Measuring Marketing Profitability Across Amazon and Shopify
Episode Summary
In this episode of The Free to Grow CFO Podcast, Jon Blair sits down with one of Free to Grow CFO’s in-house eCommerce CFOs, Kevin Jornlin, to break down how brands should think about measuring marketing performance when selling across both Shopify and Amazon. They discuss why traditional channel-level metrics often lead to incorrect conclusions, how paid media creates a halo effect across platforms, and why Shopify can appear unprofitable while Amazon looks artificially strong. The conversation dives into blended new customer ROAS, the importance of accurately understanding LTV across channels, and how cohort data can reveal meaningful differences in customer behavior between Shopify and Amazon. Jon and Kevin also share a practical framework for determining appropriate ad spend based on contribution margin and profitability, helping founders make better decisions without relying on perfect attribution.
Key Takeaways
Channel-level ROAS is misleading and often causes brands to cut or misallocate ad spend.
Incorrect LTV assumptions can lead to under-scaling or over-spending on acquisition.
The goal isn’t perfect attribution—it’s understanding financial impact on contribution margin.
Episode Links
Jon Blair - https://www.linkedin.com/in/jonathon-albert-blair/
Kevin Jornlin- https://www.linkedin.com/in/kevin-jornlin-cfa-650a40b/
Free to Grow CFO - https://freetogrowcfo.com/
Meet Kevin Jornlin
Kevin Jornlin is an experienced investor, operator and CFO. As a fractional CFO at Free to Grow, Kevin advises e-commerce brands on the science of scaling profitably.
Kevin began his career on Wall Street, where he spent 15 years as an investor before launching his own hospitality brand, Vanish Travel, as founder and CEO.
After discovering the power of e-commerce through his wife’s pet brand, Awoo, Kevin has jumped full-time into supporting DTC operators in the finance function. He loves the ecom sector because of the unique set of problems that require tackling, and for the sector’s ability to provide life-changing wealth when those problems are solved.
Kevin has a BS from the University of Richmond with a double major in Finance and Accounting.
Transcript
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00:00 Introduction to the Free to Grow CFO Podcast
04:23 Understanding New vs. Returning Customer Profitability
11:07 The Complexity of Amazon and Shopify Integration
16:57 Insights from Cohort Models and Retention Rates
22:56 Final Thoughts and Practical Advice for Brands
Jon Blair (00:00)
Hey everyone, welcome back to another episode of the Free To Go CFO Podcast where we dive deep into conversations about scaling a profitable DTC brand. I'm your host, Jon Blair, founder of Free To Go CFO. We are the go-to outsource finance and accounting firm for eight and nine-figure DTC brands.
Jon Blair (00:18)
Alright, today's a big day on the podcast. This is a Free to Grow CFO podcast first. I've got my buddy Kevin Jornlin here, one of our super awesome e-comm CFOs on the Free to Grow team. Kevin, what's happening, man?
Kevin (00:32)
Hey Jon how you doing?
Jon Blair (00:33)
Good, I appreciate you joining me. We are, like I mentioned, this is a Free To Grow CFO podcast first, having someone on our team come on the show. I wanted to have Kevin on today, because I want to talk about something really important that I'm seeing again and again and again with brands, both that we're working with already as Free To Grow clients, as well as brands that I'm encountering in our sales pipeline. It's what I'm calling a
What we're going to talk about today is what I'm calling advanced marketing profit analysis. The complexities of having an Amazon and a Shopify store. Before we dive into that though, Kevin, can you give the audience just a quick background of who you are and where you came from?
Kevin (01:14)
Yeah, sure.
So I actually started my career in the investment industry. So I worked for about 15 years on Wall Street, a couple of New York based investment firms. After that, I actually launched my own startup in the travel hospitality space. Did that for a few years. Concurrently, my wife actually launched her own e-comm brand in the pet space. And that has been going on for about five years now. And so I've kind of
grown
up with her in learning all things ecom and I've been their CFO since day one. was my education into the ecom space over time. I have picked up some clients and I am thrilled to be working with Free to Grow where I've been for about a year now. I've got six brands that I look after all in the kind of 10 to 50 million dollar revenue range.
Jon Blair (02:11)
I love it. But before we start talking about Shopify plus Amazon, like marketing performance, having worked with us now for a year or so, been the most helpful of takeaway from being a part of your wife's brand that's helped you kind of settle in as an e-com fractional CFO at Free to Grow?
