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[00:00]
A
It's proven time and time again in research. Some of the more old school, like there's a reason why they were doing that the way back in the day it was working. Brands have been built over time, on tv, on other channels, and sometimes it's even the less sophisticated ones that prevail.
[00:15]
B
Marketing Architects hello and welcome to the Marketing Architects, a research first podcast dedicated to answering your toughest marketing questions. I'm Elena Jasper. I run the marketing team here at Marketing Architects. And I'm joined by my co hosts Angela Voss, the CEO of Marketing Architects. And Rob Demar is the chief product architect of misfits and machines.
[00:34]
C
Hello. Hello.
[00:35]
B
And we're joined by Matt Hultgren, the Chief Analytics Officer at Marketing Architects.
[00:40]
A
Thanks for having me back, Magic.
[00:42]
C
Matt, it's been a minute.
[00:44]
B
We're back with our thoughts on some recent marketing news. Always trying to root our opinions and data research and what drives business results. And today we are going to be on theme, we're talking about measurement. We'll explore what's broken in measurement today, how to balance short term performance with long term brand building, and why the best marketers use multiple models to find the truth. But I will kick us off, as I always do, with some research and we have some of our own to share today. It's our report that dropped this week and it's called Measuring the Long and the Short. It tackles one of marketing's toughest challenges, proving what's really working. It argues that TV and marketing as a whole isn't unmeasurable, it's just being measured the wrong way. It explains why so many campaigns fail before they even launch. From siloed teams to unclear goals. And lays out how to design measurement into a campaign from the start. It also explores how to capture both short term response and long term brand impact, because real growth comes from balancing the two. And let's actually start with you. Why is measurement such a persistent challenge in marketing?
[01:41]
D
How long do we have here? This is a big loaded question. Not that long. Okay.
[01:46]
A
All right.
[01:46]
D
I'll try to keep it as succinct as possible. Our human behavior is very messy. It's contextual. It's influenced by far more than one touch point. And I think even with better data, better tools, more sophisticated models, people just don't make decisions in a super clean linear way. People make choices based on their emotion, their habit, their memory, their friend, their identity, social cues, none of which is easily visible in data and all of which kind of shifts over time. And I think beyond that, marketing effects are, or can be at least the majority of them. They're delayed, they're cumulative, as single ads just really rarely cause a predictable purchase, but instead build that familiarity and memory over weeks and months, which is something that most measurement systems struggle to Capture. Right, Matt?
[02:43]
A
100%.
[02:44]
B
And thank goodness I'm not managing that part of our business. It's Matt who is very smart, has a big brain, is also, I'd say, probably more of a skeptic than the average measurement thought leader we've had on the show. We have a lot of questions for you, Matt, so we're going to pepper you with them today. What is the biggest misconception brands have about attribution in general?
[03:07]
A
So I don't know who to point the blame to. I don't know if we go all the way back to Steve Jobs, Google, Meta. But what those three things have in common is the need for speed. Whether it was the iPhone and just having everything on your hands at one time. Google, you can track clicks and immediately get feedback in terms of how things are performing. Meta just piled onto Google and it's we call them the digital divas. But everyone wants results now and if you can't get it to me now, you're broken. And everyone just wants the one answer that's going to tell them, how's my campaign performing? And it's that need for speed where people sometimes forget how offline channels work and how consumers interact with media. So the number one thing we come up against is just people wanting that silver bullet solution. And I think it comes from being obsessed with those digital metrics that are so easily tangible all over the place.
[03:58]
B
Right? Google and Meta have sold that you can have a result immediately. It's going to be 100% accurate. But that is not how marketing works, as you said, or consumers work. One, one thing from the report that we've talked about before on the podcast a little bit is this planning problem. So I wanted you to explain what that is and why does it cause so many measurement failures before campaigns even start?
[04:21]
A
I don't even think I knew this existed until I had seen it out in the live world numerous times now where it's like teams can be so disjointed and they're like, hey, we're going to do tv. But it's just like this one person within a business, he didn't talk to his other fellow teams to figure out how is everything going to synergize together. And it's like, oh, I got 50 grand, I'm just going to throw it at TV and see if that works. Is 50 grand enough? Is digital set up in a way to actually help TV do better? There aren't these conversations happening. What are the KPIs? What does your boss want? What does the CMO CEO want? And it's like if you don't start from day one being very crystal clear aligned on here's my KPIs, here's what I'm trying to measure. Here's how I'm going to measure. You might go to the market at the wrong time during peak seasonality and you're for sure not going to measure anything. You might go to the market with the wrong budget where there's just no chance you're going to be able to see the lift that you're hoping to see. And it's like there's just so many campaigns that just aren't thought out. It's like, hey, performance isn't good, we haven't tried tv. I'm just going to throw some money at it and hope it works. Usually doesn't pan out very well.
[05:27]
B
What's that saying? If you fail to plan, you plan to fail.
[05:31]
A
Sounds good to me.
[05:32]
C
I like it. I think I have that tattoo.
[05:34]
B
Oh, great. No one needs to see that. Okay. Part of planning is what you've called a North Star metric. And I like this a lot because I think it's nice on the podcast to try to have some practical takeaways. You've talked about the importance of aligning around that. How could a CMO marketing team go about, first of all, what is it? And then how could they go about choosing it?
[05:52]
A
Yeah, I think a lot of times we're kind of obsessed with data now. Right? Like I have 50 KPIs, I gotta track them all and oh no, this one doesn't look good. What does that mean? And sometimes simplification can really help. It's gonna probably look different for Google and branded paid search than it does look like for tv. So sometimes it's good to compartmentalize the upper funnel channel. What is the most important thing I'm hoping this channel does for my business? Obviously Google's gonna be there to collect. People are searching for my brand, I'm getting purchases. You're going to be hyper focused on that, bringing in the roas you need. But when it comes to tv, are you looking for awareness? Are you looking for traffic to your site? Are you looking to maybe pay Google less by having more people searching for you than generic terms and making sure you're again aligned with your internal team of what's your intent of going to market with an offline channel? Building is it. Building mental availability and awareness is it. I do need revenue and we don't have unlimited cash to fund this. So making sure you know what that North Star metric is going into a campaign so you don't get into the campaign and wonder, oh no, like some metrics look good, some metrics look bad, what does success look like? You just have to be really aligned on that before you even start.
[07:04]
D
Okay, Matt, I'm the marketer and my North Star metric is day one cac. So what's your advice for me? I'm under pressure to drive immediate results. How can we think about balancing and proving short term ROI with building that long term brand growth?
[07:24]
A
You must spend a little bit with Google and Meta there, Ange.
[07:27]
D
Very, very trying to pay the bills, trying to do it very accountably.
[07:32]
A
There's definitely businesses that are in a position where they do need CAC and we're not here to say that is wrong. At the end of the day, TV does a lot more than just that. And there's a chance that you turn off TV because you're not hitting the cacs you need. And yeah, you can't just put in more budget. And we always tell our clients we're going to treat your dollars like they're our own. At the same time, we do know the power of building a brand, whether it's pricing power, having more loyal customers, growing your market share. I don't think anyone's going to complain about that. And I think again you have to figure out where you are in your business life cycle and can you afford to invest in a brand channel. We do believe TV also drives immediate results. We see it every single day where there's spikes in traffic and people making purchases. Sometimes that ROI is net profitable day one. There's other instances where we have brands that are investing in that awareness and the long term payoff oftentimes surmounts like what they see before that. So there's different situations that kind of play out live in the field.
[08:30]
D
Well, I think one of the key challenges and opportunities, especially of a channel like tv, is that it is full funnel and it does drive both immediate sales to your point. So measure CAC as well as building that long term demand from a brand perspective. But one of the challenges I know we've seen with clients as they come in is just the silos that you mentioned earlier between maybe a brand team, a performance team, an analytics team. When it comes to measurement, what's your advice to breaking down some of those silos?
