is it possible? (with Glenn Vanderlinden @ Human37)

The Measure Pod
The Measure Pod
#100 ROI positive MarTech: is it possible? (with Glenn Vanderlinden @ Human37)

In this week’s episode of The Measure Pod we spoke with Glenn Vanderlinden, co-founder of Human37. We spoke about CDP implementations, and whether or not they are ROI positive. We also discuss the composable CDP landscape as a whole and the challenges and use cases for data teams.

Show note links:

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Quotes of the Episode:

  1. “…The customer journey is transversal regardless of which department they’re encountering or interacting with. They literally don’t give a damn.” – Glenn
  2. “…It’s like buying a Lamborghini to drop your children to school. It’s a very expensive solution to a very trivial problem.” – Bhav


*Please note the following transcript is AI generated.

Intro | Topic | Rapid fire


[00:00:00] Dan: Welcome back to The Measure Pod. We have just finished a conversation with Glenn Vanderlinden, and this is a hundred episodes, so this is it. We’ve wrapped up a hundred episodes. We did promise, I say promise, but we did announce that this is Dara’s last ever episode but we managed to fit one more in.

[00:00:30] Dan: So apologies, you’ve got to listen to Dara for one last episode. His final episode will be next week, episode 101. But, I just wanted to call out Rick Dronkers. If you’re listening, this is all your fault. The reason we’re speaking to Glenn and, talking about CDPs once again, and understanding the ROI positiveness of the marketing technology, tech stacks and CDPs, I thought it was fascinating.

[00:00:50] Dan: And we’ve had a bit of a CDP chat binge in the last couple of episodes, and I’ve really thoroughly enjoyed it and found, you know, all these different perspectives and opinions to be fascinating and. I don’t know, what do you guys think? Have you come out of it knowing exactly how to do an ROI positive CDP or where are you at with all this?

[00:01:06] Bhav: I think I’ve come out of it more confused than I went in. I’m also questioning my understanding of CDPs now, if I’m being completely honest with you. I thought I understood them quite well before I started these conversations and now it feels like I’ve forgotten. But no, I thought it was a great conversation with Glenn, he’s very knowledgeable.

[00:01:23] Bhav: I think I love the fact that this conversation was triggered off the back of an interaction that happened on LinkedIn, like, like, what a wonderful way to keep the community involved in what we talk about. And I like the fact that we were able to trigger Glenn during this conversation with viewpoints and he was, you know, he was great. He loved it. He loved it. 

[00:01:42] Dan: So, Glenn, thanks for answering all of the difficult questions. So this was a post on LinkedIn from Evan Rollins. If you’re listening, thank you. you basically called out Rick Drunkers for what he said about never seeing an ROI positive CDP and then that spurred this conversation, which led into this episode.

[00:02:00] Dara: Yeah, I don’t have too much to add. I think I can, I can, echo a little bit what you said, Bhav, about feeling slightly more confused. I think I’ve gone on a journey with all these CDP episodes. I felt like at first I learned and then I feel like I became a bit more confused as it went on. So I’m not sure where I am now. I think I’m probably further along than I was before we started talking to them, but also more confused than I was maybe an episode or two ago, but that’s no fault of Glenn’s at all. I thought he was great and really loved listening to him talking about his experiences, but yeah I’m not sure how confused or unconfused I am about CDPs and whether actually they can be ROI positive.

[00:02:42] Dan: Well, you’re going to have to listen to the episode to find out all those secrets that we’re being very vague and mysterious about. Right. The last thing to mention is that, like I said, this is Dara’s penultimate episode. Thank you so much, Dara. you’ve got one more from us next week and then we’re taking a little break until we spin up the next series and figure out everything along those lines that we’ve got. Again, in the show notes, click the link in whatever app you’re listening to, you’ll get links to the crap Slack community. There’s links to everything that Glenn mentions. 

[00:03:08] Dan: And we talk about including links to CDPs that he mentions and loads of resources around what the hell a CDP is that hopefully should clear some bits up if our conversation doesn’t help, but I’m sure it will. I think the last thing is to say, enjoy the episode.

[00:03:23] Dan: So I want to welcome Glenn to the show, Glenn, thanks for joining us we’ve actually been talking about doing this for some time, before I start, asking a hundred questions and opening it up and going into the topic of the conversation, which our audience probably know already by the title of this episode.

[00:03:38] Dan: I just want to start by asking you to introduce yourself. Who are you? How have you found your way into the world of analytics? What’s the backstory or origin story for yourself? 

[00:03:48] Glenn: So my name is Glenn Vanderlinden. I’m based out of Brussels, Belgium, and I’m the co founder of a company called Human 37. We do customer data strategy, data operations, all kinds of things that we’ll talk about later. How did I find my way into the industry? Very funny. I studied business at university, which is basically the, the, the thing you study when you have no idea what you actually want to do in life. So that’s basically what I did.

[00:04:13] Glenn: And then I made things worse, sorry, because I started working at Deloitte, which is basically the place I go or people go when they don’t really know what they actually want to do either. So I spent a year and a half there, figuring out what I wanted to figure out. I learned a bunch of things, but I also learned that it’s not my place or not my environment.

[00:04:32] Glenn: And so I shifted to a different type of organisation, digital advertising agency and analytics agency where I spent eight years. growing to the ranks, working with a bunch of very smart, very interesting people. and at some point we were leading the agency, but we wanted to do something on our own.

[00:04:48] Glenn: Or at some point, like we were in our early thirties in a very good position, but we wanted to do something for ourselves and go way deeper in analytics. And then that’s basically how human 37 started. 


[00:04:59] Dan: Well, welcome to the show, Glenn. And I just have a quick question. How did you get the name human 37? I, what did that come from?

[00:05:04] Bhav: I was just about to ask about the 37, so I’m glad you brought it up, Dan. Thank you. 

[00:05:08] Glenn: Yeah, human 37. Like when you start a company, you want the name to be epic and it leads you to like all kinds of Philosophical or far fetched things and our story is basically that one morning. I was listening to a podcast.

[00:05:21] Glenn: I seen the episode or the Netflix documentary on AlphaGo basically AlphaGo versus Lee Sedol, the game of Go where machine beats humans for the very first time in what was supposed to be the most complex game, in human, for humankind or for machines to understand at least. And so I was listening to this podcast and, at some point they made a notion or they mentioned move 37 because it’s actually a move 37 that they do this move or that AlphaGo does this move.

