Employing A Powerful AI-Driven Marketing Strategy

President and GM - North America at AppsFlyer, Brian Quinn, delves into the realm of employing a powerful AI-driven marketing strategy. By leveraging advanced measurement, data analytics, deep linking, engagement, fraud protection, data clean room, and privacy-preserving technologies, AppsFlyer assists brands in making informed decisions for their business and customers. Show NotesConnect With: Brian Quinn: Website // LinkedInThe MarTech Podcast: Email // LinkedIn // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

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  The Martech Podcast is a proud member of the I Hear Everything Podcast Network. Looking to launch or scale your podcast? I Hear Everything delivers podcast production, growth and monetization solutions that transform your words into profit. Ready to give your brand a voice? Then visit iheareverything.com.

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  From advertising to software as a service to data, across all of our programs and clients, we've seen a 55% to 65% open rate.

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  Getting brands authentically integrated into content performs better than TV advertising.

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  Typical lifespan of an article is about 24 to 36 hours.

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  If we're reaching out to the right person with the right message and a clear call to action, then it's just a matter of timing.

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  Welcome to the Martech Podcast, a member of the I Hear Everything Podcast Network. In this podcast, you'll hear the stories of world-class marketers that use technology to drive business results and achieve career success. Here's the host of the Martech Podcast, Benjamin Shapiro.

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  Welcome to the Martech Podcast. I'm your host, Benjamin Shapiro, and today we're going to discuss AI-driven marketing and attribution. Joining us is Brian Quinn, who is the President and GM of North America at AppsFlyer, which provides advanced measurement, deep engagement and privacy-preserving technologies, empowering creators and technology partners to enhance customer relationships. And today, Brian and I are going to discuss how to employ a powerful AI-driven marketing strategy. All right, here's the first part of my conversation with Brian Quinn, the President and GM of North America for AppsFlyer. Brian, welcome to the Martech Podcast. Thank you, Benjamin.

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  Good to be here.

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  Very excited to have you here. I wanted to start off with our first topic, which is generally the landscape shift for this year. We've all heard ad nauseam about the impact that things like ChatGPT, OpenAI, Perplexity, Amazon, Google, we're all getting into artificial intelligence. And you sit in the catbird seat with an immense amount of data, specifically focusing on mobile is my understanding, for what the impacts have been in terms of product adoption and usage. So tell me a little bit from your perspective, what do you think the major impact of artificial intelligence has been on marketing?

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  Like you said, big topic. It feels like every conversation and every conference is now an AI conversation and an AI conference, and it's on every agenda. So I feel like it's talked about a lot. It's being tested and used and experimented in a variety of aspects within marketing, across marketing operations. And we see some scaled uses of it in products, in analytics, in personalization, and I can go into those. But for the most part, from the CMOs that I talk to across different categories and industries and different company sizes, I think we're still in a stage of a lot more sort of testing and talking

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  than we are seeing real tangible change in operations and business strategy for the most part. So I still feel that there's a lot of talk, there's a lot of personal experimentation with the tools, crafting, writing and brainstorming. But the ability for businesses that we work with and that we talk to that have genuinely changed strategy at scale because of AI, I think we're not quite there yet. I think we're still looking for that.

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  Tell me a little bit about the general tenor of the conversations you're having with marketers, specifically CMOs. When you're talking to the leaders of marketing, are they generally positive, excited, terrified? It seems like there's a lot of change. How do the heads of marketing broadly feel about the shift that we're going through?

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  I would say in general, marketing is really leaning in and excited about this. I think the benefits of efficiency, of personalization, of the ability to glean insights from your analytics in a quicker fashion is very exciting. There's other roles in the company that are probably more suspicious, skeptical, worried. But I would say in general, I feel marketing leans in, wants to be on the cutting edge, wants to demonstrate that they're leveraging this and experimenting. I think also executive teams and boards are asking chief marketing officers for their plan. What is the AI plan for the organization, for your business unit? So they're sort of being asked to produce, whether that be from solution providers or

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  internal modeling or internal efficiencies, how is AI driving the business? So I think that there's a kind of a combination of interest and lean in and also sort of them being asked on how it is expected to drive business results. But I would definitely say that the marketers are leaning in.

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  I've heard different opinions that in its current state, artificial intelligence, large language models are useful for a couple of things. One of them is data analysis, obviously copyrighting. Measurement and analytics isn't something that I really feel like artificial intelligence has done a ton for. Can you talk to me a little bit about the impact artificial intelligence has had on businesses like AppsFlyer and how is that impacting marketers' strategies?

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  You know, I think to set the stage for this, a lot of this new generation of generative AI models are well-suited when you have lots of data and it doesn't have to be perfectly accurate. And I think that broadly, when you look at advertising and marketing, you got a lot of data, a lot of touchpoints, a lot of conversion events. So you can learn things very quickly and you can feed the models very quickly. And it's marketing. At the end of the day, it's not law, it's not medicine, it doesn't have to be perfect. So these hallucinations or these imprecise outputs are sort of tolerable. So I think this is why you see a lot of innovation. I think you see, like you mentioned, in copyrighting and content generation, you see a lot of testing. When it relates to AppsFlyer, I can give you a couple of areas where we've invested.

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  And where we're close to our customers, parts of their operation where they're really leaning into this. First and foremost, a lot of the capabilities, measurement and the tools that we develop can be supercharged with AI models and some of them have existed for years and AI and the new kind of versions of AI actually make them more powerful. Fraud detection and prevention is an example. For many years, we'll take a global data set of mobile installs and mobile engagement touchpoints and we can run machine learning models across that to look for different patterns to understand potentially fraudulent behavior. And then we can block that or we can detect that and signal that to an advertiser.

