In this episode of Markigy, Scott Konopasek, the CEO and Founder of Mint Measure, shares his expert tips and advice on mastering online ad measurement. He talks about when marketers need more advanced measurement and attribution tools, effective ways to measure online ad performance, and the importance of communication skills to persuade C-suite executives to invest in your ideas. Additionally, Scott shares his predictions for the future of data privacy and attribution, and how Mint Measure's paid media attribution model can help you stand out from the rest. So, don't miss out on this informative and educative podcast episode!
As marketing budgets are being squeezed, digital advertising measurement has never been so important. At the same time, technology is moving so quickly that it’s becoming more difficult to measure the impact of our marketing strategies. This causes us marketers to reevaluate everything so we can solve these measurement problems and stay up to speed.
Having the right paid channel attribution tools and the right ad measurement technology prevents you from wasting money and time on nothing. That’s why we invited a genius in paid attribution and measurement to talk about how to measure the effectiveness of your online advertising.
In this episode of Markigy Podcast, your host Leanne Dow-Weimer welcomes Scott Konopasek, CEO and Founder of Mint Measure, to share tips and advice on mastering online ad measurement so you can create marketing strategies that get c-suite buy-in.
In this episode, we discuss:
Meet the Host:
Leanne Dow-Weimer, Founder & Host of Markigy Podcast https://www.linkedin.com/in/leannedow
Meet the Guest:
Scott Konopasek, CEO and Founder of Mint Measure
https://www.linkedin.com/in/scott-konopasek
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Visit Mint Measure’s website: https://www.mintmeasure.com
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This episode was produced and brought to you by Reignite Media.
Scott K Markigy Episode
[00:00:00] [00:00:30]
[00:00:41] Leanne Dow-Weimer: Hi there. This is Leanne with Markigy, the Science of Strategic Marketing Podcast, and I'm joined today by Scott Konopasek, the CEO and founder of Mint Measure. Scott, tell me a little bit more about you and your background and how you ended up here.
[00:00:58] Scott Konopasek: Yeah, well thanks for having me. [00:01:00] Um, you know, I. I'm, I'm a little bit unusual in that I actually went to school for advertising.
I think almost everyone that I know in advertising and marketing went to school for something else and just happened to find themselves at an ad agency. Um, So I have been, uh, an agency guy for most of my career. I spent 10 years doing performance marketing, um, at different agencies. I started my career in Salt Lake City.
Um, I moved to Knoxville and uh, started the digital [00:01:30] media department at an agency group. Agency called the Tom Bris group. Um, and then I moved to New York City and worked at a couple of different agencies there. Um, and so I've worked with, you know, everyone from the local mom and pop shop down the road to Jenny Craig and American Red Cross and worked on like Slack, pre i p o.
So, um, , you know, my background is really, you know, this very specialized media planning and buying and over the course of my career I kind of got a little bit more into [00:02:00] ad tech and how the tech works and analytics and, you know, really just kind of found that I like analytics and I like, you know, the numbers and seeing, you know, what's working and what's not.
[00:02:10] Leanne Dow-Weimer: Yeah, definitely. Um, I had someone comment that like, marketers hate being held to KPIs and measuring stuff, and I'm like, that's anything but true. Um, . So, you know, we talked a lot about the ways that things are measured and, and what they are. And you know, I think this is a bigger and [00:02:30] bigger trend as marketing budgets kind of are getting the squeeze.
Um, what, what kind of, how does that relate to what you're doing and what you've been doing in the past? Um, as far as how do you think about that differently? .
[00:02:46] Scott Konopasek: Yeah, so I think when it comes to like measurement, we kind of have to separate it into two types of categories. There is the technological landscape and privacy regulations and all the things that that entails.[00:03:00]
And then there is the like, What I'll call attitudes or the people part of measurement. So on the technology front, I think for most of our careers, and, and really the last 10 or 15 years, tracking was just kind of taken for granted. Um, third party cookies were everywhere. Platforms didn't have to worry about privacy.
Um, so. Over the last couple of years, it's become a lot more technologically challenging to measure, and it's really required everybody in the [00:03:30] space to reevaluate what they're doing if the technologies or the approach is still valid, and then figure out those technical solutions for how to address that.
So there's a lot that's, that's happening there. I think, you know, we've seen a, a. , I don't wanna call it a regression back to mms, but I'll call it a regression because mm. M started in the 1960s and they kind of got pushed aside for most brands in the 2010s because multi-touch attribution was able to add some user level data.
And so now we're seeing brands kind of [00:04:00] go back to that. Um, anybody who's doing, uh, multi-touch or bimodal attribution is figuring out technologically how do. Lean more heavily on first party data using hash device IDs. You know, how do they structure things for privacy compliant, um, or conscious advertisers.