[09:02]
A
I will say being a TV only agency again, we've seen this play out where the brand team doesn't talk to the performance team, which doesn't talk to the digital team. We try to come to the table and say, everyone please come to the table. Can we have conversations about how to make this most this campaign that's usually TV is a pretty big investment. Like you'd think you would have all the key stakeholders at the table. There's instances where we couldn't even convince them of that. But that's really. It comes down to if you want TV to work as hard as it possibly can for you, TV is driving people to search for you on the web. I would sure hope you have your digital teams at that table to have that conversation about how we can have these campaigns synergized between the two. And everyone should be there thinking through all those intangible elements you're talking about. Ang it's not just a performance channel, it's not just a brand channel. It truly is full funnel.
[09:51]
D
Totally. One of our distinctive assets, I think on this podcast is the saying all models are wrong, some are useful. And you may have been the first one to have said that on this podcast, maybe I don't know, a year ago. But how do you think about trying?
[10:05]
C
I've got that tattoo as well.
[10:06]
A
Oh gosh, it's probably a triangle if I had to guess.
[10:12]
D
You may be listening to this in the morning, but I'm just going to tell all the listeners right now. It's too late in the day for all these jokes from Rob about his tattoos. How do you think about that triangulation mat using multiple models or methods to build confidence and results.
[10:27]
A
This is not a fun topic. I usually start off anytime I'm talking to a client to say measuring TV is hard. Like it's not easy. And if we can even go back to earlier in the pod, like the reality is there isn't a silver bullet and you're going to have to be comfortable with ambiguity. That is tv in terms of each model is going to have its strengths, each model is going to have its weaknesses. And it's by best you know what those are in each circumstance so you don't go make bad marketing decisions. But it is a massive puzzle. There's a lot of different models you can use and each one is going to help you fill in that puzzle. In terms of who's responding to my Ads is different creative or media performing well? How is it affecting my overall top line? And again, there's certain models we use to help understand the insights of what media is working best. Those are not the models we use to help our clients understand how TVs performing overall. So I definitely would recommend making sure you have a really good feel and sense of what each model does for your business before even going into to TV and trying to make decisions from your perspective.
[11:27]
D
Given there's so many options and the channel is full funnel, what short term metrics do you believe really signal that effectiveness versus perhaps just being noise that's going to distract from the measurement story. And then what long term metrics have you seen actually translate into that business growth that you mentioned earlier?
[11:45]
A
Yeah, I think coming back to the planning process too, like you don't want just a quick spike and be like oh it's working or oh, it's not. Like time is a really important part of this equation. You want to make sure that you're starting to see trends and you're not getting like a false positive or a false negative. I think that's one of the first big pieces of it. In addition to that, for longer terms like brand metrics, I hope you're not going to go spend for four weeks on TV and expect for your awareness to shoot up. I'm sorry, I don't remember what I had for breakfast yesterday, but I do remember Geico commercials. And maybe that's an extreme example of 15 minutes could save you 15% or more of your car insurance. And it takes time for ads to wear into people's minds. So if you are looking for those bigger moves, it's a big bet and it takes time to plant those seeds and to let them grow and get the ultimate payoff.
[12:33]
D
We're heading into the holiday season. Just recently I saw an ad for a new jewelry company that I didn't know of, but I did take note of it. Didn't take any action on it, didn't go out to the website, but I happened to get a catalog about a week later and in the mail. And we have seen the impact of a top of funnel channel like TV driving a halo impact to other investments across the marketing channel, digital and others, direct mail, et cetera. So how should marketers look to quantify the halo effect of brand investments across all their channels?
[13:09]
A
The invisible hand of brand building, what I like to call it. And we've, we've seen it and tested it a lot of different ways, setting up incrementality tests is a fundamental way to help you understand like how are TV and paid. It could be paid social, it could be paid digital. A lot of different things synergizing together. It can be really hard if you're like, hey, again, I'm just gonna go throw this flat budget nationally and hope I see all these different cross channel synergies. A lot of times it does take heaving up in individual markets. We do have other instances of where campaign ran on TV for 12 months and what do you know, they were able to pull back on their Google budget for the first time in five years. They had been growing sequentially. 30% more to Google, 30% more to Google, 30 percent more to Google. And all of a sudden they're like, hey, people are searching for my brand name. They're not searching for our generic product. And they're able to actually reallocate that budget and continue to invest in their own brand. So it plays out in different ways for different brands, but a lot of it's making sure you are looking at it the right way. You're not just going in saying, oh, it's going to lift all boats. And it should be easy to see because usually if you say it's easy, it's probably not true.
[14:20]
C
All right, Matt, enough of these softball questions. Angel and Elena, they're just feeding you the easy ones. I got some toughies for you. You ready?
[14:29]
A
Rob, did you come up with these yourself.
[14:33]
D
Shots?
[14:34]
A
No.
[14:34]
C
No way possible. All right, so question one. You can only invest in one. You can either pick media mix modeling, incrementality testing, or synthetic controls. Which one are you going with, Matt?
[14:53]
A
They all serve different purposes. I would say right now I am going to hop on the bandwagon of what feels like the industry and, and hop on incrementality testing. I think this can take lots of different shapes, sizes and forms, but having a controlled experiment where you do the planning and set it up in a way that you know, hey, this happened because I spent on TV is a good feeling. I always say I don't like to live in the gray zone. If a test fails, I just want to know it failed so I can move on, learn from it and go to the next step. That's the whole point of incrementality testing. You do the math ahead of time, forget what the right budget is, and either you hit your metric or you don't. You learn, you move on. And that's my favorite way to do it.
[15:33]
B
Hey, Matt, for my sake and the listener's sake, can you quickly summarize what MMM and synthetic controls are too.
[15:39]
C
Basically saying, can you define that for Rob, please?
[15:42]
A
I will do my best, Rob. I'll do my best. I mean, MMM's been around for a really long time. I feel like it's made a little bit of a resurgence now with some of the open source models that are out there from open both Facebook and Google. But MMM is basically throw all your data at AI and let it look for changes over time and when. Usually this has taken two to three years of your historic data. So key point number one, if you don't have two to three years of good consistent data, don't waste your time. But from there, as you introduce new channels, whether it's tv, whether it's social, whether whatever it is it will look for, when you did make that investment, how did things shift around? As for synthetic controls, it's a new, I'd call it buzzword up there with incrementality. It's usually just a fancy way to say how can we test for cheaper? And what you're doing is you're hyper focusing in on a smaller subset of usually the country when you look for like audiences. So Maybe you pick 5, 10 DMAs and you part them up into likeness. You expose half of it, you don't expose the other half and you look for how's my exposed group doing compared to by control group. And it can be a way to reduce budgets and try to test TV or CTV for cheaper.
[16:54]
C
Matt, I'm going to say you did a pretty good job answering that question. You pass. You get to move on to the next. The next juicy one.
[17:01]
A
Thanks, Rob. I appreciate it.
[17:03]
C
What do you think is the hardest marketing channel to measure?
[17:09]
A
I feel like I'm biased. I haven't measured out of home. I can only imagine how hard that is. But being that, being that I do work for a TV agency and I know how important sometimes multimillion dollar budgets are, not only is TV hard to measure, but it's just like the critical pressure to make sure you get it right. I am going to say tv, it's just there's so many eyeballs on it. Usually the CEO is right around the corner lurking, wanting to know is this working or not. So you combine being in a pressure cooker along with it being an offline channel. I get. Usually I'm in the hot seat month one rolls around. How are things performing? Matt, please answer that. It can be kind of fun sometimes. Sometimes not so fun.
[17:50]
C
Absolutely. All right, let's hear from Matt's BS meter. Here for a minute. What's one metric or model you think marketers should just stop relying on, period?
[18:01]
A
