David Tiltman on WARC, AI, Brand Consistency and Content Churn

Boringly Effective Podcast. I'm Andrei Tarnovski, and here's something I've been thinking about for 20 years in marketing strategy, and it still bothers me. We have more research, more data, more case studies, and more smart people writing about effectiveness than ever before. And yet, when you look at what actually gets made week after week, something doesn't add up. The work isn't getting better. In fact, it isn't getting even more consistent. In many ways, it's even getting worse. My guest today is one of the few people who can see this gap from both sides. He reads the studies, he commissions the research, and he talks to people who produce it. So I asked him, what does the evidence say? Why aren't we doing it? His answer includes data that genuinely surprised me. He's calling it churn and burn, and companies are spending more on it than on their best work. We also talk about AI, but not in the way you're used to hearing about it. David explains why there is zero correlation between how creativity works on humans and how it works on models, and why priceless may be the most instructive marketing word of the next decade. This is the kind of episode that won't just make you nod. It will make you reconsider how you spend next quarter's budget. So I hope you enjoy it.

Hi, David.

Hi, Andrei.

Thank you for joining us at the Romanian Creativity Pavilion at Cannes Lions.

Great to be here.

So first of all, tell us briefly about yourself and your role in WARC. I know I'm talking to one of the bosses, but—

Yeah, so I'm the Chief Content Officer at WARC. It does what it says on the tin. I manage all the content. And you think WARC is a significant content operation, we're always publishing and commissioning and researching new stuff. So I've got a team of, on Walk specifically, around 30-odd people around the world.

Wow.

And then I have a second hat because Walk is part of Lions, the Lions Group, and there is a division of that called Lions Intelligent, which is not just Walk but also Contagious IQ, a new site called FE Insight, and The Work, which is a Cannes Lions spin-off product. And so I manage content across all of those as well. I manage those content teams.

So basically you're the one to blame for the sleepless nights when we, we are so curious to see what new—

Yes, I'm sorry, that is me.

You have probably the largest body of knowledge, of intelligence on marketing. Is there any evidence which is incredibly clear yet Almost all the market gets it wrong. Is there anything you could pinpoint?

There's so— so actually one of the themes— there's lots of areas— one of the themes this year in Cannes Lions has been the widening gap between best practice, what the theory tells us to do, and actual practice. And actually, annoyingly, that gap seems to be getting wider. Even though we know more about best practice, the gap between between good practice and what's actually going on on the ground is getting wider. And that's for a whole bunch of reasons. But if I take one example, it would be around what some people will call consistency.

Mm-hmm.

So there is a growing body of evidence that consistency pays off. On Monday, Mark Ritson and Byron Sharp agreed that consistency was key. At the same time, seeing things get more and more fragmented, more and more ideas being put into market, more and more low-quality content flooding the platforms, Consistency is actually moving in the opposite direction. We're becoming less consistent, not more consistent.

And that's although we do know how important it is.

Yeah.

Is that influenced by how the platforms are trying to get people to produce more content?

That's a big part of it. It's a big part of it. It's easy to see it as a sort of, oh, it's just marketers being silly and chopping and changing and the CMO gets bored and all of that sort of stuff. And maybe there's a bit of that. But yeah, there is a structural issue in the industry where marketers are being told that they need to just keep churning, churning, churning, churning, create the stuff, the algorithm will figure out what works. Now the problem with that is it gets very hard to maintain any form of discipline in terms of brand messaging. It's a really difficult, I know, I'm not pretending this is easy.

Mm-hmm.

But some data we released this week with Creativeet from the US and some major European markets, The sheer volume of ads was astounding. So, and it's all low-budget stuff. So 93% of the ads by blue-chip advertisers, not little, like, it's not like your local pizzeria. 93% of the ads by blue-chip advertisers, all Fortune 500, had less than $10,000 of media spend behind them. So we're just pumping, like, we call it churn and burn, but it's sucking loads of our budget in. So actually we're spending more on the churn and burn stuff than we are against our sort of big creative swings. What you might expect to see is that, yeah, we're testing and learning all the time and then we're picking the winners and putting a load of budget behind it. That's not happening.

Mm-hmm.

