Episode 228 / Gerry D’Angelo / Procter & Gamble / Ex VP, Global Media
Generative AI and the Future of Marketing
Gerry D’Angelo, ex VP of Global Media at Procter & Gamble, returns to the Shiny New Object Podcast for a special episode recorded at MAD//Fest 2023. And the hot topic of the moment is, of course, generative AI - his new shiny object in marketing.
“Experimentation within guidelines” is Gerry’s simple advice for those wanting to make the most of what AI has to offer in the advertising and marketing space. Because it’s such an exciting, new and rapidly evolving element of innovation, AI is definitely worth including in your performance marketing plans. But, how do you balance a quest for producing cheap and fast content with making sure it’s good? And how do you avoid the mistakes of the past?
Gerry talked about how the growth of social media could have been moderated differently in hindsight. Such lessons can be taken into how we use AI in advertising and how we reflect on potential unforeseen consequences of generative AI work. This can include repercussions on Intellectual Property, but also knock-on effects on content producers as users resort to holistic answers from an engine like ChatGPT over visiting multiple websites to gather information.
Listen to Gerry’s advice around experimenting with cautious optimism, as well as his top marketing tips, given to the MAD//Fest 2023 audience, in the latest podcast episode.
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Transcript
The following gives you a good idea of what was said, but it’s not 100% accurate.
Gerry D'Angelo 0:00
It's never more true than now that you can only really learn by doing and I think if we keep that very much to mind now as we enter in this new world of AI, then that can only be a good thing for us and protect against some of these unforeseen circumstances.
Tom Ollerton 0:21
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My name is Tom Ollerton. I'm the founder of automated creative, we're a creative effectiveness ad tech platform. We help turn brands' impressions into intelligence. But part of what we do is we do a podcast, I think we've done about 250 episodes or so. And every week we get to interview significant leaders from the industry about their vision for the future and what is in fact, their shiny new object. We're going to talk have a discussion about artificial intelligence today. So I just want to prep it a bit. So the way that I'm looking at it at the minute that AI is unbelievably amazing. And this is a great example of that recently.
Speaker 3 1:38
A long, long time ago and at Winterbottom's lovely tea party, which is in the smoking ruins and ashes of New York City appears woman a play no games, and it's out to kick some butts against the unimaginable, brutal, merciless and scary lobby boy of the delightful Grand Budapest Hotel
Speaker 4 1:54
Hi, then everything seemed doomed and lost until a super handsome man arises. The true hero and great mastermind behind all of this.
Tom Ollerton 2:05
The really crazy thing about this, though, is there was no code, there was no shoe, there was no nothing we just saw generated on someone's laptop in a very short amount of time. So you know, what does that mean for all of our careers? So that's exciting. That's an opportunity. But actually AI is also quite scary. You know, Snap has its own AI LLM built into the tool. And I don't know if you've seen this, but someone said, Do you have access to my location? No, I don't. Where am I? I'm sorry. But I don't have access to your information. Oh, are you lying? No, I don't have access to your location. This is quite reassuring. Where's the closest McDonald's? Oh, it's just around the corner. Right. So it's a bit scary. So is it amazing? Is it scary? Don't worry, we have Gerry here. So Gerry, for anyone who doesn't know who you are and what you do? Could you give us a quick?
Gerry D'Angelo 2:55
Yep. So my name is Gerry D'Angelo. I was until very recently, the Vice President of Global Media at Procter and Gamble, I've now actually retired from that role, which is a very kind of American way of moving on from an employer. And I'll be starting some advisory roles in September of this year.
Tom Ollerton 3:15
Congratulations, mate. So on the podcast, we always there's kind of fixed questions. And the the question that you've chosen is, what advice would you give to a smart driven student who wants to make it in the industry?
Gerry D'Angelo 3:31
So I think probably the best way of answering that question is what would be the advice that I would give myself at that stage. And if I look back at my career, I spent over 30 years working in both agencies and on the corporate side. And I've been very, very lucky. So the advice that I would give to anyone starting in the business, if they're young and hungry, and dynamic, and determined to get success is just make room for some luck. Because if I look back at my career, there have been two or three occasions where luck has played a big part in making the right move at the right time. So taking a step back, letting events kind of play out, and allowing luck to play a role in the development of your career would be the advice that I would give.
