[00:00:00] Phil: you mentioned that measurement may never be perfect, but marketers shouldn't let perfect be the enemy of good. but how do we know for sure what is good enough maybe perfect is the enemy of good, But in this case, the scarier part is that inaccuracy is also the corruption of good and what you think is good enough. Maybe isn't good enough. [00:00:21] Nadia: When you're talking about 12 months, 18 months. Don't tell me that most of your data points are missing from the CRM, because if you do, I'll say we need someone else for the team. What were you doing for the last 12 months? We were running all of these different campaigns, right? So you can collect more data than you realize But I think people focus on what they can't collect and it becomes the beginning and the end. [00:00:41] I'm like, cannot move further because this over here, I cannot bring it in. [00:00:45] ​ [00:01:12] In This Episode --- [00:01:12] Phil: What's up everyone? And today we have the pleasure of sitting down with Nadia Davis, VP of Marketing at CaliberMind. CaliberMind is a multi Dutch attribution and GTM intelligence platform for enterprise teams. [00:01:24] In this episode, we explore the periodic table of marketing attribution elements, how to decide when attribution data is. Good enough to guide strategy, treating multi Dutch attribution as an analytical tool and exploring chain based attribution models for B2B marketers, all that, and a bunch more stuff after a super quick word from one of our awesome partners. [00:01:45] ​ [00:02:39] Phil: Nadia, thank you so much for your time today. Really excited to chat. [00:02:43] Nadia: Well, I'm definitely a first time caller, but long-term listener. So super pumped to be here. [00:02:48] Phil: Awesome. Appreciate you saying that. [00:02:50] Darrell: I love [00:02:51] Nadia: Absolutely, [00:02:52] Darrell: Yeah. And [00:02:53] 1. Understanding the Attribution Periodic Table Framework --- [00:02:53] Darrell: congrats on the state of 2025 attribution report. This report must have been a massive undertaking, and I'm a big fan of the Periodic Table. Um, so can you start, let's start off by bringing us behind the scenes. Like how did, how did this all come together? What did you do? Please tell us about it. [00:03:09] Nadia: definitely. Well, the place that it came from is definitely defined by labor of love. I've been like, this is my first stunt on the marketing technology vendor side. I've been on the side of brands, um, or consumers of attribution. Right. And to me, being always in the demand gen roles, performance roles, revenue marketing roles, you know, with kind of bearing into operations. I've always executed against KPIs or certain metrics, certain deliverables, and it was not really an option. It's just like the nature of the business. You are hired to hit this specific goal, right? So you're working towards it. And I've always used attribution as like a tool of the trade, right? You have your toolbox, you have different questions, you use different things to answer those questions and to measure them, [00:04:00] right? [00:04:00] So you can tell the story to the rest of the business why they should keep the lights on in your department for the next month or the next quarter or whatever, right? And um, uh, you know, when when I switched from being a client of CaliberMind over to being the head of marketing for CaliberMind, I started paying attention to this kind of riffraff in the market. [00:04:19] This whole. Um, I don't know if it's the, the social eco chamber, but seems like it spreads further. This whole notion of attribution is dead. Well, like everything else that's dead. Right. Didn't you say yesterday that SEO is dead, a BM is dead. Like whatever it was, it, now it's dead. So knowing that I have these fantastic, talented people in my network, um, I was like, well, I wanna research this further. [00:04:44] I wanna understand the sentiment. I mean, I came through the lines of like data and statistics and, uh, you know, business degrees and marketing analytics degrees, you know, the, the market research kind of background. And I wanted to kind of put some effort into understanding the market [00:05:00] sentiment. It seems like there's very much of a disconnect. [00:05:03] This side over here, usually SMBs are claiming that everything is dead. Okay, well maybe you failed. Maybe you tried, it didn't work out. So what do you say? It's dead right? And you move on for the next silver bullet. However, on the enterprise side, these people are not like taking to social to proclaim everything's dead. [00:05:18] They're quietly doing the work and they're seeing the results and they're applying things in a significant statistical way, right? So that was kind of part of it. I want to understand why is there such a dichotomy of opinions? The other side, like why the attribution table, uh, or the revenue marketing kind of periodic table take, right? To me, it's never one thing as a means to an end. Well, there is the multita attribution as an ous of all things marketing measurement, right? It's never that. It's like so many things that may seem completely disconnected, may seem nuanced, may seem not related. Just like the elements within the periodic table within, you know, the world of chemistry. [00:05:56] However, they all come together within an, a bigger [00:06:00] ecosystem where there is a, the method to the madness of how they all are interrelated. And I feel like in a lot of cases, when you think about, like even, you know, the, the co the, the notion of Titanic hitting the iceberg, right? What you could see is the tip of the iceberg. [00:06:15] Like, you know, the iceberg took out the Titanic, the visible part. It wasn't that, it was the underwater part that took it out. And that's parts of these pillars within the periodic tables of, it's not just attribution by itself, it's the fact that there's data modeling component. There is the measurement of framework and foundation component. [00:06:34] There's the cross-functional alignment component, like all of these things that make up the periodic table. And in grade school chemistry was one of those things that was really, really hard for me. I remember in eighth grade I cheated on chemistry. I hate to admit that, but I cheated 'cause I couldn't remember the valency of certain elements. And like, you know, when I think about this world of many things that are complex that require certain degree of [00:07:00] sophistication to understand and apply it properly. 'cause it's a framework, I can think of any better way to bring it all together. And could it be a map? Sure, it could be, you know, like, uh, some some GPS type of theme. Could it be something else? But to me, the periodic table spoke to the notion of groups of related things, seemingly unrelated, but all coming together within one ecosystem. So it's a long-winded way of answering your question, but that's the background. [00:07:25] Phil: It's super cool. We'll, we'll put it up on the screen for folks that are are watching on YouTube. When, when you first shared that on LinkedIn, I was like, Ooh, interested with, with just the visual and then you kind of like zoom in and you see all the different terms and then you have 'em laid out at the bottom and it's like, it, it's true. [00:07:41] There's so many things and, and there's so much context. Behind attribution and, and we're gonna dive into to some of this stuff here, but [00:07:49] 2. Why Marketing Teams Face Higher ROI Pressure Than Other Departments --- [00:07:49] Phil: one of my favorite parts of the report was on page six, I think, where you call out the core conflict of marketing measurement. And this is something I've like dabbled and debated with a lot of different guests on the show and, and also in my, like in-house career marketing is, and should always be first about creativity and trying new things being different. [00:08:11] Bold experiments, right? But then finance and measurement are built on things like causality and decimals and perfect science and stats. Zig, there's, there's conflicting like ideas there for sure. Do you think that. Because of this, marketing teams are unfairly scrutinized compared to other departments. [00:08:32] Like why does marketing need to prove ROI For everything that we do, we need to justify our existence, but HR and product and finance, like the departments like don't have to be accountable to revenue. They just kind of exist. They're just like a thing that companies need to do. Um, why does marketing need to prove their existence? [00:08:51] Like why is everything tied back to ROI for us? [00:08:54] Nadia: I should have got a degree in accounting. I mean, I liked the class. I mean, it was interesting, right? But I [00:09:00] think, you know, people like doing the research for this report, talking to multiple people, listening to endless podcasts. There's like a ton of really good CMO