Vibe Analytics: The End is Nigh for Analytics Tech? Brett and Rio chat with Adam Greco.

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What if dashboards are dying—and analytics is about to feel more human? In this episode of Signal & Noise, hosts Brett House and Rio Longacre sit down with Adam Greco, one of the most influential voices in digital and product analytics, to unpack a provocative idea: Vibe Analytics.

Adam—former Omniture and Amplitude leader and current Product Evangelist at Hightouch—argues that the future of analytics won’t be defined by dashboards, SQL queries, or rigid reporting tools. Instead, it will be driven by natural language, AI-powered interfaces, and warehouse-native architectures that let teams ask questions the way humans think.

Together, we explore:- What “Vibe Analytics” actually means—and why it’s more than a buzzword Whether traditional analytics platforms like Adobe, Amplitude, and Tableau are at risk- How AI and conversational UX could democratize analytics (and de-specialize it)- What this shift means for analysts, marketers, CMOs, and data teams- Why warehouse-native stacks built on Snowflake and Databricks are foundational to what comes next- We also dig into real-world implications for measurement, attribution, personalization, and data collaboration—and debate whether this moment represents evolution… or extinction… for legacy analytics tech.

If you work in analytics, marketing, product, or data—and you’ve ever felt constrained by dashboards—this is a conversation you don’t want to miss. Enjoy!

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Read full transcript bellow:

Brett (00:01)

Welcome Adam Greco to Signaling Noise. It's great to have you on the podcast.

Adam Greco (00:07)

Thanks for having me. It's good to be here.

Brett (00:09)

So, ⁓A little point of interest that I thought I'd mention is one, our audience certainly wants to hear your background and your words, how you came to be one of the top data and digital analytics and product analytics experts in the industry. But a little point of similarity that we have is we both studied at the University of Sevilla, I was gonna try to pronounce that in Spanish, but I know I'd be like, I totally kill it, in the 90s It just says both.

Rio (00:40)

Did you overlap or around the same time?

Adam Greco (00:43)

I don't know, I was there in January to May of 91.

Brett (00:47)

I was in 94, right, for a year. I went through the UNC Chapel Hill program. I was at UMass Amherst, but I studied with their program and we were at the University of Sevilla, that old building.

Adam Greco (00:59)

Yeah, you probably studied in the tobacco factory. I, so I actually did not. I was crazy and didn't realize it. Studying abroad was supposed to be a party. And I actually took an intense advanced business class business program in Spanish. I learned a lot about the agrarian Spanish society and it was about a 45 minute further walk from the tobacco factory. And I lived over by the.

Brett (01:02)

The tobacco factory, yeah. In Spanish?

Adam Greco (01:24)

in Los Remedios by the fairground. So I had like an hour and 15 minute walk and then I had to do two times a day because we had to come home for the siesta. I was in really good shape.

Brett (01:26)

Yeah.⁓ yeah, yeah, yeah, I live like 50-

Rio (01:34)

Was it an actual tobacco factory or an old one to be converted?

Adam Greco (01:38)

Yes, an old one that was converted into the University of Seville.

Brett (01:41)

Yeah, and it's a spectacular building. I was like 15 minutes walk from that. ⁓ Yeah, so quite an experience.

Rio (01:41)

sounds fun. It's a beautiful city.

Adam Greco (01:48)

Yeah, I go back every couple of years because Seville is one of my favorite places and I still have been pretty good about keeping up my Spanish. I once actually did a digital analytics presentation in Lima, Peru for 45 minutes straight in Spanish and I almost passed out afterwards of my head. My head hurts so much.

Brett (01:55)

That's awesome. That is awesome. my God, you use a little bit more than the average 4 % of your brain power, right? Like I found that at the end of every day in Sevilla, and I took some classes in, all of them were in Spanish, but some of them were in Spanish for second language speakers, and some of them were like native classes. And the native classes, you just, I always say, I always use this analogy. It's like, if the elevator door opens and you're not paying close attention, you'll see that the elevator's already left, and you're just looking down at it. You're just completely lost, right? So.

Adam Greco (02:33)

Yeah, I was a glutton for punishment because after Seville, I moved to Florence, Italy and learned Italian. ⁓

Brett (02:39)

That's remarkable. Well, there we go. So yeah, so tell us a little bit about yourself and let our audience that doesn't know who you are know where you're coming from.

Adam Greco (02:48)

Yeah, so I'm a Chicagoan ⁓ native and I got into the digital analytics space in the early 2000s when I started running a website for the Chicago Mercantile Exchange. in the early days of the internet, no one knew why we had websites and we were all told we had to build a website but weren't told why. And so I just did a little bit of research and found this web analytics industry and took a chance on a little startup vendor out of Utah called Omniture and ended up being the fifth customer of Omniture and really liked that product and dove in with both feet. Started learning all the cool things it could do and ultimately kind of knew more than the Omniture people. So they hired me and I became the 165th employee of Omniture, was there in the consulting group for many years, moved to Europe, started the consulting group there, started blogging about the product, ultimately wrote the book on Adobe Analytics. ⁓ yeah, I wrote everything.

Brett (03:42)

The literal book or the playbook,

Rio (03:44)

Yeah, the actual book, right?

Brett (03:45)

yeah.

Adam Greco (03:46)

Yeah, the main book back in 2012 on the product that's kind of going away right now, but the main site catalyst product after it was renamed Adobe site catalyst, ⁓ went to work at Salesforce and became a customer again of Adobe Analytics and Digital Analytics. I was the global head of Digital Analytics for Salesforce worldwide, ⁓ then did consulting for 10 years and helped fix really bad Adobe Analytics implementations around the world.

Brett (03:55)

Yeah.

Adam Greco (04:12)

And then ⁓ after 20 years in the Adobe analytics world, wanted to learn a little more. And so I joined a startup called Amplitude and helped them kind of build out their products so that there could be a little more, ⁓ more options out there other than just Adobe and Google analytics. And that was really fun for four years and built some really cool product. Yeah. Exactly. Yeah. So amplitude was in product analytics. Adobe was marketing analytics and ⁓ you know,

Brett (04:30)

And Amplitude is known for product analytics, right? One of the leaders in product analytics.

Rio (04:34)

It's great tech, yeah.

Adam Greco (04:41)

At the time, had thought Adobe should get into product analytics. They didn't want to get into product analytics, but Amplitude was willing to get into marketing analytics. So I went there and then we threw in experience analytics with session replay. And it actually worked out really well because our Forester rating for Amplitude just came up recently. And I think Amplitude was either ahead or tied with Adobe in the Forester wave, which is really cool.

Rio (05:05)

They were completely in the lead in that latest Barstow Wave Report.

Adam Greco (05:07)

Yeah, so it's pretty cool to see that. And ⁓ of course, ironically, Adobe then got into Adobe Analytics in the end because of what we were doing in Amplitude. But yeah, so that was it. And then I was there for four years. And now I'm a product evangelist for Hightouch, which is a composable CDP and AI decisioning platform. And so it's a big shift for me. So for the first time in 25 years, I'm not in the digital analytics space. So I thought it'd be kind of fun to talk about it because I could speak much more freely. don't have a horse in the race as they say.