[00:05:49] Glenn: That is basically counterintuitive, but actually makes a lot of sense only because the machine was able to absorb so much data and to predict as much in the future as it possibly could. And so as of move 37, like that’s the move that defines that game. And it basically shows how machines can actually beat people in the game of go.

[00:06:07] Glenn: And for us, it’s kind of, it symbolises, let’s say the possibility of what you can do with data. To understand way more, to do way more, and that we need machines for that. But we kept human instead of Nour37, we kept human37 because we still believe that humans have a strategic piece in there and that it’s not only up to the machine, it’s how we use the tools and how we use the data as humans in order to get something.

[00:06:29] Bhav: I like you already, that’s one of my favourite documentaries ever. And it’s interesting, you focused on move 37. I don’t want to give too much away if you haven’t seen it, but there was also, from the Grandmaster of Go, he made what they called the God Move. And when he did the God Move, the ranking dropped for AlphaGo, and everyone was like, why did you make that move?

[00:06:49] Bhav: And the Grandmaster was like, that was the only move I could see. So it was the only game the Grandmaster won, and it was what they, and they called it the God Move. So maybe if you’ve seen the whole document, maybe you would have named yourself like human God or something. 

[00:07:04] Dan: Oh God. That would have been very bad. There’s, there’s, there’s me kind of making up like a, like a, trying to understand the 37. I just thought maybe it’s like the meaning of life is 42 and you’re just five steps ahead or something like that. Yeah. Yeah. The rest of the universe. Right. Exactly. Well, this is fascinating, but I’m really keen to jump into our conversation.

[00:07:26] Dan: And I just want to kind of set this up and talk about how it came about. So, a couple of episodes ago, if you are long time listeners of this show, we know we had Rick Dronkers on, on episode number 93, and he came on to talk to us again, actually, it was his second time on to talk about GA4, the CDP you never knew you had.

[00:07:43] Dan: And just, we kind of riffed a bit on that conversation around how Google’s positioning or repositioning Google Analytics to be their kind of Pseudo CDP environment for the Google stack going forward. And not that that’s untrue, but, that’s something that’s kind of taking form and shape over many, many years.

[00:07:59] Dan: What I was interested to see off the back of that is that someone, one of our listeners, picked up one of the statements from Rick on that episode. And I’ll quote him from the episode. He said, I’ve never seen an ROI positive CDP implementation. And that seemed to rustle some feathers, with a lot of people, but including yourself, Glenn, whereby you basically called him out saying I’m paraphrasing, but you must be doing something wrong because I can, I have seen some ROI positive implementations.

[00:08:25] Dan: So I just wanted to start there to say that, thank you, Rick for kind of, rusting feathers enough to put us in touch. And, I suppose we’ll start there. So. What, what drove you to jump in and to call Rick out on his statement that there’s no such thing as an ROI positive CDP implementation?

[00:08:40] Glenn: Yeah, this is to start as I don’t remember exactly what I said, but I think you’re very, you’re, it’s probably a very liberal interpretation of what you’re using now, but it might be, it might be, have been along those lines. The reason why I kind of reacted is because, even though I see where, where it comes from, the statement of it’s hard to, let’s say it’s hard to have an ROI positive CDP implementation.

[00:09:02] Glenn: For me, it ties mostly back to how you define use cases and how you start with such a project, right? Typically, what we see is that the outcome of a. CDP implementation is the or to obtain a customer 360 degree view. And if you start figuring out, or if you start calculating ROI, on top of that, it’s, it’s very hard because it’s just a state or a means to an end and you’re actually not doing anything with it.

[00:09:27] Glenn: So the approach that we have and when we do CDPs or CDP, like implementations, right? I think, I think in general it can be broadened up to MarTech implementations as a whole, because this could go for CRM implementations, ESP implementations. Like you can debate on a lot of things, right? It starts with the use case and pinpointing very specifically your needs and why you think you need all of these components in your environment or your stack.

[00:09:50] Glenn: If you don’t start with that, it’s going to be impossible to do it even for an analytic sequence. It’s like, it’s very hard to define. The ROI positivity of my analytics implementation, if the objective is just to have the data, right? And so for me, it ties back more to the methodology and the philosophy of how we process such projects and how we look at the implementation phases and how we approach it.

[00:10:14] Glenn: In order to be able to quantify it later on, rather than it is like, Hey, these types of tools, you never get a ROI positive implementation out of it. But then again, those are opinions, I guess. 

[00:10:24] Bhav: I’m trying to think back to my view on that conversation with Rick and I tend to yoyo with some of these things. So what I say now may fly directly in the face of what I might’ve said, but should we be thinking about MarTech stacks and CDPs and any type of technology with an ROI point of, from an ROI point of view. and because, and I think about this purely from an analytics perspective because is analytics a cost centre or is it a profit centre, right?

[00:10:51] Bhav: And When you frame things as cost centres and profit centres, you know, you kind of get into this point where okay, anything that is a cost centre should be cut when companies are going through turbulent times or if they need to be in like profit growth for shareholders, you know, whatever the ridiculous reasons might be.

[00:11:07] Bhav: And I think it’s when you frame these things as quite black and white like that, you cut things, but you don’t, you know, you forget that actually in order for marketing to be in a profit centre, which, you know, most people consider it to be, you need the tech stack to make it positive. So surely, This should all be summed together, including your tech stack. And actually, if it’s still negative, sack your marketing team, right? 

[00:11:27] Glenn: Yeah, I’ve been, I’ve been thinking about customer data platforms and like in two ways, and it’s interesting because they are very parallel, but more in the use cases, right? Not about the components itself being a profit centre or cost centre, but most, what does it enable me to do?

[00:11:40] Glenn: Is it enabling me to generate more profit or is it enabling me to reduce my costs? And the way I’m thinking about this, for instance, is very simple. Data that sits in another destination using those users as negative audiences in order to prevent yourself or your marketing teams from spamming it On those customers who have already converted, but the data is just completely disjoint.

[00:12:04] Glenn: And so at that point, like the question is, is like, are we generating positive ROI or are we reducing the cost somewhere else? Because the impact could be that the ROI of your current marketing campaigns actually goes up because the CDP or A CDP like infrastructure allows you to. Send more information to a destination that prevents you from doing certain things, right?