podcasts. This one theme was crystal clear. [00:09:11] That's across all segments of the market. Marketing is the most dynamic function within the C-suite because when you lead marketing, you are that one person that embodies the very creative kind of psychological engagement, arousing side of how you get people's attention, how you stay memorable, how you, you know, uh. Drive recall for your product or service. And then there's the other side, which is completely different, which is stem, which is stats, which is data science. And if somebody told me that, you know, it's like it's easy to gravitate from over here to over there, and every other person has that within their brain, I'm be like, I'm sorry, that's just not true. I saw the stats somewhere, I forget the, the, the, the source. But ultimately they said that nine or nine [00:10:00] out of 10 marketers would have the background in degrees other than math, stats, data science, right? So you have traditionally, like the Mad Men era, the advertising era of marketing of work, the discipline was heavily rooted, came from arousing that, you know, uh, uh, response, that attention, that ask for certain things. [00:10:21] And then the world of consumers, it's still so, but in B2B it's different. And why is it different? It's because, you know, your sales cycles are longer than I'm preaching to the choir. But it's also because. You know, you have so many VCs, you have so many Ps that give you money, and you have to be accountable for that money. [00:10:41] Now, if we compare all the other departments, does accounting have a budget? Not anything the size of the marketing budget. Does finance have a budget? Does sales have a budget? They got a little bit of the t and e, right? But not, not something massive, millions of dollars I entrusted with you to spend it or rather invest it in ways [00:11:00] that benefit the business. [00:11:01] Now, if I went to a retirement plan, 401k or whatever, or a stock company and said, here's my money and I don't really care how you invest it and how it performs, I just feel like it's the cost of doing business. 'cause everybody else invests in their retirement, right? Like nobody does that. Everybody wants to understand how is my money working? And this is where the notion of we give you money, we have to understand what you're doing with it. And I think the challenge comes within the marketing world is that you have those nine outta 10 people. However, I mean maybe it's eight outta 10, you know, these days or whatever that statistic is, right? [00:11:37] Because I feel like marketing analytics has become the degree, um, people reach for, but you have these people that really have hard time grasping that you are not here because it's the cost of doing business like it is for other departments. You might try other departments if you know this is not it for you, but you are here because you got money to spend that [00:12:00] we invested with you. And we want to have the responsible output from how this money is performing. And I think it's a very challenging concept for a lot of people to grasp, especially if they come from brand, if they come from product marketing, if they come from comms. And a lot of CMOs today, they still come from that background. [00:12:18] Like if you look at a bigger company, uh, a lot of CMOs would come through the lines of product marketing, kind of rose through the ranks. And sometimes even demand gen, like you could say it's a borderline function between kind of the creative side and the, the measurement side. But even demand gen in a lot of cases. [00:12:34] I mean, I had demand gen managers who had comms degrees, right? And they were challenged with like the kind of, uh, going above and beyond doing complex math calculations. But that's, that's where the notion is. And then you have the other departments all within the C-suite, you know, you have your finance person sitting here, you have your head of sales sitting here, they are dealing with binary data. It's like you have pipeline or you don't have [00:13:00] pipeline. And in marketing we are driving engagement, we are driving recall, we are driving the psychological response that's gonna influence the behavior. And how do you take that and translate that to people that measure the world in black and white, they measure the world in dollars. 'cause PEs invest with you in dollars. VCs give you money in dollars and for you to go and say, well, they generated X, Y, Z clicks and had we not done this campaign, we would've saved a loss. This much money. It's not the answer that they're looking for. So unfortunately, it's just the name of the game and the world of, you know, performance marketing, especially when it comes to SaaS and tech, when the the VCP presence and that return on investment increase so strong. [00:13:45] Darrell: Totally. Totally. And I, you know what? I've never heard it said like that. Like, you know, why, why does marketing always have to prove themselves? It's just like you said, it's because they're the ones with the budget. And that makes complete sense to me, and I don't know why I never thought of it that [00:14:00] way. [00:14:00] That, that, that makes, that makes a ton of sense. I that also think that there's a lot of conflict because no one can really, people continually struggle around measuring the, the value of brand. And you know, when you walk into a room and you're a salesperson and the prospect already has heard about your company and has heard great things about your company, what, what's the value of that? [00:14:29] You know, some would say that's almost priceless. You know, it changes everything. And I think that that's another reason why, um, um, this, this, this, this concept of attribution is so contentious. [00:14:44] Nadia: Sure. I'm sure it's like that MasterCard commercial. It's priceless. What's the value of this? Standing on top of the mountain and [00:14:49] looking at the world is priceless. Right? Um, and that's the BTC side of things, right? That's where the sale goes faster. But you are right. And I think also people have this [00:15:00] discomfort with a certain degree of uncertainty. Not knowing is such a big issue for a lot of people. And Phil, you had someone, and maybe Darryl, you won that episode too. Uh, it was, um, uh, Joshua Cantor Convert ml, uh, the guy who founded the company. He was talking about this notion of like, some people want answers from their data. They cannot stand the fact that you cannot get to 99.9% certainty data tells us what to do. [00:15:31] I had someone who was leading brand who would refuse to come up with names for a virtual, uh, webinar series for the next year until I told you how the names of the previous year series performed. It's like, well, how do you expect me to answer that question? But, but we're data driven. We have to know how these things perform before we come up with the next year's episodes. [00:15:52] So see, like there, there's this kind of dichotomy of some people that have to have a hundred percent, and then other people, they just need to [00:16:00] confirm that gut feel and know they're moving in the right direction and it helps them make a better decision. And I think that's what separates those who flourish in the world of business and can move fast and can make decisions with, you know, certain risk and ambiguity. [00:16:13] It's almost like gambling, right? Like how much risk can you take? But the world is moving fast. So you are not you, you don't have the luxury to sit there and collect everything that you can and then say, I finally feel so good about my data. I got everything. Oh wait, it's 18 months later, right? [00:16:30] Phil: Yeah, I love your take. Uh, Nadia I think that in most tech companies specifically, marketing typically does have one of the bigger spend budgets. And I, I agree with you in a sense, like we get this idea that the budget that we have is used to spend on performance stuff and, and part of it's spent on like tech and stuff, but. There, there is still a budget for some of the other, these other teams, like, you know, sales still has a bunch of stuff, like incentives. We're paying the team [00:17:00] like commissions. There's like cost of goods sold, overhead expenses. These sales teams are like traveling. They're, they're doing a bunch of like in-person stuff, right? [00:17:09] So sales, like, especially in bigger enterprise sales led motions, oftentimes the sales budget will be bigger than the marketing budget. The one I have the most trouble with is the product department budget. Like, typically I remember like being in house and we have like, um, like a head count negotiations with, with the senior management team, and we're fighting for like five new people on marketing and product. [00:17:32] Just has a roadmap of 17 new people that they're hiring in the next quarter. And it's like, okay, we're assigning an ROI to every single