Kevin (02:28)
The e-comm space is unique, right? I think that growing up in the investment industry, I could be a CFO for a variety of different industries, but e-comm is its own animal in a few different specific areas that I'm thinking of. One being ad spend and then two being cashflow management around purchasing inventory well in advance of selling the product.
two things if you can get them right ecom is a it's an amazing industry in its ability to generate wealth for founders very quickly as opposed to a lot of industries that take a very long time or require a lot of capital investment if you can get your marketing efficiency
Jon Blair (03:08)
Yeah.
Kevin (03:18)
correct and CAC targeting and media spend levels dialed in and you can manage your cash flow. The sky's the limit for e-comm and that's been a lot of fun to be involved with.
Jon Blair (03:32)
Yeah, I like how you framed that. I'm starting to realize some of those same things myself. recently, I saw a post from the one and only Alex Hermozi talking about, he said like, income loves speed, investing loves time. And the interesting thing about e-comm, going back to what you were just saying, you can actually build a lot of income really fast with a lot of speed in e-comm.
There's a lot of scalability, but doing it right is not trivial, right? There are very important best practices you need to follow to do that right, which is why we're gonna talk today about this advanced marketing profit analysis. So to set the stage for the discussion, one thing that we uniquely do at Free to Grow CFO is because we're a firm that works exclusively with fast growing e-comm brands,
We really go a couple layers deeper than the typical fractional CFO to understand marketing performance. And the crux of it is understanding, one, what game are you playing? Are you playing the high LTV game or are you playing the new customer dominant game or are you playing the apparel and high sku count game? But two, once you determine that, it all comes down to understanding what is the CAC
that your brand can afford? How much can you afford to spend to acquire a new customer? Each of those games are vastly different in terms of your new customer acquisition cost requirements. And in reality, what we've learned, I didn't know this in the early years at Guardian Bikes, what we've learned is that, I believe, what's his name? Mark Zuckerberg, I think, said this before and it kind of like was a famous quote of his is that like, whoever can afford,
to spend the most on CAC is gonna win. But what dictates how much you can spend on CAC is your unit economics and which game it is that you're playing. And what we've realized as we've dove into helping brands understand new customer profitability versus returning customer profitability is it's actually pretty easy to do when a brand is just selling on Shopify. Or maybe even selling a small amount on Amazon where Shopify mostly dominates their
their revenue mix. But there's this additional complexity that comes into play when there's a significant Amazon and Shopify presence because of some of the data limitations on Amazon. Now, I want you to jump in now, Kevin, because the reason I brought you on is because you have a few clients in particular where you've really dove into the weeds of this complexity. I want to start out by asking you, if you can lay out for the audience, when a brand goes from Shopify dominant
in their sales mix to all of a sudden having significant amounts of Amazon sales. Why does that introduce complexity into understanding new versus returning customer profitability for that brand?
Kevin (06:24)
Right. So let's first what type of business we're talking about here. The first order dominant businesses have a different calculus related to this question than the high LTV ones on the dominant side. It does not matter all that much to measure things like new customer sales on Amazon. So most of the brands that I work with are just doing
doing
traditional like MER stats and they're measuring their profitability that way and that's fine. Okay, so where this becomes most relevant is in a brand that has at least some level of repeat customer sales. That can be a supplement brand, a clothing brand, anything like that. All right, so new customer sales are everything when it comes to
measuring your media efficiency, your marketing efficiency, right? Now, as you said, brands tend to be pretty good at calculating NC ROAS on the Shopify channel on its own. It's not that hard to introduce Amazon into that calculation. And all you have to do is sum your new customer sales on Amazon plus
your new customer sales on Shopify and divide the whole thing by your media spend to get your combined NC ROAS that is the most important metric to start with when you're talking about evaluating your marketing spend now It's super easy to get data from Shopify on all of these metrics on Amazon It's actually not that hard to get new customers
Jon Blair (08:09)
Yeah.
Kevin (08:14)
customer sales data, like you can get it directly from Amazon Seller Central. And then of course, you can get it from a variety of tools like Lifetimely as well. that's where you need to start. Right. And then you can take your NC ROAS Let's say a brand has an NC ROAS of one and a half. All right. That's combining Shopify and Amazon and their contribution margin.
before
their ad spend is let's just say 50 % to make the math easy. All right, so that means they are not making money on the first order. We're starting at a one and a half and we're taking away half. So for every dollar of ad spend, they're getting back 75 cents in profits. So we know that they have another 25 cents to make up before they achieve breakeven.
