Digital Marketing Institute | AI with DMI | GA4 and AI
Summary
TLDRThe conversation explores the future of marketing, emphasizing the integration of AI and human-centric experiences. It discusses the shift from text-based inputs to more intuitive methods like voice commands and visual cues, and the challenges in measuring these interactions. The speakers highlight the potential of AI to enhance scalability in marketing, with a focus on privacy concerns and legal considerations. They also touch on AI's role as a 'sounding board' for problem-solving and its ability to process large data sets for insights, suggesting a future where AI and human collaboration drive marketing innovation.
Takeaways
- 🌟 AI is becoming central to the future of marketing, particularly in optimization and improving marketing effectiveness.
- 📈 GA4 (Google Analytics 4) is designed to measure human use of websites as utilities for completing tasks.
- 🚀 The next generation of marketing will focus on the humanization of marketing, utilizing all human faculties and senses.
- 🔍 Search experiences will evolve from text inputs to more interactive elements like images, voice, and gestures.
- 📊 Measurement tools like Google Search Console and Google Ads will need to adapt to capture these new forms of interaction.
- 🤖 AI will play a significant role in handling the complexity of optimizing against these new types of inputs.
- 📈 AI adoption in marketing will likely be gradual, with early adopters leading the way and the majority following over time.
- 🔧 AI will be used for scalability, helping to evaluate optimizations and decision-making in marketing, especially for SMBs.
- 🔒 Privacy concerns and legal considerations are major limitations for AI use in marketing, requiring careful handling of client data.
- 🛠️ AI can serve as a sounding board for problem-solving, providing unexpected solutions and insights from data analysis.
- 📊 AI's ability to process and analyze large data sets, such as spreadsheets from social media and keyword tools, is a valuable asset for digital marketers.
Q & A
What is the future of marketing effectiveness and optimization?
-The future of marketing effectiveness and optimization is heavily influenced by AI, Search Generative Experiences, and the humanization of marketing, which involves using all human faculties and senses in the search and interaction process.
How does GA4 measure human use of websites?
-GA4 is designed to record how humans use websites by focusing on the tasks they complete, such as pressing buttons, watching videos, or performing other actions, treating the website as a utility.
What are the next generation inputs in marketing?
-The next generation inputs in marketing will move beyond simple text inputs to include more human attributes like pointing, looking, and vocalizing, which will change the way we interact with search engines and other platforms.
How will the measurement of Search Generative Experiences (SGE) be handled?
-SGE will be measured through tools like Google Search Console, and the new AI-powered Google Ads will be measured through Google Ads itself. These tools will feed back into GA4 to present the nature of user interactions.
What challenges does AI optimization in marketing present?
-AI optimization in marketing presents challenges in understanding what exactly is being optimized against, as traditional keyword-based optimization is replaced by AI-driven approaches that may not be as straightforward to measure or understand.
How will AI impact the adoption of new marketing technologies?
-AI will initially do the heavy lifting for early adopters, serving as a test case for the technology. However, it will take time for these technologies to become mainstream and fully integrated into the consumer psyche.
What role will AI play in scalability for NP Digital's SMB division?
-AI will be used to help evaluate optimizations and decision-making, providing scalability by automating tasks that would otherwise require more human resources. This will allow NP Digital to service clients more effectively, similar to how they would service enterprise clients.
What are the privacy concerns when using AI in marketing?
-Privacy is a major concern when using AI in marketing. There is a risk of releasing client information by putting their data into AI platforms, especially if the platforms' terms state that any input becomes open-source data. Legal teams are working on guidelines for the safe use of AI in this context.
How does AI assist in data analysis and decision-making?
-AI can serve as a sounding board for data analysis, allowing marketers to input complex data sets and receive insights that might lead to unexpected solutions. AI's ability to process and analyze large amounts of data can help identify patterns and trends that may not be apparent to human analysts.
What are the limitations of AI in marketing?
-Limitations of AI in marketing include privacy concerns, legal precedents, and ensuring that AI tools do not violate client data privacy. Additionally, there is a need for a balance between AI's capabilities and human oversight to ensure ethical and effective use of the technology.
Outlines
🌟 Future of Marketing and AI
The first paragraph discusses the future of marketing, emphasizing the role of AI and Search Generative Experiences (SGE). It highlights the shift from traditional text-based inputs to more human-like interactions, such as voice commands and visual cues. The speaker predicts that the next generation of marketing will focus on humanizing the experience. They also mention the challenges of measuring these new forms of interaction, especially with tools like Google Search Console and Google Ads. The conversation touches on the potential for AI to take over optimization tasks, with a cautious approach to privacy and legal considerations.