Brett (05:40)

Yep.

Rio (05:40)

Yeah, totally fair. And that's one of the reasons why we wanted to have you on now. We had had a conversation, I think it was a couple of months ago, right? You had sent me some articles you're writing on. You had mentioned that you can speak a little more openly, freely about it now. And we talked about some of things that are happening to analytics because of what's going on with AI. mean, we're going to call this vibe analytics, a lot of what we talk about. But I mean, I think more generally just about what's happening analytics because of this.

But before we jump in, Adam, mean, when we ran into each other, you were at Amplitude as a product evangelist. You're now a product evangelist at Hightouch. It's a newish title or let's say occupation. I think Brett and I both consider ourselves product evangelists to a certain extent, right? Love it. Maybe before we dive into vibe analytics, love it. Maybe you could spend a minute to tell us like how you define a product evangelist. What does a product evangelist do? like, what did you...How much of this was you figuring out this role versus you finding out about the role? to hear a little bit about that.

Adam Greco (06:44)

Yeah, it is a unique role and this is probably my third time doing this role, maybe almost fourth because I worked for one little kind of startup. And I think the idea of the role is interesting because I think of it as a marketing role. ⁓ But I kind of fell into it when I was at Omniture because when I started blogging in the early days of blogs with Omniture, what I found is that if you educate the market and most of my blog was educating. Here's the cool things that you can do with amateur Psychatelist and I wasn't a salesperson. I was just a consultant who worked with lots of companies and I was literally just sharing here's a feature of the product and here's how I have used this feature and after those blogs became so popular, ⁓ then we would have like a conference every year. It used to be in Utah. Then it moved to Vegas and I would have a session where I would basically take everything I did my blog post and put it into a PowerPoint and share all these tips and tricks. And my session would have like standing room only. And people would be like taking all these notes and they would always come up to me. They said, your session was the most useful of anything I've learned because I can go back and do stuff. And so, ⁓ in a weird way, I kind of fell into being a product evangelist. My nickname in the Omniture days was Omni-Man. And I was like on Twitter.

Brett (08:07)

Did you have a little outfit with the...

Adam Greco (08:08)

Well, it's funny

Rio (08:09)

Ha ha.

Adam Greco (08:09)

because now Omni-Man is really big because my son has showed me the new Invincible series in the superhero. There is an Omni-Man who's the main character of this new, very popular series on Netflix called Invincible. And it's a whole comic book thing that my son has told me about. So I was a little worried. I'm actually glad now I didn't get like sued for trademark. But ultimately when I did that at Omniture, then

Brett (08:15)

Is there an Omni-Man in the new Invincible series?

Adam Greco (08:34)

When I worked with this little product called Apollo, which was this cool little thing I was trying to build to ease implementations, then I went to Amplitude and I like literally reached out to Amplitude said, you don't know who I am, but I am going to be your next product evangelist. And then I did the same thing for Hightouch. I reached out to them and said, I really like what you're doing and I'd like to be your evangelist. so it's not, yeah, there's, don't think there's a job description that generally is out there. Ironically ⁓ later.

Brett (08:53)

You probably had to define it for them, I'm assuming, right?

Rio (09:00)

I'm starting to see some. think that's changing a little.

Adam Greco (09:02)

Yeah, now we're starting to and later this year I'm actually if all goes well, I'm to be publishing a book on product evangelism. So I'm going to write a book on what it is, but just to answer your question. I think the main thing is, is it's a little bit of a cheerleader role for both the industry, the product and the company that you work for. It's a way that you it's a role in which your job is not to sell a particular deal, but to really kind of like help shape the industry.

Brett (09:08)

Nice!

Adam Greco (09:31)

and help the company work for understand what's happening in the industry. So it's very much like a liaison between the company and the industry. And so the role that I spend a lot of time doing is writing blog posts about what I hear from customers and then try to extrapolate that to what's happening in the industry. I speak at a lot of conference events, just like I know for sure, Rio, you do. ⁓ And basically try to hear what's happening at conferences.

⁓ Read what's happening online and try to kind of just see where things are going and where we fit in and so that's been a it's a fun role It's a kind of unique role and I think you need to have a lot of experience to have this role It's not like a role you could do right out of college I happen to have a very large network of people that I could reach out to to ask questions and I a lot of times we'll just have meetings with people just to hear what's going on and when you hear enough of the same things you start to identify some trends that are happening, and then you can share those internally and externally.

Rio (10:30)

Well, I love it. ⁓ I think you've done a great job helping define this role in the industry. as I mentioned, think both Brett and I, we're not officially product evangelists, but I part of what we both do day to day is, and as well as many other people. So, great job. Kudos to you for helping be a trailblazer in this respect, Adam. And then guess getting back to the main topic at hand, Vibe Analytics. And I mean, the reason why we wanted to have you on is obviously your deep background in digital web and product analytics. ⁓

Brett (10:30)

Yeah.

Rio (10:59)

It's an interesting topic because I think that right now we're looking at, because of the way technology is going, the way we can look at analytics and use analytics really could change. And a lot of people are thinking it's going to change because of this trend called Vive Analytics. Now I know this is a new trend and you could probably define it different ways, but it really, in my opinion, is probably going to change how we use data and how we interact with analytics tools. And generally speaking, as we go to a more agentic...agentic UIs, maybe the way we use SAS is going to evolve as well, analytics being a part of that. ⁓ So I think with your background being an early pioneered omniture, driving force and amplitude, and someone who's really, I think, had his finger on the pulse of digital measurement writ large over the last couple of decades, I think this is going to be a lot of fun. I think it's going to be a good discussion. And to the listeners out there. I think this is important because we really don't know where things are going. think some of us are starting to have beliefs, but we're really not sure. How will analytics be more interactive? Will it be more vibey? Will we talk to platforms and UIs and will they interact with us? Will the concept of the dashboard even be around in a few years? I think these are, it's a really good question. And maybe we should start there. like Vibe Analytics, I know maybe it's not your favorite term, but I'd love to hear like, how do you define that? And like how long have you been hearing it and what is your opinion on the state and evolution of analytics as a discipline as well as a technology?

Adam Greco (12:27)

Yeah. Yeah, I think we are at an inflection point, so I think it's a good time to talk about it. And it's always fun to kind of pontificate of what could happen in the future and try to make some educated guesses. I think the way that I like to approach things is always to understand how we got to where we are today. So really quickly, your listeners probably know this because they're pretty advanced. But honestly, digital analytics really started as web analytics, and that really started because of advertising because digital ads were out there and we were basically buying ads to, and we needed someplace to send them. know, a lot of times they couldn't just go to like a Google search list and just buy something. So we had to send them to a website. We wanted to know how often that was working and which ads were working. And so the original early days, web analytics was really a third party, non ad agency referee version of what's really converting so that you didn't just trust your ad agency to say, Hey, you gave us money. And of course it's converting. Like, so that was kind of how it started. But then once you had JavaScript tags on your website, you could track everything that people were doing. And so it kind of got into path reporting and looking at KPIs and all this and so on. And I think digital analytics has stayed pretty similar for, for a while. ⁓ you mentioned there was this convergence that happened where product teams thought of it a little bit differently in terms of product analytics. And a lot of times they were working with mobile apps. And when the iPhone came out, a lot of people are too young to remember this, but we had websites and then the iPhone came out. And when the iPhone came out, there was a mad rush for everyone to get an app and product teams became the thing to make apps. And these product teams really were like an app is different than a website. So why would we put a Google analytics or an Adobe analytics or a web trends on it?