Tom Ollerton 4:16
Can you just dig into that a little bit? That makes sense. So how would that someone in the room who is trying to, you know, follow your career to a degree? How would you make room for luck? Is that a psychological thing? Or are you putting yourself in a position where...
Gerry D'Angelo 4:30
I think probably the best way of putting a pin in that is to say like, be curious. So if I look at a couple of the big opportunities that I had, I think one of them came from me absentmindedly scrolling through LinkedIn, one Sunday morning, and I just happened to come across a role that looked very interesting. And on the back of curiosity, I kind of double clicked on that a little bit and was able to realize it was a really good gig working for Mondelez International at the time in Zurich, and the other one is just be open to conversations. Write events like this or more broadly, in your career, you just never know where some of those very, very kind of innocent conversations may lead and network like, like crazy and allow your networking to be powered by that level of curiosity.
Tom Ollerton 5:22
The question we always ask on the podcast, and I'm fascinated to know what you're going to come up with. But what is your top marketing tip that spanned your entire career that you've shared the most often that you think really represents the one thing that everyone in this room got it?
Gerry D'Angelo 5:39
Okay. So the one thing that I've tried to hold true to throughout my career is understanding the difference between marketing fundamentals, and those things that might come along on top of that, that might be very specific tactics that would be relevant to a particular time or a particular place. And that allows you to kind of hold on to things in a way that ultimately will be business drivers. And it means that you don't spend excessive time and energy running after lots of lots of things where ultimately, you'll look back at those things. And you'll realize it was somewhat of a box checking exercise and wasn't ultimately ending up in something that was driving the business that you work for at the time, or your own kind of personal development. So if you can understand and differentiate between those fundamentals, and those things that are a little bit more tactical, that kind of might fade over over appointed time, then that would be the one thing that I would advise that everyone does in that career.
Tom Ollerton 5:45
So now we're gonna move on to your shiny new object, which is AI, and the future of marketing. Now, I think I know what that means. Right? What does that mean to you? And why is it your shiny new object?
Gerry D'Angelo 6:44
Well, I think it's hard to ignore, because certainly on the back of chat GPT from a generative AI perspective, it's absolutely new, and it's absolutely shiny, and it cannot be ignored. Because every time you flip open Twitter or LinkedIn or even the news. It's absolutely there. So I think it's something that cannot be ignored. And I think the way that that certainly the company that I used to work for until very recently and a number of large other advertisers, we looked at it with genuine enthusiasm. And the reason that I would frame it like that is because there was a degree of innovation fatigue, that was that was settling in. So yes, we had blockchain. Yes. We had NFTs. Yes. We had the metaverse, yes, we had associated virtual worlds and goods. But over a period of time, it became very obvious that if you're in a large organization, that's manufacturing and distributing and retailing physical products in the real world, it was very hard to see the practical application and use cases for many of those things. And I think the difference with AI, is that those things almost automatically became evidence. So from a media perspective, which was the area of the business that I worked in, you could start to see that AI in the broadest sense through the use of technology and data was already very, very prevalent in our business and the way that decisioning was being made in the media space. And I think now from a creative perspective, you're starting to see those use cases as well. I mean, a great example I can provide on that is a brand manager that was working on a haircare brand was telling me just last week, that even in pre production, using Gen AI to come up with 20 different treatments was done almost at the touch of a button in a way that it would never have been able to be done before.
Tom Ollerton 8:41
So I was lucky enough to join a session with your peers on the World Federation of Advertisers, your media group, and so you're unbelievably well networked with these other senior media leaders globally. So I'm curious to know, how are your peers preparing for this at this high level?
