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About the podcast
The Digital Utopia Podcast is for SMB Marketers and Business Leaders looking to align their Marketing, Sales, and Service departments so they’re part of one powerhouse growth team.
Each episode will dive into the strategies, philosophies, and tools that will change your approach to organizational growth, give you renewed focus and clarity, and allow you to build a brand that not only helps you stand out—but win.
The Digital Utopia Podcast is produced by Digitopia and hosted by Frank Cowell and Joseph Freeman.
Frank Cowell: [00:00:30]
Quant, attribution analytics. So what we've been nerding out about, and we need to dig into why attribution is important. When do you use it? And when should you stop using it? Or when should you take other things into it, iteration and everything in between.
So this be a fun episode because it's going to get a little nerdy, little analytical, and heady, but let's do this, Joe. Let's try to make it more conversational and talk about the sentiment as opposed to the technicalities of attribution. Because if we did a show on the technicalities of attribution, frankly, it might be kind of boring because there are a lot of different.
Uh, algorithmic models, if you will, on how you do this stuff. And I don't think that's, what's interesting. I think what's interesting is why when and how to balance that with other things. So let's talk about it. Let's talk about what is attribution reporting first off, just to get a baseline for those that are here and maybe don't do it.
[00:01:40] Yeah, absolutely. So attribution reporting where, you know, when you run multiple campaigns across multiple channels, you kind of have a lot of plates spinning and you have a lot of ways that people can get to, uh, your brand, hear about your brand, interact with your brand and ultimately get into your database so that you can talk to them.
So it's kind of nice once in a while to take a breath and say, how well are all of these different marketing efforts working? And so attribution modeling. Gives us reports a little bit different than some of the other dashboard reports that we're used to looking at. Um, it gives us reports that shows us, which of these channels are bringing the most people at the appropriate spend.
And which of these offers that we're creating are actually resonating enough to get people to interact and, you know, download or give us their information, put it in the database so that we can follow up with them. So in a nutshell, that's what attribution reporting is. And the reason we use it is because we want to optimize our spend and our time we want to optimize all of our efforts so that we're not just throwing spaghetti against the wall, seeing what sticks, right.
Frank Cowell: [00:02:46]
It's about ROI ultimately right now.
Joseph Freeman: [00:02:47] Yeah, absolutely ROI. So, that's what attribution modeling is. I think, you know, depending on how long you've been in marketing world and how long you've been interested in reporting, you may know a lot about this. You may know a little about this. Um, Most software's come out of the box with point and click attribution modeling.
Um, and so if you have never heard of this before, you're going to get an overview right now, and you could probably just go into whatever you use, Google analytics or HubSpot, or name the software. And you could probably find some tool that will allow you to point and click some version of an attribution model into place.
And then once you do that, then it's time to geek out because then you can kind of go down a rabbit hole and really. Um, the slice and dice, some of that attribution, um, some of those models up to really fit what you're looking for and the answers you're trying to, uh, or the questions you're trying to answer in your business.
Frank Cowell: [00:03:40]
So here's what I want to do, Joe. I said we didn't want to get technical, but what I do want to do is maybe give high level overview on those different ways in which something can be attributed. And the reason I want to do that, it says, I want to get to the point of. The dangers, the pitfalls by getting to quant my getting too analytical in this and some other things that need to be considered when making decisions about what to stop, doing, what to start doing, what to expand, what to a lesson.
So give me an overview, give our, give our audience an overview of the different. Models, if you will, you know, the linear, the degradation, all that stuff. Like let's talk to our folks here about what those are at a high level overview. Cause I think that's important to feed into, you know, the rabbit hole you just talked about.
Joseph Freeman: [00:04:30]
Okay. Yeah. So, uh, you know, again, across software, you're going to find different models and different names, but generally, uh, the very similar and some of them actually are exactly the same in different software. So we're gonna use HubSpot's here cause we love HubSpot and this one is, um, Very similar to Google's if you've ever been in Google analytics, uh Google's of course is tailored more to Google.
Like it has models around Google ads specifically, but, um, there's seven basic, um, attribution models that come out of the box in HubSpot. So the first one is called first interaction, right? And this is what is the first interaction that the person in my database had with my brand. And this gives a hundred percent credit to that, um, that interaction.