[00:12:25] Glenn: It’s the equivalent of like what’s the what’s the actual cost of generating a bad experience for a user? which kind of is also the purpose of a cdp right having the customer data 360 view and then Pumping out or enabling consistent and coherent experiences across all channels that a customer is interacting with like it’s very hard to quantify those things and if we only look at the Uplift in revenue because we want to do personalization or we want to do cross sell Like it’s only one part of the revenue that you’re going to generate in the total possibilities of what a CDP allows.

[00:12:56] Glenn: And a lot of what the CDP allows for me is also cost cutting in specific ways in specific use cases. And I feel like a lot of those things aren’t put in the proper lights. most of the time. 

[00:13:07] Bhav: So maybe the, so maybe the problem is the semantics of calling it an ROI, right? When you talk about ROI, you talk about it has to be positive.

[00:13:15] Bhav: So maybe instead of it being a return on investment, you can reframe it from like value on investment, right? And then the value takes the shape of costs saved, but also, but no, I’m sorry, like revenue made or profit made, but also cost saved. 

[00:13:31] Glenn: Yeah, yeah, exactly. Like one of the, one of the use cases that comes to mind that we did with one of our customers is actually just pumping in negative audiences that were completely siloed somewhere.

[00:13:39] Glenn: They were unable to be connected to their advertising acquisition channels. And as a result, customers would be still addressed with acquisition campaigns, right? The only thing, the only thing between brackets we did was making those audiences available, keeping them up to date, automatically streaming them to destinations, being advertising acquisition channels, and as a result, we got.

[00:13:59] Glenn: X amount of the budget down, which means that if the customer is scammed by a budget or unkept, let’s say there’s still more potential, but we don’t have the budget to get that potential. It’s pure net acquisition that we can do more because we’re not wasting our budgets on customers that we already have and should not be part of your population.

[00:14:17] Glenn: Like it’s these types of things. So what’s the What’s the extra things that we can do because of the fact that we have a CDP and calculate that into the equity equation. 

[00:14:26] Dan: But this is, this is still in, in service, right. Or of something else. So that the revenue or the cost cutting doesn’t inherently come from the product or the people or the team or the agency doing this kind of work.

[00:14:35] Dan: It comes from the, in this example, the market has been aware enough to use this and to effectively change a strategy that might be mid-flow, for example, and be reactive and kind of be open to change. And I think this is. You know, this isn’t the first time that we tried to measure the value or the return of analytics or investment like this.

[00:14:53] Dan: And I feel like it is kind of chasing our tail of like, you know, technically we say 5 percent of spend over here and then the cost of our agency’s fees and the tech licence and the GCP cost is this. And then it just feels like a bit of a, I don’t know, it feels slightly redundant in that idea of kind of moving into kind of activating or like essential in the norm now.

[00:15:11] Dan: So I’m wondering when, you know, the cost of a CMS. And, you know, like Salesforce, for example, as the CRM, those aren’t always. Be improved to be ROI positive. I’m wondering when or how we get to a world where, like, this is just fundamental business architecture. And this is like a reality. Do you see that happening?

[00:15:30] Dan: Is that likely to happen in our kind of career lifetimes, or is that something that’s a bit of a way out yet? 

[00:15:35] Glenn: It’s actually, I find your question very triggering because it makes me realise a bunch of things. I’m like, it’s true that whenever we talk about CRMs, it’s more about what are the technical requirements that we need in order to be, let’s put it very bluntly, okay, like 85%, maybe 90 percent of organisations, they just use CRM as an ESP, it holds an information card about a user.

[00:15:55] Glenn: And then based on that, we trigger automated flows, right? Even though CDPs or in general, these engagement platforms, whatever you want to call it these days, because everything’s a CDP, right? Also having those functionalities like ROI is, it’s true that it’s way more of a conversation when you do those types of implementations rather than when you do it from a CRM point of view.

[00:16:13] Glenn: And I, like the question makes me, makes me say it out loud because it’s something that I guess I’ve realised in the back of my head already, but it is true. I don’t have any answer to that because I still see. Organisations do the craziest things when it comes to CRM, which are sometimes completely irrational.

[00:16:30] Glenn: And then on the CDP front, they want to rationalise or over rational things from the marketing side. Like what’s the ROI and what should we do there? What should we do? I think what you said kind of makes sense. Like what is the. actual experience. That’s how I look at it. What is the experience we want to offer to a customer, a prospect, or somebody who engages with our brands?

[00:16:51] Glenn: And what’s the infrastructure we need in order to be able to cater for that? And if it’s a CDP, it’s composable as an ESP, an engagement platform, a CRM, in the end, I don’t think it really matters as long as we agree that this is the foundation that we need for all of the things that we want to achieve. In terms of experience delivery to our customers, I guess that over time they should evolve in the same buckets because half of the CDPs are actually CRMs and half of the CRMs have CDP functionality.

[00:17:17] Glenn: So I would guess that like all these things would converge and I kind of hope it would contribute to that, over dissecting what is the ROI of this piece of the puzzle exactly and just make it go away. 

[00:17:28] Bhav: But then if, you know, when we think about it, I’m going to refer back to the point that Rick made, which was that he hasn’t seen a positive ROI. I do get where he’s coming from, because in most organisations, what you’re talking about, the planning, the use cases, this isn’t well thought through, right? There is no strategy behind it. It’s usually some marketing team like, Oh, we need this tech stack, some product manager, we need this tech stack. And you never bake into the cost.

[00:17:54] Bhav: You never bake in the cost of implementation, you never bake in the cost of maintenance, and then you never bake in the cost of the fact that it’s automatically, you know, it’s going to renew next year as well, sorry, it’s going to, the renewal is going to go up next year anyway, right? So when you talk about, you know, the fact that you have seen a positive ROI, if I was to take the books for where you’ve seen it, and look at all the numbers.

[00:18:15] Bhav: Would it actually turn, give me a positive, again, it’s not just covering the cost of the platform. It’s covering the cost of the engineering time, covering the cost of the implementation and maintenance. and then see that as a And, and find a still positive return. Obviously, the ROI positive that the marketing team have reported, it’s probably gonna be much higher if I bake these additional costs, it’s gonna come down.

[00:18:39] Bhav: But would it come down to a point where it’s still positive? And I think this is where I, I can’t figure out, like I love the negative audience use case. I think negative audience use case is a, it’s just a brilliant use case for CDPs. But how much savings are you making by not just real, like, re advertising to them, over the cost of everything else I’ve just said?