Uh, and there were also five states that, uh, starting this year have new privacy regulations coming online. So like, What's happening there? I mean, everyone's just kind of, you know, the, the technological [00:04:30] aspect is moving so quickly that it's really tough for even us as day-to-day practitioners to stay, um, up to speed.
So I think like that's just an evolving landscape. I think there are two kind of predictions that I can give around that. The first is, Um, everyone's really focused on first party data, and I think that's going to shift from anybody's first party data to brands like really starting to develop their own first party attribution and analytic [00:05:00] solutions or companies who offer that ability for a brand to kind of ingest that.
Um, the second major, uh, thing that I'll predict around the technological aspect is that usability. is going to Trump like. What I'll call rigor, the best solution, if it's really hard to use, is going to struggle. Um, even if it is more technologically sound or better tracking and a solution that's [00:05:30] maybe not as technologically sound, but that's easier to use, is going to.
um, is going to kind of be come front and center. And I think that the reason for that prediction is that most people only care so much about the technological aspect. They wanna know, can I believe the data that this is giving me? They'll ask a few questions. They might like punt it to their analytics guy or their data guy.
And if the answer is yes, then most people don't care. If the next solution over is [00:06:00] 5% better or 10% better, it then falls down to like us.
[00:06:05] Leanne Dow-Weimer: Right. I, I, I mean, . I think that we've all encountered some pretty clunky solutions where it just gets to be so frustrating to do the most basic stuff that you're just like, am I spending two hours of my time messing around trying to get this to show me the the answer to my question?
Or am I doing something that shows me kind of an overview [00:06:30] of the trend and I can spend half as much time to get what I'm after? And. You know, that's, that's huge.
[00:06:41] Scott Konopasek: Yeah. So this actually ties really well into kind of the people aspect of measurement, which is that, um, advertisers or marketers in general are not analysts.
A marketer might be really good at content, might be really good at audience strategy, might be [00:07:00] good at knowing how to buy ads in a certain place. . But when it comes to analytical knowledge, looking at big data sets, making sense of them, understanding what to do, um, that just like really falls short and there's a lot of friction that individuals feel.
So this example that you gave, like, am I gonna spend two hours? banging my head against the wall, trying to analyze some stuff. I'm gonna get frustrated. I'm gonna get mad. I'm gonna scream at my computer a couple of times and like, okay, I might actually get the work [00:07:30] done, but like, what's the emotional cost of doing the analytics?
And so, um, we, we kind of realize that marketers prefer to work on non analytical things and. Figuring out how to like help customers or help, you know, marketers in general be able to understand or develop an analytics approach and have the data at their disposal. And so I think we're going to see, um, , [00:08:00] I think a lot of tools are going to continue to supplement that lack of analytical knowledge.
So, uh, I've worked with a ton of different brands. Very rarely does a brand have like an in-house analytics team. Um, and if they do, that analytics person is typically not working on. Advertising or marketing analytics. It's business analytics, it's cohort analyses, right? All those different other things.
Um, and then ad agencies, if there are, um, analysts, they're typically [00:08:30] doing more like reporting. They're pulling reports out of Google Analytics. And so, um, There's kind of this gap in between what's needed from an analytical perspective to drive meaningful change in marketing strategies and the skillsets that are available, whether internally or, um, you know, at your agency to be able to deliver on that.
There's a, an e-marketer study that we quote, Um, all the time that says 77% of marketers lack the knowledge, [00:09:00] skillset, and or the staff to be able to interpret and apply data. And that's a really staggering number because then said other ways, only 23% of people or marketers have the ability to really use their data effectively.
Yeah.
[00:09:14] Leanne Dow-Weimer: And thankfully, I, I guess I am kind of, that's where my blue ocean is, is that I spend more time looking at the, the data. Uh, that's where my strong suit is. So like, I find this incredibly fascinating. One trend that I've noticed that [00:09:30] also impacts it is that that upstream, um, you know, if I, I've been in plenty of positions where I have to explain to someone else's investor or some, you know, the c e o of my client or, you know, some other leadership position that just does not have the bandwidth.
Or care about the details in the data. They just wanna know what you're gonna do to fix it. And the [00:10:00] faster that you can fix it, the more valuable you are. Um, and that's been, you know, that's, that's something that I think is. Is is more and more prevalent when, you know, there's memes about, you know, the different generations at work.
Mm-hmm. , um, and we'll refrain from calling any of those out. Um, but you know, there's, there's different technological abilities in, you know, different organizations and so sometimes it's just not [00:10:30] accessible to everyone on the marketing team. Mm-hmm. , um, and, and you know, and that doesn't detract from their abilities.