So for instance, If the first thing that they ever did, if we're talking about channels, the first thing they ever did was clicked on an ad. And then they, you know, through the next three months looked at web pages and they downloaded things and they, um, watched webinars and all these different things.
When you pull that report, it's only going to show you their first interaction. It's not going to show you everything they ever did. And it's going to give a hundred percent of the credit to that first interaction, um, across all of your contacts. Okay. So. Similar to that. We have a second one called last interaction, and that is exactly the opposite.
It's they've been spending time with the resources on your site and they've come back to your site through organic and through paid and through direct channels. And when they finally purchased from you, what was the last thing they did before they purchased? That'll get a hundred percent of the credit.
Okay. And then we start getting into some, um, you know, some distributed models. And so we got full path and HubSpot. And what footpath does is it gives 22.5% to the four major types of activities that someone might do. Right? So that would be a first interaction. That would be the moment that they became a lead, the moment that you created a deal for them.
And the very last interaction before all that happens. So those four things get most of the weight and then they distribute the remaining 10% of the credit to all of the little things they did in between. That's called full path. Got another one called linear, which is similar, although it gives equal credit to every single thing they did.
So if they did 10 things before they bought from you, all 10 of those are going to get 10%. Uh, you got U shaped, you shaped gives, uh, it's a 40% of the deal revenue credits, uh, go, sorry. 40% goes to the deal revenue credits, and then it, uh, it. It layers in the different interactions around that and kind of a U shape.
So it's weighted heavy on both ends a little bit less than the middle.
Frank Cowell: [00:07:05]
So that's a little bit of a first and last and kind of things in between, but with changing the waiting game, the first and the last kind of get more and then the 20% gets kind of distributed around around.
Joseph Freeman: [00:07:15] Thank you. Better way to say that.
Got it. W shaped similar to you, but it actually has little peaks in it, right? So it gives more weight to the beginning, more weight to the end and some weight in the middle. And then there's less weight to the little interactions that happened in between. And then the last one would be time decay. So time decay says, Hey, they have been poking around for a long time on our site.
Um, and they've done a lot of things. So let's give more credit to what happened at the end of their journey, because maybe they weren't as serious in the beginning. And maybe those things don't really matter as much. They matter a little because they helped keep them interested. But they weren't significant enough to make them start making big moves, right.
To give more weight to the very last thing and a little bit less to the one before a little bit less than it goes all the way back in a decay is back to the first one interaction.
Frank Cowell: [00:08:02] So what I love about what you just described, Joe, is I talked to business executives a lot and because they don't have a sophisticated understanding of analytics and attribution and things we've been talking about on the show.
Oftentimes, what they default to is like what brought me that lead, what brought me that lead. That's all I care about. And I think what you just described in these different attribution models describes how that is a dangerous question and a dangerous lens to put on your analytics. If all you worry about is what brought me that lead.
You're going to miss out on the things that influenced that lead. And that's ultimately what we're talking about when it comes to attribution reporting beyond first touch or last touch was what are the things that influenced along the way? What are those activities? And so, uh, again, this gets a little complex to put those together and to try to understand them.
But if you're here today and that's been your mode, you've been asking your marketing team for, you know, what's generating our leads. Just be careful that that is just one part of the puzzle. And just one lens on how you look at the ear activities. I
Joseph Freeman: [00:09:15] think that's a great yeah. Point because think of your own buying behaviors, especially with a big purchase, think of like a car, right.
If you were just to ask what got you into the dealership to buy the car, it might've been an ad. It might've been a radio ad. Uh, you know, it might've been a billboard. It might've been the fact that you drive by the same place every single day. And you just decided to pull him. Um, but if you really think about what got you to wanting to buy that car, it was a lot more than that.
It was you seeing a friend driving the car. It was you reading an article. It was you watching a TV show and the car was in it, right? There's a whole bunch of different influences maybe for months and years leading up to what you would attribute as what got me into the dealership. And so we kind of as marketers, especially want to know that because when we talk about Pre-Suasion.
The sale. We talk about all the things that go into the psychology of buying well, before you even know you want to buy as marketers, we want to be able to, this sounds bad, but want to be able to exploit that we want to double down on the different activities that can happen all along the way before the buyer even really realizes they want to buy.