And then a whole new crop of vendors like Mixpanel and Amplitude and a bunch of them came up. And basically the world split between I have one analytics tool on my website, another on my mobile app. And even though the same customer eventually was using both of those platforms, which made no sense. And so I think we finally got to the point where all of the digital analytics vendors have converged. Yeah.

Rio (14:39)

They've converged again, right?

Brett (14:40)

They've unified, yeah.

Adam Greco (14:42)

Yeah, so whether it's Adobe, Google's still working their way through it because they've got they've got a different mobile app than they do with their GA4. It's kind of coming together. But I think we're getting to the point where where all that analytics has converged. But I think at the end of the day, digital analytics has always been about going into an interface so that you create a bunch of pre-canned reports or maybe you have the ability to do some kind of almost like pivot pivot table reports and really reporting on what happened yesterday, what happened last week, what happened last month. It's been a very reactive thing with the goal of identifying insights that you can then go back to the website or mobile app team and say, hey, I think if we change this or change that, maybe things will get better for our users, we'll sell more stuff. And then we can go back into analytics and see if our theory was right. So it's been a very reporting focused, a very reactive.

Brett (15:38)

Yep.

Adam Greco (15:38)

And now that we're entering into the world of AI, as we've all heard, like anything that is very kind of routine, those are the things that AI is starting to replace. So I'll pause there just to make sure like we're all on the same page of kind of where we came from and where we've gotten to now. And then we can dive into what I think are going to be some of the changes because of AI.

Rio (15:59)

Yeah, it's interesting you mentioned some of that stuff and like about I think 10 years ago, no one would have considered a website product, right? But I think that's the most people probably would now. And then looking at how are people interacting with products, whether they're mobile apps or websites or what have you. I understanding that and using some of the same, whether segmentation and personas and analysis, I think is very important. So I have seen that convergence over the past couple of years. I know, Brett, you had a couple of questions about analytics maturity you wanted to ask, right?

Brett (15:59)

Yeah, and Yeah, yeah. And I was sort of thinking it's, like, could put a frame around, I think you were starting to hint at this Adam, like the criticality of data analytics for organizations, whether you're a brand or their agency, or you're a publisher, right? It's obviously critical to survival, to differentiation, whether you're differentiating content or you're standing out amongst the noise of advertising out there. ⁓ Do you tend to think of things ⁓ through kind of an analytics maturity curve type of framework? And I've seen these frameworks a few times in my career where you think what you described as like your basic reporting to me is like descriptive analytics, right? And then you move to more diagnostic and then predictive.

Adam Greco (17:04)

Mm-hmm.

Brett (17:07)

and then prescriptive, and then AI starts to get into the self-learning sort of category. And it's just like this evolution of sophistication. mean, how do you coach organizations to, or traditionally coach organizations to think about that?

Adam Greco (17:13)

Exactly. Yeah. And I mean, when I was a consultant for many years, I was kind of disappointed with where people were on that maturity curve because I can't tell you how many organizations, even large organizations are basing decisions based on vanity metrics, which is just like awful. ⁓ but there are

Brett (17:28)

Yeah. click the rates.

Rio (17:38)

It's a big problem in media, I mean, for sure.

Brett (17:38)

Yeah.

Adam Greco (17:40)

Yeah, I I think, you know, I've tried to work hard to work with companies to understand, like, what were the key questions that they wanted to be able to answer? And the way I would pitch it to them is I would say your business is now moving online. And one of the one of the things that sucks about a business being online is you lose this kind of human touch. You can't read people's faces when you're talking like you're in a store. A person who's in a store can basically say you hold up a sweater. They could tell immediately if the customer is like, no, I don't want that. They can kind of do that It's hard to do online. I think digital analytics is a great way to basically listen to your customers. But you're listening implicitly using data. But it's infinitely harder than just reading someone's face and get in having a conversation with them. And most companies are just not really good at that. But you have to be able to figure out what are the questions you want to answer. And a lot of it is kind of making changes. But I was shocked at how most companies were doing just the real basics with digital analytics analytics and I it was great for me as a consultant because I would come in and I'd say on a scale of one to ten like you're like a three and I can get you to a seven eight or a nine and I would get paid big bucks to do that. So it was great for me but it was bad for the industry. But even the best digital analytics program or implementation is still pretty reactive and we didn't have a eye back then. So getting back to Rio's point with like vibe analytics where I think we're going to start to see is that.

AI is going to be able to analyze massive amounts of data and actually proactively help you make changes to websites and apps faster than a human could. And some of those will be good. Some of those will be bad. I think a lot of the humans are going to be needed to kind of like review what the AI is about to do and make sure that it's not going crazy. But I think that ultimately the nirvana for digital analytics is to absorb all the data as quickly as possible and impact a change because of the data and then measure that change proactively instead of having a team run a dashboard have a meeting talk about it and then wait four weeks for a developer to make a new change to a page then wait another four weeks to see if we have enough data to determine if that was a result and then I mean all of that I think is going to be compressed down to like minutes and I think that's the ultimate goal. And I think the current digital analytics tools that are out there are not ready for that. And I think there's going to probably be a whole new generation of analytics tools that are going to come out that are going to leapfrog that.

Brett (20:09)

Yep. Yeah, it's like skipping the first couple of steps in that sort of maturity curve, right? It's the capturing of data, the diagnosis of data, getting quickly to the ability to predict what's next or to prescribe a recommendation or suggestion. But you're saying the tools today aren't quite ready for that reality.

Adam Greco (20:28)

Yep. Yeah, and I think the sad part, the thing that always frustrated me about digital analytics, and I love the industry and I don't want to crap on it, but the thing that really bugged me is that a lot of times, if you think about what you have to be to be successful with digital analytics, you've got to do an implementation, you've got to get people who are good at analysis, you've got to build reports, dashboards, make sure you have the right questions, come up with the right hypothesis of what you should change, make a change, and then have that change be positive. And at that point, that's, I just rattled off probably about eight or nine steps. At that point is when you can start to think about getting ROI. And that's why I think it's been challenging. It's like everyone needs digital analytics and wants it. But when I,

Brett (21:17)

Yeah.

Adam Greco (21:27)

really talk to companies and find out are you getting true ROI from it. It's hard to get that ROI because it's hard to be repeatable with the data and continually coming up with new ways that you're you're improving the bottom line or saving the company money. And I think that this new I think AI is going to shrink that time frame so that you can get to ROI faster like for example I was talking to a friend of mine the other day where I was saying imagine a world where you literally have an AI and you point it at a web website URL and in five minutes it tells you here's the exact analytics implementation that you need here's everything you need to track we've already put the tags on the site were already starting to collect the data you have to push go and then the minute you push go an hour later it says here's the things were seen that you need to change on your website and it's proactively telling you all the things you should change in the website in the mobile app and I think we're getting there I think companies like amplitude are really pushing and trying to get there but I think it's going to be a couple years before you know, it's truly automated and going like that.