person on marketing. They're gonna be doing product marketing, they're gonna be helping MarTech, they're gonna be jumping on ads. But the product team doesn't have to do any of that allocation. [00:17:49] Like they just assign people to a new thing, that new feature on the roadmap. And no one is asking the product team, like, what's the ROI on that feature that, that we're gonna add in there. [00:18:00] Like, what's the ROI of these four people that we're at, like, why, why is that the case for marketing? And it's not the case for product. I feel like you already kind of answered that, but that, that was my only like, um, [00:18:10] you know, like takeaway there. Like, other teams do have budgets and some companies, like, I have some friends that work at big enterprise and like the, the marketing budget is like 6% of, of budgets. Like, it's, it's a tiny sliver. [00:18:22] They're barely doing SEM stuff. So Yeah. What, what, what are your thoughts, sir? [00:18:27] Nadia: You know, I feel like certain departments are viewed as mission critical to business [00:18:32] success. Product, in my view, is one of those. If we don't do X, Y, Z, then we all gonna fail. Then this is not gonna work. And whatever we have today, we might lose that. I mean, this is like the extreme view of what it is, right. Within marketing, there's one thing, the depth of marketing and the variety, the, the, this dynamic side of marketing, like many other functions do not take the time nor should they, to understand, kind of get immersed because it is a certain, you know, [00:19:00] it's, it's a skillset that gets acquired over decades, not something that you explain overnight. [00:19:04] And then people assume they can do it. And there's this assumption that comes from the madman days of the simplicity and, you know, [00:19:10] pamphlets and brochures, right? And how much time do you wanna spend proving people wrong and go into this tug of war? I feel like it's the very essence of the credit within, you know, the world of attribution that shapes people, you know, you or me, who, who did this right? Rather than, you know, help people understand how you contribute to us winning together. And [00:19:28] that's a different mindset. And when people feel that the questions of headcount do not come up [00:19:34] nearly as often. Because they can see that you are helping them to be successful. But I know for some people it's really hard to step back and say, please be in the limelight. [00:19:43] I am here to enable you, to empower you, to help drive the business forward, because that's what we're all here to do. Otherwise, we all go home and don't get paid. [00:19:50] Phil: Yeah, it's so true. I just wish there was more of that mission critical association to marketing and, and to the branding stuff that Darrell [00:20:00] just talked about. It's mission critical to have these new features in the product and on the roadmap, why isn't it also mission critical for us to invest in brand and shorten our sales cycle and lower cac? [00:20:12] And so anyways, I, I know I'm preaching to, to the query here. [00:20:15] 3. Why Attribution Fails Without Data Stewardship --- [00:20:15] Phil: Let's, let's chat about attribution and like the, the definition of the word itself. I think that there, there's something to unpack here because you kind of mentioned one of the thesis or the ideas behind the, the 2025 state of marketing attribution report was that you kept seeing on LinkedIn all these like talking heads saying, you know, attribution is dead. And when most people hear the term attribution, they immediately go to multi-touch attribution MTA in this like whole world of assigning credit. And I can't blame those people because, you know, I, I was in that camp not too long ago myself before a lot of the guests that I had on the show and this big exploration that it did on MTA and they kind of like opened or enlightened me a little bit like it e [00:21:00] and I can't blame those people because like if you were to Google, well, we'll put up some screenshots here, but like if you Google or ask at GPT, like what is marketing attribution? You, you get what you expect. Like marketing attribution is the process of identifying, assigning credit to marketing touchpoints. If you ask chat GPT, what is attribution in the context of marketing and marketing attribution is figuring out which touchpoints influence the customer's decision. So right away, Google and Chat GPT, they're both thinking that by asking attribution you're thinking of MTA, but Mt A is just one of the methods of attribution. [00:21:36] Attribution means figuring out what marketing efforts drove revenue or business outcomes you're connecting spend to, or campaigns to revenue. And when you, you kind of like coin it like that with at g pt, like no, I didn't ask you for the definition of multi-touch attribution. I was asking marketing attribution ist, MTA, just one of those methods. Got it. Yeah, you're right. [00:22:00] Let's zoom out. Marketing attribution [00:22:01] Nadia: It's agreeable. It always [00:22:03] Phil: Yeah, always Yeah. But yeah, so, so when someone writes one of those posts and you saw those, like attribution is being dead. For the folks that know that attribution is just like a, the discipline of time and marketing to revenue, they, they look a bit silly by saying attribution is dead right. But there, my, my question to you is that like there is an argument and you kind of talk about this in the report, there is an argument when it comes to the question of, is multi-touch attribution dead or what's the meaningfulness of it? Because this whole method of assigning credit and creating, like you said, this internal tug of war over credit between sales and marketing. So what advice do you have for shifting the mindset from blaming credit claiming to, to using like attribution for learning and decision making? Long-winded question there. What are your thoughts there, Nadia? [00:22:56] Nadia: I think if we take a step back and kind of first [00:23:00] assess what is attribution in general, it's a framework. Business is built on frameworks. You have to have frameworks. None of them are perfect. George Box's quote comes to mind. All models are flawed, some are more useful than others, right? Um, but it's a framework and it's a tool to answer certain questions. And I feel like, um, when the concept became popularized and democratized by all of these tools that had an MTA, some sort of MTA or attribution module in them, think about Google Ads. It had its own thing. It will tell you how your campaigns are before me, right? Then you look at HubSpot, they had something, you have Marketo, you have Salesforce, like meta. [00:23:43] Everybody had some kind of attribution tool, a BM platforms that allowed you to see how well that platform is driving whatever it is that you're driving with that platform, right? And it democratized this concept and it simplified it where they said, oh, this is for everyone. This is [00:24:00] so simple. Uh, uh, uh, you know, a no data scientist can do it no problem. [00:24:04] And I understand that, but we have to be mindful about things that are free with purchase, right? I went to a makeup store at some makeup and they said, today we have this promotion. We're giving out lipstick. It's free with purchase. She shows me the colors and they're the most hideous, hideous colors, but they're free. [00:24:21] You know, take it, right? I mean, I took it. It's not that I'm gonna use it, but it's the same kind of concept, right? Because you are given it for free. It's not there to be, to be precise, to be, to, to embody how the framework came about. And it's a data science framework, right? It's a methodology developed by data scientists. So for you to be able to even configure all of your stuff, right, where it's not just the HubSpots eye of mortar looking into the universe that HubSpot can see, or the Google Eye of Modor, right? Seeing the whole mortar, using the Lord of the Rings, uh, uh, framework, right? You have to see the entire middle earth. Can [00:25:00] you see that? No, you can't. You can see slivers of it. So I feel like a lot of people tried that. And as I was talking to people, you know, during the kind of the data compilation part of the, the research, I noticed that on the SMB side, that is very prevalent. And why is it so, it's because in SaaS companies, smaller companies usually have one person who is doing demand gen and a little bit of more ops and da dabbles with systems, right? [00:25:27] And that person has to be, the jack of all trades is by the way, master of none. But we don't wanna say that second part, right? Jack of all trades. Um, you have to be good at everything and that you never get it a hundred percent. 