[00:18:59] Glenn: That’s a fair question. I think the negative audience use case makes sense if you spend a lot of advertising dollars, let’s say. So that’s the first thing. It depends on the scope and the size. I do believe, and I kind of want to stand by my point that I think, like, ROI, positive CDP use cases or implementations exist because there’s a number of factors as well, right?

[00:19:20] Glenn: You’re right that you need to take into account licensing, implementation time, all these types of things. What I also think is that a lot of people make that statement and I’m not saying Rick specifically because we know each other well and we banter around these topics all the time. But what I do think when people think about this topic or when a let’s say a CDP has this speech or this narrative, It’s usually about like, okay, but the implementation time of a CDP is very long.

[00:19:47] Glenn: the way I tend to think of it is if use cases are defined properly, you can actually accelerate your ROI because I don’t need my entire product to be tracked or everything to be available in order to drive my use cases, right? So that’s the first thing. So it’s very hard to get an ROI positive CDP implementation in the first 12 months.

[00:20:05] Glenn: If it takes six months to implement because you’re not in the use case mindset. So that’s one thing. The second piece is like, okay, your, your point is correct. Where you say you have implementation costs, you have the licence costs. On the other hand, I like to think of it differently as well. Like what’s the alternative?

[00:20:24] Glenn: The alternative is that you build something yourself. A lot of the speech is around like, but you already have the data because it’s in the data warehouse, right? To some extent I agree, to some extent I disagree. For instance, I think that there’s very few organisations that have proper Clean behavioural data in a data warehouse that is ready for use cases, right?

[00:20:47] Glenn: So it means that we need to do a lot of work on the data warehouse Which means that we’re replacing licences with engineering costs. And if you look at it from that way, in my head, at least, if you’re convinced that you want to have a CDP, it is because. Hopefully it’s not because you think you need a customer 360 degree view for the sake of customer 360 degree views, but it’s because you have a list of use cases and based on those use cases, you can actually define, do you need a package CDP or are we going to do something which is more like what they call these days, like composable or whatever and figure it out from there.

[00:21:19] Glenn: But in my head, at least it’s still a, and if I take extreme examples in the composable, where you start building everything yourself, it’s an exchange between licensing costs. And, costs in, in hiring people or engineers, which are also not cheap. Right. Plus the maintenance, because there’s a bolt, the build phase.

[00:21:37] Glenn: And then there’s the maintenance phase. Like every time an API changes, the teams need to be able to cope with that API change. And so it also means you might want to have another tool sitting on the back of your data warehouse to do reverse ETL, which in the end is still a licence, right? And so on, in the end, I feel like we’re on a spectrum.

[00:21:54] Glenn: And the question is not maybe are we ROI positive on a CDP implementation, but are the efforts that we’re doing with regards to first party data, zero party data, customer data in general, are those ROI positive, taking into account the entire cost that we have? And for me, that depends on how strong your use case is.

[00:22:12] Dan: So you’ve, you’ve mentioned the buzz term, of the series at the moment, the composable CDP, I just rang, went ding, ding, ding in my head as soon as you said it, but I mean, and this is, this is the key thing, right. It’s going to be the build versus buy debate, the composable or package CDP, although I always liken it to like renting or buying, right?

[00:22:30] Dan: Like do we rent. A software, or do we buy it for yourself and it might be the same monthly fee, but eventually you end up with something you get to keep at the other side of it and you go into that maintenance phase. Right. Or maybe who knows, maybe it works out to be the same overall, but, so let’s talk, let’s talk about that.

[00:22:45] Dan: So like one of the things that I’m still, I’m learning lots about, seeing successes and failures of, and we’ve had lots of very interesting chats over the last couple of weeks on this podcast about the idea of that. Or at least what I’m consuming, it all points to this idea that the only way is to do a composable CDP because every product tool software, everything out there is claiming to be a CDP now.

[00:23:06] Dan: And so the landscape is muddying so much that I, you know, there’s, there’s very unlikely that people that call themselves CDPs can do everything you need a CDP to do. So the only option is to build it. And then all of a sudden you’ve got companies that are. Maybe not as mature on the technology scale are talking to us about CDPs because they want a CDP, but then they don’t have an engineer.

[00:23:27] Dan: They don’t have any analysts, they don’t have this. And it’s becoming a very difficult thing. It’s kind of like, it’s very like, I liken it to the idea of attribution about 10 years ago, there was such a buzz term. Everyone wants attribution, but doesn’t know what it is, how much it costs or where to go for it.

[00:23:41] Dan: And there’s always the buzz term of the year, the two years or whatever. So where, where does that put? Composable CDBs. What’s the value of them? Like, and, and, and is it for everyone or actually, is there a target demographic audience for this kind of stuff? Especially when you mentioned earlier at the start of this, like the ROI of them, because that company I gave an example of, they’re not going to see an ROI on that in a long time if they don’t have someone dedicated to maintaining or doing this kind of stuff. 

[00:24:05] Glenn: I don’t like there’s a lot of ideas that come to my head. So I’m just going to go with it and I’m not sure if it’s going to be structured, but let’s see where we end up. Is there a type of company, like the easiest, almost stereotypical way of thinking is exactly like, are you a buy company or are you a build company?

[00:24:21] Glenn: For me, the second piece is as well, like where do you want to hire for talent? Because it’s true that if you do CDPs, typically you’re going to. Use more APIs, which means you need more developers front and back to get the data there, while in the data warehousing, you’re going to use engineering because let’s assume the data is already there, right?

[00:24:38] Glenn: So it’s a, it’s a difference in how much, how much, how much am I taxing, which teams? With workload, with effort and how am I already staffed and how do I want to develop my future talent pool in the company? That’s one thing or one spectrum, one part of the spectrum, I guess. A second part is like, what are, what are my use cases? Right. 

[00:24:58] Glenn: Again, and I keep coming back to it. Like, do I need a full fledged CDP? When the only thing I want is like, get my data, which is stored in a database. of all the people who bought and just made a lookalike audience in an advertising platform to do positive or negative retargeting, whatever you want to call it, then there’s the pricing.

[00:25:18] Glenn: The thing is as well, like where composable CDP players have been very strong as I think is by hurting this package CDPs more on the aspect of pricing, where are you? Go with yearly contracts in a package CDP, like composable CDP components typically say, Oh, we just bill you on the number of rows you move.