Rio (22:31)

It's interesting what you said about the dashboard. I think that's always been kind of the challenge with analytics is ultimately in order to consume analytics, you need dashboards, but then people get lost in these dashboards, right? You you create all these different dashboards, all these different pages on them and they show different things. like understanding what it means can be challenging. So.

Adam Greco (22:50)

Yeah. When

Brett (22:50)

Totally. Yeah, it's a lot of data, not a lot of insight or easily accessible insight.

Adam Greco (22:51)

I was at Salesforce...

Rio (22:54)

Totally.

Adam Greco (22:56)

Yeah, I'll give you an example. When I headed up analytics at Salesforce.

I took the job and literally they told me afterwards that my job was to keep these four dashboards updated. And I was like, that's not what I want to do here. But they were spending 90 % of their time on that. So I automated all of those dashboards and use this cool integration with Adobe Analytics and use Microsoft Excel. And basically everyone got an email every Monday. Here's the dashboard. And one person would spend an hour and say, here's a couple of things that we think you should know. And then the rest of our time was all spent trying to figure out what things we could change on the website to improve our lead generation and so on. And so we moved from, I have this idea of a thermostat versus a thermometer. We were like a thermometer organization that was just like reading the temperature.

But the difference between a thermometer and a thermostat is that you could change the temperature with a thermostat. And so I wanted us to spend 90 % of our time on thermometer and thermostat projects when we were spending 90 % of our time on thermometer. And that mindset really helped change because that's when you start to get more value.

Brett (24:00)

Sounds familiar. Yep.

Rio (24:01)

Yeah. Yeah, it's interesting. looking, I guess, returning to vibe analytics. I guess the, it's really based on hypothesis that at some point very soon, but as we go to a more agentic led, agentic first web, right? That SaaS is going to change instead of knobs and controls and panels and dashboards. you know, I mean, well, that's a lot of what as digital marketers, we spend our time doing is going into these platforms and changing things, right? The, you know, the to your point before. If you really look at Vibe Analytics, it's based on a hypothesis that that's going to happen. And then Vibe Analytics is going to be more interactive. You're interacting with these SaaS platforms more the way you're talking to people, whether it's text or speech. And if you really take that a step further, does this ultimately result in almost a despecialization of analytics? Are we going to end up in a place where we're really not analysts, non-technical people?

You could argue this would be good, right? It's more democratized. We'd actually be able to use this without deep training. What does that do to the profession?

Adam Greco (25:06)

Yeah, it's a great point. And that's what I think is going to be a monumental shift. There's a couple of different ways. There's a whole cottage industry right now of employees and consulting firms and agencies whose sole job is to tag, implement analytics, and then do dashboards and tell you what's happening with those dashboards all of those jobs are gone. They are all going to go away in the next year or two. You are going to go in and just literally ask a question through a chat bot.

Brett (25:30)

Yep. Yep.

Adam Greco (25:38)

And it's going to go in and just tell you the answer. Just like today, the idea of reading through two pages of Google results seems really like antiquated and you just assume you're going to just get the answer from AI. think the same thing is going to happen. And I think the profound impact of that, I think the one who's the people are going to be hurt the most are people whose whole career is tied towards these mundane, like building dashboards, building spreadsheets or domain knowledge of a tool. Like I keep telling people if you're an amplitude expert, a Google Analytics expert, or an Adobe Analytics expert, like you're that's not going to be around in five years. Like the implementation is going be automated, the data collections to be automated, and the analysis allowed that's going to be automated. So you need to find another job. And I do think it's going to have a profound impact on the digital analytics vendors. And this isn't the reason I left the digital analytics industry completely, but there is a part of it is I wonder what does the future look like for the Google's Adobe's amplitudes in the future ⁓ because of AI. And here's how I'll explain it. If you use an off the shelf digital analytics product, any of them, Mixpanel, Amplitude, any of them, you're basically collecting data, sending it into that particular they use a proprietary database to make sure that the reports come back really snappy and then you can do your analysis. Well, most companies are backing up that digital analytics data into a cloud warehouse. And so you're going to have the digital analytics data mixed with all of your other customer data. And so the theory that I have is

even though these vendors are all doing the right thing and putting AI in their tool, if you are going to do a chatbot AI to say an amplitude or an Adobe Analytics, like you'll get an answer, but you could probably do the same thing direct to the warehouse and get a similar answer. And if you don't, if the UI becomes an AI chatbot, then why do you need the pre-canned reports that come out of the box in all these digital analytics tools? And if you don't need the pre-canned automatic reports then why do you need to be sending them any data at all? Why do you need to pay them for data collection? Why don't you just send all of your event data right to the warehouse and someone is going to build a really cool AI on Snowflake and Databricks and AWS and Google. And why don't you just ask your question there? And so I wonder if the digital analytics vendors get squeezed out in the next couple of years.

Brett (28:11)

Yeah.

Adam Greco (28:18)

And if Snowflake, Databricks, if those become the digital analytics vendors of the future because they have all of the customer data and then someone just has to build a AI.

Rio (28:28)

Yeah.

Brett (28:28)

Yeah, they're like the super highways of sort data management. We noticed that when I was at New Star which we were acquired by TransUnion, is that the biggest problem that we had with our big brand clients was data fragmentation, to your point. They had data in all of these places, either at the analytics platform level, at the warehouse level, like GM as an example, had 60 different data warehouses. So half of our job from a data analytics perspective, which led to things like MTA and MMM outputs, was really data unification, data normalization, sort of re-platforming, which inevitably went to the cloud, it went to the snowflakes, it went to the Databricks, and guess what? We were building identity resolution and data, and all of that stuff, data cleansing, all within native build applications within Snowflake.

Adam Greco (29:11)

Yep.

Rio (29:12)

you have to, right, yeah.

Adam Greco (29:17)

But what you just said is funny. It's kind of why I moved from the digital analytics world to the composable CDP world, because I see that digital analytics is really a subset of customer data. And you probably want to analyze all of the customer data. And while some companies will try to shove all of their customer data into like an Amplitude or an Adobe Analytics, like

Brett (29:31)

Yeah.

Adam Greco (29:42)

I think my gut and what my bet is, is that these cloud warehouses are going to be the logical place for that. And so if I want to analyze all of the customer data, I can't do that with a digital analytics tool, but I could do it with a CDP. And a CDP has been kind of an interesting evolution.

Rio (29:57)

Had a myth? It's interesting you say that, because we had a guest on from a VC firm a few weeks ago, and he talked about how he felt SaaS was generally safe with AI disruption, because you still need databases, right? You're still going to need certain functions that SaaS tools have, even if the UI changes. But I guess your point is maybe changing my perspective on this, because if you don't need data collection anymore, if that's all automated with AI, right? If the database architecture to store it, it goes into the Cloud Data Warehouse instead of, let's say, some intermediary. ⁓analytics tool with the Hedgeson's database database is data structure if the and even the dashboards themselves can just be done using that's using text and prompts on the fly instead of pre-canned dashboards like You've basically taken away every like you've taken away everything that analytics platform offers right? And it's just you just it's either done by AI or it's stored stored in the cloud that our house. It's really interesting

Brett (30:29)

platform. Yep.