'cause you're lacking resources. Your data is all over the place and you, there's just not enough time in the day to even dedicate to data, right? You may not be able to understand the business questions that you ask and translate that into the types of data that you wanna collect to build the model and the framework that works. So like the failure rate is so, so, so high. But you have all these [00:26:00] businesses, small and medium size, that are numerous, that are out there, that all tried things and they just came up with disappointments and their disillusioned and their boss says, well, what are, what are the results of this? [00:26:11] Well, it doesn't work. It's dead. I tried and I just couldn't come up with anything that's meaningful. Right. They get laughed out of the rooms, the sales doesn't believe and just goes on and on and on and on. Now, um, well actually I, I will make one more comment here and I've had some good friends of mine that, that come from that world that grew up in the world of smaller business technology, very data savvy. It was like, this is just nonsense. And they're very convinced and I'm thinking, well, I'm not gonna argue with you 'cause what's the point? I understand you lived in the world of Google ads your entire life. You drove digital stuff, you never worked for enterprise and. You never had those conversations that required you to present some kind of a framework and drive the argument or like this, you know, kind of debate style discussion [00:27:00] from the point of view of a framework, right? However, when you look at enterprises in the report, it says 75 or somewhere, you know, almost eight outta 10 enterprises still use multitask attribution. They don't have a problem with that. And they got their 15 to 17 platforms on average that all are collecting data. They have resources, they have analysts, they have data scientists, they can configure, set things up. They have technology. If they don't have data science, they have technology that's more advanced. That's not the free lipstick with purchase, right? That you set up specifically for your go-to market and for those enterprises. Another interesting thing was that they don't use just one. Model MTA, right? They would use multiple because there are multiple questions that they wanna answer. And again, it's not like the, I feel like the market goes into this panacea mode, right? A BM oh a BM saved us, right? Didn't save us. Then it's SEO then we're actually the other way around. Then it's ai, right? And then there's this disillusionment comes like, the hype cycle is such a great [00:28:00] concept to visualize that. And, uh, I feel like MMTA was that like finally I can justify my things or wait. This doesn't match the tool says that my attributed revenue is twice the size of my pipeline in Salesforce. And I never bothered to look, well, maybe I don't even have a seat because I'm in a small business and you know, I, I don't need a seat in Salesforce. I go with my spreadsheet or my HubSpot report to the, the meeting with sales and, you know, quarterly and they laugh at me because their pipeline is half right. Like all of those nuances. And I've lived that life and I saw that in, I mean, I've been in small companies, I've been in big companies. There's a huge difference. [00:28:36] There's a huge difference in how you even drive this narrative. And if you're reporting into A CMO, and in my case, you know, my last two roles, I was reporting into the CMO and being that arm to create the reporting to help drive data stewardship, to translate what it is that they're being asked into numbers. [00:28:54] And you know, the other way around. That's a very different approach. You learn to appreciate [00:29:00] methodologies and you know, they're flawed. If they were a hundred percent everybody could do it, right? Everybody outta high school could take a job and be a marketer. I mean, vibe marketing is there. I mean, that might, might do it, [00:29:13] Darrell: Totally. [00:29:13] Nadia: it's essentially you have to be responsible with the data that you have and responsible in a way where you understand what it means. [00:29:21] You understand the limitations. You set those expectations with others who may be less data savvy or may not have the kind of the, um, sophistication needed. And this is in no way negative, right? But sophistication, meaning like the, the of knowledge within the industry. And you help 'em understand, you help 'em bridge the gap. And if you don't have that data stewardship or that data acumen and you don't know how to help people see that, it doesn't matter what framework you use, it will all fall apart eventually. [00:29:48] ​ [00:31:53] Darrell: I, I, I like to think about it two ways. Like on one hand. You have the, the big boardroom story where [00:32:00] you have mul multi-touch attribution and you must explain to the board why what you did with your budget was so successful. And, you know, no hate to that a lot of marketers get put in that position. [00:32:12] You know, we gave you all this money prove, like, you know, show us what you did with it. So they say, okay, MTA. And then there's the other side, which is the actual practitioner side where people know, just like you said, that, you know, MTA is a directional tool that gives you data about what's happening and then you must decide what to do with it. [00:32:34] And, you know, not only is it not gonna be a hundred percent, I love what you said, you use multiple models, you know, it could be, it could be time, decay, U-shaped, linear, whatever, you know, or even different implementation models to try to get a, a direction or, or of what to do. Um, 'cause at the end of the day that's, that's. [00:32:52] That's what really matters to practitioners. What are we gonna do next? And, and I, I think that that's the, the, the people really using attribution in the right [00:33:00] way are, are thinking in that way. Um, but anyway, [00:33:02] 4. Treating Multi-Touch Attribution as an Analytical Tool --- [00:33:02] Darrell: I'd love to talk about like maybe some success stories. Um, you know, times when, you know, you've helped teams or maybe your yourself, um, um, you know, go through this like culture shift of like, Hey, let's not just look at, at MTA as a, as a panacea. [00:33:20] Let's not just blame other teams. Like, can you share, you know, kind of like a, a real time that, that you've helped teams through this. [00:33:28] Nadia: For sure. So in my previous role, uh, this is the GOVTECH world. This is the world of messiest data as it is just because the, from the contact standpoint, you get the stakeholders that get voted in and out of office. Any given day of the year, regardless of how ZoomInfo updates the world of contacts and data integrity, right? You have the world of non matching domains. You have 60,000 plus records if you have the entire US [00:34:00] database of counties, cities, towns, you know, agencies. And then there's the Canadian side. So like this, this world of endless de-duping matching obsolete, no longer there kind of contact world was essentially my playground. And we were driving a go, uh, uh, an a BM theme, go to market, right? Because governments buy in groups. It's a buying group, it's a, it's a committee. So you have to be able to collect the, the journey across the, the buying cycle. Whether it's 18 months, sometimes it was 24 months. So think about it, for 24 months before you close anything, you have to be able to tell the story. Quarter after quarter of what marketing did our sales cycle was like nine opportunities, stages long. I've seen some companies in the competitive world in that space that were 13 stages within the sales cycle, right? The nuances there, right? So depending on what segment it was, because it was such a huge market, [00:35:00] and no matter how much budget you have, the budget is still finite. [00:35:03] I mean, this is a mid-size company, you know, with very, um, responsible and curious investors, the PE companies behind it that wanted to absolutely understand how their money was working. And for different segment, the go to market was different. You have smaller counties and you have, you know, that engage a certain way and they drive a certain size of the opportunity. You have bigger counties or you have bigger DMVs within the country. We're selling to DMVs as well. It take forever to close. People leave office, new person comes in, gotta start the whole thing all over again. The Canadian government is even better. It takes forever to get things kind of over the finish line, right? [00:35:42] So you are looking at that very long spectrum and depending on what your goal is, whether it's expansion into the new market, within a certain segment, you would use a different model. So for us, first Touch was absolutely it when we were trying to figure out who are the new contacts that we can market to within this [00:36:00] specific segment, within the channels that we go to market through, whether it's events, we did over a hundred events. Like any marketer's nightmare. A hundred events I had, my events person was busy. She loved it, but she was busy. Right? And you have to justify that. And then you flip that model to understand like, okay, so if our goal is not penetrating this new market segment and say First touch is what I'm, I wanna look at just to understand how good am I within this specific channel? [00:36:27] Should I spend more money on it? Am I driving that first time engagement from this channel? We had this specific channel, which was small counties in the southeast. And we've noticed that, that the, the dynamic was there that if you have a conversation with them at an event, and then it didn't matter what you did in between from the digital standpoint, whether you sent them emails, whether you show them ads, but if you get them to attend a webinar on demand. 