Unpacking Incrementality: The Nuance of Marketing Effectiveness

[00:00:00] Taylor: Welcome back to another episode of the e commerce playbook podcast. Today, you get a rare occurrence. Normally Luke is here when I am not some might say there's not enough oxygen for us both to talk at the same time in a room, but we're going to give it a shot today. And we're going to be diving into a topic that is.

I would say it's a kind of a, a buzzy trend word right now around incrementality and some of the things that we're seeing as it relates to the work with our clients directly. And some interesting discoveries that we're seeing as it relates to the meta incrementality in particular, but we want to talk about this today.

So Luke, you are the man on the streets. You are the tactician in residence. We are excited to have you back. Welcome to another episode.

[00:00:43] Luke: So I'd be here forward to diving in. I think this will be an interesting conversation. Given that we have a certain perspective, I think around incrementality, attribution tools, just sort of that broader conversation and this, I hope we'll be able to have sort of a nuanced

[00:01:01] Taylor: And you can take that another month, maybe if you decide that appropriate amount of time to

[00:01:07] Luke: lump be lumped in this big category together but that's not that's not true of what really they're, they're doing. And I think they have a, they have a place in the, in the right spot within the mix.

[00:01:18] Taylor: Yeah, I think that's a great point. Is that is important to draw clarity and definition to these terms in a way that level set the conversation for what we are describing and talking about. And. Attribution is a topic that is not for today, and it's one that we've covered a lot in terms of the issues that we have with measurement in the form of attribution through various form factors that are disassociated in particular from the optimization of the platforms themselves and some of the problems that we believe that that causes.

But for today, we're interested more in it. Incrementality with particularly my interest is to try to help brands think about. Where they can get the greatest incremental reward for their dollars in this moment. And not even just incremental revenue, but I would say incremental contribution relative to their bottom line.

And so maybe, maybe Luke start with how do you think about and define incrementality and maybe what are you, what are customers usually in pursuit of when they sort of drag you into their incrementality journey. We need to be. Well, that would still pass.

[00:02:35] Luke: the, the way I frame it is where's the next dollar best spent that's going to lead to the resulting profit dollar that most likely would not have occurred otherwise. So where can I allocate my dollars in a way that's going to drive incremental contribution that likely would not have occurred if I had not allocated a dollar to that specific channel. It's not concerned with how do I sign credit to the ad dollars and their productivity on a general basis, not concerned with what is it new or returning customer revenue, that's important to tease out as well. It's overall contribution dollars to the business agnostic of. The specific channel that it's attributed to, or the specific customer cohort that it's driving through.

And so these conversations come up when brands are looking for ways to deploy dollars to help beat to help comp or beat their revenue forecast specifically and in the context of. We're trending down compared to a historical time period or a time period that we'd like to comp up against. Where can we deploy dollars to bridge the gap and help find incremental contribution dollars to the business? Likely would not be there if we did not those dollars otherwise. So that's where I'd frame up incrementality in terms of more common language and specifically incrementality is using a holdout or scale tests to look at the incremental impact of ad dollars through various tactics.

So, through the use of those specific tools GLS either in a hold or scale test fashion. at what is the impact of either holding out a set of geos or scaling into a subset of geos within this specific tactic or channel? How does that result in increased business contribution for that brand?

[00:04:18] Taylor: Yeah, and I think that's a great summary. Thank you. And the idea that it's the dollar that would have not occurred otherwise, I think is really the key is that, and I want to level set that what I think this is a noble, good pursuit, the idea that we would hold our dollars to a cause and effect impact, where we are not just finding corollary relationships where we spent here and revenue came, but that there's a causal relationship between the dollars we're spending and the effects that we're creating is really important.

Now if we start and say that that is a benefit, that that is a positive, that the idea of holding out, comparing two groups of potential customers, some that receive an ad, some that don't, and comparing the results is a good structural process for answering a question about what historically occurred.

