Mar 1, 2024

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Episode 11: GA4 and AI: Shaping the Future of Optimization

by Christopher Coomer

Posted on Mar 1, 2024

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In this episode of AI with DMI, Chris Coomer of Neil Patel Accel and DMI expert Cathal Melinn explore the future of AI-driven marketing optimization in the context of GA4. In conversation on the podcast with Will Francis, they touch on:

  • The shift towards utilizing human attributes in marketing strategies.
  • How AI can aid in evaluating optimizations and decision-making.
  • Concerns regarding data privacy and the responsible use of AI.
  • The evolving role of AI in measuring and improving marketing outcomes.

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Video Transcript

Will: You know, if we start to look towards the horizon and what might, you know, the future of this stuff might look like, what kind of things are we seeing emerge there in that realm of optimization and improving our marketing effectiveness?

Cathal: Yeah, so as everything, it's all AI. And Search Generative Experiences and all these things. So what I think, and this is where I keep using this word human. So like the human use of a website is, I'm using it to complete a task. And that's what GA4 is set up to measure. I am going to use a website as a utility. I'm gonna press a button, I'm gonna watch a video, I'm gonna do something, but ultimately I'm using it as a utility.

What GA4 tends to do is record how humans use websites. Now the next generation of marketing is going to be, in my mind, the humanization of marketing. So we're using all of our faculties and all of our senses to do things like search. So with search, it would have been an input to get a result. So a text input to get a result. You know, that was our single input was a text input. Our next inputs will be things like, I'm going to circle this picture or I'm going to point at something or I'm going to use my voice. It's all of our human attributes that we're going to use so the inputs are changing. The inputs are changing from those simple straightforward text kind of inputs to a point or a look or like something you vocalize so the measurement of that is going to be tricky I have to say. I think that you know, we're going to see some very interesting developments in these kind of linked products which Chris has talked about like Google Search Console or Google Ads because they're ultimately on the front line in terms of collecting that first-party interactions with Google so SGE will be measured through Search Console. The new AI powered Google Ads will be measured obviously through Google Ads. Those integrations will then therefore have to feed back into GA4 and present what those inputs actually look like.

Will: But it's tricky that isn't it? Cause it's, you know, if you're optimizing in sort of very old traditional world, you buy against some keywords, well you can optimize for the keywords that perform better. And the more you put that in the hands of AI, then the more you have to put the optimization in its hands as well, because you don't really know what you're optimizing against anyway. You just say, you know, you started off by just handing over your money and saying, do your thing. So is it just sort of where, does that just lead to a giving up, just basically passing off far more of that work to AI, do you think that will happen quickly over the next year or two?

Cathal: Yes and no depends on how people are using it. So, like all these things take time to kind of get a foothold in the consumer sphere. So for example, like with ChatGPT, it sent everyone into tailspin when it was launched, but Bing still only has 5% market share. You know, so it takes a while for these things to really kind of ground themselves in the customer psyche. So how are people using these?

I do think that AI will for a while do a bit of the heavy lifting for those kind of early adopters and that's what we'll use as our test case and then we'll have a better roadmap for what's coming next but the majority of people are probably not going to be doing all the supercharged things that the SGE and all the kind of AI-powered technology can do in any time soon, you know, so we've a bit of time before we see it happen.

Will: Yeah, sure, yeah. Chris, what do you think the future of measurements and insight and optimization look like in marketing?

Chris: I think we'll see scalability through AI for sure. So I mean, at NP Digital, what we're going to be exploring this year is using AI to help us evaluate optimizations and decision making. So the SMB division of NP Digital and PXL, we have 500 clients. So the biggest challenge in terms of revenue opportunity for us and just making sure that we're servicing the clients the way that we would service an enterprise client is essentially having either scalability or more people. So I evaluate, I kind of see the idea of AI taking over on that scalability. I mean, I just hired an AI person on our team that will be starting in about two weeks. And she, our goal to come in is I was like, I'd like you to evaluate paid media opportunities, use AI to make actionable insights, you know, take that optimization, take that data and see if AI can do the same thing that our analysts are doing. Side-by-side comparison.

Will: What kind of tools is she likely to deploy, do you think?

Chris: Oh, Lord knows. I mean, I, yeah. Well, I started looking at, you know, I'm not an AI person. I love the concept of it, but like my Python skills are at best, like mediocre compared to my team members. Thank God they're good. Um, but yeah, she, we can script in Python to create automation and, and evaluate the data that's coming through. So she gave me about 30 platforms that she's decent in. Um,

That's her job. I'm quite sure she's a human computer at this point. But some things I'd never even heard of. And she's like, oh, yeah, absolutely. When we were doing these data science operations, we were doing blah, blah. And I was using this platform. I'm Googling this platform as we speak. I've never heard of it. And I was like, this is incredible. So I imagine that we're going to go into each of these platforms and kind of evaluate how they work. We work really close with our legal team because the big concern about AI is privacy.

And just making sure that like while we're utilizing the platform, we don't want to release client information by putting their data into a platform. Some of them have in their terms like when you create an input, when you put anything into our data platform, it becomes open source data. So we're really cognizant of that. We're very careful about it. So I know that our legal team's just coming out with our AI initiative, what we can and can't use, how we can and can't use it, and what we're going to do.

Limitation I think for AI. In addition to what Cathal is saying, privacy obviously being the biggest concern, you know, there's going to be legal precedent, making sure what can and can't be used and how it can and can't be used. And we'll be on top of that. We have an amazing attorney that was a computer science engineer, and went from making video games to being a lawyer. So love his input, looking forward to seeing what we do with that. But I'm hoping that AI is careful to protect users' data so we can utilize it better on our end.

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Christopher Coomer
Christopher Coomer

Chris is a results-driven VP of data, analytics, and business intelligence driving data management, analytics strategies, and technical architecture to scale optimized enterprise operations. As a trusted advisor and strategic business partner, Chris develops meaningful data insights and infrastructures through business intelligence and data analytics strategies to optimize business functions and drive impactful ROIs. Chris is also an enthusiastic and passionate educator in the field of data and analytics and marketing at The University of Tampa.

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