Gerry D'Angelo 9:00
Yeah, I think I could sum it up by saying cautious optimism. Because the optimism is coming about through the immediacy of these use cases. But the caution is coming about because we've seen a number of different waves of of innovation, and sometimes things can go wrong. And so that cautiousness is being manifested by some guidelines. So when it comes to particularly generative AI, you have to take into account a number of different things. So for example, on IP, you have to be very, very watchful that to what degree is your own IP? How can that be protected when you're using prompts to go into a number of these applications and also, the output of this stuff, you also have to be very, very watchful that the IP can be protected and owned in a way that perhaps it wasn't before. And also things like product claims. So as well as IP just need to be very, very careful that any of the outputs with generative AI can withstand scrutiny in terms of challenges around product claims.
Tom Ollerton 9:20
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So you don't have a crystal ball. Your opinion is very valid, but what do you think is gonna happen in the kind of six to 12 month timeframe of this stuff? What's your prediction?
Gerry D'Angelo 11:00
So I have to answer that from a very personal perspective. But I, I'm quite glad in a way, because for 10 or 15 years, I've witnessed almost in like real time, how the creative side of our business, the creativity and the technology side of our business are on two very divergent paths. And that's actually been quite sad to see because you can kind of see them sailing off in in different directions. And I think where I'm very hopeful for the future, is that generative AI, in particular, can stave off this somewhat uncomfortable reckoning between the two of those things. And it can in turn become the bridge that starts to put creativity and technology back on the path together. And that can only I think, be good for the industry more broadly.
Tom Ollerton 11:51
And when it comes to these technologies, do you think we should just get on with it? Or do you think there's a certain amount of like self governance that needs to happen first?
Gerry D'Angelo 11:59
What I think we definitely have to get on with things. I think, with Gen AI, in particular, and AI more broadly, it's never more true than now that you can only really learn by doing. And I'm super encouraged to see that extra air experimentation is being encouraged both in large advertiser organizations and also in the agencies. And so I think we have to do that. But we've also got to do that with a very watchful eye on what happened in the past. So there are some things that happened in the past that if we had a sense of being able to ask, you know, what could go wrong, we would have ended up with some much better outcomes. And I think the probably the biggest learning from that is in the social media space. And I think if we keep that very much to mind, now, as we enter in this new world of AI, then that can only be a good thing for us and protect against some of these unforeseen circumstances, consequences.
Tom Ollerton 12:55
I don't know how much you can talk about this. But what you know, as you sort of left p&g, what were you seeing as being the experiments there?
Gerry D'Angelo 13:05
So I think there was clearly a lot of work that was going on in the innovation space. So I think people were really tempted by beginning to understand how they could drive innovation and NPD. And then right at the other end of the scale, there was a lot of functional work, that people were beginning to experiment so that could AI be used to take out a lot of time and manual intervention in those areas. So those are the areas that I think I'd say I was seeing most experimentation on.
Tom Ollerton 13:39
And you mentioned before, like IP and so on, but what do you think the ethical considerations are? I know that there's a lot of challenges that people are making around? Well, this has been generated by AI, but AI is trained on a data set, which tends to be something that a human made. So what's your view on?
Gerry D'Angelo 13:59
Well, I think the watch outs, you've really got to put this into the bucket of unforeseen, unforeseen consequences in the sense that, yes, you could take time and cost out of the equation, but what's going to happen in terms of the end product, and I think probably a good example of that, I think it was Amazon that was doing using AI to filter out CVs for recruitment. And they stopped doing that after about four months because they realized that there was an inbuilt bias in terms of ethnicity and gender, that was impacting the number of people that have candidates that they were shortlisting. So I think as long as you're asking yourself the question, What could go wrong? What are the unforeseen consequences of some of this work? Then the more guarded you can be against some of those things.
Tom Ollerton 14:57
So I was, talking at a Google event the other day, which is really interesting, and someone said something that really scared me. And he basically said that, that these large language models are based on pre existing content on the internet, billions of pages, millions of sites, Wikipedia, and so on. And he was talking about an interesting shift between the way we would search for things, use a search engine, you search for somewhere nice to go on holiday, something to eat tonight, whereas these large language models are almost a find engine, in a way you immediately arrival I think, what should I do this weekend, with my five year old, there you go, those five ideas, I don't have to research it, it's kind of been done for me. So there's this idea that what the large language models have been trained on are people contributing to these websites, reflect on going to these websites in the first place, they aren't going to contribute. So we can have this a new form of the internet, where we're using these sites a lot less. And we're relying on large language models a lot more for answers. And I'm curious to know how you think that will play out and how that affects you.