'cause they were never, they would never attend it live because they did not wanna show their interest too implicitly because they did [00:37:00] not want a salesperson to follow up. But they thought that if they attended on demand got like this, this veil of I'm still staying anonymous even though they still fill out the form. [00:37:08] Right. So they would attend it on demand, then the BDR follows up and Absolutely, it's a beginning of a conversation. So that's a perfect example of your U model, right? You have this first very specific channel related touch. You have to talk to them at an event. If you said we should invest more in events. It would do absolutely nothing because what we notice for that region, you have to have them on a webinar where they give you another hour of, of their life. They kind of, you know, you grow on them, then you continue talking to them. Then the BDR calls and they feel like they already know you. And that concept of like trust and kind of having your relationship for that specific market was so important that you could do whatever you wanted outside of these two channels and invest however much you wanted. [00:37:53] Your CAC would go through the roof. But see, in this specific case, I feel like the dichotomy of reporting versus [00:38:00] analytics comes to mind. Where reporting is just whatever number you log into your tool and it says, this week LinkedIn performed, you know, out of this world you should invest more In LinkedIn that's reporting. [00:38:10] You have the finite pivot table of something versus something and you see what it is and there's nothing you can do about it. Analytics is where you, you dive deeper, you investigate and you kind of try to understand what's working, what's not working, and how is it nuanced based on. Name the scenario, right? So this is, this is the way I think about using attribution, not as a means to an end. This is how much revenue I did, and it's all marketing source, you know, good job. To me it's rather, can I get curious with my data? Can I apply these frameworks to get answers to very different questions? And then you bring those answers to the executive meeting and they're like, oh, this actually makes sense. [00:38:48] I trust you now because I understand what you're doing without diving into like, what's the weight over here or what, how is the value distributed? Like you're gonna get 'em lost. So that, that would be one of those practical examples.[00:39:00] [00:39:00] Phil: Super cool. Uh, one thing, NA, that we wanted to chat about, like [00:39:05] 5. Exploring Chain Based Attribution Models for B2B Marketers --- [00:39:05] Phil: we've seen a lot of measurement methodologies kinda shift away from touch-based weights to more probabilistic weights, so. Less credit distribution and more about pattern recognition and, and analytics. Um, in the state of 2025 attribution report that you guys did that you highlighted chain based attribution models, specifically Markov chains as this like next, uh, evolution of, of multitouch. Um, so I, I spent a bit of time like researching this. This is the first time I heard about chain based. And as I understand it, and correct me if I'm wrong here in how you guys see this, but chain based promises to be able to look at the entire sequence of touches in real buyer journeys, and then it uses probabilistic data to figure out which touch points are most influential. But the looks at all the touchpoints in real journeys, like that statement alone [00:40:00] was a red flag to me in my research. Like I don't believe that we can measure or see the entire sequence. There's always gonna be touches that are not trackable. And you call this out in the report too, like lots of companies are investing in dark social. [00:40:13] All of our, uh, partners on the podcast invest in podcast ads. There's exec dinners, there's private slack group recommendations. Like none of those things are gonna show up in any MTA model, chain based markoff or not. So if we know that we don't have all the touch points and we're never gonna have all the touchpoints, and that we in some cases are missing perhaps the touchpoint that may have led to the conversion, what use is it really to have MTA data that doesn't accurately tell us if a campaign was incremental or not? [00:40:50] Nadia: I love the skepticism, but I think it's very healthy and I think a lot of the audience shares it, right? I'm like, ah, how do I know? Right? That's just the nature of the business. You never know a [00:41:00] hundred percent. However, to your point. Um, the, the concept of chain base, it's very much, I, I think it's very aligned with account based marketing and measuring account based marketing and tracking the entire journey, right? The idea of buying groups and people doing certain things. What, what it does. If you take the regular even based model within the MTA and you realize that there's a lot of noise in this model, I know that I have to stay present, say on LinkedIn or in Google Ads or whatever, but I know that these things are just incremental touches. [00:41:31] They don't really make the difference. But then I have sales engagement over here. I have BDR calls, I have maybe event attendance, so whatever those channels that most enterprises use to go to market, right? Because these are not like after hours, you know, let me go on TikTok and see what, what everybody's doing for it. [00:41:49] Automation, orchestration solutions. Like it doesn't happen that way. It's more predictable then the. It allows you to figure out what channels matter and how you can suppress the noise from other [00:42:00] channels. It could be unique to specific market segment, like what I described with, you know, the, the, the small counties that, that I experienced. [00:42:07] It could be unique to certain industry, could be unique to certain area of the world, like whatever it is. But that is absolutely true, that depending on how you go to market and what offerings you have, people will engage with those differently. And once you start paying attention to your data and you kind of start diving deeper into the analytics, again, having the sophistication, the understanding and kind of the, the critical assessment of what you're seeing, you will notice that certain things don't matter. Good example from, you know, my, my previous life, um, again, within the government world. had healthy skepticism that email opens and email clicks did not really mean anything because when somebody's sitting in the office and just, you know, has time to kill, they might read you an email. Doesn't mean that they're trying to buy anything. [00:42:50] They just have the time to go through their inbox. Right. So, you know, email touches had to be suppressed or certain emails that would have newsletter in the title, right? In the [00:43:00] traditional attribution model, you would include all of that. And it's just, you know, one of the touch points in the, uh, when you assign weights, you would either give a zero weight or you would just exclude it all together. [00:43:09] So it's more sophisticated kind of approach, uh, that allows you to choose what matters for your market. But to your point about the dark social, and actually before this podcast, I looked up the term 'cause I'm like, who coined this? Like, what is I, I, I mean, I thought maybe Six Sense or Chris Walker or [00:43:25] whoever was [00:43:25] Phil: Walker. Yeah, he's the one I would think of [00:43:28] Nadia: Wrong. [00:43:28] So that was 2012 and it was the Atlantic. I used to read The Atlantic when I [00:43:34] was doing my grad school, right. And that was a journalist. It never come from a marketer. How can, how can [00:43:40] this not come from a marketer? It was a journalist who was trying to write an article on all the things where people go for advice. That kind of go outside of the area of what you can see right away. So that, that's where the term comes [00:43:50] in. And actually had a funny story. We were, you know, this was a, a meeting of marketing and sales. This was a six month meeting, kind of figure out what we're doing for