If you have someone that's just amazing at design and they're incredibly artistic, do they need to know what's going on with sequel? Like, do they Right? Um, but. What, what matters is, is how well that, that piece of content performs. The, the graphics, [00:11:00] the copy, the placement, all of it. Um, and so, you know, we, we've kind of said some terms.
I wanna make sure we like, kind of circle back , gosh, I hope I say these jargony things and I cringe. Um, but I wanted to revisit, uh, the definition of some, so when you say first party data, how do you.
[00:11:21] Scott Konopasek: first party data is data that is given to an entity by a user, and that entity that [00:11:30] received the data, owns it and has the permission to use it for whatever purposes.
[00:11:37] Leanne Dow-Weimer: So a real life example of that would be if you had a website and you had visitors come to your website and your own recording. , um, platform, you know, your own stuff. Mm-hmm. intelligence, getting real technical here stuff, um, . But, but you're, [00:12:00] you capture that yourself instead of having a plug in from someone else that captures it, um, per se.
Or like, where do we, where do we call the line there?
[00:12:09] Scott Konopasek: So let's, let's quickly talk about like the most common types of first party data, because if you say to most agency people, at least that's the world that, that I'm, I'm working with most days. They think, oh yeah, our, our advertiser has a CRM chock full of email addresses, and we have the personal information of the people who [00:12:30] made purchases from us in the past.
Absolutely first party data. The the customer went to the website, gave that information, whether that was part of a transaction for a service, or whether that was just like, Hey, sign up for our newsletter. So that's what's like most common. But there's another type of first party data that is much less well known, which is first party cookies.
And so you don't hear advertisers very often [00:13:00] talking about owning or having their own first party cookies and their own first party data. Um, and so this is one of the things that we're working on, and they're a handful of others in the space working on it as well, where essentially an advertiser has the ability, if they have the right technology, or they work with the right partner so that when a we, a user comes to their website, they generate a first party cookie on that user.
Now how that data is stored, Matters because that has implications for its lifespan [00:13:30] and tracking. So typically this is stored on a server outside of the browser. This unlocks a whole host of new capabilities. So couple of the, the most common capabilities with first party cookies is first the ability to capture platform IDs.
You can ga capture Facebook's click ID for every single user that came through. Paid advertising. Same with Google, same with TikTok, same with every single platform. That data is readily available. Um, you can also set this [00:14:00] cookie. Um, an almost unlimited amount of time. Um, so you could set this cookie for five years and say, if this user comes back in five years, I will still know that it's them.
And you don't. Well, there there's some gray area about like what you have to do in terms of asking users for that. the ability to drop this cookie. It's not in their browser. So like technically you don't really need to, uh, I won't, I won't kind of go into that. So, [00:14:30] well, it's,
[00:14:30] Leanne Dow-Weimer: it, the reason why I bring that up was because I live in California, one of those states where we have enacted new laws this year about C C P R A in different things.
And um, so the definitions are, are always important to circle back on because some states are just, You know, the wild, wild, less do whatever, go for it. Um, and other states like mine are a little bit more, um, trying to [00:15:00] define and, um, have legislator legislature about it, but it's still so new that it's not always the, the most fitting.
Um,
[00:15:12] Scott Konopasek: yeah. Um, can I, can I get on a soapbox for a moment, please? Yeah. Yeah. So, you know, speaking of like. So when Google announced a death of third party cookies that sent shockwaves globally, what are we gonna do? How's this gonna work? Apple said, [00:15:30] Hmm. I'm gonna one up you Google. I'm going to block everybody.
I'm going to ask in really in an unfavorable way, if a user will allow you to track. But then for ourselves, we're gonna ask in a really favorable way to try and get users to allow us to use their data and to track them. Um, and so we are in this like, Era of web two, where the dynamic is I can use a platform for free in [00:16:00] exchange for free service.
I sign away all of my data rights. I have no rights at all to recall my data, to stop my data from being resold. You have limited rights to use my data for advertising purposes, and you capture all of the monetary gain. Now, CPA is the first real attempt to claw. Power from the platforms. And so over the last two or three years, we've seen every kind of solution under the sun to try and [00:16:30] figure out how do we circumvent third party cookies?
How do we keep tracking users? But what nobody has done that I've seen is say, well, why don't we. , give the user their data and figure out a really neat, clean, easy way for them to permission everybody who they interact with. So if I go to a website, imagine having what is, think of it like a virtual USB drive, and you show up to the website, you plug in your drive, and you have default permissions.
I am [00:17:00] a male between the ages of 24 and 40. and I make between x and Y dollars. And that is the default information that I am okay sharing. Now, maybe I wanna read an extra article, maybe I want to like peruse something and they say, well actually we, in order to give you this content for free, we wanna show you ads and we need more data from you so that we can, you know, have this value exchange and.