Jon Blair (08:44)
Yeah.
Kevin (09:08)
profitability. Okay so that's the starting point.
What is then extremely important here is to calculate your LTV. All right. And the LTV over three months, six months, 12 months, really what you need to do is you need to put together a cohort model. Again, cohort models are very easy to calculate on Shopify, but on Amazon, that's actually not something that you can pull from Seller Central. It's not available. So this is where you really do have to use
a third party tool and there aren't many that we've come across. There is lifetimely There's one that I ⁓ tend to prefer, which is called expand fi. And then you can use that data to get your cohort model on Amazon and you combine the whole thing together to get a sense of when you're ⁓ achieving profitability. And this is so important because what brands, I mean, if you don't have the data, you can
Jon Blair (10:06)
yeah.
Kevin (10:10)
assume that your Amazon cohort model is the same as your Shopify cohort model. In other words, customers are coming back to repurchase at the same rate on your website versus Amazon. But in reality, I have seen those two channels delivering extremely different cohort models. In some cases, Amazon is much, much better.
Jon Blair (10:26)
Mm-hmm.
Kevin (10:38)
front and center was subscribed and saved very often. it's not, yeah, it's not hard to imagine an Amazon customer coming back to repurchase much more than a Shopify one. But I've actually seen it the other way around with some brands that heavily incentivize people to check out on their website with their subscriptions. So the point being you have to get both of these channels right in order to, to
Jon Blair (11:04)
Totally.
Kevin (11:05)
get that LTV right.
Jon Blair (11:07)
Yeah, and
like to drive point home further, why is this a problem in the first place? It's a problem in the first place because most of the brands we're working with have significant top of funnel ad spend in places like Meta where there's truly a halo effect. So if we as CFOs were to allocate 100 % of Meta spend,
only to the Shopify channel and you were to pull Shopify new customer sales versus Shopify LTV over a given time horizon, you may incorrectly determine that the payback period of your meta spend is much longer than it actually is because you haven't accounted for Amazon, right? Now, I wanna also drill into a couple more points that Kevin just mentioned. One being like, why do new customer dominant brands not have to worry as much?
There's a new customer dominant brand that Kevin and I have worked on together where returning customer sales is such a small dollar amount relative to new customer sales. You can basically call 100 % of their sales effectively for this analysis you can consider a new customer. So you don't really have to analyze on Amazon how much is being returning customers because it's so immaterial.
that at the end of the day we can basically assume all of their sales are new customer sales, because that's just the makeup of that particular brand, the product category, the price point, and the rest of their product this is uniquely an issue for brands that have some sort of significant LTV. Now, there's another category of brand.
that has significant repeat purchase but does not have the consumable or supplement style like, you know, fast LTV frequency, and that's apparel. If you have an apparel brand and you are selling on Shopify and Amazon, using one of these tools like ExpandFi to really understand new versus returning customer across both Shopify and Amazon blended is incredibly important because if not, you're going to falsely determine, you're gonna falsely calculate
erroneously calculate whether or not your new customers are actually profitable or unprofitable. And like, I'd love to have you give an example that you've seen, Kevin, but like, I've seen a brand without doing this combined analysis, right, like before working with Free to Grow CFO, incorrectly conclude that they should cut back their meta spend because it looked unprofitable when assuming that Shopify
was the only attributable sales. And then once the Amazon data got pulled in, it was like, no, no, no, keep scaling that meta spend. Can you tell me some of the surprising conclusions that you've been able to draw when you've used ExpandFi to bring in the full picture of Amazon versus Shopify, know, new versus returning customer sales?
Kevin (13:55)
Yeah.
Yeah. And the thing you'll often find for those types of brands is they maybe will understand and come to the conclusion that you just mentioned, which is that it looks like we're not making money on meta. However, we know that some of these sales are showing up as Amazon sales. And so what we're going to do is we're going to just take out a certain percentage.
and we're going to move it over into our Amazon channel and that will make us look better on our MetaSpend or Shopify spend and it'll kind of even things out. But what percentage you choose to shift from one channel to the other is, it's just very difficult to get that accurate. There are other tools that do that like Prescient, but what
Jon Blair (14:56)
Totally.