the second half of the year. And we knew that [00:44:00] events were so important, at least for the sales team, they wanted to do more of them. The board did not wanna give us more money to do more events. And the question to me was like, well, can you tell us what we get out of events? And I ran my, I I pulled the data from Marketo, I looked at everything in Salesforce, all of my campaigns, made this massive chart and gave it to Chad, GPT and said, Hey, can you tell me, based on the date stamp, how does this all relate? [00:44:27] 'cause I was trying essentially to do the kind of the, the manual way of figuring out how do event touches related to opportunities. This was before we had CaliberMind and I couldn't, so, you know, when the sales asked for more events that based on the touch points that I have, I cannot tell you that we are making a meaningful difference with these events. But we are such and such anecdotal knowledge. Like did such and such put the lead into Salesforce? And the salesperson looks at me and goes, you are telling me that in 2023 or the 24 [00:45:00] 20 24, I still have to manually go into Salesforce. We don't have some kind of an automation system to capture context from events. And I was Stu fight. I'm thinking, are you thinking Alexa married to ZoomInfo? Automatically running things as it listening on your phone, who you are, talk like there's, there's this element that you still have to do the work. [00:45:23] There's no way around it. There's no magic bullet like you are having your dinner. Well, how hard is it to enter the names [00:45:29] of the people? Create a campaign for it, put the names of those who did the dinner. Now you could say, well how about LinkedIn? Sure, LinkedIn could be more difficult to measure, but what do you think? Drive certain wonderful things from LinkedIn engagements that you cannot capture. And if that's the case, then you are answering a different question. Do you see that in LinkedIn analytics? Do you see it in Google Analytics? What makes you think that there's this impact outside of your gut feel or, you know, this anecdotal knowledge. So there's still that, you know, uh, creative inquiry into [00:46:00] what are you trying to solve for and should you stand paralyzed until you solve for it? [00:46:05] Because what's the cost of opportunity of doing nothing? [00:46:10] Darrell: Totally. Totally. And I think that this is why, you know, this is why rules exist and why, why we can't have nice things is because there's, there's these bad apples that think that they just, they don't have to do anything, you know? And that [00:46:23] Alexa, [00:46:23] Nadia: There's a lot of them. [00:46:25] Darrell: there's a lot of 'em. So you have to like, put all these guardrails in place that maybe, you know, you wish you wouldn't have to. [00:46:30] But [00:46:31] 5.2 Markov --- [00:46:31] Darrell: Can I ask a follow up question on that Markoff, uh, you know, chain, uh, model? I, I, I understand that, you know, different than like a linear model where every, everything gets credit. You're actually removing the ones that don't make sense. Um, how about the order? The order of the touchpoint, is that important? [00:46:51] And you know, how, if, if so, how do you determine like what order of touchpoints actually makes sense? Or am I reading that wrong and, and the [00:47:00] order doesn't matter? [00:47:00] Nadia: No, see, that's, that's where the kind of, the cus uh, the, I don't think it's a noun custom ability, but customizing the whole model and how it applies to your go-to market would come from like, clearly this is not something that you would just cook up in house. Right. And say, [00:47:15] no data science. I'm gonna paralyze you guys for the next six months 'cause we're coming up with this big project and that's all we are gonna do. [00:47:21] Right. There's something clearly that you have to use adequate resources. You know, for example, within CaliberMind, our team helps, PE helps people set this up based on how go to market. So they [00:47:31] Darrell: hmm. [00:47:31] Nadia: explain their process, you understand what matters, and then you set it up in a way where you will change it based on what you see coming in. And one interesting thing is I was, you know, we were kind of put in that section together. I happened to talk to Michelle Garner, who is a senior data scientist from Microsoft. And the woman is amazing. She's so knowledgeable and I was curious. I was like, well, in the world of all of these things, you know, attribution is that use M-M-M-M-M-M is dead using incrementality, right? [00:47:58] Like, like, can [00:48:00] you tell me how you guys think about it? They actually did a presentation marketing analytics summit, and she said that. At Microsoft, they actually run an advanced markoff chain multitask attribution model to help their teams make decisions. And again, this is Microsoft. I know that they got, you know, hundreds upon hundreds of analysts and machine learning people. [00:48:19] Like we're not trying to equate that to regular smaller business, but it kind of sets the tone of people with depth and knowledge and expertise. Still say that, you know, this matters and we see value in it so that we could make decisions that accustomed to our business. And I feel like that was part of like why everything else out of the box failed. 'cause it's out of, out of the box. If two businesses went to market the same way, they would not be able to compete, right? Like they start changing how they go to market and that's your competitive advantage. But how is it that we don't change how the tools measure how we go to market? And when I think about these things, I think about like what other [00:49:00] methodologies other in business that could be scrutinized. I think about the pipeline sales pipeline, right? Nobody ever scrutinized the sales pipeline. It's holy. Like you don't touch sales pipeline. But think about the Salesforce probabilities, 10% versus 20% versus 50%. It is so biased based on what the sales guy's thinking at the moment. [00:49:20] And then you look at the stages. I've seen businesses, like I said, with three stages. I've seen businesses with 12 stages and how these stages change. It's up to the rep. If this happened, band qualification, med pick qualification, you change the stage, but it's very, very biased, right? Nobody ever scrutinizes that and everybody puts a lot of attention on getting that right. I'm thinking like, why is it that this framework. Is untouchable. Nobody says we're gonna scrap pipeline. We're gonna come up with, I don't know, GPS journey for sales, whatever it might be, right? I'm just coming up with stuff on the fly. It doesn't happen. But with marketing, like we're always looking for the next best thing. [00:49:59] 'cause we [00:50:00] tried, didn't go in depth, didn't put much effort sometimes into tried something out of the box and then off we go to the next thing. And I don't know the answer to that, but I've noticed that it differs very much amongst bigger businesses that respect process and methodology because they understand that's how they survive. [00:50:15] That's the continuity of operations and small businesses. They're just like, throw spaghetti at the wall and just see what sticks and go get different type of pasta and try it again. [00:50:25] Phil: Yeah, it's a, it's a really interesting comparison, the, the pipeline percentages and, and how confident you are. I, I think the difference there for me is that. It's like, it's a bit fluid, it's dynamic. Like I know reps that they, they, they change that percentage, like based on the number of emails they get. Uh, I, I've created a couple Zapier flows where the percentage actually changes based on like the time it takes for them to reply to an email in a certain sale cycle. So, um, but, but it's an interesting comparison and I think like [00:50:56] 6. How to Decide When Attribution Data Is Good Enough to Guide Strategy --- [00:50:56] Phil: one of the themes that comes out of the report and, [00:51:00] and maybe some of the stuff that you're seeing is that like. MTA isn't perfect because we don't have like a way to see the entire journey. It's always gonna be invisible stuff like the dark social stuff. Um, but I feel like one of the main takeaways is that like, perfect is the enemy of good in this case here. And one, unpack that a little bit because in the report you mentioned that one of the core reasons why MTA fails is under documented and offline touchpoint. [00:51:28] You kind of talked about that in your previous answer. You're having a VIP exec dinner with seven people. Why didn't you log that in Salesforce? Like there's ways for us to capture that data. Um, and, and you know, there's, there's some ways of. Making sure that, that this happens, but you know, when important buying moments aren't documented. [00:51:48] You mentioned in the report that attribution reports