Regardless of all the different [00:17:30] applications, there's no platform or company that I've seen that is saying, users, it's your data. Let's figure out a convenient way for you to control and consent that data wherever you go digitally. So I really think that that's the future. I think, you know, we have five states all with different regulations, all with different stages of enforcement, and that's California's big initiative for this year is to like step up that enforcement like.
We can't have 50 different rules for 50 different. There has to be [00:18:00] some equal footing, and that's either federal legislation that sets basic privacy guidelines, or there's something that, you know, you called a digital bill of rights that basically is passed nationally to say this is the law. Like users own their data, they can do X and Y with it.
Here's the allowed value exchanges. Um, so we'll see what ends up happening. So there was actually just an article from CNN today. Uh, the DOJ filed a second antitrust lawsuit against [00:18:30] Google. They have a court date scheduled for September, and they are specifically looking to break up their advertising monopoly, which means that they're gonna have to divest something like search and YouTube from their DV 360.
They're going, and so, okay, Google announced the dozen of third party cookies. They did that because they didn't have to have third party cookies to interop operate. But what happens when. Google no longer owns all parts of the equation. They're gonna have to have some [00:19:00] interoperable way of communicating across platforms, some unified id, some way of, of tying this all together.
So, um, I think we're gonna see change continue to happen at an astounding rate, but I think that like, Broad legislation at the federal level to set like a baseline so we're not working off of 50 individual states rules and um, some sort of, I'll call it return to like consumers owning their data and that being a [00:19:30] given.
Right. And like an element of like privacy almost. You can almost call that like under the original bill of rights like no one has Right. To like fester through my data and search through my data without my permission and.
[00:19:43] Leanne Dow-Weimer: Yeah. , the way my mind works was coming up with solutions, right? So I'm like, it's almost like we need like a, you know, a driver's license.
N F T where it lists, where it's an N F T that holds the data that you are willing [00:20:00] to, like a mix between an N F T and like Bitcoin, right? Where you, you pay so many bits to share like as an N F T, like the certain amount of data. Um, and, and. , you know, I get goosebumps because there's so many cool things on the horizon that are going to be solutions that aren't going to come to these types of problems.
Um, and then kind of coming back to our original conversation, because um, I feel like this is a rabbit hole, we could go very far [00:20:30] down. Um, you know, we start getting into like web three and like what's, you know, things like that. Um, but today I wanna talk more. You know, the ads that exist today and how we as marketers can put together data-driven strategies based on the data that is available.
And, and so one of the things that you guys do is you have a certain kind of attribution model. Um, do you wanna kind of like, talk me through what [00:21:00] that is and how it's. .
[00:21:03] Scott Konopasek: Yeah. So before I talk about the, the specifics of a model, let's talk about the different levels of data and how they're used. Because, uh, what we found is that what everyone thinks about typically is what we call level one, uh, optimizations or level one data.
This is your in platform data. You go into Facebook, you see that creative A is performing better, or you go into Google and you're gonna adjust your bids or your keyword extensions, right? Those are your in platform [00:21:30] optimizations. Um, I would. Lump Google Analytics into this, uh, kind of level one very basic, very fundamental.
Now, not to sidetrack us on more trends, but all of these platforms have gotten really good over the last 12 years at optimizing their platform. Like you no longer have to do all this work in Facebook to have a good ad campaign. They just kind of take care of everything on the. So level two [00:22:00] optimizations is not looking at a specific channel and optimizing there, but it's looking across your channels and saying, how do they work together?
Let me adjust how channel A delivers to better interact with channels B and c. Um, and then there's level three, which is kind of the role of classic media mix models where mta, which is every quarter or every six months, you kind of look broadly at the business, at the trends, at your broad allocations.
And you say, okay, this quarter we're gonna be introducing [00:22:30] digital video and we're going to be allocating X and Y. And you start to like, allocate your budgets in broader strokes with a little bit bigger view of, of, uh, the business. So, um, We don't really, our, our particular methodology assumes that the platforms are gonna do their thing and that agencies or marketers are gonna kind of have that squared away.
They, lots of people know how to do that very well. So we focus on level two and level three, and we use a special process called bimodal attribution. [00:23:00] Um, and so the way that we think about ad performance is that if I'm running in multiple ad channels, some of, the users in my campaign are only gonna see ads in a single place.
They might only see Facebook ads or TikTok ads or search ads. And so I wanna be able to understand how often a channel is reaching and converting those incremental new users. But then sometimes users are gonna see ads in multiple. . places And so I want to understand if Facebook is a part of that [00:23:30] multi-channel path to purchase, how does Facebook lift the conversion rate?