Now maybe we could talk about some of our. Concerns about the application of these things in some ways. And then we'll get to some of the results that we've found interesting. So generally I'll, I'll share a few of mine and then you can layer in is that the challenge is that you can look at and answer a specific question in a specific period of time.

But then what you're left with is an application of that learning over a future period where a lot of the variables can change. So we may run a holdout or an incrementality study on a channel in a specific period of time it's February. And we did it on Google branded search versus not. And then we are left having to apply that incremental factor.

Usually what it produces is some multiple, Of the results relative to what the platform is reporting. So it's, you know, got a 130 percent incremental outcome relative to the result or 62%, whatever it might be. And then you apply that factor going forward in your measurement of that channel. Right. Is that sort of how you see brands most commonly applying these results?

Great.

[00:06:22] Luke: So what's important here too, is like running the geo, a geolive test brands can do this outside of a specific platform as well. It just takes a really thin layer. Thoughtful, well structured test and execution and someone with experience.

And so platforms like, measured or house. io, like there's, there's a few out there that are more commonly known. Just have a really good, clean setup for being able to do this. That doesn't require you to be a data scientist. And so like that, they, they structure these in that way. And then the output of them is exactly that an incrementality measure, which is a multiple.

And so. Specifically, what that'll look like is the platforms will pull in the platform attributed revenue usually based on a click basis. So I, in most cases, you're going to look at your Facebook attribution on a seven day click basis. You kind of define that. And then the incrementality metric will be applied against that attributed revenue.

So let's say. My meta row house is a 1. 57 day click, and I'm getting a read of 100 percent incrementality from platform after doing a geo lift test, 100 percent is going to be applied against the 1. 57 day click. So my incremental Ross is going to be just a 1. 5. Whereas if. It's a 200% incrementality read.

My incremental ROAS is gonna be a three incremental roas. My on platform is gonna be a 1.5, which is gonna indicate that there is a large number of unattributed conversions on a seven day click basis. That my meta media mix is actually leading to within other channels. And that specifically, that that percent incrementality measure is the multiple that's applied against the. Efficiency read on that platform. And then you can use that for yeah, making decisions on an ongoing basis. And so to your point, think it's really interesting to pull out two main things, which is how often should the incrementality multiples be reassessed or, or measured. And then and then what do you do with the, the reads that it's giving you from those platforms and in terms of cadence. most most folks will recommend like quarterly revisiting a geo lift test, at least for your core to your channel. So, like, especially for meta and Google search P max doing a quarterly revisit of of a geo or scale lift test just to validate your income income mentality because things change your product makes changes all of those sorts of factors.

So that sort of a cadence is. What's most recommended for from from these different platforms in terms of how often should I rerun GLF test for those incrementality

[00:08:51] Taylor: So one of the things I find challenging is often I have seen that in that cadence of re reviewing the incrementality measures that they may change, right? So talk to me a little bit about what you see in terms of the consistency. Of incrementality results across channels. And then let's talk a little bit about what are some of the variables that go into channel level incrementality measurements, because it seems to me that there are sort of like infinity possible settings within every channel that may or may not affect the incrementality of any given period of time.

[00:09:29] Luke: So, the GLF tests can dramatically alter what the incrementality measures are from from different channels. I don't know if this is something I would say in my experience, this isn't something that's has enough emphasis specifically from partners doing these tests in terms of how wide the variance can be in your post geo lift test reads from your channels versus what the starting point incrementality reads are on a platform like measured, for example, you're going to get a starting point incrementality read that's based on a subset of customers in a similar industry.

Based on folk brands of a similar size and then using their MMM, MMM on your current media mix to sort of like get you to a starting point incrementality read for that channel. And then they recommend doing a consistent GLF test to read that we're, we're in the middle of a incrementality test for a brand currently doing a geo lift test on meta total account spend for a large brand that we, that we all know.

And currently the incrementality reads are coming back over twice as high as what the starting point initial reads. It's actually, it's actually closer to closer to three X as high currently we're about three weeks into a four week test. will alter over the coming week. But based on the volume we're currently at, the income totality rates are not going to come in lower.