Kevin (15:00)
I found is if you just take out 30 % of your Shopify spend and move it over to Amazon, there are just too many moving pieces there to come up with some accurate insights. So that's why I like looking at everything at the top down level. And then once you go into, let's look at one channel versus the other, then, and how much we're spending on our Amazon ads versus our Shopify ads, you can maybe start to tweak
Jon Blair (15:10)
Totally.
Kevin (15:29)
those spend levels based on what you think that percentage is. So to put a finer point on it, what you'll often see is a brand selling on Shopify and Amazon has a ROAS of let's say like three.
Shopify but like 10 on Amazon, right? So it looks as if their ads are much more profitable on Amazon than than Shopify but once you take into account that halo effect and once you also take into account that Amazon tends to be a lower margin channel when you look at an all-in bottom line profit on ad spend you find that they're much
Jon Blair (15:52)
Yeah.
Kevin (16:14)
more equal than you might have expected. And really the only way to test or my preferred way of testing how much we should shift between one channel or the other is to run tests. And specifically like on Amazon, let's adjust our ad spend on Amazon. Let's cut it in half and let's see what the impact is on sales and ultimately
what we care most about, which is contribution margin for the business. All right, so if you shift ad dollars between one channel and the other and your contribution margin for the business goes up, then that is a sign that you're kind of calibrating that spend in the right direction.
Jon Blair (16:43)
Totally. Totally.
Yeah, it's interesting insight that I want everyone to take away from this discussion is that all of these different levels of analysis, and when I say level, I really mean the perspective that you're looking at, right? Some of them are lower, more granular perspectives. Some of them are higher level perspectives. They all tell us slightly, they all paint the picture.
from a slightly different angle, right? And so if you think about it, you're trying to kind of piece together this three dimensional understanding of what's going on with marketing performance and no single analysis tells you everything. They all tell you something and you kind of like, they're all one piece to the puzzle and if you look at all of them, you can kind of begin to get a sense of what the moves you're making in ad spend are actually doing to what matters most.
contribution margin, why? Because that's the driver of profitability. And here's what it's not, and I wanna make sure that people don't get confused about this. We're not talking about that Free to Grow CFO has figured out the perfect attribution method for all ad spend. What we're doing is we're doing a financial analysis, right? We're doing a financial analysis of various...
levels of perspective on how accretive we believe your ad spend is to the business's bottom line and to give you some sort of a sense of how one sales channel in Shopify is contributing to that differently than Amazon. Now, one thing you mentioned earlier, Kevin, like some surprising differences on what you thought was happening on Amazon versus what you found when you actually started
looking at cohort models and some of the data that was available in ExpandFi. Can you walk the audience through a couple examples of some surprising findings when you actually went through and looked at the cohort model for Shopify versus Amazon and then combined?
Kevin (18:56)
So I work with one.
pet supplement brand we brought on ExpandFi to understand the cohort behavior of Amazon. And it jumped off the page in the sense that their LTVs, their retention rates were almost like three X what they were on Shopify. And I had had a feeling that that was the case, but when you actually put the numbers behind it, it becomes, it becomes very interesting.
not only that, this brand has like two main products and the retention rates of one product were just vastly different from the other. So that can then be an indicator
you can direct more ad spend to that product that has a higher LTV and not only direct more ad spend, but you can accept a lower NC ROAS. So on product A, maybe it's got to be at least a one NC ROAS, but on product B, because that retention rate is so good, well, you can actually go down to a 0.8 NC ROAS. And so that they've implemented that.
Jon Blair (19:50)
Totally.
Kevin (20:07)
And it seems to be working well.
Jon Blair (20:10)
so the important thing is that, the important takeaway is there are counterintuitive insights when you get down to this level, right? And knowing that is important because when you don't know these various insights, you're not exactly sure what you can and can't afford to do on ad spend and acquisition costs. So this is like,
incredibly, incredibly important. And I'll say it's different for every brand, right?
It also, in my mind, it directs not just to that you can be a little bit more strategic on acquisition, maybe by like product line or by SKU, but it also may dictate whether or not you should spend some more time working on Amazon retention versus Shopify retention. Shopify retention, you're gonna be messing with things like Klaviyo and email workflows and things of that nature. The retention game on Amazon's a different game.
right, in terms of the activities, the agencies, the freelancers. And so, what Kevin is walking you through right now with some of these examples, it's not that your CFO, if they understand how to do this, is going to be able to tell you every little activity that you should engage in to improve the numbers. But if we think about this as like a spectrum of activities you can get involved in, before these analyses,
Kevin (21:10)
Sure.