I will say a lot of times there's. It's tough because this is probably. This is not going to be a popular choice, but everyone is obsessed with like, new cac, new cac, new cac, new cac. And I, I think I'm going against every venture capital firm right now. So I might be voted off this podcast forever. But TV does so much. It definitely drives new, but it also, like, invigorates existing too. And if you can't look at the whole picture, I think I'm less anti newc and more so. Don't rule out different segments of people. Like, whether it's new, whether it's existing, if it's driving revenue, I think you should be happy. And like, people like hyper focus on whether it's new or existing. I just don't like metrics that like, say, hey, let's ignore this half of the picture. Because my boss, like, told me this was the only thing to look at. Because a lot of times we find the full value in TV across more things than just one.
[18:55]
C
I love that answer more because I just hate the acronym cac.
[19:00]
B
Yeah, Rob's trying to get that acronym band.
[19:03]
C
I'm sorry, CAC sounds like something you do when you have a hairball. So I'm just. I would love to eliminate intelligent people in boardrooms saying the word CAC just shouldn't happen. So I'm with you on that one. How about the other direction? What do you think is the most underrated?
[19:19]
A
There's just these massive correlations that exist. I think sometimes people, like, fight against. It's as simple as, hey, when you spend on tv, people search for your brand. Hey, when you have a higher share of voice, your brand grows. And while these aren't maybe as sexy as oh my roas is a 100. There's just correlations you can't deny. And it's like just simple math. And it's proven time and time again in research in the field, you name it. So, like, some of the more old school, there's a reason why they were doing that the way back in the day. It was working like, brands have been built over time on tv, on other channels, and sometimes it's even the less sophisticated ones that prevail.
[20:02]
C
Good answer.
[20:03]
A
All right, you give me a score. Like, is that a seven in your book, Rob?
[20:08]
B
And now Rob's going to answer the same question.
[20:11]
C
Now, I'm going to absolutely tell you let's turn.
[20:15]
D
Turn it on Rob.
[20:16]
C
Rob. Turn the.
[20:18]
D
Rob, many marketers are exploring, exploring AI attribution tools. What do you think they should be excited about, Rob? What do you think they should be cautious about?
[20:28]
C
You know what, I just, I, I love it. I would say Eminem and cac. I mean I would just, that'd be my answer.
[20:34]
A
I, I think you just made up a new acronym. Can you please define that for me?
[20:38]
B
You're talking about Candy.
[20:40]
C
M. M's, exactly. M and M's and cac.
[20:43]
A
Do you want me to take that one for you, Rob?
[20:45]
C
I do love me, but I love me. I love me some AI. I do love me some AI. And I hear there's AI attrib tools. Haven't played with them myself. Wouldn't know the names of them, but I know you know all of them. So are you excited about them? Are you like, what's Matt's hot take?
[21:03]
A
Almost three years since chat GPT changed the way everyone thinks about everything. And I will say for us data people out there, it's taken some time for the cooler gadgets to come out as like at first. Oh, like I'm talking to what feels like a human. It's getting to a point now where we're starting to feel the speed more than we were on the front end of that three year journey. So definitely excited by the way. It's able to talk across data sets, across organizations, it's able to tap into more and more every single day. And I think the speed and automation is, it's getting intense. We're feeling it, we're loving it. At the same time, garbage in, garbage out. A There's been a fair amount of warnings out there in terms of that too. And like people are now trying to plant seeds to throw models off. And there is some of that if you bring that within your own business, like you have to make sure that whatever you're feeding AI is of high quality and it's making the right decisions more often than not. Like we'll get data sets and it's like, oh, made a little mistake when I pulled that and sent that to you guys. And it's like, okay, if we had fed that to an EA model, it just would assumed your mom and dad giving it the right information. Like no, it would go off and make the wrong decision. So quality control is 100% a concern. Like you have to make sure you have really tight constraints around that and you're only feeding it good information. Super excited just to see where it can Go in terms of modeling and performance. On the flip side, where does privacy go? And what can you give it? What can't you give it? So it's continuing to evolve. It's exciting. I don't think marketing's gonna look the same in, in five years. I think in five years it'll be two years. After that, it'll look dramatically different. I think it's just going to continue to evolve really, really, really rapidly.
[22:46]
C
The future's coming fast at us. Matt, where do you see it going in the next few years?
[22:51]
A
We're already feeling it out there, like having designed frameworks for testing again. Five, 10 years ago, people would just come to TV and throw money at it and see what happened. People are now realizing that might have been a naive decision. And making sure you have design going into your tests, like measurement just doesn't just happen. You can't just like run a test and then measure it after the fact. You have to go in intentionally. And there's a lot more third party attribution companies popping up that help you think through design. We walk each one of our clients through, how can you design a test that you can measure? Because that's the most important thing. There's so many people that go test TV and they're like, I don't know if it worked or didn't work. Can you help me do it better next time? And it's like, wow, that was six figures, seven figures, eight figures, like, you name it right out the door.
[23:38]
B
Well, Matt, thank you. Thank you so much for answering all of our questions. I feel like there's a lot of really practical takeaways there for any marketer to wrap us up with something a little more fun. What is the most surprising thing data has ever taught you about yourself?
[23:52]
A
I shouldn't say this is surprising, but I've felt it this year more than ever. I don't know if it's because I have two little kids. I don't know if it's because I'm getting old, but there is a element of sleep and your physical performance. I ventured off to do a half marathon this year, and I will say the days I only got a couple hours of sleep. The running the next day was not so, so hot. And now with watches and gadgets all over the place, clear correlation between sleep and performance in terms of running.
[24:21]
C
I love sleep.
[24:23]
D
It's so good.
[24:23]
C
I sleep like it's my job.
[24:26]
D
I'm glad you have a job, Rob. Yeah, mine. What's that saying? If you want to know what People value. Look at their bank account. It's that only in my head. It's related to what are the most important things that you're working on. Like, I love a good time tracking exercise to actually do a bit of checks and balance on. Are you really working on the things with the right quantity that are so important in your life? Sometimes we all need a little check.
[24:52]
A
You tell me to put my phone down more often.
[24:55]
D
I need to put my phone down more often. I feel like, all right, Rob. When I saw this question, I was like, oh, God, what are we going to learn about Rob?
[25:03]
C
Well, I just. So I had a. I had a blood panel done recently for.
[25:09]
A
For a.
[25:10]
C
For food intolerance. In two days ago, I learned I'm extremely gluten intolerant. So that's a big. That was a big data point that I didn't know about myself and explains a lot about my visits to the restroom. I'm 51 years old.
[25:27]
D
I thought we were going to get through it without that, but I'm 51.
[25:31]
C
This is quite an age to learn such a factoid.
[25:36]
A
Elena, please follow that up.
[25:38]
B
Mine's not going to be anything, anything like that. We had a company on site, we had a speaker there who asked us to everyone go look at your screen time on your phone. I think that data was very interesting for me. I got wake up call. Just like the amount of time you spend on your phone. We use our phones, like for work and different types of life. So it can be hard. But definitely after I saw that, like, I'm setting time limits on some of these apps before I start just doom scrolling. So I'd recommend that go look at your screen time and look at averages too, because I was scary. He had people sit down in the room as he got to. I think it was, he was getting to like, better screen, like, less screen time.
[26:18]
D
Yeah, he started with 10 hours or something and then worked his way backwards. And I think there was two, two out of all of us. That was maybe like at an less than an hour. Is that what we ended up with?
[26:31]
A
Yeah.
[26:32]
B
Crazy.
[26:32]
D
That was pretty amazing.
[26:33]
C
It has to be the first product feature that shames you for using the product. Let's shame people for using our product.
[26:44]
B
That shows you how addictive it is. They weren't worried about that.
[26:46]
C
Yes, that's true. That's true.
[26:48]
B
All right, great. Matt, thank you so much for joining us.
[26:51]
A
Thanks, Matt. Absolutely. Thanks for the invite. Appreciate it, guys.
[26:54]
C
Thank you. Thank you.
[26:56]
B
That's it for this episode of the Marketing Architects. We'd like to thank Taylor de Los Reyes for producing the show. You can connect with us on LinkedIn. And if you like the podcast, please leave us a review. You now go forth and build great marketing.
[27:11]
A
Angela vanished.
[27:12]
C
Boy, this is really.
[27:14]
B
Rob, I'm just going to need you to just roll with right here.
[27:17]
C
I don't know, just weird. There's something weird going on.
[27:20]
D
Look at my.
[27:22]
A
Probably in settings, you can usually do, like, a freeze.
[27:25]
C
It's so weird. Like, people are like, I've never seen this before, but I don't want to screw it up and leave and then come back, so let's just go. I can't even look at you guys because it's too weird.
[27:35]
B
Marketing architects.