That's for sure. They're going to come in higher and at least 50 percent higher, if not a hundred percent higher, 120 percent higher based on where things are currently going at. what that leads to is a really different set of behaviors and thinking around what is the, where does the maximum opportunity for our brand live in terms of where we should allocate our ad dollars and where we should be, should be thinking about new initiatives. And in this case, Previously the ideas were around, okay, if this is the state of our current medium X, we need to go look for investment into new areas, right? We need to let's ramp up DV three 60. Let's ramp up credo prospecting. Like let's look for new channels and new campaign types within those channels that we can.

Test and push ad dollars into, but if your meta reads are coming back in incrementality, that's saying your incremental ROAS is close to a three within that channel. Then it makes you start to think that the highest impact activities you can have is trying to spend as much as you can on meta while holding that efficiency level, which is net new offers, angles, creative audiences, everything on meta to maximize the outcome within that channel. And it, and it will redirect. The organization completely in terms of where the focus is on channel diversification versus amplification within meta.

[00:12:06] Taylor: Yeah, and this is, this is one of those things where I'm just going to caveat right now, something important about CTC and our business structure, because, you know, this last month I've been sharing a lot of data about Metta performance and the critique that we will give is the idea that we are biased and have an incentive to propagate that Metta is a good channel as if there's a financial incentive that underlies that.

With the particular customer you're talking about and 98 percent of CTCs portfolio. We have no deals related to a percentage of ad spend. And in a hundred percent of cases, we have no deals related to percentage of spend on meta. And we make no additional dollars. If people spend more money on meta, we only make incremental dollars.

If their contribution margin is a business gross. That's our only shared financial incentive. And so the reason that we are so pro meta is because it is the place that primarily drives incremental positive contribution margin. And in this case, it's another example where a customer. Has a perception of channel and diversification and risk, and is looking for a way to assign impact as broadly as possible.

And the result back from the incrementality study is, Hey, in this primary growth channel, there's actually. Way more impact than you're even giving credit for on a seven day click basis and reporting. And what that got to me was one, I want to talk about the structural account setup that we think yields incrementality because it's funny.

I had, so I had a 40th birthday party on Sunday or on Saturday night and we had some friends there. And one of them was a leader of an e commerce brand that incrementality study back from meta directly that actually showed that the account was like, you know, Way over reporting revenue relative to impact.

Now their account structure is very different than ours in the sense that it has a much more broad ranging set of objectives besides just conversion. It has reach and video views and all the other brand awareness plays as well. So how do you think about how account structure impacts incrementality and how, when you do these tests, you have to have a consideration for the underlying setup of the account itself.

Not just, just assume that meta as a channel is a channel as a channel, regardless of what brand exists.

[00:14:19] Luke: So let's break down incrementality into some of its component parts. Cause I think they speak directly to then what the account structure should be. That then helps to impact those factors. I think measured does this in a, in a great way actually to define what impacts changes in incrementality over time.

And so when you're comparing to previous time periods, you can see. How is my incremental ROAS changing? But then what are the drivers for that incremental ROAS? And there's actually four specific factors that they pull out that impact the incremental ROAS reads. First is your average order value.

So that being a higher is going to have a positive positive impact on Incrementality that being lower is going to have a negative impact. The next metric is impression conversion rate which is which is really click through rate. It is, what is the percentage of folks that are seeing my ads?

Are they clicking through my ads? And that being higher has a positive impact on your incremental ROAS as well. It's, it's really interesting. This will be one we could, we could spend a whole episode on. CPMs is another factor that CPMs being higher has a positive impact on incremental ROAS as well. And then the incrementality reads from

[00:15:28] Taylor: so I'm just going to pause there because this is a thing that like, I'm exhausted defending this, but this is so to be clear, this is not our language. You're, are you reading this from measured incrementality in particular? So in the assessment, increased CPM is a positive signal of incrementality.

Just to, I just wanted to say,

[00:15:48] Luke: Positive. It's

[00:15:49] Taylor: okay, thank you.