Jon Blair (21:34)
you're guessing where on the spectrum you're going to make an impact with any decision you make. Now that we are using some of the, know, Kevin's examples using these tools like ExpandFi and whittling down these insights, you can now work on like one area of the spectrum. You know, what activities do we think are going to drive this metric? And then the great thing is you can measure it again after you execute on those activities and see if they actually drove the outcome that you were hoping for all the while.
being able to take a step back and say, are we making contribution margin dollars and thus profit go up or down as we mess with these things? And so, you know, being that we're a uniquely EECOM focused firm, these kinds of analyses are, have to be near and dear to our heart, things that we love doing, and they have to be a part of the financial planning and analysis mix because without it,
we can really just say, ⁓ you spent more and your blended MER was this versus what it was last month. So all that being said, Kevin, are there any, thoughts that you have? if there's a brand founder who's listening right now and is like, man, this is piquing my interest, do you have kind final advice on, like, where should they get started or?
maybe what should they look into first to see if they might be a good candidate for a tool like expand fi.
Kevin (22:56)
Yeah, sure. So
So if you think about what is one of the most important decisions that brands have to wrestle with on a month in month out basis, that is what is the appropriate level of ad spend. All right. So there is a, are a few different directions that you can take that the bottom up, which is basically like spend as much as you can at this NC ROAS. And that's good. But there's also the top.
down, which is what we work as CFOs very closely with our brand founders on. And I can share a formula that I use to help brands with that decision.
If anyone who's run a business before knows that there's there's almost this like mental issue that comes from having one line on the income statement that is a inflow and all of these other lines underneath it that are all expenses and outflows. And you're like, wait a minute, how am I, I only got one thing coming in and then I've got like 200 things going out. How am I going to, how am I going to make money here? Um, but that
that that metric for this conversation, the inflow source is returning customer contribution margin. You start with returning customer contribution margin, and then you take things away from it and you can solve for what is my minimum net income level. Okay, so let's go through an example. Let's say a brand has $200,000 of returning customer contribution margin each month. They then
have 100k of fixed overhead. Alright so they're left with 100k but then they want to solve for a minimum
net income of let's say 50 K. Okay. So then that drops them down to $50,000 that they can lose on acquiring new customers. Okay. So we just went through all the reasons for calculating NC ROAS. And this is one of the most important ones, right? Where it's like, you can tell your brands, you can spend up into the media spend level,
Jon Blair (24:58)
Love it.
Kevin (25:15)
that will result in a $50,000 loss on acquiring new customers. So as long as that marries with the campaigns are doing well and they're hitting the NC ROAS thresholds that deliver a decent payback, then that is a good way of marrying the bottom up with the top down on ⁓ calibrating total levels of media spend.
Jon Blair (25:38)
I love that. That is super solid advice and I also think it just simplifies this conceptual framework that I think gets over complicated by a lot of people. it's like if you understand LTV to CAC, you're like some sort of like an ad spend whisperer. It's not that complicated. what you just laid out I think is super, super helpful. So look, before we close here,
I'm gonna tell a funny story about having Kevin on this podcast. I've been holding back on saying, it's time to land the plane. Because Kevin, who has listened to many podcast episodes that I've hosted is like, hey man, I found you've got like a signature phrase at the end of every podcast. It's like, we're gonna land the plane. And so, this whole time I've been holding myself back from saying that. But, it's time to land the plane, Kevin. Here we are, this is a great discussion. I really
appreciate having you come on. This is a topic that's so important for brands. I know a ton of people in our audience are experiencing this challenge with this advanced marketing profit analysis. And I think some who are considering launching into Amazon, they now are a level up in their thinking of like, okay, I need to be ready to handle this. So I appreciate you coming on, Before we land the plane, I would love if you could give the audience
Where can the audience find more about your wife's brand? What is it called and what's your website?
Kevin (27:00)
Thanks for that. Yeah, happy to land the plane with you, Jon. My wife's business is called Awoo, A-W-O-O, and the website is awoopets.com. And you can find their stuff on Amazon and Shopify, as well as a few other channels.
Jon Blair (27:03)
Yeah.
Awesome, definitely check it out, definitely.
And you can be sure,
you can be sure that they know what their combined NC ROAS is for Amazon plus Shopify, that's for sure. Well, thanks again for coming on, Kevin. I think we might have to do this again soon.
Kevin (27:22)
You got that right.
That sounds great. Thanks, Jon.
Jon Blair (27:28)
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