[00:25:38] Glenn: Right. So if in the first six months, I only, or in the first, like, let’s say 30 days, I move like a hundred thousand rows. And then in the next quarter, I move like. triple that amount. Well, I’m going to scale my pricing with my usage. Whereas for all packaged CDPs in the past, the pricing was really a tricky point.

[00:25:55] Glenn: The first thing that they would ask you from the get go is like, how many unique users do you have? While the customer’s like, how, how, how should I know? It’s exactly why I’m buying a customer data platform to give me that view, right? I need my identity resolved. And then there’s the whole thing of, which components do you need?

[00:26:12] Glenn: Like we wrote this article together with Arpit from Database, like almost a year ago now, I think, where we said like, Hey, everybody’s a CDP, but actually a CDP is a collection of components. First figure out which components do you need and then figure out which tool actually works for you. Right. Because all of a sudden everybody’s a CDP, which makes it very hard.

[00:26:31] Glenn: To figure out what you actually need. So yeah, kind of like, I think I don’t have a straight answer, but those are kind of like the thoughts I have about CDPs and composable versus packaged, I guess. 

[00:26:42] Bhav: Yeah, I think they’ve, the companies took on the philosophical mantra of understanding the CDP. We must become the CDP. I wanted to make a joke earlier about the fact that you said that people who are against CDPs or opposed to CDPs would be like, oh, the implementation costs are high and it takes a long time. You know, all of the arguments. and I want to clarify that I’m very neutral in this conversation.

[00:27:08] Bhav: Like Dan and Dara will agree. I just like to ask difficult questions because I’m a difficult person. but actually the people who are like making those arguments, they’re probably also the ones that are telling you. Hey, we can solve your problems with one line of code injected into your, into your, tag.

[00:27:22] Bhav: And then that’s all it takes. And then you take, you know, you’re 12 months down the line and you still haven’t got your data being pushed and your analytics isn’t collecting. So, I just want to say like, you know, I’m not, I’m not anti CDP or pro CDP. I just like the difficult questions. 

[00:27:36] Glenn: But for us, it’s kind of the same, at least like for us in the company, when I say ours, it’s like we do both, right? We do composable versions. We do package versions because of the context of the organisations, the use cases that they have. It’s kind of our job as well to guide customers to figure out what works for them. Sometimes they already purchased something like we help them implement. And if I’m very honest, like, I think it’s also just Error coding just a means to an end, right?

[00:28:02] Glenn: Because it doesn’t necessarily matter which route we take. It just matters that we are able to deliver the experience that we want to those customers, to the teams, to marketing, to product, to whatever. And everything depends on what that experience is that you, how you’ve defined it and what the requirements of all the teams are and there’s multiple roads to get there. 

[00:28:21] Dan: Obviously, it depends. It’s going to be the answer everywhere for this kind of stuff but just to kind of zoom in and get an opinion from you in one perspective. So right now we’re recording this at the end of February, 2024. Let’s say you’ve decided to go package CDP for whatever combination of reasons. Is there a go to kind of package CDP that you look at, does it truly depend on anything? Or are there like two, three, four big players that are like the ones to choose between? 

[00:28:45] Dan: We’ve done a lot of talking about things like composing them in the GCP and all these other products that can plug and play, but I’m just thinking of off the shelf solutions. Like there’s going to be a bunch of people that are sitting in an organisation right now that are like aspirational high. Of getting this thing done. But then the reality is like they say, they don’t have developers, data scientists that have engineers to do this stuff. So maybe they’ve got the budget and they’re not sure where to even begin.

[00:29:11] Dan: Obviously, we’re going to put all your details to have a conversation with you and to reach out in the show notes. So they should do that first and foremost, but I’m just wondering what that landscape of package CDPs truly looks like right now, if there’s a way to kind of whittle that down to, let’s say a couple that you kind of, you’re a fan of right now and I’ve subject to change, but is there a kind of starting point that you kind of investigate on, on your client’s behalf?

[00:29:32] Glenn: yeah, I think from a, from a package point of view, we’re working a lot personally with segments, and particle, like the, let’s say the, the big CDPs, the original CDPs. I don’t know if that’s even correct, but like whatever, right. So the ones that were there first, the OGs of customer data. we’re seeing a lot of likes, and it’s interesting, right?

[00:29:54] Glenn: Because what is a CDP? CDP then becomes the debate. We’re seeing quite some customers who are trying to solve CDP use cases through product analytics tools, amplitude mix panel, one positions as a CDP, the other does not, but then the question is, what is a CDP, right? And for me, like the orientation kind of trickles down to what do you actually want to achieve?

[00:30:15] Glenn: If you think of Segment, for instance, originally it started like a CDI, customer data infrastructure. It’s like the Lord of the Rings of SDKs, one SDK to rule them all. Ripper replace everything by one is again afforded. Like if that’s what you need and it makes sense you add engagement on top of it and you have a cdp, right?

[00:30:33] Glenn: And particle is kind of in that philosophy as well. Their position is kind of a bit different. They’re big competitors in both fields But both of them have more capabilities when it comes to for instance identity resolution. Which is something that tools like Amplitude and Mixpanel, for instance, resolve identities, but only at two levels or something, right?

[00:30:52] Glenn: So if you have complex identities, and if you have the CDI component where you actually want to forward data and the whole package and transform it, it’s going to work less. And then there’s like the marketing CDPs, because in the end you have like the OG CDPs, like you call them. You have the product analytics that are moving into CDPs more.

[00:31:10] Glenn: And then I feel like you have the real marketing CDPs, which is like a, for instance, a bloom reach, which is really almost a blend of a personalization tool, built for marketeers, which has CMS capabilities and all of these type of things. But this isn’t necessarily very strong on the CDI side, or at least historically than it used to be.

[00:31:30] Glenn: And so it kind of depends on what’s the angle you start from. One is very product oriented, one is very engineering driven, which has marketing components, and the other one is almost exclusively marketing driven. So the interesting part is if you think of it, a lot of organisations that we see that buy CDPs, package CDPs, it gets bought, for instance, by marketing, right?

[00:31:49] Glenn: And all of a sudden they realise that they need extensive engineering resources. They need to pitch the buy in, they get the buy in. Okay, boom, we’re there. But then once the project gets going and we start consuming data, all of a sudden the people in marketing who are the owners of the customer data platform actually realise that they’re sitting on top of all of the data that is generated by all of the customers with all of the interactions with the organisation, right, the purpose of the CDP, but their scope or their, mandate is only marketing, right?