[00:15:51] Luke: with honestly, I don't know how each of these four factors are weighted in driving incremental ROAS. I do know that A geolift or scale test, which is the final fourth factor of your incrementality read does have the highest impact on the incremental ROAS from that channel as it should like your most recent geolift test is going to inform the incremental ROAS. But your average order value, impression, conversion rate, or click through rate, and then your CPM, those three factors also feed into how the incremental ROAS reads change over, over time. Because you can think about it this way, your GeoLift or scale test, static. If you run that once a quarter, you get that read and that populates in the platform, but your incremental ROAS is actually dynamic over that time period because your average order value impression click through rate and your click through rate and CPM fluctuate over time.

So those are the three factors that will fluctuate, not remain static. And they're overlaid over your most recent geo or scale of tests. That's sort of the foundational read for that channel.

[00:16:51] Taylor: Yeah. It's almost as if price is a signal of value in the advertising world, right? Like the, the things that are cheap or cheap for a reason. Okay. So continue on. So, so we have these sets of underlying measures now, and one of them you've been talked about as click through rate. So how then do you think about how the optimization or campaign structure relative to those incremental inputs would affect incrementality fair.

[00:17:16] Luke: yeah. So, it might be helpful. Actually, we could take a step back from Meta and talk about a different platform because the same principles apply and then we won't get pigeonholed into our Meta argument. But the, the so within the within the Google's platform, our incremental ROAS has, has increased as well for this specific brand.

Hmm. Over time, I'm looking at the total mix of our Google branded search, our Google non brand search, our performance max, and then any standard shopping campaigns we're still running at this time last year, which may have been a few and then the biggest change within the Google mix specifically is There was this brand had a brand awareness like high, high level brand ambassador that we were engaged with at this time last year.

And we were running a lot more YouTube media. So upper funnel, non conversion optimized YouTube, YouTube media we were running YouTube for action. So I won't say non conversion optimized, like there's an opportunity for that person to convert, but YouTube is a much more upper funnel channel compared to the performance max, obviously. So the main thing that's changed within the Google media mix for this brand is cutting YouTube investment specifically. And that has led to more incremental, higher incremental ROAS and return from this channel, even at higher levels of spend. And so when you look at those factors that we talked about, The CPMs, the click through rate, the impression conversion rate, our CPMs are for sure up, right?

Because YouTube, YouTube, you're going to get a much cheaper inventory, but our click through rate is substantially higher as well because YouTube's trying to lower click, driving a lower click through rate than Pmax and the other channels. And so that, that in itself, the media mix there shows. What investment in different sub channels within Google is going to do in impacting your incremental ROAS and the same principle applies to paid social, just like you mentioned, Taylor, like if you're, if we're running non conversion optimized campaign at this time last year which we weren't, but if you're running reach or video views or whatever, like that is going to negatively impact your incremental ROAS in every, in every circumstance that I've seen, similar to how we're seeing that play out on the paid search side of things. a piece of it. And then the second piece of it, in addition to the overall media mix and what optimization optimizations you're going after is how you're bidding against your conversion media as well. And in this case, for this brand, one of the biggest changes is we have more roas goal bidding.

So cost control, specifically roas goal bidding. Within this account, much more than we had at this time last year. And there were, there was some highest value campaigns running at this time last year, which isn't the case anymore. Everything is Roscoe cost control bidding, which has increased the impression conversion rate and CPM, which has increased the incremental Ross on the block.

[00:20:00] Taylor: was great. So there's something really important here. So I think a very oversimplified narrative that happens in our industry is to think of incrementality as this thing that moves up as you move up the funnel. Right. So people would say like, Oh yeah, the problem with meadow or branded searches, it's all just bottom of funnel.

It's non incremental. Okay. This is really poor thinking. What I would say is that there are versions. Of bottom of funnel advertising. And I mean, true, like bottom, bottom, like just like display remarketing and allowing a video or view optimization in your remarketing traffic or DPA on meta branded search.