Adam Greco (30:52)

But I'll give you another example. I'm sure you all have used Power BI, Tableau, and Looker. Okay. So BI tools, have you ever sent data to a BI tool? You don't. You send data to a warehouse and then a BI tool sits on top of a warehouse. Why is digital analytics any different? Why, because of digital analytics, are you sending data to a special third party SaaS vendor, whether that's

Brett (30:57)

We're using Power BI. We're using all three of those. ⁓ Yep.

Adam Greco (31:21)

Mixpanel, Adobe, Amplitude, you name it. And it's mainly because there's certain reports that are really difficult for BI tools to do that are time series like path reports and persistence.

But I just imagine in a couple of years, AI is going to be able to solve all that. And so I'd say nine out of 10 companies I talked to are backing up all of their digital analytics data in the cloud warehouse anyway. And they're paying twice. They're paying for all this event data, one in like an Adobe, and then they're duplicating it. if you were going to sick AI at something, would you rather sick it on something that has a portion or all of the data?

Brett (31:49)

Yeah, and then they're duplicating it.

Adam Greco (32:01)

Now, initially it'll be bumpy because if you ask a digital analytics type question through AI to a cloud warehouse, it may not understand that this is like a digital analytics question, but how long is it going to take for AI to figure that out and be like, Hey, this smells like a path report that they're looking for. And it'll just come back with the right visualization. And I'm not saying this happened tomorrow.

Rio (32:20)

Well, as an organization, the taxonomy of the data, which is going to be, but even then, mean, AI probably starts to handle that better over time too. We had a question a couple of weeks ago about digital asset management. mean, is it more or less important with AI? Because if you're using AI to classify metadata, let's say, identify and write metadata for things, do you actually need it stored in a dam? Because one of the big things the dam does is offers the taxonomy and the storage for actually grabbing things. Do you need AI? So I guess that's interesting too.

Brett (32:44)

Yeah. Yeah.

Rio (32:48)

If everything's going to Cloud Data Warehouse and you're using AI to grab it, stuff it in there and organize it, I think that's very interesting.

Adam Greco (32:57)

Yeah, and I'm not saying this happened tomorrow. It's just I'm looking at how fast AI is accelerating. And I think that there's a chance. And I think that the people who I know who are in the industry need to start thinking about like, maybe I'm wrong. But if I'm right, what does that mean for their job? I do think that it'll end up saving a lot of companies money because I think they're going to say, I don't have to then pay $2 million a year. ⁓to Adobe Analytics, I'm just gonna take all my data, skip Adobe Analytics, send it right to the warehouse and basically be able to answer 80 to 90 % of the questions that I answered today, but just do it right off the warehouse. I think that'll be interesting.

Rio (33:35)

They'll still need some application

Brett (33:35)

Well, and-

Rio (33:36)

that actually do that search for them, right? Even if it is AI, let's say AI powered and then actually give them the answers or some kind of dashboard. They may not dashboard, but some kind of analysis, right? They'll still need something to do that.

Brett (33:41)

Yeah. Yeah. But the advantage of the data warehouse is whether it's Azure or AWS or Databricks or Snowflake is they're starting to sort of eat into large portions of the brand and publisher ecosystem. So the majority of both sides of the buy and sell of the industry for advertising specific are in these platforms. So when it starts to lead to data collaboration use cases beyond first party data, right? You need to have an easy way to do that. And your point solution platform that's specifically built for let's say web analytics, isn't gonna have the same capabilities of ingesting and data sharing and data collaboration, is what ⁓ the Snowflakes, it's like we used to do a ton of partnerships where a brand and a publisher partner would be sharing data in a privacy sort of compliant, clean room type of environment right within a native building Snowflake. And that can't happen, that couldn't happen in our separate individual data warehouse. It had to happen natively.

Adam Greco (34:45)

Yeah, let's take it even further. Let's say that you're a company A and you want to partner with company B through a data cleanroom but company A is using Amplitude, company B is using Adobe Analytics. How are you sharing data? But if all of them end up in these cloud warehouses, then you can have some data clean rooms where you can securely share and partner with people. I think it's going to be interesting. And I think if I were the digital analytics vendors, I would be thinking, how do I make my product work, but make it work in a composable way off of the warehouse?

That to me, I think is the future. There's a couple of vendors who've started doing that, but until the big vendors do it, it's not going to be a trend. But I think you shouldn't, in the future, a company should not have to send a separate version of data to a third party SaaS tool and also have it in the cloud warehouse. They should be able to just do it composably off of the warehouse. And that's happening in the CDP space very rapidly. And I think it'll eventually work its way to many other SaaS products. And since we're talking about digital analytics, it might work its way to digital analytics in the next couple years.

Rio (35:53)

Yes, it just they kind of the zero copy future composable feature. And I think to with clean rooms, mean, like mean, I snowflakes already doing this already. Clean room is probably not going to be another destination, right? It's just going to be part of your of your cloud data warehouse environment that has certain privacy rules applied to it where you can collaborate data and do your control and can join analysis, analysis and other things in there. Right. ⁓

Adam Greco (35:55)

Yeah. Yeah.

Brett (36:13)

Yeah, and both parties canprotect their data too and know that their data is not being usurped or used for other purposes, all that sort of stuff, right?

⁓ So realistically, it sounds like we're talking, we're hinting at, Ryo and I had a little conversation before we talked about this and we kind of geeked out on this, it looks like we're coming up to like another innovator's dilemma type of situation in the industry where there's gonna be a bunch of players, whether it's in the digital analytics space, yeah, that are gonna be listening to their customers. We talked about, if you haven't read the Clayton Christian, sure you have, the Clayton Christian's book, right? You listen to your customers, they're not gonna tell you where the puck is going necessarily.

Rio (36:36)

Good for the analyst companies, definitely, right?

Brett (36:50)

looking at what's right in front of them today, next quarter, the quarter after that, but beyond that. So do we have a, like if there's a lot of successful CDPs out there, there's a lot of successful composable software companies out there, do we see a future where they're gonna be, an innovator's dilemma problem, where they're just not gonna change fast enough and they're gonna be replaced by a whole new...

Rio (36:55)

Yeah, no one knows what it's going to look like, right?

Adam Greco (37:13)

Yeah, I actually wrote, that was the title of a blog post I just put out about a week or two ago. And I do think that that's, you know, we always go through these cycles. And if we start with digital analytics, I think that there's hundreds and thousands of companies that are using a current analytics tool. And I think those vendors are going to come to a pivotal point and decide, are we going to just kind of like put ourselves out of business and come up with a new AI approach? And I think what I'm seeing so far right now is more that they're putting AI as a way to like be like a new interface to speed up doing the things that you do manually.

Brett (37:55)

Yeah.

Adam Greco (37:55)

versus kind of really starting from scratch with with AI first. So I think that's definitely happening in the analytics space. And I think it's going to be interesting. I've already seen a couple of new startups that don't have the baggage of a lot of old stuff. I mean, like if you look at Adobe, they yeah, Adobe already has two analytics products. They've got the Adobe analytics one I wrote the book on. They've got a new one, customer journey analytics. So they've got CJ said they've got two analytics products. And now

Brett (38:07)

Yeah.