[00:32:19] Glenn: So all of a sudden there is like support data that’s available and there’s. Engagement data and their CRM data and their ticketing data and there’s advertising data available and it all pulls together. So it also forces these organisations to rethink kind of bottom up through operations, how they’re structured and thinking about what are the experiences that we’re driving for customers?

[00:32:40] Glenn: Because as organisations grow, you get a CRM department, you get a support ticketing department, you get a sales department, you get a marketing department. And even though everybody focuses on their job, the customer doesn’t really care, right? So the customer journey is transversal, regardless of which department they’re encountering or interacting with.

[00:32:56] Glenn: They literally don’t, they don’t give a damn. I like the CDP for me is the first tool that kind of has the capability to provide that overview, but it also means that the organisation kind of needs to transform and think about things like, Hey, but who’s managing this, who is responsible for one, the customer data as a whole.

[00:33:14] Glenn: And to make sure that these initiatives actually make sense, because in the end, if you’re very honest, the only thing it’s doing is it’s pulling data together, resolving identities and making it available for interactions. Like give or take, right? It’s the very dumbed down version. So the question is like, who’s going to decide what we’re going to do with all of these interactions and how are we going to shape these customer journeys and what are the different scenarios?

[00:33:34] Glenn: So that’s the thing that we see more and more, like regardless of which CDP you bring in house, does it come from engineering? Does it come from data products? Or does it come from marketing? Like it kind of converges into this big question before, during or after implementation of like, okay, but how are we going to.

[00:33:50] Glenn: Now that we have this custom entry 60 degree view, what are we going to do with it? And who’s responsible for architecting all these scenarios? So you inevitably kind of come to a, I hate the word, but like digital transformation. but more true operations because people are all of a sudden seeing like, Hey, people who are complaining and have open tickets with support, we should not reach out to them with.

[00:34:12] Glenn: Campaign emails to upsell on something because they’re just pissed off. They just want their stuff to be resolved. They don’t need this right now. And so you start interacting with other departments, bringing better ideas, bringing cooler ideas, and actually like building better experiences because all of a sudden you’re sitting on top of something else. So it’s, I’m deviating, but it’s kind of like what I have in my head. 

[00:34:32] Dara: It’s not always going to evolve over time though, because you’re going back to your, your kind of focus on use cases. Are you, are you typically going to be speaking to a single department? Maybe a small group of stakeholders or even one stakeholder who has a use case that you then go in and you, you, you, have a solution for that particular use case, which then surfaces more data within the business. They start to act on that, then other departments start to see that and think, hang on, we want to get involved in this. 

[00:34:58] Dara: And then gradually that grows over time, because I can’t imagine you’d go in and be able to see that end, or you might see it, but would most customers not see that end, that end goes straight away and you’d have to go in in smaller steps, typically, which could then change whether you might initially be using like components of a composable CDP, but then eventually in time, you might realise you need to move to package or do something else entirely.

[00:35:24] Glenn: That’s a fair point. I think the way we, we come in and in two ways, usually either we come in and there’s a CDP project and it’s decided at C level or VP level or whatever you want to call it and like, we need to do this and we have everybody around the table, or we start with a one department that is actually like leading the charge.

[00:35:44] Glenn: And it is serving as a POC, right? And typically that is marketing because marketing, if you’re very honest, use cases with marketing are easier because a lot of the interactions happen outside of the infrastructure or the perimeter of the organisation itself. You can show how customer data can be used for better experiences by spending money outside of the organisation rather than adapting processes that are very ingrained and rigid within the organisation.

[00:36:10] Glenn: Think of the support process, right? So typically that’s. That’s the, that’s the most successful track and usually what would happen, even if we come into that first track through the sea level and everybody’s around the table, we would carve out a specific area where we would start because if that area is successful and then it will evolve.

[00:36:27] Glenn: Right. And at the same time, it allows us to be flexible on ROI calculations, right? Because if we want to implement everything everywhere, it means that we’re going to be working for nine months without actually doing something. If we carve out specific pieces in specific parts of the organisations around use cases, like in a couple of weeks, we can actually get stuff going and like see results, which means that it also shows the buy in or generates the buy in for other departments to submit their use cases and actually evolve more organically out.

[00:36:54] Dan: So. This is, this is always, this is always the way and, and I can, I can sense it in Bhav’s like his facial expressions that he just, we always end up talking about marketing and marketing analytics, and it’s always the marketing team that holds the purse strings or do something, but, coming from a product perspective and experimentation perspective. Do you see this kind of extending beyond into that world? Because often it starts with marketing. The POC will be over there, but like, what’s the, I mean, I’ve seen this and it still happens today. You’ve got a CRM team, which is independent from the marketing team.

[00:37:24] Dan: And they, they kind of use that as an email marketing team. And it’s always separate to over here. And, I’m wondering if this will happen. If this, if the idea of a CDP is like the next generation, there you go. Star Trek reference for everyone next generation of the CRM, right? It’s the next generation of that.

[00:37:39] Dan: And it’s detaching that way and saying that there’s a better way of automating across all these tools, not just generically email. And, when it comes to things like, personalization and experimentation often relies a bit more on things like real time streaming data, which doesn’t always happen from the advertising or marketing perspective.

[00:37:55] Dan: So what, what, what’s that growth there beyond marketing applications? I know it’s possible, but does that happen? Has that started to shift and move kind of like thinking around the experimentation and product side of things as well? 

[00:38:08] Glenn: yeah, you mean like customer data being, or CDP is more in the spectrum, being in the spectrum of other teams and marketing, right?

[00:38:15] Dan: Yeah, exactly. So what, so we’re talking a lot about marketing applications and marketing teams being able to sign these things off and kind of like the, they’re the, kind of the spark of a CDP can come from marketing, but. Does that exist outside of marketing right now, or is it more like a kind of marketing team doing that thing and we’re going to latch on and do what we want as well? Like, does that, does it ever start the other way around? Does it come from the CRM or the kind of experimentation team and go the other way, for example? 

[00:38:42] Glenn: The experimentation team, it would be hard to tell for me. I don’t see them very often, so I can’t say yes or no. If I say no, it’s probably still happening, right? what I would say from a CRM point of view, it’s like, I think they’re demanding for it. Or they have an appetite for it. The question then usually becomes like, yeah, but it, but it’s the CRM. That was the added value of a CDP because our CRM can do that too. Right. Our CRM also sends data to your advertising platforms.