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  AI models strengthen that. So the more data that we can feed that, the better and the quicker the models are. And AI is also being used by the fraudsters themselves. So it's this cat and mouse game when it comes to fraud. So this is sort of one domain and one use case where AI is really driving a lot of innovation on sort of both sides of that equation. I would also give you an example of the analytics. So we're coming from a world where to really get any insights from an analytics platform, you need dashboards and user interfaces developed. That takes data engineers, that takes analysts to create these capabilities. It takes SQL queries to be developed to tap into these databases.

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  In a recent product that we launched a year ago, we wrapped it with a chat GPT-like interface and how a business user can ask questions in plain natural language about what's happening to the campaign. Tell me about my audience, tell me about my insights. And they can get insights immediately and take action on that. And it's a very different change from the resources and the process of not too long ago. So the ability to extract that in a very human language way, I think is a game changer. The last example I'll give you is an area that we've been investing in, which is related to sort of the creative analytics and creative optimization. So you see a lot of hype, you see a lot of talk around how Gen AI tools allow you to create.

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  And produce ad creatives and copy and content. You hear less about the ability for AI to understand that content and what works and what doesn't. And what drives business outcomes? We've developed capabilities on that side. So we have AI and specifically a computer vision model, which will take a look at a video. And it can break down that video into different scenes, different elements, what parts of the video are distinctive, without any human labeling or work to set this up. And then it will tell a marketer what aspects of video, what scenes, what order, what combinations, will drive the best outcome across all their campaigns, across all their networks. This just wasn't possible two years ago.

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  So we see AI embedded in our products. We see AI enabling better insights and actionability from an analytical perspective. So I think these are just kind of a few examples of where it's touching our business.

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  It seems like the challenge in the current stage of marketing is how to get around the mind-bendingly broad adoption and possibilities of what you can use this new technology for. And, you know, I liken the rise of artificial intelligence to the launch of the Apple App Store. I think of it as the, this is this generation's iPhone moment, where it's like, this is a 25-year adoption curve to really let this technology sink in, adopt. And we're seeing some early movers and some traction and some success. But the people that are the most successful adopting that are the ones who are able to think of the creative ways to leverage the technology.

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  Like you said, you are uploading a video and having it say, here's what's interesting and creative about this video. I've created essentially a personal assistant to help me with business strategy. So I can figure out what I should be doing on a weekly basis to help lead my team and create better content and products. Is there any sense of how people are using the technology the most? Or what has been the most effective? I guess really the question here is what data do you have? Or what have you heard in terms of how people are evaluating the usage of AI? And what's actually working and driving them to feel like it is helping business, not serving as a distraction?

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  I've seen some frameworks that have been developed around what type of organization, what size, what function, and where specifically generative AI tools and models are finding success. So I think there's becoming some organization around that, some frameworks that help companies sort of understand and give some clarity there. I think there's a tremendous amount of testing happening and people are still looking for that. When we see generative AI models embedded in SaaS products that are developed in a distribution model to scale and to connect to internal data sources and are already living in an infrastructure, I think we see great success. And what I mean by that is, there's a ton

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  of innovation, and I'm sure I'm only seeing a fraction of it, but there's a ton of innovation and startups that are coming to market that are targeting CMOs, they're targeting marketing departments, they're wrapping themselves in SaaS or cloud business models, and they're a new AI something. And a lot of them are interesting, and many of them are point solutions, they're meant to solve a specific problem. We see a lot of testing. Feedback I constantly hear from marketing executives are, this has to live inside of some system. This can't be a standalone point solution on an island and expect to get adoption and scale. So what system of record is this plugging into? How can I feed this, my own first-party data,

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  safely, confidently, for it to sort of scale? And I think these are some of the challenges we see. We see a lot of testing. I imagine we're going to see a lot of churn in AI-enabled software products, you know, in the coming months. I think we've already started to see it because while it may solve a particular problem, it's not really housed anywhere. It's not sitting in a core system. And there's a constant need to consolidate tools, unify first-party data sets, look at, in our world, measurement across lots of platforms in a single view. So if these innovations aren't homed somewhere, if they're not housed and connected, then I think it's going to be very hard to sort of get that operational scale that they're hoping for.

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  Here's my takeaway from this conversation is that artificial intelligence can be overwhelming. It can be distracting. It can be additive. Often what we're finding from the executive levels is that marketers tend to be very positive about artificial intelligence. I feel like it can continue to grow our business, to help us scale as marketers, to reach more people, to do better, to do more with less. But it has to be built off of the back of something. You have to leverage your first-party data, use your internal systems of record, and build on top of the business that you already have to make your artificially intelligently driven marketing strategy successful. And that wraps up this episode of the Martech Podcast.

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  Thanks to Brian Quinn, the President and GM of North America, for AppsFlyer for joining us. If you'd like to get in touch with Brian, you can find a link to his LinkedIn profile in our show notes, or you could visit his company's website, which is AppsFlyer.com. Just one more link I'd like to tell you about. If you didn't have a chance to take notes while you were listening to this podcast, head over to martechpod.com where we have summary of all of our episodes and contact information for our guests. You can also subscribe to our weekly newsletter, and you can even apply to be a guest on the Martech Podcast. Of course, you can always reach out on social media. Our handle is @martechpod on Twitter, Instagram, and Facebook, or you can contact me directly on LinkedIn. My handle is Ben J. Schaap. And if you haven't subscribed yet, and you want a daily stream of marketing and technology

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  knowledge in your podcast feed, we're going to publish an episode every day this year. So hit the subscribe button in your podcast app, and we'll be back in your feed tomorrow morning. All right, that's it for today. But until next time, my advice is to just focus on keeping your customers happy.

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  Thanks for listening to the Martech Podcast, an I Hear Everything production. Looking to launch or scale a podcast like this one for your brand? Then visit iHearEverything.com.