These can be really low incrementality at the bottom of the funnel, because when we think, go back to this idea, the purchase that wouldn't have happened. Otherwise there's no obligation to any action oriented to a subset of customers that are very close to the purchase path. Okay. Now people jump from there to a secondary conclusion, which is then therefore top of funnel media, YouTube, television, et cetera, must be the most incremental because it is customers that are nowhere near purchase because they are the least aware fundamentally, but in reality, it's sort of like, a loop that comes back around, which is that.

Yes, that bottom of the funnel stuff that I mentioned earlier is really low incrementality, but so is the brand. So is that very top of funnel traffic in almost every case, because of you go back to those inputs, the estimated action rate, all of the, the causal factors that say the customer actually was impacted are also really low, which is why the inventory is so cheap.

So somewhere, this is what I think. People just think it's just linear. It moves the incrementality moves up as you move out the funnel. And that is just not the case almost ever. What's really the sweet spot for incrementality. And this is where I'd love to focus on then in your perspective. So if we sort of say that in both, in a lot of those cases, and again, don't come at me with your edge case.

I understand that there are cases where both branded search. I saw one example or TV can be incremental. I'm not saying it's binary. Yes or no, there are cases, but in general, those things have lower incrementality. Now in the sweet spot of the middle where we see high levels of incremental impact, what do those campaigns look like?

Look, what are they structurally in your experience?

[00:22:20] Luke: Yeah. And maybe, so to take one step back before we get to the campaign structure on your point, like every channel, the Also degrades at a very different rate, which is the important thing to pull out here, which is, for the brand we're talking about in this case, their incremental ROAS read from branded search is actually one of the highest in the account. As, as, as it should be, but you, once you start spending 10, 000 a month, more like increase your investment, 10%, it drops off a cliff. So if you think about like the diminishing returns curve, like each one of these channels is a really different format just like structure, what that looks like.

We're like branded search. You could think of being like really vertical in terms of like the optimal point, but then it starts dropping off once you start investing more, whereas meta has a much longer tail on the top. And like, you're trying to, you're, you're able to ride that more. And what's funny is, like, when we think about tatari or like, running, running TV, like that's going to actually probably have one of the flattest curves, which means like you could scale for a very long time before you start seeing meaningful diminishing returns, but overall, the incrementality is lower, right?

So, like, you're getting a 0. 3. Like a 30 percent incrementality there versus like 100 percent on meta, you could hold your 30 percent on TV for a long time. Like you could 5x your investment and it'll probably stay there, which is, think part of the draw to find platforms like that, where like you can just scale and scale and your income mentality is not going to start dropping off where it is going to on branded search, for example.

[00:23:51] Taylor: And this, this is so important. This is another reason why you have to, and I'm speaking now, if you are a smaller eight figure brand and you are hearing really big brands talk about these other channels, here's what I want to cautious. Caution you with if you're hex cloud or Jones road beauty or what you've been running at a ROAS that is like the 90th percentile Like you are so efficient in these core channels, way more efficient than you small business, because they have great brand reputation, amazing product market fit, all these things.

So when you go get 30 percent incrementality in a channel that scales a ton that might still pencil, you might still be profitable and able to produce huge unlock of additional volume, because even at that 30 percent measure, it's still works. And this is why the brands that win. Okay. That can scale the biggest are able to spend the most money on a customer and still convert them.

It's the old Henry forward saying either the customer value is high enough to them. This is why insurance is like the biggest spender. Customers are worth tens of thousands of dollars over long periods of time, right? So they can go spend a ton of money on top of funnel advertising that has low incrementality, but it's a flat curve that scales infinitely basically.

But it's not to say that you can go produce efficient volume there today. Like, and this is, I think the noise and the muddle of the way these things get sort of extrapolated and applied that I think is, is frustrating is that they are different channels with different objectives and values relative to the individual business needs and capabilities.