[00:39:09] Glenn: Our CRM also enriches XYZ. Our CRM can also consume web trackers and APIs and data warehouses. So I think like you mentioned it earlier, right. There’s, I think to some extent there’s going to be this conversion of like. What is a CRM and what is a CDP because the CDP is a bunch of capabilities. The interesting part is most CDPs don’t have analytics capabilities, right?

[00:39:32] Glenn: So like dashboarding on top of that data, you still need to externalise it. So that might be for like a second or a third phase, but having that full customer 360 degree view is actually what CRM was supposed to do like since forever. But apparently it’s very hard. I’m not a CRM expert. I would guess that it’s because of manual input, all these types of things.

[00:39:52] Glenn: But a CRM in a lot of cases for a lot of organisations, when they talk about CRM, they actually mean emailing. And it means that they only grab the data they need in order to be able to send out campaigns to re-trigger users. To be able to upsell them, to send them newsletters, and it’s kind of like this whole email channel lives separately from the rest.

[00:40:11] Glenn: And I think the CDP kind of facilitates the conversation to say like, hey, but CRM, let’s make things clear within our organisation, CRM is actually emailing. And emailing is a channel. Just like marketing has other channels, just like support is a channel, just like sales is a channel, just like chatbots or lead forms are a channel.

[00:40:31] Glenn: And so how do we bring these things together? Because we kind of need this metal layer on top of it in order to consolidate things and actually show us truly what this customer 360 degree view is about. 

[00:40:41] Bhav: So I have a, I have a theory which I’ve been thinking about now since you’ve been talking and I’m going to tie it back to the topic of this conversation, which is the ROI of the tech stack and maybe the ROI of the tech stack, not tech stack, marketing stack, tech stack, whatever you want to call it, is only positive depending on the team which raises the need for it.

[00:41:02] Bhav: So hear me out. Marketing raising the need for CDP will always result in a negative ROI tax, negative ROI because of the fact that their use cases are so limited. It’s like buying a Lamborghini to drop your children to school. Right? It’s a very expensive solution to a very trivial problem. So I, and maybe if the, for, for CDPs to really see the positive light of day, they need to originate their origin story within an organisation needs to come from a team which has more of a wider reach.

[00:41:39] Bhav: And for me, that’s always going to be the data team. Right. Because the data team, if they are the ones who are championing CDPs, they’re championing it, not just for the purpose of action, being able to take them off the action, being able to be taken off the back of the implementation, but also they can use that data for analysis and insights and you know, whatever you want to call it, you know, think about, especially when we talk about a 360 view of the customer.

[00:42:04] Bhav: So, and I’m going to yo yo here. So as an analyst, I love the concept of a CDP. Because it means that I can do real in depth analysis, I can look at the impact on lifetime value and churn of users who have had to engage with the CS team and, you know, you, blah, blah, blah, all that stuff. I can do really insightful analysis of the backend, which I can then feed into the CRM team, the CS team rather.

[00:42:27] Bhav: And say, look, this is the impact you have. Like, get to, if our CS scores aren’t higher, we’re having a knock on effect on lifetime value. But if I wear the hat of a marketing person, to be able to just exclude the audience or, or do some type of CRM type targeting. It just doesn’t feel like I’m going to get the value because sending an email is cheap, right?

[00:42:49] Bhav: Let’s face it, maybe paying for an ad per click or something like that. It’s not too expensive in the grand scheme of things. You have some control over how much you spend and where you turn it up and turn it down. So maybe that’s where CDPs can highlight their value. It’s, it’s, you know, they’re going into the marketing channel and that’s why we’re sitting here questioning the ROI in like the value of it.

[00:43:10] Bhav: But We all know intrinsically, like the four of us, we’re smart people. We know that ROI on the CDP exists. It’s just that the originating source is creating a situation where people are challenging it. That’s my view on it. That’s my theory. 

[00:43:25] Glenn: No, I think it’s a good reflection. It kind of triggers me and it gets me on the fence on a couple of things, which is what I like. And not to say that you’re wrong, absolutely not. I think there’s a sense of truth that it’s challenging for marketing teams to show the ROI. I also think it’s challenging for a lot of organisations to have data teams that actually have that width and have that ability to think about the use cases, right?

[00:43:49] Glenn: Because the thing is for me, it always starts, and that’s an opinion, I guess that we, or a philosophy that we have at our company, like it starts with the use cases. and if it starts with the use cases, like data teams are rarely, at least to my experience, gonna own the use cases, they’re gonna ask somebody from the business who sits in marketing, and so they’re going to define the use cases, right?

[00:44:08] Glenn: And then data teams are going to operate a bunch of stuff. they’re going to be able to do analysis, but like, if you have a great data team, you’re like, obviously they would be involved that way. But I feel like it’s a challenge for most data teams because the fact that data is a A popular resource within your organisation, which means that these people are de facto already swamped and they don’t need to be usually have the bandwidth in order to help the thinking or have the bandwidth that mind space, let’s say, to think about the use case or in the business use case, because their world consists of data, right?

[00:44:40] Glenn: They need to maintain the data flows. They need to make sure that the data pipelines don’t break your transformation works, dbt don’t break all of these types of things. And so they live in this mid layer, and I feel like a lot of data teams these days are very good at what they do, which is the data space, but as the organisation grows, they actually also get further from, from the job to be done to some extent, or the why they are doing it, right?

[00:45:01] Glenn: Because if you need in depth specialists about data, you’re focusing on that. And you’re further from the entire chain of how things happen, where it’s harder to orient. But being said, like, I worked with customers, organisations that have brilliant data teams, and that are actively involved. Typically what I see is like, it’s smaller size, it’s tech first organisations where marketeers are also analytics people and where data people also have an analytics background, which kind of creates this like overlap and they talk about business.

[00:45:31] Glenn: This is what connects them, right? and based on like, Hey, we could do this because the impact would be X, Y, Z, do we have the data? Yes, we have the data. How will you deliver it? I’m thinking about delivering it that way. And like, because these teams are smaller, you get less. Specialised jobs on very specific things, which means that they’re still involved in everything, which makes the business work around use cases rather than like, Hey, my, my dbt pipeline is not performance enough and I need to upgrade it in order to do X, Y, Z. I’m exaggerating, obviously. 

[00:46:01] Bhav: So maybe it should be the product team. That’d be my final. 