The winners, as in that we had a bucket that gained over $100,000 of media investment, that only accounted for about 18% of the total spend. The 93% Volume accounts for 30% of total spend. So more money is going into the bottom end than it is to the top.

So basically all of them are fighting for the same huge, immensely small amount of people that might or might not buy.

Well, partly it's about performance. So yes, there's lots of performance assets, but it's not just brand performance. It's the gravitational pull of these platforms is towards small, small execution, small ideas, small duration, test, test, test, test, test. But there seems to be a lot of testing but not a lot of learning.

Okay. You mentioned that this study of yours has been made on the more developed markets.

Yes.

Do you have lots of studies on the emerging markets, on the smaller markets?

So we have been looking at that. It does depend what market you mean, but I guess the closest thing we have to that, it's not as in much depth as the thing we've just talked about, but we've done a lot of work in Asia on whether the rules of, the rules or laws of advertising that have been drawn up in places like the US, the UK, Australia, whether they apply in other markets. And largely we are finding there are, they do.

Mm-hmm.

So in Asia we had a project called the PACE Principle, which was looking again at brand and performance. And in Asia, the dimension is often size. speed. It's like the Asia is such a fast-moving place and everything gets to market quicker. Again, we saw the same law, like rules play out in terms of you do need to be quick. There is, there is room to be culturally resonant and, and all the rest of it, but that shouldn't come at the expense of a clear north star strategy, everything laddering up to the same space.

Mm-hmm.

Because, you know, it makes intuitive sense if you stop thinking about it as like rules of marketing and start thinking about how do customers behave. Those sorts of things are kind of universal in all markets, in all parts of the world. Most people are not actively shopping for something at any one time. So the job isn't just to find the few people who are in market, it's to find the much bigger people who are not currently in market but might be and talk to them. We have started to look at that, not specifically for Romania, unfortunately, but we have started that process, uh, in Asia. I think what, um, we're really excited about over the next couple of years is as we integrate the EFEs into our organization, because the EFE case study data is so deep and covers so many markets, we'll be able to run these studies on, on a lot wider set of markets.

If On any of these smaller markets, you found anything that was unexpected and anything that does work there and could work on the bigger markets, on the more developed markets? The second one is analyzing the brands that win. Isn't that a bit of survivor bias, or are those rules, do they apply to any—

I'll start with the survivor bias one because I think— am I allowed to swear on this video?

Please do.

I think there's a lot of bullshit about that. And I think some of it is just researchers fighting with each other. We have this terrible tendency in the marketing world for one person's theory to argue with another person's theory.

It's how science grows.

Yeah, it's quite annoying though.

Hi.

Now look, let's take the specific example of where, of, of, of where this has happened, right? So Les Burnett and Peterfield produced a whole body of evidence based on the IPA effectiveness awards.

Gorgeous, Rothard.

Yeah. And over the past, like, whatever, 15 years or so. Yes, that is a massively difficult dataset because it is largely UK cases. It is the best stuff that the industry produces, the best, most effective stuff the industry produces. There is this sort of accusation of survivor bias. Now, what is interesting is when the sort of rules that they, or the findings that they discovered in this body of evidence started being tested in very different types of data.

Mm-hmm.

The same things emerged. It's a relatively small sample size. It has that survivorship bias. Yes, all of that is true. But what was super fundamentally interesting was when you took that to other datasets that were not case study-based, that were based on large datasets, that operated in different markets, So like the US, we pretty much found the same thing. Of course, the nuances maybe changed, the angles changed slightly, but we've now found that yes, you need to do brand and performance in datasets in Asia, in the States, different parts of Europe. I think we can put some of that survivorship bias stuff to bed because we've actually seen that by taking a relatively small but very deep body of data, that we know quite a lot about, it can give us hypotheses that we can then test more broadly. It does sort of annoy me that we, like, people, like, would just dismiss that.

Yes.

That can't be right because, okay, well, let's accept that the data has limitations, but take that as an encouragement to go and use the findings and test them somewhere else.

To test again the principles, not— okay. Are there any lessons we can learn from those who did not survive in the market? Is there anything we can find out new to us by researching them?