Summary7 min read

The Marketing Architects

Episode: The Long & Short of Measurement with Matt Hultgren

Date: December 16, 2025
Host(s): Elena Jasper, Angela Voss, Rob Demar
Guest: Matt Hultgren, Chief Analytics Officer, Marketing Architects

Overview

This episode delves into the enduring challenge of marketing measurement—with a focus on balancing short-term performance and long-term brand building. Drawing from new proprietary research and decades of practical experience, the hosts and guest Matt Hultgren tackle campaign measurement myths, attribution misconceptions, how to break down team silos, and the need for rigorous planning. The panel offers actionable guidance for marketers and explores emerging tools and models in effectiveness measurement.

Key Discussion Points & Insights

1. The Persistent Measurement Challenge

(00:43 – 02:43)

Human behavior is messy and context-driven. Consumer decisions stem from emotions, habits, memory, and social influences, making them difficult to precisely track in data.
Marketing effects are cumulative and delayed. Single ads rarely drive immediate purchase; instead, campaigns build familiarity and brand memory over time—a pattern most measurement systems miss.

"People make choices based on their emotion, their habit, their memory, their friend, their identity, social cues, none of which is easily visible in data and all of which shifts over time."
—Angela Voss (01:47)

2. Misconceptions about Attribution & Digital Metrics

(03:06 – 03:57)

Marketers chase instant feedback from digital channels and expect the same from offline (like TV), leading to unrealistic expectations ("the silver bullet solution").
Digital platforms (Google, Meta) have nurtured a culture of immediacy and supposed perfect measurement—unrealistic for complex, multi-channel campaigns.

"It's that need for speed where people sometimes forget how offline channels work and how consumers interact with media."
—Matt Hultgren (03:34)

3. The Planning Problem

(04:21 – 05:27)

Siloed teams and unclear goals undermine campaigns before they start.
Many marketers treat TV as an add-on without integrating strategy or defining clear KPIs.
Budget, timing, and cross-team coordination are often neglected, leading to wasted spend and measurement failures.

"Teams can be so disjointed...I got 50 grand, I'm just going to throw it at TV and see if that works. Is 50 grand enough? ...There aren't these conversations happening."
—Matt Hultgren (04:28)

4. The North Star Metric

(05:31 – 07:04)

Rather than tracking dozens of KPIs, marketers should align around a single, strategic “North Star Metric” for each channel.
This fosters clarity on campaign intent (brand, traffic, revenue) and helps teams define success upfront.

"Simplification can really help...just be really aligned on that before you even start.”
—Matt Hultgren (06:13)

5. Balancing CAC and Brand Growth

(07:04 – 08:30)

While short-term customer acquisition cost (CAC) metrics are vital for some businesses, building long-term brand value delivers market share, loyalty, and pricing power.
TV can drive both day-one results and longer-term growth; brands must assess their stage and goals.

"We do know the power of building a brand...having more loyal customers, growing your market share. I don't think anyone's going to complain about that."
—Matt Hultgren (07:44)

6. Breaking Down Team Silos

(09:02 – 09:50)

TV works best when brand, performance, and digital teams collaborate.
Measurement should account for TV’s full-funnel impact and encourage holistic planning and shared KPIs.

"If you want TV to work as hard as it possibly can for you...I would sure hope you have your digital teams at that table."
—Matt Hultgren (09:18)

7. "All Models Are Wrong, Some Are Useful"

(10:12 – 11:27)

No one model or tool ("silver bullet") reveals all truths; marketers must triangulate using multiple approaches for confidence in results.
Each model has strengths and gaps; understanding these is key to good decision-making.

"Measuring TV is hard. Like it's not easy...there isn't a silver bullet and you're going to have to be comfortable with ambiguity."
—Matt Hultgren (10:26)

8. Short-Term vs Long-Term Metrics

(11:27 – 12:33)

Short spikes can be misleading—look for longer-term trends to gauge effectiveness.
Brand metrics, like awareness, take sustained investment; expect delayed results.

"If you are looking for those bigger moves, it's a big bet and it takes time to plant those seeds and to let them grow and get the ultimate payoff."
—Matt Hultgren (12:16)

9. Quantifying the Halo Effect

(13:08 – 14:20)

TV and other top-of-funnel investments have a halo effect—boosting other channels (paid search, direct mail, etc.).
Incrementality tests and regional heaving-up can help reveal cross-channel synergies in spend effectiveness.