[00:46:04] Dan: Oh, of course it comes back to the product team. 

[00:46:09] Bhav: I just feel like product are, like they’re the teams who care about the customers, the customer experience. They should also be wearing the commercial hat, right? Like they’re kind of exposed to so many areas and, and they’re the ones who have control of the engineering resources, right? Effectively so why don’t make it, why don’t make it a product problem anyway, I digress. 

[00:46:28] Glenn: Yeah, I think it’s more of an overlap, right? Because if you think both in SaaS and in e-commerce, I feel this is correct. Like SaaS is like subscription or onboarding non completion rates, right? And in e-commerce, it’s cart abandonment rates.

[00:46:41] Glenn: Everybody thinks about cart abandonment as a CRM slash email and as a result marketing effort. But actually, if you think of it, it’s inherently a product effort, right? If we can measure what the drop offs are. From our abandoned cart or from our funnels and which the results, which results in abandoned carts, like it’s a signal both for marketing, like, Hey, product, by the way, while you’re doing this lift to optimise our product, what we will do is we’ll send out abandoned cart campaigns in an automated way in order to get those users back.

[00:47:11] Glenn: And in the meantime, you can optimise that checkout flow in order to make it more performance, right? So it’s like a symbiosis where one lifts more or does more work while the other like on the product side, work is needed, but they can’t do it immediately, which means that marketing is stepping up.

[00:47:27] Glenn: And if product improves, marketing needs to step down because while actually the thing works. So I think it’s more like a symbiosis in general, but like, it’s not something that is thought of that way often.

Rapid Fire/Outro

[00:47:40] Dara: Okay, I think that’s a good point to draw a line. I think it’s been a really good conversation. We could probably keep going for hours. but we’ll, let’s leave room for maybe a part two further down the line. So before we let you go, Glenn, we’re going to put you in the hot seat and ask you some rapid fire questions. So the first one is what challenge do you think will be solved within the next five years? And you can go broad or narrow, but I’d say just, you know, generally within the, within the data and analytics world. 

[00:48:09] Glenn: I’m going to take the liberty to actually flip the question. If that’s allowed, I’m going to ask myself, or I’m going to rephrase it as. What are the challenges that you hope are going to be solved? One is people caring about data quality, because now the trend is that everything is automated and everything is artificial intelligence, but very few people care about data quality. And the second one is caring about customer experiences in the broad field.

[00:48:31] Glenn: Not only about better marketing campaigns, because marketing campaigns are just a product. That is delivering an experience. It’s also about onboarding funnels. It’s about product engagement. It’s about support And I hope that people or in general organisations will refocus on the experience that they’re giving the customer Because that’s the big challenge that organisations need to deal with in order to be sustainable and all of the effects that we see or all of the incremental efforts that we see today about like doing better campaigns or Building my campaign this way or that way or only incremental, right?

[00:49:03] Glenn: They’re only like adding fractions. I think the big question is like, how can organisations come back to that customer centricity and I hope kind of CDPs or customer data force them to go back there and rethink how they’re engaging with a customer. Okay. 

[00:49:15] Dara: So in that future customer centric world, what will be the biggest challenge?

[00:49:20] Glenn: Understanding what a good customer experience looks like. And the reason why I’m saying that is because I actually encounter organisations That have spent a long time building top notch infrastructures, but that struggle with coming up with the experiences that they want to deliver. So in a world where everything is perfect, and we have an overview of what the customer is doing, what the state of the customer is, the data quality is perfect, the infrastructure is perfect and up and running, like what does a good customer experience look like and coming up with that, going to the customer and actually figuring it out.

[00:49:58] Dara: So what is one myth that you’d really like to bust? 

[00:50:02] Glenn: The data is a silver bullet. 

[00:50:04] Bhav: Yeah, it is. 

[00:50:05] Glenn: Amen. I have, I have a lot of conversations where we do product analytics implementations. And the expectation is that the tool will tell the people what to do. The tool will just give you an overview of what is happening and you need to build a hypothesis.

[00:50:24] Glenn: You need to validate that hypothesis. You need to take risks and develop things and experiment to figure out. What customers want, because basically any tool is just, or data is just a portal to how customers are interacting with something, but it’s raw material and you still need to be able to work it as an analyst, I would say.

[00:50:45] Glenn: So yeah, I would actually add that to the skillset that there were the challenges that are required in the future, like building an analyst mindsets. is more important, I feel, than being able to master a specific. 

[00:50:58] Dara: That is a fantastic answer. it’s if you’d wave a magic wand and make everybody know one thing, what would that be?

[00:51:07] Glenn: No, I think it could be maybe two things. Data is not going to solve all of your problems. It’s going to be a means to solve your problem, but it’s not going to solve the problem itself. So don’t wait for data to be there in order to be doing something. maybe, maybe I can, if I can do three, the second thing is.

[00:51:27] Glenn: nothing can be measured a hundred percent, brings me back to the attribution thing. I have a lot of conversations around attribution and people waiting for data to be completed in order to do something. It’s never going to happen. And the third thing is your data quality, and I’m going to swear, sorry for this, but if your data quality is shit, AI will only make it worse you’re going to be delivering terrible experiences at an incredible proceeding scale so fix your data quality first. 

[00:51:59] Dara: Last but not least, what’s your favourite way to wind down when you’re not working? 

[00:52:04] Glenn: A slow morning, waking up, having proper breakfasts, making coffee, reading a couple of pages in a book and then going to the climbing gym.

[00:52:14] Dan: It sounds great. Well, thank you so much for all of that. And I think those are some incredible answers. And, what a way to wrap up a hundredth episode of the podcast. So again, thanks for joining us on this, Ben. It feels like we’ve had a bit of a CDP binge season on the podcast that we’re kind of coming to an end with, or at least who knows, we’ll probably still be talking about the same stuff in different ways in the next couple of years.

[00:52:35] Dan: But once again, if people want to reach out to you, or get in touch with you or visit the website, where can they do that? How do they get in touch? What do they, what do they say? 

[00:52:44] Glenn: human37.com or find me on LinkedIn. That’s the easiest to get in touch with me. 

[00:52:50] Dan: Nice. We’ll stick all the links in the show notes so you’ve got that jam packed with a bunch of variable UTM parameters just to mess up with their data quality so that they can’t use AI in the future. Awesome. Well, again, thanks again. A lovely chat and we’ll speak to you soon. [00:53:04] Glenn: Thank you very much for having me.

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