Generative AI for marketing: 10 things digital marketers are doing with generative AI right now

Brands are using generative AI for marketing to get better faster. I recently chatted with Winclap general manager Avi Ben-Zvi about how he’s saving money, increasingly velocity, driving better ad performance, and boosting bottom line sales and revenue with generative AI.

I’ve already talked about how generative AI could double or triple the size of the gaming industry, how Amazon could use generative AI to make SO MUCH AD CREATIVE, and shared generative AI marketing tools that generative AI generated for me.

In this post I want to cover how marketing can use generative AI for …

1. Ideation: making new ideas
2. Generating creative assets (duh!)
3. Accelerating creation of … well … everything
4. Reducing the cost of creative
5. Localizing ads (with a hefty dose of caution!)
6. Doing voice overs
7. Running better A/B or multivariate tests
8. Delivering 10X more assets
9. Allocating budget (ok, this might not be generative AI)
10. Creative avatars

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Generative AI and performance marketing: 9 things that are possible now

What’s possible with generative AI in marketing?

Probably way too much.

1. Ideation: making new ideas

Humans are creative. But humans are also busy, tired, and (let’s be honest) fresh out of new, innovative, creative ideas. Having an infinite idea box handy is a wonderful thing, which is why Ben-Zvi is using tools like ChatGPT to get fresh input in his gray matter.

“We’re using Gen AI to start the process of actually ideating,” Avi Ben-Zvi says.

ChatGPT might not give you a concept that you can just run with verbatim. In fact, it probably won’t. But human brains are amazing creative association machines: bounce ideas off of them, and new ideas appear almost spontaneously. Kick off the process with generative AI, finish it with good old-fashioned wetware.

2. Generative creative assets

Sure, this one is a no-brainer. But it’s not just images for an ad: creative assets include text, images, voice, video, and more. And that’s a game-changer because it makes every team member their own team. Now writers can design, English speakers can publish in Spanish, and graphic designers can make videos. 

(Sure: we need to add a bunch of caveats to each of those, and mistakes can be costly, but the fact is that marketers are already using generative tools to 10X their output, and the tools are getting better by the day. Put the right guardrails in place, and you’re off to the races.)

3. Accelerating creation of almost everything

When I go to Creative Diffusion to make some art for a podcast episode, blog post, or social post, I get a result in about 20 seconds. Usually there’s something interesting, but often I’ll finetune my prompt or just regenerate until I get a result that works.

“We’re using Gen AI to start the process of actually ideating,” Ben-Zvi says. “But also most importantly, generating assets at a faster velocity, and generating them for a fraction of the cost.”

That’s art in minutes.

And that’s powerful.

The same is true for translations, for voiceovers, for legit deepfakes (keep reading for kosher use cases!) and much more. Again: employ guardrails to ensure that outputs are quality and won’t damage your brand.

4. Reducing the cost of creative

Whether you’re using Creative Diffusion or Midjourney or a custom model trained to your brand’s look, feel, and standards, it’s pretty clear that when you can create in seconds or minutes, you’re saving bigtime.

5. Localizing ads

This sounds dangerous, right? I mean, screwing up on a translation is a really good way to instantly annoy people that you want to please.

Absolutely.

But … localization isn’t just about text and language. Sometimes it’s about ceviche. Or spaghetti, butter chicken, or Chairman Mao’s Red-Braised Pork.

“We’ve done something with DiDi when it comes to food delivery down in the Latin market, right? We wanted to do something in relation to celebrating national food dishes. So we gave it some direction and we gave the AI some direction in terms of … hey, we want to generate a dish that’s typically known in Mexico, for instance, or in Peru, and we want it to be ceviche, and we want it to show this and give me something with steam and have it fading out.”

Make sense: now you can localize ads with food, or activities, or sports, or clothing, colors, and much more.

6. Voiceovers? Yes, voiceovers.

ChatGPT might not do it but Fliki will not just do text-to-video but also voice cloning and voiceovers. Which means you can do some really cool stuff.

One example I heard recently:

A brand wanted to do something hyperlocal in China. with a big international star. So they used deep faking technology to basically clone the star into a virtual self, and then had him or her say things that were hyper geolocated for their various stores or locations

The result: potentially millions of pieces of creative from this one mega star.