And so in order to really get a complete view of ad performance, you have to quantify how often a channel reaches and converts incremental new users and how it lifts the conversion rate of other channels in the media mix. And those get quantified with metrics like an I C P A, what's the cost to drive an incremental conversion?
And mnl, which is the lift on the media mix. If [00:24:00] programmatic and search come together, that converts at 7% versus search by itself at 3% or three and a half percent. I can say the MML of programmatic is two. It doubles the conversion rate of my existing. So this bimodal approach, incrementality and medium X lift is kind of how we think about the world of performance and ad optimizations, and we focus on that level.
So if I see that a particular channel is driving a lot of growth [00:24:30] really efficiently, I'm going to allocate my budget differently than if I see a channel that is not reaching new users, but is doing a great job of supporting and converting that later interest. Yeah,
[00:24:43] Leanne Dow-Weimer: and you know, I think that there's a lot of of ways that, you know, if.
How it sophisticated things, right? So one of the things that we're seeing is that there's a lot of anti antiquated [00:25:00] methodologies, and then there's some very basic brute force methodologies, and then there's the, you know, the players that are kind of getting that, that bigger and bigger growth, right? So, uh, when you have, one of my biggest pain points has been having disparate.
Data sources and having a hard time connecting them to be as accurate as I want. Um, and so, um, it drives me nuts when I can't get things connected because I have no idea, you know, like [00:25:30] one real world example of where this might be impactful or where someone might want to consider something, uh, like a change in how.
They're making their models is, let's say you have your website and someone downloads something from your website. Okay, great. So now that they've shown some intense some interest, you want 'em do retargeting ads, you are now retargeting them. Where are you retargeting them? , how precisely, like, do you know that they go to LinkedIn?
Do you know that they go to Facebook? Where are [00:26:00] you doing your retargeting? Do you know which one, you know is attached to that one person? How are they just seeing both? And then they just get really freaking annoyed because they feel like you're digitally stalking them. You know? Um, and these are real, real world scenarios that play out all the time.
And I think that, um, especially a lot of the smaller businesses, they don't understand how this all interacts with each other.
[00:26:24] Scott Konopasek: Yeah. Um, and you know, we, there's a time and a place for [00:26:30] needing more advanced attribution tools. Um, and we've kind of done some work on this. So if you are a small business and you fit these criteria, like Google Analytics and your level one data, your platform data is just fine.
So if you spend less than 1 million per year, you're probably okay just using Google Analytics. And if you. Your budget in search and social. So if I'm spending, you know, the vast majority of my budget, let's say it's 600 grand a year, and I'm spending [00:27:00] in Facebook and I'm spending in search, and I know that if I have an extra $10,000 to spend, I'm gonna put to one of those two platforms, Google Analytics is sufficient.
So the kind of criteria or the moment in time where, Buying a piece of measurement technology and ideally some support behind that to make you se, to make sense of the data, um, is when you kind of cross that $1 million threshold. And or you add three or more ad channels. So this could be search, [00:27:30] social, and remarketing.
This could be affiliates. You know, chances are if you're doing search and social, you have some sort of like email marketing. And so you start to fold that in. So if I'm running on search, social email, remarketing. And then maybe I'm like, Hey, you know, I'll throw a couple of affiliates in there because it's paper performance.
Well, suddenly you have five different acquisition channels and understanding how those are working together, or if every new place that you're spending money is incremental driving additive growth becomes really [00:28:00] important. And so that's when picking any sort of a tool and any sort of a methodology is going to be helpful.
And we obviously think that the bimodal showing the incremental and the lift on conversion rate is the most. . Yeah, absolutely.
[00:28:13] Leanne Dow-Weimer: I think that that's, that's one of those questions is, is who and when is this appropriate? Right? Because not all strategies are translatable between all places. If you're a startup and an incubator, this is too soon.
Yeah, typically. Typically. Right. That [00:28:30] always gotta put the asterisk because there's always somebody, um, , you know, it's something that they should know about for the future, right? Because you don't know what you don't know. And if you're starting this journey and you're thinking to yourself, okay, I wish I could do X, Y, and Z, you gotta get there first.
Um, you have to have the other things supporting it. Um, and so my soapbox [00:29:00] is that I've seen a lot of. And, and previous employers that want to have a certain strategy or channel or tactic before they're ready to do the things that support it. So what I mean by this is, let's say there is a company with about, you know, 5 million a r r, and like, yeah, let's do Pinterest.
Uh, okay. Um, tell me more. [00:29:30] Why do you have, uh, SEO content that you're doing that you're trying to uplift? Right? No. No, you don't. Oh, okay. Um, you know, and, and so, you know, understanding the time and place and the support, you know, the, and then what, and, and being the grown up in the room that's like, Hey, that's a bad idea.