Rio (38:10)

the package or the tech debt, right?

Brett (38:11)

Yep.

Rio (38:18)

CJA, right?

Adam Greco (38:22)

what do they do, you know, cause they're trying to get everyone to CJA, but is, is like, should they be getting people over to an AI version of analytics instead? Or is AI going to just be a quick little, you know, front end to what they already have. And I think underneath the tech debt of a lot of these legacy vendors, whether it's Adobe, Salesforce, you name it. I think there's just a lot of legacy technology and you can put a cool little AI veneer on it. I wrote a blog post calling like, it's like a lipstick on a pig in some cases.

Brett (38:47)

staple it on top of your ⁓ yeah yeah yeah

Adam Greco (38:51)

But like, I think that's not going to cut it in today's world. Like you have to come up with a whole new way of thinking about it. And, and I think the CDP space is further ahead than the digital analytics. So we could use that as an example. Like you had, you have a bunch of vendors, Adobe, Salesforce, Telium, Action IQ. Many of them are being acquired because like their technology is kind of doing it the old fashioned way, the non composable, the non warehouse way. And they probably had to decide, do we want to start over?

Or do we just cash out? And I think a lot of them are cashing out. And I think the big legacy vendors that we run into the most, Salesforce and Adobe, like they have really great products, but they're just heavy. They take a long time to implement. They are quasi warehouse native composable, but not truly built from day one. And they're carrying over a lot of this kind of tech debt. And we're just seeing more and more companies that right now in an unstable economy have to like save a little bit of money.

They want to invest in their warehouse. They don't want to have multiple data, copies of customer data for both legal and privacy reasons. And so all the winds are kind of blowing towards composable and warehouse first. at first, when, when high touch first came up with this concept, like they were laughed at and the analysts didn't cover it. A lot of the legacy vendors said it was dumb. And now all of them are falling over themselves to position themselves as composable and as warehouse.

Rio (40:16)

Every CDP is composable now. I've noticed that.

Brett (40:17)

Yeah, yeah. And can we, I think it might be helpful for the audience. My brother talks a lot about this. He's the president of Elastic Path, which is a composable commerce company. Just to define kind of the machinations of how that works. Like when you have a CDP and it's composable and it directly integrates to a native warehouse environment, like a snowflake or a didgeridoo.

Adam Greco (40:31)

Yeah. Yeah, the idea in general of composable or warehouse first is that you are not storing data in an extra place. You are sitting on top of an existing data store, usually a cloud warehouse, but you're offering the same functionality. Now in a CDP, the key functionality is identity resolution, the ability to build audiences.

Brett (40:52)

Yeah.

Adam Greco (40:58)

the ability to do analytics on your audiences and then to activate audiences to either add networks or email or maybe even just update customer records in Salesforce or other SaaS tools through reverse ETL. And so that's the feature set, but how you do it is very different. And if you, the easy answer is if you ever have to store any data in a vendor, then they're not composable. That's just an easy litmus test.

But also, the other part of composability is being able to purchase different features without having to buy the whole suite. for example, it's very difficult to buy. You can't really buy Adobe real-time CDP without buying AEP. Now, who knows? Maybe Adobe will disagree with me on that, but that's not what I've heard from a number of companies. And so you have to do your profiling and your identity resolution. That's all in AEP. And then real-time CDP sits on top of AEP.

Brett (41:30)

I was gonna ask that, yeah. Yeah. Yeah.

Adam Greco (41:53)

But like we just believe in our core is that the warehouse, the should be the cloud warehouses should be the center of truth should be where all of your customer is. It's the most efficient, most cost efficient, and they are adding features to snowflake and Databricks at an infinitely greater pace than tealium Adobe Salesforce are in their CDP. Like I don't think I would want to compete with Databricks, snowflake, big query.

Brett (42:15)

Yeah. in that world.

Adam Greco (42:21)

In the data warehousing world, it's just the economies of scale that you can have. It's like if you think of what's in China, what's the cars they have that are competing with like Tesla? I forgot the name of it, the electric cars in China. Yeah, BDO, like they just have that down. kind of think of as like Snowflake and Databricks are like the BDO. Like they've got it down. It's cost effective. And then you've got Tesla, which is great. I have a Tesla. It's a great car. But like it's more expensive.

Brett (42:25)

Yeah.

Rio (42:32)

BDO? What is it, ORF?

Brett (42:35)

Yep.

Adam Greco (42:48)

and it's a little more proprietary and so on. So I think that's kind of the analogy and I think the world is moving more towards the BD video.

Brett (42:50)

Yeah. Yeah, so it's like if I have an identity resolution use case today, I can sign on with vendor A that's got a composable capability in that area. And then just add on, just like you do in a classic SaaS world where you're like, hey, this feature's great out, this feature's great out, add on additional features and capabilities over time. And I'm not paying for the suite, right, and getting a kind of a volume-based discount because I'm buying the whole package. Yeah.

Adam Greco (43:16)

Yeah, you're not paying for stuff you're not using. And we have a lot of companies at high touch that have, they figured out their own identity resolution. So they just send us the resolved identities and they don't have to pay for that part of the product. But most packaged legacy vendors, like you pay for everything, whether you use it or not. Yeah. B Y D. Yeah. But I think the main thing is people want flexibility right now. And I think, especially in a real, in a weird economy, people aren't looking to drop $10 million a year.

Rio (43:34)

It's BYD by the way.

Brett (43:36)

BYD, yeah

Adam Greco (43:46)

Like they're like, hey, I want to just have the flexibility. So if I don't like something I can change it and that's the other benefit of composability in this applies to CDP and analytics is if you don't like like let's say you're using cubit, which it happens to be a warehouse native analytics tool. If you don't like it after a couple of months, could switch if there was another warehouse native one that you like you could switch very easily because you're not storing any data in it. You're just mapping it to the schema you already have in your warehouse. So it means that you can swap vendors in and out very, very quickly and very easily. And so you're not making these big commitments to one big monolithic marketing.

Brett (44:22)

Well, yeah, but then the vendors are stuck in the situation, you know, coming from the SaaS world, stuck in the situation where it's all one-time revenue recognition versus, you know, multi-year deal recurring revenue, which is a death knell. So how do you prevent these companies from literally going out of business because they don't have any ARR? Everything's one-time revenue because people are switching in and out.

Rio (44:35)

Yeah, how do they deal with that, right? Yeah, they're going to get crushed, right? Short-term, they get crushed. Even if, like, let's say they have their iPhone moment. In fact, I'd want, like, be curious, like, when do think that'll happen? Like, let's say, like, when, like, when we get to a point where it's either an incumbent or I think you're right, Adam, it's probably going to be a new, like, a startup that just says, you know, we don't have the tech debt, we don't have the baggage, we don't have the trained customers on our old platform, let's just try something new. And everyone's like, wow, this is, we never knew we wanted a touchscreen, Brett, your point before, but like, we wanted one, right? Never you want, how far off do think that might be?