[00:25:22] Luke: Yeah. Yep. and so I think, Like the sweet spot for most brands really is meta based on what, what we're seeing, because like the running at that 30 percent incrementality is not going to pencil for the majority of brands, even though you could scale into oblivion potentially. Whereas like you can't just keep pummeling money into branded search and your bottom funnel. You know, PMAX non brand exclusion campaigns, because the incrementality of those are going to start to drop, drop off, right? They're just capturing demand there. So where can I create net new demand? That is at a positive incremental contribution and, and meta is where that opportunity exists for, for the large majority of brands.

So in terms of the, yeah, go ahead.

[00:26:05] Taylor: Well, I was just going to say, okay, so, so, and I would just even go a little bit further than just meta. It's not just meta generally. To me, it's a specific construct within meta that is really. The like the mat, when people talk about a magical product or met as the best platform, it's actually really a very specific structural engagement in meta that I think is their ability to actually drive user to action in a novel way that is like disproportionate to everything else.

So maybe let's talk a little bit about in this case, what are these campaigns? What is the structure that is allowing us to do this? And then how do we, and then maybe we're going to talk hypothetically about how we're going to take these reads and then apply them in a way that allows us to even drive more value.

[00:26:46] Luke: Yeah. So, three, three very important things in terms of the account structure on meta, that's going to lead to the highest incremental contribution. One is all campaigns are optimized for purchase conversion. And, and this is like taking. this is taking for granted that you have the pixel up, right?

Your EMQ scores above an 8. 0, like you're getting all the signal on product catalog set up well, right? Like all of that is really important to make sure your conversion purchase optimized campaigns are driving the thing that you want them to, but purchase conversion optimization. Second, using cost controls. Specifically we've seen higher incrementality from ROAS goal bidding versus. bit or cost cap, which I think is important because it leads into the third one, which is separated by key product category or even specific product funnels see really differing incremental impact reads from one product category versus the other.

So purchase conversion optimized using cost control bidding likely raw school is going to lead to the highest incrementality because that's going to connect to each of your product categories, having different incremental contribution and having different AOVs as well.

[00:27:58] Taylor: Yeah. So the raw spitting often is value optimized, right? So you're getting that AOV impact as well as we're using a seven day click optimization in this case, which I think is an important part of this as well. I'm excited to test a few of the places where we are using some broader view and things just to see what happens in that sense.

But, but it is important to understand even within the confines of an incrementality measure for the channel at the campaign level, or I think in measure, they call it topic or whatever the, the subset is. There's really variable outcomes across those different results in ways that some of these are more than others.

And I think a lot of that has to do with how much preexisting demand for your products are there. So we have a lot of times we think about brands as homogenous amongst their product mix, but it's really not the case, right? If you're Lululemon, the women's yoga pant has substantially more existing demand than men's sweaters.

If they're even in that category, you know, like there's just. A subset of organic demand that exists around some of these products versus others. And as you move into novel categories, that's going to differentiate a ton too. So those are all really important to consider, but the incrementality, even in meta can get decay really quickly when you get into.

More view optimization, broader conversion objectives, these various things. Now, again, there's ways to pair them together and do hold out and you should run them, find the answer for yourself. But in terms of where that sweet spot of incrementality, and this is, I think sometimes why I find the practice of incrementality to be redundant because the result is always the same.

Click optimized meta prospecting with a holdout of your existing customers, or you know, a subset to lapse customers is always the most incremental thing you can do. And so when you think about the result being twice as good as the result in platform, all of a sudden now we can set our cost controls are pretty low relative to our previous expectation and still be driving positive results for the business.

[00:29:51] Luke: Yeah. And I think maybe to then take this to a step in terms of like what the business outcome and that expectation should be. I think it's important to say like, The goal here isn't to just increase the incremental ROAS reads within your meta dashboard, right? Your measure dashboard, like the, we're, we're trying to drive the business impact.

And so ultimately that should be showing up on the P and L level for your, for your brand. But before you even get there, you can start to see signs of what the incremental impact is. And we're starting to see this for the brand that we've been, been talking about here, which is like, as we've been scaling up meta into these really strong, incremental reads what is the downstream impact that we're starting to see for this specific brand? They have had some been experiencing some pretty significant. Year over year headwinds in terms of the contribution from their organic search channels, their direct channels. Like when we think about Google analytics and kind of that breakdown, those core channels that signal organic demand related to some of brand ambassador impact.