(And yes, if you read above about legal deepfaking … this is what it referred to.)

7. Running better A/B or multivariate tests

We used to run tests on the colors of buttons. Avi Ben-Zvi isn’t impressed by that kind of minutiae, and doesn’t think that significantly moves the needle over time.

Because generative AI can help you make so much more, so much quicker, and so much cheaper, the scope of what you can test vastly expands.

“It’s the type of person you’re featuring, the way you’re featuring the product, obviously things like the length of your video or … voiceovers,” he says. “Is it a male voiceover? Is it a female voiceover? What type of value proposition? Are you testing out different brand messaging in each of these? There’s so many different elements to test within a video. And time again, every study shows, right: with the amount of brands that are out there today, especially direct to consumer brands, users are more inclined to purchase from a brand that they feel connected to.”

Better tests means better outcomes. And better outcomes means more revenue.

8. Delivering 10X more assets

Faster and cheaper?

2 + 2 = 4, and faster + cheaper = more.

Where creative proposals were once accompanied by 8 to 10 different creative elements, now they’re bundling 100 or 200. In other words: 10X’ing creative.

9. Allocating budget

This is always hard, and has a lot to do with measurement, historical results, and future predictions. AI can help here, whether we call it generative AI or not.

“We use something called our budget allocator, which is a predictive model,” Ben-Zvi says. “That’s looking towards the future and saying, okay, if I’m spending $5,000 here, $2,000 here, $1,000 there, what is going to happen to my cost per customer acquisition? What is going to happen to my return on ad spend … and playing with those numbers a little bit to see how the predictive model is going to respond.”

Useful, especially if it’s accurate.

The good thing is that models like these generate a lot of data, and machine learning can process that data and continually refine the model — as long as it’s fed with accurate results data — into future improvements in precision.

10. Creative avatars

Sometimes you need a spokesperson. A real human takes time, costs money, and maybe they’ll pull a Jerod-Subway on you and do something truly horrific that damages your brand.

AI avatars are almost free, and brands can control exactly what they say and do. It may not work for everyone, but there’s definitely a role here for marketing.

Much more on generative AI and marketing in the full podcast (including its impact on measurement)

John Koetsier: How can you use generative AI to turbocharge your ad creative? 

Hello and welcome to Growth Masterminds. My name is John Koetsier. Everyone needs more creative all the time, much more, but building it at scale is hard. It’s challenging. It’s expensive. You need people for it. Can generative AI do the job for you or at least help you somewhat?

To figure it out, we’re chatting with Avi Ben-Zvi. 

He’s Winclap’s general manager for the United States and North America. And works with clients like Shell, Paramount Plus, Rappi, Etermax, Lemon, and MovieStar. Welcome, Avi. How are you?

Avi Ben-Zvi: Great. Thanks for having me, John. Super excited to chat today.

Building with generative AI

John Koetsier: Super pumped to have you. What are you building with Generative AI?

Avi Ben-Zvi: There’s a lot we’re doing here. And ultimately the creative space has long been hampered by the fact that generating those assets can be expensive. It can be timely. It could be difficult to start the process from start to finish.

What we’re trying to do is change that trend right now. So we’re using Gen AI to start the process of actually ideating, helping us ideate, but also most importantly, generating assets at a faster velocity, and generating them for a fraction of the cost, whether it’s assets that don’t have humans in it, or even you actually using humans as well. And avatars that are replicating what creators are typically doing in something like a TikTok video that you’ll see, and it’s definitely a new frontier that we’re excited to explore.

Making your own style

John Koetsier: Super interesting that you’re talking about avatars and that brings up interesting points, right?

Because a lot of games have characters or they have a look, they have a feel, right? And so if you’re going to use a generative AI solution, you can’t just go to Midjourney or Creative Diffusion or Dall-E and say, blah, blah, blah, prompt and get what you want necessarily. You’ve got to give it a style.

You’ve got to give it some training. You might say, here’s a, here’s some images. How did you do that?

Avi Ben-Zvi: Yeah, absolutely. So that’s when our team has the human element, right. And the understanding to say we understand what typically works with this advertiser. We’ve done some creative testing in the past … here are some scripts to potentially work off of. Here are some ideas of the ways we want to approach this. 