"We do have other instances...where campaign ran on TV for 12 months and what do you know, they were able to pull back on their Google budget for the first time in five years."
—Matt Hultgren (13:41)

10. Lightning Round: Tools & Models

(14:34 – 16:53)

Favorite Method: Incrementality testing ("If a test fails, I just want to know it failed so I can move on. That’s the whole point.")
—Matt Hultgren (15:06)
MMM (Media Mix Modeling): Best for large, historic data sets; looks at shifts over long timeframes.
Synthetic Controls: Enables lower-budget, rapid testing by splitting regions or groups for comparison.

11. Hardest Channel to Measure

(17:03 – 17:49)

TV is the toughest due to its offline nature, investment size, and executive scrutiny.

"Not only is TV hard to measure, but it's just like the critical pressure to make sure you get it right."
—Matt Hultgren (17:16)

12. Overrated & Underrated Metrics

(18:00 – 20:01)

Overrated: Obsessing over “new CAC”—it ignores the broader impact TV has on existing customers and total revenue.
Underrated: Simple, proven correlations—like the link between TV spend and branded search, or share of voice and growth—remain deeply powerful.

"I just don't like metrics that say, hey, let's ignore this half of the picture because my boss told me this was the only thing to look at."
—Matt Hultgren (18:47)

13. AI in Attribution & the Future

(20:16 – 22:45)

AI is rapidly making strides in attribution—enabling analysis across datasets and faster automation.
Quality control is crucial: “Garbage in, garbage out”—bad data yields bad guidance.
Data privacy and continued innovation will shape the next wave of marketing measurement.

"It's getting to a point now where we're starting to feel the speed...but quality control is 100% a concern. You have to make sure you have really tight constraints."
—Matt Hultgren (21:22)

14. The Importance of Design in Measurement

(22:51 – 23:37)

Successful measurement demands intentional test design from the start.
Marketers must set up frameworks prior to campaign launch to ensure their spend can actually be measured effectively.

"You can't just like run a test and then measure it after the fact. You have to go in intentionally."
—Matt Hultgren (22:58)

Notable Quotes & Memorable Moments

On Measurement Myopia:
"Everyone wants results now, and if you can't get it to me now, you're broken."
—Matt Hultgren (03:26)
Old School Still Works:
"Some of the more old school...there's a reason why they were doing that way back in the day—it was working. Brands have been built over time, on TV."
—Matt Hultgren (19:38)
On Data and Life Learnings:
"There is an element of sleep and your physical performance...clear correlation between sleep and performance in terms of running."
—Matt Hultgren (23:51)
Rob's Comic Relief:
"CAC sounds like something you do when you have a hairball."
—Rob Demar (19:02)
The Group on Screen Time:
"Go look at your screen time and look at averages too, because I was scary."
—Elena Jasper (25:38)

Timestamps for Key Segments

00:43 — Introduction to measurement challenges
03:06 — Biggest attribution misconception
04:21 — The planning problem in campaigns
05:33 — North Star metric and practical advice
07:04 — Balancing CAC with long-term brand
09:02 — Breaking down marketing team silos
10:12 — Using multiple models for measurement
11:27 — What short- and long-term metrics really mean
13:08 — Measuring the halo effect of TV
14:34 — Favorite measurement method & lightning round
17:03 — Hardest channels to measure
18:00 — Overrated and underrated metrics
20:16 — AI attribution tools: hype and caution
22:51 — The importance of intentional test design
23:51 — Fun: What’s the most surprising data insight about yourself?

Practical Takeaways

Start by aligning goals and KPIs across teams in the planning stage; avoid fragmented or reactive measurement approaches.
Choose a clear, realistic North Star metric for each channel and know what you intend to achieve.
Use multiple models and approaches; accept ambiguity but aim to triangulate truth.
Remember: "All models are wrong, some are useful."
Recognize TV and top-of-funnel investments create value across channels, not just direct return.
AI, automation, and attribution tools offer promise—provided the underlying data is well-governed and high-quality.

Tone

The conversation is friendly, candid, and practical, with genuine expertise and just the right balance of humor—making even technical measurement topics approachable and actionable.