are inaccurate and we totally agree there. Um, but then in the trends reshaping attribution section, you mentioned that measurement may never [00:52:00] be perfect, but marketers shouldn't let perfect be the enemy of good. And that sometimes approximation can be used as a signal and that estimates matter more than precision. [00:52:10] So this is where we're, um, Darrell was talking about like using direction MTA four direction, knowing that it's not perfect, but like, Hey, at least we have something, we're going in this direction. Right. The question I have for you, Nadia, is like, I think perfection will never be achieved in any online trackable mechanisms because we are humans after all. And if I ask you Nadia or Darrell, like why you made your last 10 purchases, you probably couldn't even pinpoint the exact moment that triggered that purchase. Our memories are faulty. We have, you know, tons of biases involved in it, but how do we know for sure that when it comes to measurement that what we are measuring is good enough? [00:52:53] Like what is good enough and how do we know that it can be used as direction versus when [00:53:00] it's inaccurate to the point and it's incomplete and, and the direction it tells us to go in isn't gonna be correct. And so like maybe perfect is the enemy of good, like we kind of talked about. But in this case, the scarier part is that inaccuracy is also the corruption of good and what you think is good enough. Maybe isn't good enough. Like there's a super fine line between accepting imprecision and falling victim to something that's completely inaccurate. How can marketers track that violence? Uh, Nadia, like how do you use data that's good enough to guide us knowing one that like when incomplete data might sometime mislead us? [00:53:40] Nadia: I think that's a very valid question. And you know, I think if we start with a traditional tech stack set setup, if we're talking digital world, the things that we can capture, right? If you continue looking at individual systems and what they show. You will never get there. You will be continuously imperfect, inaccurate, [00:54:00] double counting. [00:54:00] Like I will not take a stab at any of the platforms, but you know, the hearsay is that every platform will inflate a little bit what it's showing you because you're investing money with it. So it has [00:54:09] to show you that it's making a difference, right? So all of those nuances, none of that is connected to your sales or even business bloodline, whether it's your, you know, uh, um, ERP or your CRM, whatever it is. [00:54:22] So you are continuously fighting windmills and like you either choose to go with that and create this tolerance of like, okay, I know this is like my daily existence and I have to do it in a solid spreadsheet. So I have some kind of a, you know. Attribution light setup, that helps me with some, not all. Like you have to develop that tolerance to deal with it. Like, I would not, I would not wanna be there. I've definitely been in those shoes, like, you know how I became a client of a tool like CaliberMind and, you know, there are others that I'm not here to promote the tool, but essentially bigger businesses decide that they need to have data stewardship, data [00:55:00] literacy, data leadership around how do we deal with this massive data? We bring it all together. And that's the whole, I mean, this could be a commercial for any CDP or any, you know, data warehouse. Like you have to have it there. Can you bring it from all places? Like you will be probably 70, 80, 90% where you need to be with 10% missing. Oh, I don't know, the performance of my billboard. What would it change if you knew and how much, you know, difference? Would it, uh, cause like certain things, right? I'm not, I'm not skeptical of all the things. And then on the, on the other flip side of it. Something that I heard from the former CMO of a MailChimp, I think she's now CMO at a WP Engine. She was talking about how enterprises buy when it comes to complex solutions. [00:55:43] I'm talking, I'm not talking about staple stuff. I'm not necessarily even talking more tech talking. Think it thinks, you know, uh, cybersecurity, think finance stuff, right? It would never come from Google. Click. Because you just don't wake up one day and say, Hey, Google, what is the [00:56:00] best cybersecurity? Yada, yada, yada, right? Chances are you would go and seek for that information through more predictable for the marketer of that enterprise and that product channels, because they're out there. You would join communities, you would go to webinars. You would go to events. Like it's a more predictable path. Am I oversimplifying it completely Kind of negating the notion of ads. I mean, maybe a little bit, but you kind of get the idea with staple products, the decisions are made quickly and you go to Google or chat or whatever it is, right? Like give me this, and that's the beginning and the end of your journey. In e-commerce, it flourishes. This notion of quick sale is there, but when you're talking about 12 months, 18 months. Don't tell me that most of your data points are missing from the CRM, because if you do, I'll say we need someone else for the team. What were you doing for the last 12 months? We were running all of these different campaigns, right? So you can collect more data than you realize what you can collect. But I think people focus on what they can't collect and it becomes the beginning and the end. [00:56:59] I'm like, [00:57:00] cannot move further because this over here, I cannot bring it in. So I think this notion of how much do you need to make a decision is a very important thing. And then the other side of it, if you isolate sales, which most of the tools that we talked about, do not consider anything sales related. You are creating this rif like, I am doing my thing. This is marketing. You are doing your thing over there. And I don't care how many calls you place, how many hands you shook, how many babies you kissed, right? I'm just doing my thing. Tracking Google ad touches, like people get offended, [00:57:30] people don't believe you, like talk about, you know, ruining trust [00:57:33] that that's the way to do it. [00:57:35] Phil: Yeah, that's so true. Like all the, the terms about marketing influenced pipeline, like salespeople just hate that term 'cause they're like, yeah, we know what you're doing. But I closed that deal. I kissed these seven babies like the, [00:57:48] I am the person responsible for this sale, and we're not [00:57:51] disagreeing ' [00:57:52] Nadia: em see themselves, let them see themselves on that journey, [00:57:54] right? Like once you, once, it's a collaborative effort. You don't even get the scrutiny around it. All [00:58:00] you, you prove your point. You show touches, you show how sales got involved and look it, you need us, we need you. We win together. And the argument goes out of the door. [00:58:09] But that's not how the aash goes. It's marketing influence, which those sometimes could be fighting wars. [00:58:14] Phil: Yeah, no, I, I asked and Nadia again, and I find this super fascinating because like, I, I, I, like, I, I run the podcast and like I, I live off of like the, the ads that we generate from sponsors, right? And selling sponsorship on podcast ads is one of those dark social things. Like it doesn't show up on, on MTA models that might show up sometimes in like post-sale conversations and surveys. But it's one of those things where like, I've been in the shoes of someone trying to convince marketing leaders to invest in this and create brand affinity and like associate themselves with like, you know, solo creators in the space. And they're just like, a lot of these teams see it as completely. Experimental budget. They can't track it in their MTA model. [00:59:00] So like, it, it's not even a conversation starter with them. And so like I've become obsessed with this notion of just like, you know, if it doesn't show up in your MTA model, it might still be super important to the bottom line. Like, and, and it's hard because like, not everyone remembers they heard an ad on a podcast, but, um, yeah. [00:59:18] I appreciate your, your [00:59:19] Nadia: No, I believe that. I think you're absolutely right, and I think that's a great example of how every business goes to market differently. Your industry is very unique. Like how many others just like you. I mean, you can probably count people on, you know, your hands and your toes and that would be it, right? [00:59:34] It's a small market, so it is nuanced and it's very relationship driven. So I would say, you know, definitely you're looking for things that may not fall within the traditional lines, but for more predictable, large scale businesses. It's a lot of it is very measurable. A lot of it is very trackable because these businesses have learned to exist over decades, and it's the motion that continues