Frank Cowell: [00:10:17] Yeah. And I think this is leads into the point I wanted to make, which is the attribution is important. Understanding the different models and the influencing. Moments are important, but there are a lot of things that will influence that are very, very difficult to measure. So you mentioned the person that buys the car and maybe it was the ad and, and whatnot.
Th the actual marketing department's activities, but there were a lot of things that the marketing department didn't do such as you saw your friend, you know, drive up in one, there was, there was, uh, you know, an article you read from a long time ago that someone else wrote, I mean, There are all these things that the marketing department didn't do that influence that.
And then there are these things that the brand does at large, just to cement that familiarity what Roy H. Williams known as the wizard of ads, calls, customer bonding, not brand building. And so those customer bonding activities are wildly important. To making the decision to do business with a particular brand, but it's, there are things that are very difficult to measure and maybe aren't salient for people when they're asked, why did you buy this product?
They may not name those things that you did to create those customer bonds. And I think that's the danger we'd run into, especially in B2B businesses where. You know, your executive team is asking you, you know, what brought us those leads, what brought us those customers is they forget that an important part of being a business is bonding with your customer base in a lot of the activities that you do are longterm.
Doing attribution reporting often focuses on short-term decisions. What campaign did we run that worked. What campaigns should we stop doing? That's a very, very short-term mindset. The long-term mindset is a lot. I often say it's a lot like religion. You got to have faith. You got to build the bonds with your customer base and the marketplace.
And know that that is an important part of what's influencing people to do business with your brand, but it's a balance. And that's why I mentioned this at the top of the show. Is this attribution's important. You have to understand it, make some short-term decisions, but you have to know which long games to continue playing.
And those long games are the ones around creating bonds with your marketplace.
Joseph Freeman: [00:12:47] Yeah, I would generally agree with that. I think we do need to make the point that attribution modeling can be very helpful for long, long games as well. You can look back quite a ways and see over time. Uh, I mean you can look back forever and see over time what's working.
What's not. So I think we need to point that out. That that is, that is possible. That is one way to use it and it is good to use it. I think where you might get into trouble with that is, you know, over the course of a year, over the course of two years, you run a whole bunch of different types of campaigns and seasons change and buying habits change and pandemics happen and stuff happens, right.
That makes it start to kind of homogenize. You kind of start getting less insightful data. The longer you look right. Because. It starts to all normalize when you've got all that going on. Um, you know, and, uh, another thing to kind of avoid in terms of a pitfall is the, the, the fact that, uh, um, in a small dataset, a large deal could skew it in a big way.
Yeah. Right. Looking at attribution reports that show how much money was, and you've got five sales and one of them. 300% more than your average sale. You're going to feel like whatever model you pulled, that last interaction model. For instance, you're going to say that was the ad that we got to double down on.
Cause that's the one that brings the most money. When in reality, it just brought in one big deal. And so you gotta be careful with small data sets and honestly, small data set. Maybe you don't need attribution modeling. Maybe you just need to pick up the phone and call your customer and say what got you to me.
Frank Cowell: [00:14:16] Yeah, I think that goes back to an previous episode where we talked about marketing automation. In fact, I had an exchange on LinkedIn with someone where I left that opinion, that opinion, that I'd given them in the show. And then I left this opinion on LinkedIn about, you know, look when you're small and you have small velocity and, you know, low velocity in your business, you don't need a lot of this stuff.
You know, if you need two customers per month, screw automation, just go get two customers per month, right? Just go start talking to the marketplace and creating relationships such that you get two deals a month. You don't need all this other BS. Uh, you don't need attribution at that point. You don't, you need to just talk to those two customers that you've landed.
Hey, tell me about what you were searching for. Tell me about like, the things you're interested in being close to your customer is the best form of attribution. The point at which you have scale such that. You can't ask these questions at scale one-to-one and you can't have those let's let's sit down and have lunch at scale.
That's when attribution starts to become way more valuable and a tool in your arsenal. But again, not the only tool. It shouldn't be the only lens by which you make your decisions on your engagement activities. You know, that, um, that customer bonding, as you mentioned, when you look and you could see. In an attribution report over a long period of time, you could see it.
My 2 cents on that would be, you could see it, but you have to draw some of your own inferences and assumptions because it becomes less direct. You know, when you look at those wider timeframes, you start to have to make assumptions about the correlations because they're not so direct anymore. When you zoom out to these long timeframes that you're talking about doing things that are more customer bonding, as opposed to a campaign.