Well, it depends what you want to know, I guess. If you're trying to find out why they didn't survive, that could be useful. Because knowing how to win is a different question to knowing how not to lose. Now, the problem you have with that is it's very, very hard to get good data on stuff that didn't work, because no one wants to own up to it. No one wants to go, yeah, I'm going to enter a case study on how this thing totally bombed. Yes, in principle, but actually getting the data is quite difficult.

There's probably more ways to lose than the number of ways to win.

Of course. Yeah. I mean, if you accept that the default is, the baseline position is you are probably going to lose, then you have to understand all the things that, like, you know, the things it takes to then win.

Now let's get back to the question about smaller markets. Is there anything that applies there and maybe would be relevant for the American market?

Yeah, there's always stuff you can take. Again, I'm gonna use Asia as an example because we are closer to that at Walk. So we are doing a lot of work at the moment around the worlds of social first, creator, and the links between those areas with sort of commerce because Asia leapfrogged the West in those sorts of spaces. Now, yes, they are smaller markets. I mean, China's obviously not, it's enormous, but they're very developed in certain areas. And so what we are seeing in terms of the way those spaces play out in Asia actually tells us about what, what may or may not happen in the West. It's not always a perfect one-to-one match. Things like live streaming became massive in, in Asia. It hasn't really ever caught on in other parts of the world for a number of different reasons. What's really interesting is where you might look at, you know, look at these different markets and think, what are the sort of universal stories in those markets where that market might be either slightly ahead or have a slightly interesting experience, like interesting set of circumstances.

Mm-hmm.

So for example, I mean, it could be about technology, but it could also be about, are there specific categories in that market that are growing particularly quickly where actually that might tell us how a category could be developed? Or like you could, you could find new ways to solve a particular consumer problem in another. Another market. I don't always like the sort of idea that the big markets know what they're doing and the small have to learn from the big. It's often about, you know, each market's got its own specialisms and its own expertise and its own things. And once you learn about stuff, you can then translate it into, you go, actually, that could really have relevance over here.

One of the important subjects on this Cannes edition is AI. Basically every second speech had mentioned it, at least. As a marketing strategist, partially I do understand how AI is influencing my work, but how does it influence the creative part? By you, I mean WOC.

Yeah.

Do you have a lot of studies on the creative effectiveness?

Yeah.

So look, it's hard to boil AI down into a few talking points because it's existential. Yeah. Every single It touches every single conversation in Cannes, even the ones that aren't about AI are sort of about AI somewhere. I think there's some really interesting things going on. So for us, I would say this Cannes has been about properly understanding what you might call the second-order effects of AI, or at least starting to. So if initially it was like the first year, like I said, a couple of years ago, the conversation was around bloody hell, what is this? How do we make it work? Like, can it actually create stuff? Are humans still required. Last year it was more about the direct impact on the economics of the advertising industry. Oh, you know, do we still need the same number of people? Are we gonna be a much smaller industry, et cetera, et cetera? Now there's a bit more of a balanced debate where we can see, look, this thing is going to, this thing is gonna change the industry, is gonna change all our processes. It's gonna change the way strategy is done. It's gonna change the way we research categories. It's gonna change the possibilities of creation. Doesn't mean that humans come out of that.

Mm-hmm.

But we're starting to have more conversations around, as I say, the second-order effects, which is if everyone's using AI, what does it mean to be distinctive? And what does a brand need to do to be machine-readable so that the distinctiveness comes through into the models?

Mm-hmm.

I'm gonna give you an example. It comes back to the consistency point I've already made. We did a big guide on brand building in the age of AI. And as a little bit of fun, we looked at Mastercard, the credit card brand. We asked a bunch of the different models to tell us how does Mastercard compare with other credit card brands? Guess what word came up in all the answers?

Priceless, I guess.

Priceless. A consistent 20-year strapline.

Yes.

That ties the product to the customer benefit. perfectly, that's what shows up in the models. So at the very least, maybe we see a resurgence of consistent taglines. But actually, it tells us something much more fundamental, which is that the models love consistency, and they love consistency in the information they read. So how do we engender consistency through everything we do? Or at least, I think the word this year is coherence rather than consistency. But for like Mastercard, didn't come up with that strategy in order to affect an LLM 20 years into the future. But the knock-on effect of them having done that is that they are actually very well placed in this space.