going. [00:59:57] So it's a little bit of a different go to [01:00:00] market. [01:00:00] 7. Why Marketing Operations Defines Multi Touch Attribution Success --- [01:00:00] Darrell: Can we talk about like rev ops and data leadership real quick? Like how does rev ops play into this whole marketing attribution thing? Like who owns it? Have you ever gi given some thought and what have you seen, um, like is there a function that best owns um, um, attribution? [01:00:15] Is it like analytics? Is it revenue ops? Is it marketing ops? And then what can op, what can operations teams do in general to make sure that organizations are successful or at least get off to the right start when implementing, uh, multi-touch attribution. [01:00:31] Nadia: That is such a loaded question. There are like so many layers to that question. I love it. I think if you step out of just the one functional team, which is rev ops. And think about what is the methodology of how marketing helps the broader go-to market team, move the needle? What is the process for our funnel, our stages, our channels, our campaign nomenclature and naming [01:01:00] conventions? [01:01:00] All of these things, right? Like this is the, I always say that the success of any marketing, uh uh, or any A BM or any demand gen tactic starts and stops with marketing operations. I mean, I've led marketing operations team teams, and I know that if you don't have that excellence and how you bring things together, everything else is just secondary, right? [01:01:19] You just cannot undo it after the fact. And once you have that established and the business is clear, just like rev ops is clear on the sales pipeline stages, that would be clear on the marketing funnel, whether it's your lead funnel. Whether it's your account funnel, maybe you have both, and there are some, you know, cross pollination between how, you know, people flow into accounts and whatever that is, whatever that complexity is, making it clear. I think that's step number one. Even before you touched anything attribution related. And, um, I remember hearing this, uh, on a podcast from someone who is with a, a na, um, association of [01:02:00] National Advertisers. They have a CMO practice and they were talking about a research that they ran when it came to metrics and how marketers or heads of marketing established the metrics that marketing will deliver on. [01:02:11] So your KPIs, your OKRs, right? So they got 120 marketers in the room, and these are all CMOs, VPs of marketing said, can you come up with the most important marketing metric that me that matters to you, that you measure? Right? So 120 people came up with 98 different metrics. Then the same, the same practice took 30 C CEOs. [01:02:33] And I guess the difference in size is because you know it's harder to get a CMO in the room. They're busy people. But that's my speculation. They took 30 C CEOs and they said, what are the most important metrics for the business that you wanna measure? They came up with three. And when they heard that the marketing bunch came up with 98, [01:02:51] they were mad. [01:02:52] I would use a different word, but they would not be probably appropriate here. Right. They were mad. They're like, and this is the nonsense that's happening on that [01:03:00] side of the house. How is this possible? Right. So I feel like just having that clarity of aligning what it is that you are doing to what matters for the business. [01:03:08] So you do speak the same language, that's the, whether it's the language of the hard dollar or whatever it is, the intermediate metric is Right. That is important. And then attribution, where does it live? It can live in marketing operations, if that's all you got. And your marketing operations person is data savvy and has the kind of the affinity for statistical methodologies, and I'm not talking like advanced stuff, I'm just talking understanding and being able to interpret the data, right? If you have marketing analytics team, I mean we could live there. Marketing analysts, they're amazing people. They're super savvy people. They would probably go and, you know, build things and extract things that you never thought existed. But if all you got say is, you know, uh, rev ops and your rev ops person is it, and has the, what the ops person had in the previous example of the marketing analyst, it, it really depends on the person's tolerance of uncertainty and being [01:04:00] able to work with data in marketing analytics. [01:04:02] I think that's where it matters the most. And the marketing leader understanding what it is that they're trying to achieve and sending down those directions to people who are actually boots on the ground, who are looking at things, connecting things, so that the story comes back in a way that you would expect. [01:04:20] Phil: Super cool. Nadia, really appreciate your, your, your take on that, and I appreciate you, uh, going through the conversation there. And yeah, humoring, uh, our, our skepticism [01:04:29] Nadia: It was fun. You guys had tough bunch. [01:04:33] Phil: uh, we'll, we'll link it to the, the state of, of attribution reports to think the, the periodic table is super cool. The work that you guys did to, to kind of promote that is, is also really great. We'll, uh, yeah, we'll, we'll try to figure out, like for, for the cover our like, uh, a little periodic table theme to to, to this [01:04:49] episode here. [01:04:50] 8. Why Time Management Drives Career Fulfillment --- [01:04:50] Phil: We got one last question for you, Nadia. You're obviously VP of marketing, you're a keynote speaker, you're a frequent traveler. You're also a mother of two. Uh, a Ridgeback parents and avid runner, occasional triathlete and amateur new age pianists. One question we ask everyone on the show is how do you remain happy and successful in your career, and how do you find balance between all the things you're working on while staying happy? [01:05:14] Nadia: So I have this philosophy that the most valuable thing that you have is time and how you spend your time and who you give your time to is ultimately what makes you happy and makes you feel accomplished, right? So when I look back at my day, and I know that all of these things that you just named, I did what I needed to do. [01:05:33] I dedicated time, I had the discipline to do all of these things in order, and somebody would, would call me, you know, obsession of the calendar person, right? But it's true. Once I have the collection of all these things that matter to me. I feel fulfilled. Like I feel like I spent my day and it did not get wasted. [01:05:50] 'cause that's one less day that I have. And sometimes it is a lot of things. But as you go through your meetings on your LinkedIn Cal or on your, um, outlook calendar or your Google [01:06:00] calendar, right? You just feel like, okay, that was a good day. I feel like that at the end of the day, once I hit all of my things, if it means getting up at four 30 in the morning, I mean that's what it means to be happy, right? [01:06:09] Then you would have to go to bed earlier. But, um, it's balancing all of those things and making sure that my time was spent wisely and people that I invested in, or things that I invested in, really the ones that nurture my soul. That's my secret to happiness. [01:06:25] Phil: I love it. How do you handle, like saying no to conversations that you already know are, are not gonna, like, be fulfilling to you? Like how, how do you gently say no to those things? [01:06:35] Nadia: So I actually had an interviewer, um, not so long ago, and the person was very excited for the role and it was not the right fit. And I said, listen, I'm gonna tell you something that you're not gonna like, but I'll just save you the time because time is valuable. I don't think you're gonna be a fit. And the person did not expect that directive feedback. But to me it [01:07:00] was being gracious and actually having mercy or not stringing [01:07:03] them along. Like, dude, I will tell you why this does not work, [01:07:06] Phil: a hundred [01:07:07] percent. [01:07:07] Nadia: this to you because it would be worse if you are on the other side of the fence many months, weeks, whatever, later. Right? And you realize that. So they appreciated that. [01:07:16] But sometimes it's just saying things as they are, which may not be the most popular methodology we try to sugarcoat. But I always say that the one skill, and I live in the south, right? So we sugarcoat everything. But the one skill that I'm very adamant to learn better is how to sugarcoat things. I just go straight for the chase. [01:07:35] Phil: Yeah. Awesome. Great advice. Na, I really appreciate your time. Like I said, we'll we'll share out to the link to the report there. Um, you guys did a great job at putting that together. Thank you so much for joining us today. This is super fun. [01:07:46] Nadia: Yeah. Thank you guys. It was fun.