Loading summary

Transcript104 lines

[00:00]
A
It's proven time and time again in research. Some of the more old school, like there's a reason why they were doing that the way back in the day it was working. Brands have been built over time, on tv, on other channels, and sometimes it's even the less sophisticated ones that prevail.
[00:15]
B
Marketing Architects hello and welcome to the Marketing Architects, a research first podcast dedicated to answering your toughest marketing questions. I'm Elena Jasper. I run the marketing team here at Marketing Architects. And I'm joined by my co hosts Angela Voss, the CEO of Marketing Architects. And Rob Demar is the chief product architect of misfits and machines.
[00:34]
C
Hello. Hello.
[00:35]
B
And we're joined by Matt Hultgren, the Chief Analytics Officer at Marketing Architects.
[00:40]
A
Thanks for having me back, Magic.
[00:42]
C
Matt, it's been a minute.
[00:44]
B
We're back with our thoughts on some recent marketing news. Always trying to root our opinions and data research and what drives business results. And today we are going to be on theme, we're talking about measurement. We'll explore what's broken in measurement today, how to balance short term performance with long term brand building, and why the best marketers use multiple models to find the truth. But I will kick us off, as I always do, with some research and we have some of our own to share today. It's our report that dropped this week and it's called Measuring the Long and the Short. It tackles one of marketing's toughest challenges, proving what's really working. It argues that TV and marketing as a whole isn't unmeasurable, it's just being measured the wrong way. It explains why so many campaigns fail before they even launch. From siloed teams to unclear goals. And lays out how to design measurement into a campaign from the start. It also explores how to capture both short term response and long term brand impact, because real growth comes from balancing the two. And let's actually start with you. Why is measurement such a persistent challenge in marketing?
[01:41]
D
How long do we have here? This is a big loaded question. Not that long. Okay.
[01:46]
A
All right.
[01:46]
D
I'll try to keep it as succinct as possible. Our human behavior is very messy. It's contextual. It's influenced by far more than one touch point. And I think even with better data, better tools, more sophisticated models, people just don't make decisions in a super clean linear way. People make choices based on their emotion, their habit, their memory, their friend, their identity, social cues, none of which is easily visible in data and all of which kind of shifts over time. And I think beyond that, marketing effects are, or can be at least the majority of them. They're delayed, they're cumulative, as single ads just really rarely cause a predictable purchase, but instead build that familiarity and memory over weeks and months, which is something that most measurement systems struggle to Capture. Right, Matt?
[02:43]
A
100%.
[02:44]
B
And thank goodness I'm not managing that part of our business. It's Matt who is very smart, has a big brain, is also, I'd say, probably more of a skeptic than the average measurement thought leader we've had on the show. We have a lot of questions for you, Matt, so we're going to pepper you with them today. What is the biggest misconception brands have about attribution in general?
[03:07]
A
So I don't know who to point the blame to. I don't know if we go all the way back to Steve Jobs, Google, Meta. But what those three things have in common is the need for speed. Whether it was the iPhone and just having everything on your hands at one time. Google, you can track clicks and immediately get feedback in terms of how things are performing. Meta just piled onto Google and it's we call them the digital divas. But everyone wants results now and if you can't get it to me now, you're broken. And everyone just wants the one answer that's going to tell them, how's my campaign performing? And it's that need for speed where people sometimes forget how offline channels work and how consumers interact with media. So the number one thing we come up against is just people wanting that silver bullet solution. And I think it comes from being obsessed with those digital metrics that are so easily tangible all over the place.
[03:58]
B
Right? Google and Meta have sold that you can have a result immediately. It's going to be 100% accurate. But that is not how marketing works, as you said, or consumers work. One, one thing from the report that we've talked about before on the podcast a little bit is this planning problem. So I wanted you to explain what that is and why does it cause so many measurement failures before campaigns even start?
[04:21]
A
I don't even think I knew this existed until I had seen it out in the live world numerous times now where it's like teams can be so disjointed and they're like, hey, we're going to do tv. But it's just like this one person within a business, he didn't talk to his other fellow teams to figure out how is everything going to synergize together. And it's like, oh, I got 50 grand, I'm just going to throw it at TV and see if that works. Is 50 grand enough? Is digital set up in a way to actually help TV do better? There aren't these conversations happening. What are the KPIs? What does your boss want? What does the CMO CEO want? And it's like if you don't start from day one being very crystal clear aligned on here's my KPIs, here's what I'm trying to measure. Here's how I'm going to measure. You might go to the market at the wrong time during peak seasonality and you're for sure not going to measure anything. You might go to the market with the wrong budget where there's just no chance you're going to be able to see the lift that you're hoping to see. And it's like there's just so many campaigns that just aren't thought out. It's like, hey, performance isn't good, we haven't tried tv. I'm just going to throw some money at it and hope it works. Usually doesn't pan out very well.
[05:27]
B
What's that saying? If you fail to plan, you plan to fail.
[05:31]
A
Sounds good to me.
[05:32]
C
I like it. I think I have that tattoo.
[05:34]
B
Oh, great. No one needs to see that. Okay. Part of planning is what you've called a North Star metric. And I like this a lot because I think it's nice on the podcast to try to have some practical takeaways. You've talked about the importance of aligning around that. How could a CMO marketing team go about, first of all, what is it? And then how could they go about choosing it?
[05:52]
A
Yeah, I think a lot of times we're kind of obsessed with data now. Right? Like I have 50 KPIs, I gotta track them all and oh no, this one doesn't look good. What does that mean? And sometimes simplification can really help. It's gonna probably look different for Google and branded paid search than it does look like for tv. So sometimes it's good to compartmentalize the upper funnel channel. What is the most important thing I'm hoping this channel does for my business? Obviously Google's gonna be there to collect. People are searching for my brand, I'm getting purchases. You're going to be hyper focused on that, bringing in the roas you need. But when it comes to tv, are you looking for awareness? Are you looking for traffic to your site? Are you looking to maybe pay Google less by having more people searching for you than generic terms and making sure you're again aligned with your internal team of what's your intent of going to market with an offline channel? Building is it. Building mental availability and awareness is it. I do need revenue and we don't have unlimited cash to fund this. So making sure you know what that North Star metric is going into a campaign so you don't get into the campaign and wonder, oh no, like some metrics look good, some metrics look bad, what does success look like? You just have to be really aligned on that before you even start.
[07:04]
D
Okay, Matt, I'm the marketer and my North Star metric is day one cac. So what's your advice for me? I'm under pressure to drive immediate results. How can we think about balancing and proving short term ROI with building that long term brand growth?
[07:24]
A
You must spend a little bit with Google and Meta there, Ange.
[07:27]
D
Very, very trying to pay the bills, trying to do it very accountably.
[07:32]
A
There's definitely businesses that are in a position where they do need CAC and we're not here to say that is wrong. At the end of the day, TV does a lot more than just that. And there's a chance that you turn off TV because you're not hitting the cacs you need. And yeah, you can't just put in more budget. And we always tell our clients we're going to treat your dollars like they're our own. At the same time, we do know the power of building a brand, whether it's pricing power, having more loyal customers, growing your market share. I don't think anyone's going to complain about that. And I think again you have to figure out where you are in your business life cycle and can you afford to invest in a brand channel. We do believe TV also drives immediate results. We see it every single day where there's spikes in traffic and people making purchases. Sometimes that ROI is net profitable day one. There's other instances where we have brands that are investing in that awareness and the long term payoff oftentimes surmounts like what they see before that. So there's different situations that kind of play out live in the field.
[08:30]
D
Well, I think one of the key challenges and opportunities, especially of a channel like tv, is that it is full funnel and it does drive both immediate sales to your point. So measure CAC as well as building that long term demand from a brand perspective. But one of the challenges I know we've seen with clients as they come in is just the silos that you mentioned earlier between maybe a brand team, a performance team, an analytics team. When it comes to measurement, what's your advice to breaking down some of those silos?