🤖 AI in Data Analysis and Scalability
The second paragraph delves into the practical applications of AI in data analysis and scalability within a marketing context. It discusses the hiring of an AI specialist and the exploration of various AI platforms for automating tasks and providing actionable insights. The speaker expresses concern about privacy and legal issues related to AI, mentioning the importance of working closely with the legal team to ensure compliance. The conversation also explores the use of AI as a sounding board for problem-solving and the potential for AI to handle large datasets, such as spreadsheets and social media analytics, to uncover unexpected solutions.
Mindmap
Keywords
💡AI
💡Search Generative Experiences (SGE)
💡GA4
💡Humanization of Marketing
💡Inputs
💡Optimization
💡Google Search Console
💡Google Ads
💡Scalability
💡Privacy
💡ChatGPT
Highlights
The future of marketing is heavily influenced by AI and Search Generative Experiences.
Human use of websites is shifting from text inputs to more interactive methods like voice, images, and gestures.
GA4 (Google Analytics 4) is designed to measure how humans use websites as utilities.
The next generation of marketing will focus on humanization, integrating all human senses and faculties.
Measurement of new AI-powered marketing tools like Google Search Console and Google Ads will be complex.
AI will take over some of the heavy lifting in marketing, especially for early adopters.
The adoption of AI in marketing will take time to become mainstream.
AI's role in marketing will evolve, with a focus on scalability and decision-making support.
NP Digital is exploring AI to evaluate optimizations and decision-making, aiming for scalability.
AI's potential in marketing includes acting as a sounding board for problem-solving and generating unexpected solutions.
AI can process and analyze large spreadsheets of data, providing insights for digital marketers.
Privacy concerns and legal considerations are significant limitations for AI in marketing.
AI's ability to handle and analyze data from various platforms like social media and keyword tools is valuable.
ChatGPT can be used to analyze data from social listening tools and keyword tools.
AI's constant availability allows for continuous problem-solving and the potential for eureka moments.
AI's role in marketing is not just about finding expected solutions but also uncovering unexpected ones.
The integration of AI into marketing tools like Google Ads and Google Analytics is being explored for more accurate measurements.
Transcripts
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?
Yeah.
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
true.
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.
So how are people searching?
How are people using YouTube?
How are people using the search engine?
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?
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?
So...
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.
Chris, what do you think the future of measurements and insight and optimization
look like in marketing?
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.
What kind of tools is she likely to deploy, do you think?
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,
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.
Yeah, absolutely.
What about you, Cathal?
What do you see, how do you see AI helping us in the analysis?
Are you using like ChatGPT's data analysis functionality much practically?
Great, you know, I actually see it as a sounding board and I'll explain it like
this.
So did you ever have a problem you're trying to solve and you ask someone and
you say it out loud and then you solve your own problem?
Through the kind of layered prompting of things like ChatGPT and other chat based
stuff You can have those eureka moments like you are Archimedes jumping out of the
bath and running down the street of Athens going Eureka.
I'm after coming up with this amazing, amazing solution here.
So what AI allows you to do is use it as a sounding board.
Now this is not something a lot of people are kind of talking about.
They're kind of, you know, they're going on journeys and they're kind of coming to
the expected solution.
But what about the unexpected solution?
And this is what I'm most interested in when it comes to AI because unlike your
colleagues who want to finish work at four o'clock or five o'clock on a Friday, AI is
always there.
And it will always answer your questions, and continue to answer your
questions and your layered questions, giving you the ability to use it as a
sounding board.
And again, have those eureka moments.
So that's what I've been using AI for a little bit.
See what I love, I love the fact that you can drop spreadsheets into ChatGPT, that's
one, that's probably the file type I feed it most.
I love the fact that if you export analytics from social media, insight
tools, social listening tools, keyword tools, that's when it does interesting
stuff.
I don't think you should be saying to ChatGPT, hey ChatGPT, give me a keyword,
you know, list of keywords, that's not it.
What you wanna be doing is taking real data
and big heavy spreadsheets that would take a lot of wading through and say, here you
go, now tell me stuff about this.
And I find it's actually in general, very good at doing that.
I think that's one of its most interesting applications.
anything that can eat up spreadsheet data is like it's gold dust for digital
marketers
Google Analytics?
I have not tried that, but have you ever tried Google Analytics or Google Ads
reports, feeding it that sort of stuff?
done some Google Ads reports, there's always a little bit of bias in that, so
you know, you take everything with a pinch of salt, but I haven't done any Google
Analytics stuff, but certainly Google Ads stuff, just because I typically focus most
of my attention in on Google Ads itself.
You
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