I mentioned last year where they were investing in terms of influencers and, and and athletes. So they have these headwinds that are showing up in their organic search and direct channels. I was, we've been scaling up into meta. The contribution from that channel has increased, but what started to happen is organic search and direct have started to comp up compared to last year. We're starting to see the user volume grow, starting to see the last click revenue attribution from those channels and Google analytics start to comp back up from last year. And we're not going about this in a way we're saying, how, how do we drive as many impressions as possible to help fill the gap in organic search and direct?

Right? Like, how do we just drive traffic volume? That's going to. We're saying, how do we invest in the highest increment incremental channel? That's going to lead to day one incremental profit dollars, and then downstream impact of more dollars from other channels that we're seeing those headwinds on. And so that's where you can start to see this play out is not just the impact within the channel itself, but how does this look on your channel? On your organic direct channels within your marketing mix. And how did those start to react once you start to lean into your highest income data?

Cause that's what we should expect to happen, right? If these are driving dollars that are above what the platform taking credit for from a click your other channels should start to show some impact of that increment of contribution.

[00:32:05] Taylor: Yeah. And in this case, like when we talk about how dramatic it is. So if we think about, again, let's Tiptoe very gently here into attribution, which is to say, when we were running these campaigns, you have a seven day click optimization that you're measuring on a seven day click reported attribution. And that the incremental report was actually closer to, if we had set up the account, looking at 28 day, click one day view attribution.

Again, I put out a tweet about this that I think was confusing. I'm not talking about optimizing for that, but I'm saying that when we looked at the revenue attributed via that model, there 28 day, click one day view. It matched the incremental ROAS that we saw in that campaign in a way. That's like, Holy cow.

Like, and if we all think back to 2016, 17, and this is what I was referring to, that was default meta and we all loved it, right? 28 day, click one day view, rock and roll. That was the attribution setting that we all measured and reported on. And so when we, I think a lot of times we forget that when we comp to ROAS from those eras, we were using a very, a much broader attribution model in that type.

[00:33:06] Luke: Yeah. And what's interesting as well is. we were to switch those campaigns to start optimizing for view attribution, likely the would start to tank. So the optimization is still purchase conversion ROAS goal building bidding separated by product category, but the actual revenue contribution from those campaign is more closely measured on a 28 day click one day view in terms of the incremental impact. from the account set up in that sort of a structure.

[00:33:34] Taylor: That's right.

[00:33:34] Luke: and and it's really interesting because it flips it the other way around. Instead of saying, Hey, we're going to go for trying to drive 28 day click one day view metrics. That's going to drive down our CPMs are going to look better, right? But our CTR is going to start going down and capitalities going to lower.

No, we're going to drive. Click based purchases from these campaigns in this specific structure, knowing that the incremental impact is actually more what that 28 plus one is going to take, take credit for,

[00:34:00] Taylor: Yep. Nobody ever got muscles looking at the weights. You got to interact with them. It's not different when you think about incremental impact and advertising. If the user is not interacting with them, the incrementality is going to be lower. But Luke, we appreciate this. We're excited to keep sharing the results that we're seeing here.

And to really hold ourselves to the obligation. And you even set it setting aside all of this channel level measurement and assessment. And we are still the rule of law. The end result on the PNL is still the thing that governs truth more than anything else. What we're trying to get is directional application against the thing that makes the greatest impact on those measures.

Measuring marketing tactics with financial outcomes still is the core principle. And we're just trying to make sure that we are getting causal in our behavior as we go. So any last words that you'd leave them with before we head out?

[00:34:48] Luke: None,

[00:34:49] Taylor: That's it.

[00:34:50] Luke: no more words needed,

[00:34:51] Taylor: There you go.

[00:34:52] Luke: ROAS goal separated by product category.

[00:34:55] Taylor: Rock and roll. Thanks, man.