[09:02]
A
I will say being a TV only agency again, we've seen this play out where the brand team doesn't talk to the performance team, which doesn't talk to the digital team. We try to come to the table and say, everyone please come to the table. Can we have conversations about how to make this most this campaign that's usually TV is a pretty big investment. Like you'd think you would have all the key stakeholders at the table. There's instances where we couldn't even convince them of that. But that's really. It comes down to if you want TV to work as hard as it possibly can for you, TV is driving people to search for you on the web. I would sure hope you have your digital teams at that table to have that conversation about how we can have these campaigns synergized between the two. And everyone should be there thinking through all those intangible elements you're talking about. Ang it's not just a performance channel, it's not just a brand channel. It truly is full funnel.
[09:51]
D
Totally. One of our distinctive assets, I think on this podcast is the saying all models are wrong, some are useful. And you may have been the first one to have said that on this podcast, maybe I don't know, a year ago. But how do you think about trying?
[10:05]
C
I've got that tattoo as well.
[10:06]
A
Oh gosh, it's probably a triangle if I had to guess.
[10:12]
D
You may be listening to this in the morning, but I'm just going to tell all the listeners right now. It's too late in the day for all these jokes from Rob about his tattoos. How do you think about that triangulation mat using multiple models or methods to build confidence and results.
[10:27]
A
This is not a fun topic. I usually start off anytime I'm talking to a client to say measuring TV is hard. Like it's not easy. And if we can even go back to earlier in the pod, like the reality is there isn't a silver bullet and you're going to have to be comfortable with ambiguity. That is tv in terms of each model is going to have its strengths, each model is going to have its weaknesses. And it's by best you know what those are in each circumstance so you don't go make bad marketing decisions. But it is a massive puzzle. There's a lot of different models you can use and each one is going to help you fill in that puzzle. In terms of who's responding to my Ads is different creative or media performing well? How is it affecting my overall top line? And again, there's certain models we use to help understand the insights of what media is working best. Those are not the models we use to help our clients understand how TVs performing overall. So I definitely would recommend making sure you have a really good feel and sense of what each model does for your business before even going into to TV and trying to make decisions from your perspective.
[11:27]
D
Given there's so many options and the channel is full funnel, what short term metrics do you believe really signal that effectiveness versus perhaps just being noise that's going to distract from the measurement story. And then what long term metrics have you seen actually translate into that business growth that you mentioned earlier?
[11:45]
A
Yeah, I think coming back to the planning process too, like you don't want just a quick spike and be like oh it's working or oh, it's not. Like time is a really important part of this equation. You want to make sure that you're starting to see trends and you're not getting like a false positive or a false negative. I think that's one of the first big pieces of it. In addition to that, for longer terms like brand metrics, I hope you're not going to go spend for four weeks on TV and expect for your awareness to shoot up. I'm sorry, I don't remember what I had for breakfast yesterday, but I do remember Geico commercials. And maybe that's an extreme example of 15 minutes could save you 15% or more of your car insurance. And it takes time for ads to wear into people's minds. So if you are looking for those bigger moves, it's a big bet and it takes time to plant those seeds and to let them grow and get the ultimate payoff.
[12:33]
D
We're heading into the holiday season. Just recently I saw an ad for a new jewelry company that I didn't know of, but I did take note of it. Didn't take any action on it, didn't go out to the website, but I happened to get a catalog about a week later and in the mail. And we have seen the impact of a top of funnel channel like TV driving a halo impact to other investments across the marketing channel, digital and others, direct mail, et cetera. So how should marketers look to quantify the halo effect of brand investments across all their channels?
[13:09]
A
The invisible hand of brand building, what I like to call it. And we've, we've seen it and tested it a lot of different ways, setting up incrementality tests is a fundamental way to help you understand like how are TV and paid. It could be paid social, it could be paid digital. A lot of different things synergizing together. It can be really hard if you're like, hey, again, I'm just gonna go throw this flat budget nationally and hope I see all these different cross channel synergies. A lot of times it does take heaving up in individual markets. We do have other instances of where campaign ran on TV for 12 months and what do you know, they were able to pull back on their Google budget for the first time in five years. They had been growing sequentially. 30% more to Google, 30% more to Google, 30 percent more to Google. And all of a sudden they're like, hey, people are searching for my brand name. They're not searching for our generic product. And they're able to actually reallocate that budget and continue to invest in their own brand. So it plays out in different ways for different brands, but a lot of it's making sure you are looking at it the right way. You're not just going in saying, oh, it's going to lift all boats. And it should be easy to see because usually if you say it's easy, it's probably not true.
[14:20]
C
All right, Matt, enough of these softball questions. Angel and Elena, they're just feeding you the easy ones. I got some toughies for you. You ready?
[14:29]
A
Rob, did you come up with these yourself.
[14:33]
D
Shots?
[14:34]
A
No.
[14:34]
C
No way possible. All right, so question one. You can only invest in one. You can either pick media mix modeling, incrementality testing, or synthetic controls. Which one are you going with, Matt?
[14:53]
A
They all serve different purposes. I would say right now I am going to hop on the bandwagon of what feels like the industry and, and hop on incrementality testing. I think this can take lots of different shapes, sizes and forms, but having a controlled experiment where you do the planning and set it up in a way that you know, hey, this happened because I spent on TV is a good feeling. I always say I don't like to live in the gray zone. If a test fails, I just want to know it failed so I can move on, learn from it and go to the next step. That's the whole point of incrementality testing. You do the math ahead of time, forget what the right budget is, and either you hit your metric or you don't. You learn, you move on. And that's my favorite way to do it.
[15:33]
B
Hey, Matt, for my sake and the listener's sake, can you quickly summarize what MMM and synthetic controls are too.
[15:39]
C
Basically saying, can you define that for Rob, please?
[15:42]
A
I will do my best, Rob. I'll do my best. I mean, MMM's been around for a really long time. I feel like it's made a little bit of a resurgence now with some of the open source models that are out there from open both Facebook and Google. But MMM is basically throw all your data at AI and let it look for changes over time and when. Usually this has taken two to three years of your historic data. So key point number one, if you don't have two to three years of good consistent data, don't waste your time. But from there, as you introduce new channels, whether it's tv, whether it's social, whether whatever it is it will look for, when you did make that investment, how did things shift around? As for synthetic controls, it's a new, I'd call it buzzword up there with incrementality. It's usually just a fancy way to say how can we test for cheaper? And what you're doing is you're hyper focusing in on a smaller subset of usually the country when you look for like audiences. So Maybe you pick 5, 10 DMAs and you part them up into likeness. You expose half of it, you don't expose the other half and you look for how's my exposed group doing compared to by control group. And it can be a way to reduce budgets and try to test TV or CTV for cheaper.
[16:54]
C
Matt, I'm going to say you did a pretty good job answering that question. You pass. You get to move on to the next. The next juicy one.
[17:01]
A
Thanks, Rob. I appreciate it.
[17:03]
C
What do you think is the hardest marketing channel to measure?
[17:09]
A
I feel like I'm biased. I haven't measured out of home. I can only imagine how hard that is. But being that, being that I do work for a TV agency and I know how important sometimes multimillion dollar budgets are, not only is TV hard to measure, but it's just like the critical pressure to make sure you get it right. I am going to say tv, it's just there's so many eyeballs on it. Usually the CEO is right around the corner lurking, wanting to know is this working or not. So you combine being in a pressure cooker along with it being an offline channel. I get. Usually I'm in the hot seat month one rolls around. How are things performing? Matt, please answer that. It can be kind of fun sometimes. Sometimes not so fun.
[17:50]
C
Absolutely. All right, let's hear from Matt's BS meter. Here for a minute. What's one metric or model you think marketers should just stop relying on, period?
[18:01]
A