Adam Greco (45:10)

I mean, we're seeing it now. mean, high touch is growing at 140 % right now. And most of the kind of packaged legacy CDP vendors are either growing at two or 3 % or there's like segment just came out of their port where they're actually negative 5%. And I think it's just that model. just is it had its time. And I think it's time for the, it's the world is shifting. And I think it's kind of a non, I think it's both non composable is going away.

Brett (45:34)

The non-composable model?

Adam Greco (45:40)

And I think AI, and if you put those two things together, it's like a double whammy on a lot of these legacy vendors. And I think like Salesforce is, I love Salesforce, used to work there and they're doing their agent for stuff. But I think most people I've talked to are like agent forces is just kind of a veneer on top of the same products they've had for 10 years. And I think, I think we're entering the, yeah, I think we're entering the golden age of where new vendors going to come up left and right, because AI makes it so easy to start a new company.

Rio (45:58)

Yeah.

Brett (45:59)

Yeah, which aren't exactly easy to use.

Adam Greco (46:09)

start a new product and you can get things going. So, you know, Scott Brinker's chart, I wrote a blog post about ⁓ what I call micro composability, where I actually think we're going to end up with instead of 15,000 vendors, we may end up at 45,000 vendors, because it's going to be like each part, like you could take identity resolution and there may be a vendor that says, I'm going to do a really good job of probabilistic identity resolution. And you could plug that into your warehouse instead of having to buy a whole identity resolution package, you're just buying a part of identity resolution. So I think it might keep some.

Rio (46:40)

Well, I mean, think about how much easier

Brett (46:40)

It's like an app-based future.

Rio (46:42)

it to start a company now, right? Instead of millions of dollars and teams of engineers, maybe you only need like, I I was talking to like one designer I'm good friends with, he's got one engineer part-time, they're able to vibe code really incredible applications. mean, obviously in order to actually get things production ready, it probably takes some heavy lifting, but he's able to move it to like five yard line, right? With very...

Adam Greco (47:07)

Yeah, you can get to that product market fit. You you could find out really quickly instead of having to take a year to find out if you've product market fit. You could find out in a couple of weeks.

Rio (47:16)

Right away, right?

Brett (47:16)

Yeah, it almost seems like an app-based ⁓ SaaS model where it's like you're buying individual applications. My question with somebody like a high-touch and composable is how do you increase switching costs? So brands, if they're only using one feature, how do you get them to lock into long-term relationships when they, right?

Adam Greco (47:36)

Yeah, it will. That's the best part about it about composability. You can't and it sucks as a vendor, but here's the here's the good news. If your product continues to deliver value and if you actually iterate and I think that's what we're finding is we have like 95 % retention rate and basically because we just keep cranking through new stuff like we just launched a bunch of AI products and I think that you have to be able to always add new value and

Brett (47:47)

Yeah. Mmm.

Adam Greco (48:04)

not to badmouth other vendors, but there's a number of vendors out there that they get a customer. They've had the customer for 10 years. If you talk to the company, how much value do you get from this monolithic vendor? They'll be like, like we don't get a lot of value, but like the idea of getting rid of it is really like not pleasant. And I think there's a lot of companies right now that for the last 10 years have been in this, like, if I could get rid of this, I would get rid of it, but it's a pain to remove.

But once you move to the warehouse is the center and you move to a composable mindset, you don't get trapped or locked into any monolithic vendor. You could still use a couple of those vendors products, but you don't have to. And you could swap them out anytime because most of your logic and your data is stored in the warehouse that you own. So I think it's going to create much better SAS products. I think customers are going to be happier and they're not going to feel trapped. And for us, it's at high touch. We get really scared how easy it is to switch from one composable CVP to another composable CVP, which keeps us on our toes to make sure we're always delivering really good products and services.

Brett (49:09)

Yeah, back to the innovators dilemma topic, This is going to facilitate and force faster innovation, ⁓ less of that sort of sitting in your laurels to your point, right? It's like mini computers or disks, but amplified in a sense because the switching costs are lesser, arguably.

Adam Greco (49:28)

And I know we've really ⁓ diverted from our whole digital analytics conversation. So happy to go back to what wanted to do. But this has been fun to just kind of ⁓ riff for a little bit.

Brett (49:33)

Yeah

Rio (49:33)

A little bit, yeah. Well, yeah, well, guess, I mean, I love, I love local possibility topics. like, no, no issues with me. mean, but I guess, you know, going back to vibe analytics and analytics a little bit. mean, like as someone who's been in the trenches for, for, you know, for a long time, like what would be your advice to let's say anyone who's in analytics or wants to get into analytics? mean, like with all of these big seismic changes coming with, you know, the potential potentially like extinction level changes for some of the legacy vendors and a lot of really cool startups, maybe many, many more startups coming up with that are really are changing the game. Um, use, know, whether it's five analytics or just using AI to change out people in Iraq with, um, with dashboards in general, like what would be your advice to anyone in the industry?

Adam Greco (50:20)

Yeah, I mean, it's a little scary if I were like I have a couple of kids who just graduated college and I don't know that I would tell them to go into, you know, digital analytics right now, just knowing what I know. But I do think there are still a lot of opportunities. ⁓ One, there's going to be this conductor role where you are kind of the conductor to AI and helping it figure out what should it be, you know, verifying that it's tracking the right things, that the data quality is good. So there's that role. But I also think that a lot of people don't understand how important storytelling and turning insights into something at a company that can influence change is. And so like I give presentations for a living and I attribute that to a lot of my success when I was in the digital analytics world as a practitioner is being able to take data and wrap it in a story and say this is why because really if you think about it you're going to someone at your company and saying, I'm asking you to change the homepage, which is a very heavily trafficked page for a very big business based on data. And you've always got an executive who's going to be like, no, my gut instinct says we shouldn't do this. And so you've got to be able to kind of do the politics. You've got to be able to tell a narrative story that says, let's picture a world where this is on the homepage. And once they do this, they do this. And I can show you, because we did an experiment that we think we're right because we tried with 10 % of the population and then we did see this result, but it would be a big change for us. And we think this is worth the risk. And if it doesn't work, this is our contingency and being able to tell that story like AI is not going to be able to tell a story like that in the near future. Now, if we get to a world where everything is completely automated, then I don't know what that means for data storytelling, but I think that there's going to be a need always to interpret data and insights and communicate that within the organization. But I think a lot of the other grunt work is going to really go away in a couple of years.

Rio (52:19)

Yeah.

Brett (52:19)

Yeah, it's like the elevation of data science and data analytics, Because it's funny, we talked about this in a couple of episodes, Rio, how 10 years ago to become a computer engineer was a great career path.

Rio (52:19)

How do you say that? I... Yeah.

Brett (52:33)

You'd be building stuff, was a huge need with the startup boom. And now AI has replaced that. It's the most ⁓ poorly ⁓ recruited role out of college of any kind of role in the business world. Now we're saying data analytics and portions of data analytics, especially the grunt work are gonna be disintermediated. But there's this role for the orchestrator, the conductor, the strategist to come up with the plan and deliver.

Rio (52:38)

There's always need for more engineers,

Brett (53:03)

the insights to humans, right? Yeah.

Rio (53:06)

Yeah, yeah, it's

Adam Greco (53:06)

How many of

Rio (53:07)

like it's the analysis.