So, for instance, we’ve done something with DiDi when it comes to food delivery down in the Latin market, right? We wanted to do something in relation to celebrating national food dishes. So we gave it some direction and we gave the AI some direction in terms of … hey, we want to generate a dish that’s typically known in Mexico, for instance, or in Peru, and we want it to be ceviche, and we want it to show this and give me something with steam and have it fading out and doing all these different things. Right? 

So we’re giving it that direction. We’re iterating off of it, and then we’re pulling in all the other things that we want, like a voiceover.

Or text in the background that we want to potentially test highlighting the national day or highlighting the dish itself, whatever it is that we can then AB test, whereas in, if you’re doing that all with the human element, it’s a lot to go in and create those things to professionally shoot that to even source the dishes in that example.

In this case, we’re able to do it all within the clicks on the computer. And then also add different variables so we can actually AB test, which is what every performance marketer is actually looking for.

Voiceovers in multiple languages

John Koetsier: Absolutely. So it sounds like you’re using it as part of the process with the people you already have.

Is there a piece where there’s just, it’s just surprised you it’s created something that you didn’t know that you needed, didn’t know that you wanted, but you saw it and thought, whoa. That’s amazing.

Avi Ben-Zvi: I think there’ve been a couple areas. I think one of the most interesting use cases I’ve seen set for it is in international businesses, right?

To have an avatar speak … one avatar speaking many different languages, I think is truly amazing. And so you’ll have it in English, then French, then Portuguese. And especially in a world where everybody’s focused on being globally enabled, that’s really important. And it’s really hard to do that with just the human element.

And here we’re able to do it fast and at scale, purely through these avatars. 

And I see it, I’m like, problem solved. Unbelievable.

John Koetsier: You’ve discovered the digital influencer, the digital star, the digital hero. There was a story I heard, I guess it’s about three weeks ago now about a star in China, and they wanted to do something hyper local with this big international star.

And they used deep faking technology to basically clone this individual into a virtual self and then say things that were hyper geo located for their various stores, locations, whatever it was all over the country. So there’s literally a million pieces of creative from this one mega star.

Multiplying creative

Avi Ben-Zvi: That’s amazing.

It’s truly amazing that you’re able to do that and a lot of the proposals that we’ll put in front of our advertisers — now with human based creator influencer content, we can maybe start with pure human, and then as we look to scale that and get more assets, that’s where we’re going to, when we’re going to lean into that generative AI aspect.

And it’s going to go from, Hey, our proposal has eight, 10 different assets to a hundred, 200 different assets, which was a world that was nearly impossible to think about before when you had the creator/influencer marketing things starting to become a major focus for paid marketers. But now this is becoming a reality where you can do that.

And especially as creative as the star of the show, when it comes to marketing right now, it’s really hard to achieve great performance and a lot of the other variables like audience, algorithmic bidding, whatever it is, you really need to focus on creative. So especially as creator content is starting to scale and become popular, this is a great way to lean into a performance variable that is increasingly important in the market.

John Koetsier: The possibilities are amazing. 

Hey, you can get The Rock and say, Hey, come on down to this place in this neighborhood in Caracas, Venezuela, or something like that. And there you go. Boom. You’ve got him.

Prompt engineer or just creative worker?

There’s a bit of a debate in the generative AI world about, do you call it prompt engineering or is that maybe too high a level? Where do you fall on that? Is it a prompt engineer or is it just, you’re asking the AI for stuff.

Avi Ben-Zvi: Well, I think it’s a balance prompt engineer is probably underselling it a little bit because I think it’s got to be a lot more than that. The human element is still really important.

I think even if we go back to before AI, automation in general has become a thing, but even as automation has started to escalate. You still need that human element for the strategy for driving things forward in a more innovative way. And I think that’s still the case here. And like I said, having that historical knowledge, haven’t done testing before.

So yes, you’re leading the prompts and that’s where prompt engineer comes from, but you’re going even further than that. And you’re understanding the nuances at a much deeper level than just simply saying, I need something like this. Give me something like X, Y, Z. You’re going much deeper with it.

And especially when you eventually end up pairing that with smart measurement tactics, that’s when you can go even further into those nuances to develop the right types of generative AI creative.

John Koetsier: Let’s hold those measurement tactics for a moment because I want to get into those, understand those, and I’m interested in those that are sometimes in — I want to say in the creative in terms of how long somebody is looking or engaging or watching or playing or something like that — as well as what happens after the creative, let’s hold those for just a second.