Basically, there's not a huge difference between building this distinctiveness for humans and for machines.

There is a difference. So we had a really interesting session this week. Jellyfish and INSEAD and WARC had done some research into whether creativity worked on models as well as human minds. In short, there's no correlation, zero correlation between the way it works on the 2 things. The next phase is about, as I say, how do you make a brand machine readable? How do you make your advertising machine readable? We don't stop the work of talking to humans because that matters.

We just add a layer.

But there is a layer of, well, okay, what does that mean? Is there an additional layer of work we need to do to ensure this is coded in the right Do we see brand as the context layer through which AI understands who we are and how we behave? Actually, this creates a whole new level of brand strategy that probably didn't exist before, or at the very least, it makes doing that thinking, doing that brand strategy far more important upfront. Because if you are presenting inconsistency to the models, it doesn't know what to read.

Binet and Field or Byron Sharp?

I can't— how do you pick between those two? Whoever I choose, the other one will kill me. They're both right. Yeah, I think they're both right, but in sort of different ways. I think the work that Byron Sharp has done around popularising the work of Andrew Ehrenberg is really, really fundamental because it gives us a way of understanding how categories work, how consumer buying works, and then lots of other stuff layers on top of that. So Burnett and Field were not see themselves as in opposition to Byron Sharp at all. They would see what they are doing as a way to interpret some of the ideas in how brands grow into something that feels more practitioner-focused.

So basically Byron Sharp set the matrix where every other researcher can—

I do know of researchers who disagree with Byron Sharp, but certainly the people like Binet and Field, yeah, look, they might quibble on specific points and specific points of nuance and emphasis, but they wouldn't argue with the big picture.

A Cannes Lion or a sales uplift?

Again, I'm going to be boring and say both, but I'm going to say a Cannes Lion because I think the game isn't just about driving sales come what may. It's about building sustainable brands that can drive profits as well as sales. Yes, of course, we need a sales uplift, but Are we doing that? Are we driving that sales uplift with techniques that are also driving, like building that sort of sustainable, like profit growth?

What is more useful for marketers, reading more work or watching less LinkedIn posts?

Look, you can look like, like we should all, we should all spend less time on LinkedIn. I think we can all agree on that. But if you talk to marketers in can still— the ones that get the most from the festival are the ones that work, that spend some time in the basement looking at the work itself. Because it is, it's really good stuff and it is a reminder. We talk about theory and data and these big abstract concepts a lot, but at the end of the day, a lot of, at least the marketing community, communications, not all marketing, but the job comes down to actually creating something. Something has to go out into the world.

Mm-hmm.

You know, we're not just building pipes. We're at— the craft is important. And I think reading more of the actual work itself and understanding the craft of it, not just the sort of the big idea or the ChatGPT summary or whatever it is, but how they actually got it done. and the story behind how it came to life, I think is really important because it is a reminder that craft is a really important aspect of not just the creativity, but the ability of that creativity to connect.

This is a perfect thought for ending this discussion. Thank you so much again, and thank you not only for joining us here, but also for— I will repeat myself— the sleepless nights when we were curious to read everything you have. Available on walk.

But you can never finish walk. It's not possible.

Definitely.

One thing David said stayed with me after we finished recording. He described the tension between marketing evidence and marketing practice, and he didn't try to resolve it neatly. The gap exists because the system rewards different behaviors than the evidence recommends. Platforms want volume, budgets follow availability, testing keeps producing data, but not always learning. I'm Andrei Tarnovski. I'm Andrei Tarnovski, and I've been doing strategy long enough to know there is no simple fix for that kind of structural problem. But the conversation also made one thing clear: the brands that will be best positioned 5 years from now are not necessarily the ones producing the most content today. They're the ones that can stay coherent while everything around them speeds up. If this episode made you think differently about how you allocate a marketing budget or how clearly your brand reads to the machines that are increasingly processing it, share it with someone who needs to hear it. Subscribe to Boringly Effective wherever you get your podcasts or follow us on YouTube. And if you want the key takeaways, the best quotes, and the full transcript, along with a weekly roundup of what actually matters in marketing, go to boringlyeffective.com and sign up for the newsletter. Thanks for listening. Boringly Effective Podcast.