You're just gonna throw money at nothing. Yep. Um, But the, once you get to a certain point, [00:30:00] having the right tools in your toolbox stops you from throwing money at nothing. and that's very
[00:30:06] Scott Konopasek: important. Yes. And so this is where like when we are working with C-Suites, whether that's a C E O, A C F O and the occasional C M O mm-hmm , they're like, well, why am I gonna pay for measurement tech?
Why do I need this thing? It's like, well if you wanna be able to know if that dollar that you're spending is driving results, like you have to put the infrastructure into [00:30:30] place. Um, and this is one of those things. , an ounce of prevention is worth a pound of cure. Having the data or the technology in place to measure what you're doing and if it's working is so much easier before you start spending your, your advertising budget.
But if, like you greenlight a new project, let's say, let's suppose it's digital video, right? This is a common like moment in time that we're interacting with people and they're like, Hey, yeah, like we've been like growing pretty steadily. We're. to get ready to do some [00:31:00] brand stuff, and we're gonna do some digital video and some ctv.
I'm like, okay, well how are you gonna explain to your C F O how that worked? Oh, well, you know, like maybe like a video completion rate. I'm like, well, what do you currently use for your reporting? Google Analytics. Okay, well you're never gonna see that in Google Analytics, do you? How long do you think it's gonna take before your CFO says, we are seeing zero results, turn it off.
And so, You know, the, the strategy of getting the right [00:31:30] technology in place is actually like really fundamental. So this is actually one of the reasons why I started Mismeasure. I was at an agency and I was just the guy who was like running around on every account being like, yeah, but, but what's the measurement strategy?
But what are you planning? Like, okay, I know you wanna do this cool thing, but like, how are we gonna tell the client if their money that we spent was working or not? Or like built value. and I just realized, you know, I worked probably across like 20 different accounts at different [00:32:00] points in time. Nobody was thinking about it and clients were looking to their agencies to provide that sort of guidance and that help.
And so that was kind of an aha moment for me that says, oh, well people need this sort of measurement planning. They need this help. They need the like guidance to put in place. Things, whether that's a strategy or a framework or a technology, so that when they're spending their money, they can actually prove out the value of that.
And for the agency, that means being [00:32:30] able to retain your client. Cuz if you can't prove your value, like they're, they're gonna change. And ultimately being able to get more spend under management by having the receipts and the data to go to your customer and say, Hey, we did this thing, here's how it worked.
And you know, here's the.
[00:32:46] Leanne Dow-Weimer: Yeah. And then, I mean also there's the, the trust factor, right? Agencies aren't known for client, they should be known for client [00:33:00] trust. They should be the good one. It's absolutely imperative that you be trustworthy, incredible, and. , you know, the, the proof and the pudding, you know, the, the proof to back it up.
But so many times, um, and this is part of why I moved away from having my own agency, is I was like, man, like people are out here getting away with wild stuff. I'm like, where's the, it's just like, and then I've even been in certain situations where I've noticed that the [00:33:30] data that we have in-house, um, Or like, you know, it wasn't per se, you know, in-house, but it was for a client and they had, you know, done a different component to a different agency.
And I was like, okay, well where's the, where's the metrics from this? And they gave such bullshit, fake numbers. I was like, where, where is this even coming from? I can cross reference this and tell you that that's not [00:34:00] true. Um, and so, Agencies don't always have the best reputation for being credible, and I think that when.
if, if as a leadership in an agency, if I was positioning myself, part of the way that I did position myself was, no, no, this is data driven. This is based on numbers. I am not doing this because I think it's fun. I do. But, um, you know, [00:34:30] this is, this is what the numbers show. This is your increase in revenue.
This is your increase in engagement. The, this is data driven. When I notice that something fails, I stop doing it even if I loved. because it's not about me. Um, it's about what performs. Yep. And so long tangent short was that as an agency one, having good tools to say, yes, this is the metrics, this is what's really happening, and having [00:35:00] that be credible, um, is very important.
But also this other part, you know, earlier on we talked about clunky and hard to use things. Um, the c. Doesn't wanna see, uh, all white Excel sheet. They don't, they, they want you to make a slide that says click through rate, and then they want it to say equals dollars. [00:35:30] And, and that's really like, they wanna know was it better?
Was it. , are you doing better at your job and bringing me more money? Yes.
[00:35:39] Scott Konopasek: Um, so there's like the rule of threes, whether you're in comedy or anything else. So, uh, when we work with seed suites and, and high level people, we have a rule of three. And so that is on any given topic or point or anything, you can only.