Generative AI technologies

I want to ask about the technology you’re using. Did you grab something open source? Are you using Creative Diffusion, Midjourney or using something different … using something you created yourself?

Avi Ben-Zvi: Yeah, we were definitely tapping into some of the third parties out there and there’s a lot of good stuff.

We’re certainly using Midjourney for images, for videos. We’re using something called Fliki for voiceover, which I think is super great also. People often forget about the voiceover element, which can be great because you can have assets you’ve already generated and then you’re adding just that influencer creator element on top simply using voiceover.

And even getting those scripts out there and working just within the ChatGPT to ensure that it’s relevant and it’s spot on with what we need, but it’s amazing. We just needed a couple of our key points to hit on and it can really get us a great starting point for our teams to build off of and get even more creative.

John Koetsier: It’s … if you just sit back for half a second and you put yourself in the mindset of two years ago and you just replay what you just said, this is insanity, right? It’s amazing. It’s literally almost incredible because of the creative toolbox. has evolved so much and so quickly.

You just labeled off like four or five different AI solutions that are part of your workflow, popping in at different parts for video. AI generated video that’s pretty cutting edge for your stills, for your voiceovers, all this stuff for your text, for even for the ideas itself … That’s a massive shift. And you know what? We don’t even really have the like out of a box tools or out of the box suite for gen AI yet. We have some stuff, right? Adobe’s got a few things, but a suite that pulls it all together. We haven’t seen it yet. It’s still very early days.

Early days for generative AI

Avi Ben-Zvi: Yeah it’s super early.

And you mentioned this seismic shift within the industry. I’ve been working in digital for 13 years now. And as creative has become more important, it’s become harder and harder — I think — for marketers to develop creative, that’s really good. And the key element of really good, I think, is the creative in creativity has often been lost.

And I think here, because you can do variations so quickly, and you can do much more testing, we’re getting that back. But that’s why the human element is certainly important too, because it drives a lot of that creativity. You could just do it faster now and you can test out different ideas.

Whereas before … you’re getting killed on budget. You’re getting killed … like I need this asset tomorrow. I don’t have time to generate something that’s super out of the box or going to really transform the way people think about our brand. And now you can actually do some of those things and be a little bit more creative when it comes to your creative, which is great.

But yeah, I think we’re just at the tip of the iceberg. Like you said, go back 2 years … we’re not really talking about any of these things. So I’m excited to see how this develops and how advertisers start to approach this in a really scalable way because we’ve just started this process.

John Koetsier: 13 years of working in digital? Clearly you started at 10!

So I had that all my career as well. Hey, it’s a good problem as we age, so that’s all good. 

Marketing measurement and generative AI

Let’s get into some of the measurement stuff. Tell me a little bit about the measurement technology you’re using and tell me a little bit about some of the early results you’re seeing in terms of, are you seeing better CTR?

Are you seeing improved conversion rates? Are you seeing … better … What are you seeing, how are you measuring and what are you getting out of it?

Avi Ben-Zvi: Yeah, absolutely. So there’s a variety of different ways. You mentioned it earlier. There’s certainly the in-platform stuff, CTRs, conversions based on a pixel that’s in the particular platform that you’re advertising on. 

We’d like to take this to the next level though, because for a lot of these consumer journeys, this isn’t just a sort of last click type of play. This is an engagement play. This is them getting adept at interacting with the brand. So we’re doing things like incrementality testing, doing something like geo holdouts, right, to understand when we’re going live with this particular creative in a given market. Are we actually starting to see more sales come through? And the key word being there, sales, not media conversions. Are we actually seeing sales come through? Is this really driving a true business impact? 

So making sure that you’re tying back this creative testing towards something that’s real intangible from a business perspective, the sort of second piece to that is tech and what we’re building there to make sure that you are optimizing your media throughout.

So speaking of AI, we use something called our budget allocator, which is a predictive model. That’s looking towards the future and saying, okay, if I’m spending 5,000 here, 2,000 here, 1,000 there, what is going to happen to my cost per customer acquisition? What is going to happen to my return on ad spend and playing with those numbers a little bit to see how the predictive model is going to respond.

But another form of AI … in the measurement section to help us go out and scale and achieve efficiency from the outset.