I will say a lot of times there's. It's tough because this is probably. This is not going to be a popular choice, but everyone is obsessed with like, new cac, new cac, new cac, new cac. And I, I think I'm going against every venture capital firm right now. So I might be voted off this podcast forever. But TV does so much. It definitely drives new, but it also, like, invigorates existing too. And if you can't look at the whole picture, I think I'm less anti newc and more so. Don't rule out different segments of people. Like, whether it's new, whether it's existing, if it's driving revenue, I think you should be happy. And like, people like hyper focus on whether it's new or existing. I just don't like metrics that like, say, hey, let's ignore this half of the picture. Because my boss, like, told me this was the only thing to look at. Because a lot of times we find the full value in TV across more things than just one.
[18:55]
C
I love that answer more because I just hate the acronym cac.
[19:00]
B
Yeah, Rob's trying to get that acronym band.
[19:03]
C
I'm sorry, CAC sounds like something you do when you have a hairball. So I'm just. I would love to eliminate intelligent people in boardrooms saying the word CAC just shouldn't happen. So I'm with you on that one. How about the other direction? What do you think is the most underrated?
[19:19]
A
There's just these massive correlations that exist. I think sometimes people, like, fight against. It's as simple as, hey, when you spend on tv, people search for your brand. Hey, when you have a higher share of voice, your brand grows. And while these aren't maybe as sexy as oh my roas is a 100. There's just correlations you can't deny. And it's like just simple math. And it's proven time and time again in research in the field, you name it. So, like, some of the more old school, there's a reason why they were doing that the way back in the day. It was working like, brands have been built over time on tv, on other channels, and sometimes it's even the less sophisticated ones that prevail.
[20:02]
C
Good answer.
[20:03]
A
All right, you give me a score. Like, is that a seven in your book, Rob?
[20:08]
B
And now Rob's going to answer the same question.
[20:11]
C
Now, I'm going to absolutely tell you let's turn.
[20:15]
D
Turn it on Rob.
[20:16]
C
Rob. Turn the.
[20:18]
D
Rob, many marketers are exploring, exploring AI attribution tools. What do you think they should be excited about, Rob? What do you think they should be cautious about?
[20:28]
C
You know what, I just, I, I love it. I would say Eminem and cac. I mean I would just, that'd be my answer.
[20:34]
A
I, I think you just made up a new acronym. Can you please define that for me?
[20:38]
B
You're talking about Candy.
[20:40]
C
M. M's, exactly. M and M's and cac.
[20:43]
A
Do you want me to take that one for you, Rob?
[20:45]
C
I do love me, but I love me. I love me some AI. I do love me some AI. And I hear there's AI attrib tools. Haven't played with them myself. Wouldn't know the names of them, but I know you know all of them. So are you excited about them? Are you like, what's Matt's hot take?
[21:03]
A
Almost three years since chat GPT changed the way everyone thinks about everything. And I will say for us data people out there, it's taken some time for the cooler gadgets to come out as like at first. Oh, like I'm talking to what feels like a human. It's getting to a point now where we're starting to feel the speed more than we were on the front end of that three year journey. So definitely excited by the way. It's able to talk across data sets, across organizations, it's able to tap into more and more every single day. And I think the speed and automation is, it's getting intense. We're feeling it, we're loving it. At the same time, garbage in, garbage out. A There's been a fair amount of warnings out there in terms of that too. And like people are now trying to plant seeds to throw models off. And there is some of that if you bring that within your own business, like you have to make sure that whatever you're feeding AI is of high quality and it's making the right decisions more often than not. Like we'll get data sets and it's like, oh, made a little mistake when I pulled that and sent that to you guys. And it's like, okay, if we had fed that to an EA model, it just would assumed your mom and dad giving it the right information. Like no, it would go off and make the wrong decision. So quality control is 100% a concern. Like you have to make sure you have really tight constraints around that and you're only feeding it good information. Super excited just to see where it can Go in terms of modeling and performance. On the flip side, where does privacy go? And what can you give it? What can't you give it? So it's continuing to evolve. It's exciting. I don't think marketing's gonna look the same in, in five years. I think in five years it'll be two years. After that, it'll look dramatically different. I think it's just going to continue to evolve really, really, really rapidly.
[22:46]
C
The future's coming fast at us. Matt, where do you see it going in the next few years?
[22:51]
A
We're already feeling it out there, like having designed frameworks for testing again. Five, 10 years ago, people would just come to TV and throw money at it and see what happened. People are now realizing that might have been a naive decision. And making sure you have design going into your tests, like measurement just doesn't just happen. You can't just like run a test and then measure it after the fact. You have to go in intentionally. And there's a lot more third party attribution companies popping up that help you think through design. We walk each one of our clients through, how can you design a test that you can measure? Because that's the most important thing. There's so many people that go test TV and they're like, I don't know if it worked or didn't work. Can you help me do it better next time? And it's like, wow, that was six figures, seven figures, eight figures, like, you name it right out the door.
[23:38]
B
Well, Matt, thank you. Thank you so much for answering all of our questions. I feel like there's a lot of really practical takeaways there for any marketer to wrap us up with something a little more fun. What is the most surprising thing data has ever taught you about yourself?
[23:52]
A
I shouldn't say this is surprising, but I've felt it this year more than ever. I don't know if it's because I have two little kids. I don't know if it's because I'm getting old, but there is a element of sleep and your physical performance. I ventured off to do a half marathon this year, and I will say the days I only got a couple hours of sleep. The running the next day was not so, so hot. And now with watches and gadgets all over the place, clear correlation between sleep and performance in terms of running.
[24:21]
C
I love sleep.
[24:23]
D
It's so good.
[24:23]
C
I sleep like it's my job.
[24:26]
D
I'm glad you have a job, Rob. Yeah, mine. What's that saying? If you want to know what People value. Look at their bank account. It's that only in my head. It's related to what are the most important things that you're working on. Like, I love a good time tracking exercise to actually do a bit of checks and balance on. Are you really working on the things with the right quantity that are so important in your life? Sometimes we all need a little check.
[24:52]
A
You tell me to put my phone down more often.
[24:55]
D
I need to put my phone down more often. I feel like, all right, Rob. When I saw this question, I was like, oh, God, what are we going to learn about Rob?
[25:03]
C
Well, I just. So I had a. I had a blood panel done recently for.
[25:09]
A
For a.
[25:10]
C
For food intolerance. In two days ago, I learned I'm extremely gluten intolerant. So that's a big. That was a big data point that I didn't know about myself and explains a lot about my visits to the restroom. I'm 51 years old.
[25:27]
D
I thought we were going to get through it without that, but I'm 51.
[25:31]
C
This is quite an age to learn such a factoid.
[25:36]
A
Elena, please follow that up.
[25:38]
B
Mine's not going to be anything, anything like that. We had a company on site, we had a speaker there who asked us to everyone go look at your screen time on your phone. I think that data was very interesting for me. I got wake up call. Just like the amount of time you spend on your phone. We use our phones, like for work and different types of life. So it can be hard. But definitely after I saw that, like, I'm setting time limits on some of these apps before I start just doom scrolling. So I'd recommend that go look at your screen time and look at averages too, because I was scary. He had people sit down in the room as he got to. I think it was, he was getting to like, better screen, like, less screen time.
[26:18]
D
Yeah, he started with 10 hours or something and then worked his way backwards. And I think there was two, two out of all of us. That was maybe like at an less than an hour. Is that what we ended up with?
[26:31]
A
Yeah.
[26:32]
B
Crazy.
[26:32]
D
That was pretty amazing.
[26:33]
C
It has to be the first product feature that shames you for using the product. Let's shame people for using our product.
[26:44]
B
That shows you how addictive it is. They weren't worried about that.
[26:46]
C
Yes, that's true. That's true.
[26:48]
B
All right, great. Matt, thank you so much for joining us.
[26:51]
A
Thanks, Matt. Absolutely. Thanks for the invite. Appreciate it, guys.
[26:54]
C
Thank you. Thank you.
[26:56]
B
That's it for this episode of the Marketing Architects. We'd like to thank Taylor de Los Reyes for producing the show. You can connect with us on LinkedIn. And if you like the podcast, please leave us a review. You now go forth and build great marketing.
[27:11]
A
Angela vanished.
[27:12]
C
Boy, this is really.
[27:14]
B
Rob, I'm just going to need you to just roll with right here.
[27:17]
C
I don't know, just weird. There's something weird going on.
[27:20]
D
Look at my.
[27:22]
A
Probably in settings, you can usually do, like, a freeze.
[27:25]
C
It's so weird. Like, people are like, I've never seen this before, but I don't want to screw it up and leave and then come back, so let's just go. I can't even look at you guys because it's too weird.
[27:35]
B
Marketing architects.