Adam Greco (53:07)

those will need? I don't know, but we'll see.

Brett (53:10)

Yeah, fewer people, yeah.

Rio (53:11)

The analysis, the thinking, and then the presenting, right? The storytelling. I mean, I think it's good not just in analytics, but I think a lot of occupations, a lot of professions, right? I mean, I've talked to lot of people in consulting, right? I think that if AI is going to take notes for you and do a lot of the grunt work, right?

That means that, okay, you're not gonna be able bill for that stuff anymore, but that means you're gonna have more time to think about things. But that means, I used to always say this to consultants on projects, like, what does it mean? They're not paying you to like take notes and regurgitate it and build nice slides, right? mean, and I think that's less important now than it was, right? Like, what does it mean? Figure it out, what is the impact? Yeah, sure, you can use AI to help you think through these things, but I think that's gonna be out of my group here. It's gonna be more important whether it's in analytics or applying analytics to...let's say to business recommendations or whether it's do we need a new website, do we need a website at all? think all of those things, the ability to think through and understand what these signals mean is gonna be more.

Adam Greco (54:07)

Yeah, and I think that AI is probably going to get to the point where it's going to recommend like here's five different things that I think you should do to improve your conversion rate. And then you're going to have to kind of take those five things. Think about it. Work with your teams. Work with your executives and say we're going to stack rank these. We're going to try this one first. And if it doesn't work, go to this or maybe try these two at the same time. So yeah, it's going to be a lot of I think it's like instead of being a player, a lot of people are going to start acting like coaches.

Brett (54:34)

Yeah, it just really, is just accelerating the move through the maturity curve to bring that theme back, right, back to the prescriptive piece. Because at end of the day, it's like, should I do next? Speed to insight, right? And if you got a lot of that decisioning and sort of data capture and data analysis happening automatically, then it's just quicker for ⁓ companies to be able to evolve and adapt to whether it's you're selling a product or you're selling content, right? ⁓said this in our last interview, Rio. He said, you're engineering to relevance. Well, what the hell does that mean? Engineering to relevance. That's really what it's all about, delivering relevant experiences, whether it's on the content side, the website side, the mobile app side, a product advertisement. And the only way you can do that is with data. And we've been promised this for like 20 years, being in the ad tech industry.

Adam Greco (55:24)

Well, I'll throw another crazy one at you.

I can see a world in which humans aren't even needed ⁓ to view the website or mobile app because I'm starting to see people talk about building synthetic personas, which are AI personas that are trained on the current population. So imagine you have a new section of a website or a new app. And before you launch it to the public, you basically feed it a bunch of fake humans, bunch of AI humans to use it the way a human would. And you might be able to use digital analytics and AI and digital analytics to say, Hey, this page isn't working. This page is working and basically almost use them as like a focus group or a beta test. And it doesn't cost you anything. You don't have to waste your advertising dollars. You basically, and you can do the same thing for ads. You might be able to like test five different ads with an AI user group see which one performs best and then keep validating that with humans. And eventually if it's always, you know, the same as the humans, then like, you can just know exactly which ad you should do.

Rio (56:21)

Thank Well, and after a while, do you even need humans anymore? Like if you're just having agents do things for you, right? they're, right? Well, think about it. Like if agents are going to go buy a plane ticket for you, book a hotel for you, you don't need to go to like, I don't need to open up a United app anymore to book, right? An agent does it for me. like eventually, you're optimizing.

Brett (56:30)

We're gonna be playing a lot of golf.

Adam Greco (56:33)

Yeah, we're gonna be... Yeah.

Rio (56:50)

web experiences. I mean, that's happening already. Like they're being optimized for AI and you can push direct, you can push content updates directly to API with like perplexity, for example. But I think at some point, maybe you have two webs, one for humans, one for AI. And at some point as human traffic starts to dwindle, you know, to your point, maybe not only you're not only testing with synthetic humans, maybe you're just testing for AIs.

Adam Greco (57:13)

Yeah, but someone has to buy the products and services eventually.

Brett (57:16)

Yeah, and Adam, I think you made a good point. think we could, we're coming to a close here, but I think you made a really good point about specifically synthetic data training sets, right? Because you have to have a truth set to train models on to say this is exactly what this is exactly reflective of a human being's behavior on a website or this is exactly reflective of, ⁓ know, in our business, we look at like ⁓ advertising attribution. So we attribute ads, you have to look at an ad and say, okay, who's the brand? What's the product? What's the product category? What's the messaging, the copy, the visuals, everything. And you know, you have to train the AI on how to recognize those things so that it's repeatable a truth set. Synthetic data sets are oftentimes the best way to scale a learning set that doesn't require, like you said, focus groups or manual mechanisms to create a bunch of data to train on. Because if you train on the wrong data, it's not going to do anything good for you. ⁓

Rio (58:14)

I hope I never have to do another focus group.

Brett (58:20)

Well, this is great. I think, is there anything else from a recommendation perspective in terms of the future of data analytics, Adam, that you'd like to tell our audience?

Rio (58:29)

It will be nice.

Adam Greco (58:31)

Yeah, no, think, I mean, just to kind of summarize, because I know we are a little bit all over the place. I think the way I'm picturing this is that the interface to do digital analytics is going to change, whether that becomes a vibe analytics or AI chatbot analytics. I think that that interface is going to take over a lot of the grunt work of building reports, dashboards. But then I think once we get to that world, I think that's going to force a different change to say, well, where are we pointing this AI at? we pointing it at a digital analytics data set only, or are we going to point it at all of our customer data and have it figure out the kinds of questions that a digital analyst would answer, keeping in mind the whole customer data set? And if that happens, I think we're going to see a major shift in the vendor landscape where the cloud data warehouses become the back end. And then the current digital analytics vendors will have to decide, do they build an interface that they think is worth enough that someone would pay for on top of the cloud warehouses. Do the cloud warehouses build an AI interface onto their own interface and they become the new digital analytics vendors or do a bunch of new startups build AI that answers the digital analyst questions directly on the warehouse? And I think that's going to be probably one of the biggest changes. And then from a personnel standpoint, I think the role of a digital analytics both implementation and analysis are going to really be shifting from doing the grunt work to doing much more of the coaching and conducting of an AI doing a lot of the implementation, the coding, the analysis and the dashboarding so that you're really kind of making the bigger decision. So I think the next two to three years are going to be really impactful for the digital analytics space and for me, I kind of like being on the sidelines to be able to watch all this and not have like a heart attack every month. If like my job is going to go away because AI is, is removing the need for digital analytics products, but I could be totally wrong. And people could be using Google analytics, Adobe analytics, amplitude, you know, 10 years from now. So, time will tell, but you know, you just, all you can do is look at the trends that are happening right now and kind of extrapolate that into the future and make an educated guess.⁓ And so we'll see who wins out in the innovators dilemma in the digital analytics space.

Rio (1:00:57)

This is fantastic. Thank you.

Brett (1:00:57)

There we go. You couldn't have summarized it better, right? Than that. Thanks Adam. was great having you on Signal and Noise.

Rio (1:01:02)

Appreciate your time. 100%.

Adam Greco (1:01:05)

Yeah, thanks so much for having me and yeah, it's been great.