The evolution of creative testing

John Koetsier: Nice. Very nice. Okay. So generative AI is changing a lot. Are you seeing any other changes or evolution in the creatives for mobile ad tech right now?

Avi Ben-Zvi: I think there’s a lot of changes as it comes to here.

Well, if I look back three, four, five years, The big sort of creative change was always like a change of background color, is it pink? Is it blue? Is it green? Is it black? Right? And everything else stayed the same. That was like the way performance marketers interacted with the world back then.

And I’m not sure that kind of stuff works. Maybe it does to a certain extent, but I think it actually caps at a wall with the way with how complex the digital media landscape has become and how complex the consumer journey has become within that digital media landscape. There’s so many touch points to being hit with ads and different organic journeys, and they’re on countless apps compared to 5 years ago, right?

So I think just how savvy creative has become or needs to be is a massive change in the industry from where we were four or five years ago.

John Koetsier: What does that mean? So let’s say that five years ago: let’s make the button red, let’s make the button green, which one performs more? AB test! Multivariate!

Okay. So that’s where we were. We were taking baby steps. So what’s the next evolution that you’re seeing? It’s not just the background or the color of the button. Are they totally different things? Is it totally out of left field stuff? And we’ll just throw stuff out there and see what happens. What is it … is it an evolution of the brand story?

Avi Ben-Zvi: I think it’s like all the above, right? It’s the type of person you’re featuring, the types of the way you’re featuring the product, obviously things like the length of your video or let’s look at like voiceovers. Is it a male voiceover? Is it a female voiceover? What type of value proposition?

Are you testing out different brand messaging in each of these? There’s so many different elements to test within a video. And time again, every study shows, right? With the amount of brands that are out there today, especially direct to consumer brands, users are more inclined to purchase from a brand that they feel connected to.

And they’re going to connect more to a brand that’s honing in more on what really works. as opposed to a brand that’s just trying to click convert right away. And that’s why at Winclap, we’re very focused on this sort of growth transformation story. And that’s really about sustainable, profitable growth, not like that quick hitting, let me just acquire a customer for one time.

It’s developing that connection with a particular consumer.

Customer journeys, MMM, and device identifiers

John Koetsier: I found it interesting that you’re talking earlier about the customer journey, and you mentioned it now, just as you’re talking about the complexity of the customer journey. And three years ago, five years ago, if we’re talking about the customer journey, we’d be talking about lots of measurement, customer data points, touches, cookies, IDFAs, GAIDs, all that stuff, right?

And some of that still remains relevant, but what you talked about earlier was basically triple M, lift, incrementality, right? And that is the new way of measuring. It’s not as precise, but it’s actually in some senses more accurate because you’re measuring actual full on complete results. Did I, did my sales improve?

Did my bookings improve? Do I have more subscriptions? All that stuff and then somehow all these different factors played a role. That’s an interesting transformation as well.

Avi Ben-Zvi: Yeah, I think so. You’re just seeing, right, that there’s, it’s hard, it’s getting harder to think about how you’re going to measure your media and the effect and the impact of your media four or five years ago, I think, you look down and people could get away with being very last click focus, even though we’ve known for a long time, that’s an imperfect understanding of the way a user interacts with the world, but they could get away with it and they could be successful.

Look at the amount of direct to consumer companies who built their business off of a pure Meta-then-Facebook acquisition strategy that was driven by something like that type of measurement, and I think today … complexity, the privacy changes, all that has obviously shifted how users interact with the world and also how brands can measure the efficacy of their media.

So you have to be a little bit more strategic when it comes to that on the flip side of that. I’ve seen brands who are also like, hey: I know measurement is imperfect period in digital, and like, I’m just gonna let go of measurement. I’m going to do things that are purely engagement focused, and I’m just going to measure, do I see lift in my sales?

And I know a very popular new-agey soda brand that takes that approach to TikTok and they’ve seen incredible success and they haven’t been hampered by finding the perfect measurement model and figuring that out before they go out in scale,

John Koetsier: There is no perfect measurement model. Everything that you can measure has some value, some more than others.

But yeah, ultimately does it result in growth of the brand and growth of sales? Very interesting stuff. Thank you so much for this time, Avi.

Avi Ben-Zvi: Yeah, thank you for having me, John. It was great.