And so to me, I think that's the biggest suggestion I would make to people is one, you've got to have enough philosophy for this, to, for you to waste your time on this. And so that way you get leverage. Right. And then the other thing is balance that with the activities that build your brand and balance that with the longterm things, you know, the build Goodwill and, um, bonding in your marketplace.
Joseph Freeman: [00:16:26] Yeah. The, the, the other thing is that. When you are looking at different attribution models, I think they're good pointers. It's hard for me to really say this is infallible data, because there are many different ways that you can kind of put that data together. For instance, if you're pulling a revenue attribution report and you want to know how many dollars were generated from a specific type of interaction or model, you now have additional things to think about.
You now have to think about, well, do I only care about the one. Contact that was associated with that deal as the main point of contact. Do I only want to know what that person was doing on their journey to, to buy, or do I want to rope in more people from their cohort? Do I want to look at what everyone at their business was doing?
Because surely they were getting offline and going and having conversations around the water cooler about. Uh, you know, the product, the service. And so do we want to include that, uh, data as part of relevant information for our decision-making around this model? And so it starts to get very, um, it can get very complicated.
Now I would say don't get very complicated with it. Choose something kind of simple to start and just be consistent with that because that'll give you more insight than really probably you've ever had before. And of course over time, as you get more sophisticated with it, you can get very detailed. But I would say that is, is, is better reserved for bigger data sets and more complicated marketing teams with lots and lots of channels and lots and lots of maybe products that are being sold within those
Frank Cowell: [00:17:56] channels.
Yeah. At that point, a lot of the bigger brands have. Uh, data engineers, data scientists on their teams, so that they can pour over the data and, and follow hunches. You know, I mentioned you zoom out, you're going to make some assumptions about a correlation that you're seeing to try to, you know, assume what causation is.
Well, when you're big enough, you would have data scientists who would kind of get down to causation and try to prove that a little bit more empirically. Um, but to your point, um, keep it simple and balance that with again. Getting to your customers and staying close. Like you have to balance that with other types of information, not just this quant, you know, to get quantitative approach real quick before we wrap up here.
Uh, because I think this was a good overview for people who are maybe just starting to dabble in attribution or, or thinking about employing it because they're getting questions from their executive team. Let's talk about a couple of simple ways to get started for those people that are here today, and they're not doing this, what are a couple of simple ways to just get started?
And, um, and let's, let's leave our audience with that.
Joseph Freeman: [00:19:07] Yeah. So, um, you know, getting you, can't my opinion can't really get started without the right software. This is not the type of report, um, that I would want to, you know, manually pick up data and put in a spreadsheet and use formulas to, I mean, you could do that, but that seems like a lot of work to me.
Um, so I would say you, you at least need to get some sort of software in place and. If you're not at a place where you are spending a lot of money on marketing software and you, and you don't want to that's okay. You can go to Google analytics, you can, and you probably already have that. I'm sure you have that installed on your site.
And if you've never looked around in there, um, just look through the menu and you can find in their attribution reporting and you can literally just click on these different types of models that I outlined earlier. Again, the ones I said earlier were specific to HubSpot, but very similar in Google, that would be one easy way to get started.
And you can just see how are people getting to my website? And if you happen to have goals set up in your Google analytics, um, you know, for people filling out forms and people clicking on buttons, you can also pull those reports around that. If you want to get, you know, more sophisticated, you got to just get, you just got to start using software that can do that.
Uh, you know, again like HubSpot, where it's collecting data all the time, across many different types of interactions and then built into it is attribution reports. You can literally just click a button, say, show me the content that is creating. Uh, deals, show me the content that's creating new contacts, show me the channels.
Um, you know, show me the emails you can get kind of granular with what types of interactions and content you're looking for. But, uh, you do need software for them.
Frank Cowell: [00:20:43] Yeah. So that's great. And if you would like to, uh, connect with Joe or I, or even learn more about the methodology we teach that does the things that go above and beyond attribution like that customer bonding we've been talking about.
Give us a visit email@example.com. We'd love to connect with you and help you further this discussion around attribution. But until then, we'll see you next time for episode 45. Take care.