Three thoughts or ideas. If you [00:36:00] give more than that, it's going to get lost. And then we follow a three part structure, which is, here's what's going well, here's what's not going well. Here's some options or steps that you can take. And each of those have. Three things. Here are three things that are going well.
This, this, this. Here's three things that aren't this, this, this, and here are three things that you can do to do more of what's working and do less of what's not. And that format is about as much as an executive can take in at any [00:36:30] given point in time. They care about bottom line, up front. They care about the trend and direction that things are moving.
And if there is a problem or if something isn't going well, that there are action items lined up, ready to be done that are going to address and fix that.
[00:36:46] Leanne Dow-Weimer: Absolutely rethinking the threes that I should have set up for my podcast. But um, you know, we flow, we go with the flow here. Yeah. Um, . Yes. The, the rule of threes is very [00:37:00] impactful and overwhelming people with choice or giving them homework when it's your job is not the way to go.
Um, and so, you know, I think that as marketers, one of our biggest battles, once again, you know, you mentioned it, is the, the. Cost center versus revenue generator. And, um, you know, we've, we've kind of spelled out how attribution can help prove that you are a revenue generator, , [00:37:30] which is very important to marketing budgets and headcount and all of it.
Um, now where do you think this should go next? ,
[00:37:47] Scott Konopasek: like where, where does this go for the industry? Yeah. Um, okay. So I have a lot of thoughts on this. Let me, let me try and give me three. Give me three. All [00:38:00] right. Um, okay. So the first thought is that how attribution data is used depends on the size and stage of the.
So most of the time people think about attribution as retroactive justification. I spent X number of dollars, my model. Predicted whatever it predicts, and now I'm able to [00:38:30] justify that 25% budget to paid search was right because my model said I get 25% credit for search. And that is the role of attribution in large enterprises.
If you are spending more than 30, 40, 50 million a year, the role. You want to go buy an MTA or an m and m that says, Hey, yeah, you should get another 50 million next year. Maybe you should tweak a little bit how you allocate your budget, but like that's the role. [00:39:00] Now there's a list of maybe 2000 companies in the United States that have the luxury of this retroactive justification.
For the rest of us Pleb, uh, the, there's, there's two realities. The first is that most businesses are grow or die, right? Whether you're VC funded or not, like you have to be acquiring new customers and paid marketing is the way that that typically happens. Second fact is that, 99% of [00:39:30] brands do not have the brand equity to turn off marketing.
And if they turn off marketing, their sales are going to shrivel up, if not to zero, to very near zero. So, um, with those two things in mind, the classic, what is my justification for my marketing spend actually doesn't fit for most people, for most, for, for most businesses, the better question is, How can I deploy my marketing dollars [00:40:00] smarter to get better results for the same spend?
Or how do I use my attribution data to know how much to ask for and where to allocate it? And so I think like it's really important for us to like distinguish that the classic way that people think about attribution is only fit for like 2000 companies. If you're one of those 10,000 people who works in the marketing department at those.
Awesome, great. Like you have a different need than everybody else. If you're doing 10 million a year in revenue, 50 million, [00:40:30] a hundred million a year in revenue, you are still working on growing and you will always have a marketing budget. And so it was this delineation that led us to think about like, okay, how do we now take this insight and make it into something that A C F O could sign?
and it means that we're not just using attribution data to retroactively justify. It's about how do we use this data tomorrow to make better decisions than we did [00:41:00] yesterday? Because as long as I can show the CFO F that I'm getting better, or that I have a tool and a process for how to make these changes, that's gonna massage most of the concerns that a cfo.
Now there are, uh, the other concern that you brought up is like a cost center. What does it take for a company to do attribution? Well, if you follow kind of what I'll call the 2010 2012 playbook, you might hire somebody [00:41:30] internally with a bachelor or a Master's in data science and they're gonna spin up a model and they're gonna have teams and they're gonna do all this work.
Um, , the attribution that they're doing is still probably retroactive justification. It's not about in-flight improvement. So, um, the way that our company approaches this is that we have designed our insights to be in flight. We work at that level two. So how do I get channel A to work better with Channel B and C [00:42:00] and.
For, we call it qualifying campaigns for anything that's lead gen or e-commerce. We actually offer an ROI guarantee where we say, we know that if you follow our process, you will at least double what you pay us. So, you know, we typically charge out a percent of ad spend. So let's suppose that we charge someone 2%.
We're gonna guarantee at least a 4% improvement in scale of results in revenue. In cost per right. There's a number of different metrics that can be used. Um, [00:42:30] and so this is something that we found disarms the CFOs. Oh, you mean that you're gonna guarantee that this data's going to be interpreted and applied?