Gerry D'Angelo 16:03
I think from a user perspective, the the utility is going to be much greater that if you put in a question or a query or a prompt, and you get back a much more kind of holistic answer is going to be super useful. So I can understand from a consumer perspective how people will lean into that. But it's going to raise questions from a content perspective. I hadn't really thought about it in those terms. If you know, if the if people weren't going to the sites and creating the content, is this going to kind of create this negative spiral? I hadn't thought about it that way. But I do think about it from an IP and a monetization perspective. Because if content is being scraped relentlessly to create some of these outputs, then what does that really mean for the content providers? And how that gets monetized? And how people make a living off the back of it? I don't know the answer that. But I think we certainly need to be asking ourselves some of those questions as these models become more and more prevalent in their usage,
Tom Ollerton 17:02
I was watching a presentation by our global head of strategy. Amy Wright. And she was saying that we all need to make a choice between good, fast and cheap. And we've been in the AI automation space as a business for five years. And I think what she says is very true. Or someone said recently, also, like shit that arrives at the speed of light is still shit. And what we find is, it's the intersection of these tools that do things very fast, because human creative and strategic thought that produces the optimal results. I'm kind of curious to get your view on that.
Gerry D'Angelo 17:40
Yeah, no, definitely. Well, I, I certainly accept the premise. What would you say good, fast, cheap. In an ideal world, you'd have all of those things, I think, but it's very, very hard, I think, to get 100% delivery, and all three of those things, and you're gonna end up making some compromises somewhere. I think the natural bias is going to be the AI will lend itself to faster and cheaper. And the question mark is going to be around the good pace. And I think on the on the good pace with it, it's going to be some questions around the veracity of the content. And for us as as big advertisers, that veracity of the content might be in terms of how valid a product claim might be, or how ownable a piece of IP might be. But I think going forward, it's going to raise more and more questions about the content, how it gets provided, how it gets created, how it gets generated, how it gets distributed, how it gets funded? And I don't know the answer that I think it's going to become increasingly difficult to deliver on all three.
Tom Ollerton 18:47
And this kind of technology seems to be available to all it's quite cheap. To have a quick, it's quite easy to use. The there are certain brands within like a portfolio, like from png that have more refined more use from it, or is it everyone should be using these things all the time?
Gerry D'Angelo 19:05
I think that I think it's applicable to all brands. So you're talking particularly from a generative AI perspective, or AI more more broadly,
Tom Ollerton 19:13
from a generative AI perspective,
Gerry D'Angelo 19:17
I think the brands that have a greater degree of or greater potential to drive their business through personalization. There's a more kind of immediate relevance and impact for generative AI. Because I think one of the things that's held true for Procter and Gamble brands or Mondelez brands or even the other businesses I've worked out in the past is the ability to have a very, very broad based appeal and create fame on the back of that, and that's been the driver of business success in many cases. However, if you are talking, for example, in the diapers business, then being very, very specific to who you're talking to, and then being able to speak to the pain points for those individuals and then tailor creative on the back of it. And we've certainly seen that with some of the work that we've done with you for SK II and herbal essences, where we've been able to drive much greater or higher effective, creative on the back off that much more quicker to market.
Tom Ollerton 20:23
So we're kind of coming to the last minute now, so a bunch of people in this room are excited, maybe slightly worried about the impact of AI, what's the one thing that they should be doing in the next week to help prepare?
Gerry D'Angelo 20:34
I'm going to try to give you a very short answer. So experimentation within guidelines.
Tom Ollerton 20:40
Brilliant, and that is a lovely way to finish it. Gerry, thank you so much for your time.
Gerry D'Angelo 20:45
Thanks, Tom.
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