Number 77% of marketers don't have that capability, and so part of that is in. The tech functions and the, the bimodal aspect, but it's also in some of the service and support that we give to customers to make sure that they're able to understand what they need to do. And so regardless of, you know, whatever platform or tool or approach, like being able to [00:43:00] draw a line between data and actions and then actions and ROI is gonna be the way to win over the C-suite in authorizing and green lighting a new piece of measurable.
[00:43:14] Leanne Dow-Weimer: Absolutely. And then because I have to, we do wanna mention that not everything in marketing is measurable. Correct. You can't measure dark human to human [00:43:30] conversations. You can't measure, can't measure broadcast radio. Can't measure broadcast print. Oh my god. Billboards. Like, you can guess and you can come up with some best, you know, ways to do that.
but it's, there's always gonna be guesswork. And while we want to have our hands on all the data, we we're still, we, like you, you mentioned earlier if a brand ha doesn't have enough brand equity, you can't just cut [00:44:00] off all the marketing actions And, and so you know, this step and this attribution fits.
Part of the whole part of marketing, which also includes stuff that can't be measured. So always gotta put in that asterisk when we talk about attribution because while part of me wishes we could measure everything, part of me will be forever grateful. The Big Brother isn't that big. .
[00:44:29] Scott Konopasek: Yeah. [00:44:30] Yeah. And so things like print and billboards are like faith-based mediums, right?
You buy it because you have a piece of research somewhere and somewhere the, the marketing team believes that being in this place is going to be beneficial, whether there, there's not really a lot of data to back it up except for like initial research. There's
[00:44:51] Leanne Dow-Weimer: some, I had a bias that was a thousand percent against print.
And the thing [00:45:00] is, is that you always wanna go to the water cooler of where your people are at. And there is definitely a segment of people who get their information and enjoy reading the paper. Mm-hmm. and that segment of people for like the LA Times is actually quite large. It's something like 5 million Wow.
And it on a Sunday. And so it depends on what your organization. It depends on the stage of funnel you're trying to answer for. [00:45:30] And it depends what type of organization you have. If you are a brick and mortar physical location and your people, you know, let's just call it app, if, if I was going to open a really cool concept bookstore in downtown LA, I would put it in the.
Because it's local, it's relevant. People read, they read more than one thing. And , [00:46:00] it's, you know, I, I, it would be within that context, you know, it, it, it would definitely be aimed at that segment of people and the types of books I would carry would be re like, reflected by who those people are. Now, would I put in a print ad for mint measure?
No.
[00:46:23] Scott Konopasek: Yeah,
[00:46:23] Leanne Dow-Weimer: not really. Probably not. But you know, um, billboards, if, if you are putting up a billboard in [00:46:30] downtown San Francisco when you are driving over the Bay Bridge and you're coming into the financial district and you see those giant billboards and it's like sunset and it's just, it's a. , I remember so many big billboards from there.
I remember Salesforce billboards, I remember, you know, even just like Apple or like, you know, like when they first came out with iPhones and, and all these things. And you're getting a lot of people all at [00:47:00] once. And if they're driving into the financial district of San Francisco, it's for a reason. Yep. Um,
[00:47:07] Scott Konopasek: so, , there's a place for every medium.
And there is, every medium still exists because there is still a fit and a need and a business where that makes more sense than a lot of other places. Um, unfortunately there is no one size fits all. And, you know, understanding and having the strategic chops to be able to understand when it's appropriate to [00:47:30] do a thing or not to do a thing, um, is a big part of that.
And so for anyone who's doing, you know this off, Marketing and doing these different like executions. Like there are ways to triangulate the value of print. If you have multiple locations, you run print in one part, in one location and not in another. You run radio in one market and not in another. You put billboards next to some locations and not next to others.
Um, and so, you know, while it might not be from [00:48:00] a. Digital, digital statistical model. Like there are ways to understand if a specific channel like that is going to drive results.
[00:48:10] Leanne Dow-Weimer: Absolutely. I hate to cut it short, um, but I think we're outta time, so Yep. If somebody wants to get ahold of you, where's the best place for them to
[00:48:19] Scott Konopasek: find you?
Uh, you can find me on LinkedIn. I'm very active on there, always posting, um, advice, tips, thoughts about all things analytics and attribution. [00:48:30] Um, you can also find us on our website, mint measure.com. Um, and then my email address is actually on the screen, so, uh, always send me an email too.
[00:48:40] Leanne Dow-Weimer: Awesome. Well, thank you so much for being my guest and for having this conversation.
I loved learning all about this and, uh, you know, thank you for entertaining me about my, my Bitcoin NFT schemes, uh, .
[00:48:53] Scott Konopasek: Well, thank you. I've enjoyed this conversation as well.
[00:48:55] Leanne Dow-Weimer: Thank you so much. You've been listening
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