Transcription
In the last month, we have made the largest shift to our media buying strategy that we have made in a very long time at AJF Growth. And it goes against many of the things that I've said on this podcast for a very, very long time. And I'm going to tell you all about what it is right now and why you should do the same thing.
Okay, here's the shift. Ready? I won't belabor it too much. We are fully embracing incremental attribution. Incremental attribution is an optimization method in your Meta Ads account. You probably have seen this. You probably know it. They actually first rolled it out a little over a year ago. They announced it as a feature at Meta Performance Marketing Summit. At the time I released a podcast episode about why I thought this was a big deal. Uh why I thought it was really great, I was excited about it, and why I thought we would be adopting it at some point. And that day has come.
We first tested incremental attribution as an optimization method for your ads. Uh you know, a while back. We we tested it uh you know right kind of right when it first came out and it it performed really poorly. So we kind of left it aside for a while and and didn't worry about it. That was confirmed by the public incrementality test data that was being shared by the likes of Common Thread Collective and House and other people like that who are sharing data like this all the time. Incremental attribution sounded like a great idea in theory, but in the beginning days it just was not very effective.
So, let's talk about what incremental attribution is and why I think it's so valuable. Because for us, and I want to get in front of this right now, it has been a massive unlock for performance for our brands. It has been really, really, really effective. Uh, and and I think if you watch or listen to none of the rest of this, and I'm going to make the case for this in a minute and explain some of the details of this in a minute, but uh I if you don't watch or listen to any of the rest of this, I'm just going to tell you right now, go test it. Go test it in your ad accounts. go try it and test it specifically by reducing spend on competing uh optimization methods and increasing it on incremental attribution and seeing what happens.
Okay, so um I I'll talk more about the details of that later as I kind of get to the end of this episode. But that's the basic idea. Okay, I I just think if you listen to nothing else I say, if you don't understand any of how it works, go implement it. Go see if it will work for you for both highest volume, highest value, everything and see what you can find. It's been really effective for us. uh if a media agency is managing your spend, force them to do it. That that's my that's my that's my appeal to you.
So, let's talk about what it is and um I'm going to break this all down and I think it will really help you understand the tool and why it's good. So, incremental attribution is an attribution setting you can select at the adset level in your campaign builds in meta. When you go, you set um your attribution, you know, you can do highest volume or highest value. At first, at the campaign level, it's all the usual selections, right? You can optimize, you know, for highest volume or value. So you can optimize for cost per result goal, for target rowass, for bid caps. Those are the campaign optimization settings for purchase optimization. But then at the adset level, you can optimize for which conversion event you want. You can optimize for different attribution methods. And one of those choices is do you want standard optimization or incremental optimization. And it's that simple. The the way you opt into this is that you simply say select a dropown and say I'm going to optimize for incremental attribution. And that is it. You don't need to do anything else. And and that's it.
Now I want you as I begin to explain why I think this has been effective for us. I want to start from the very first principle of all first principles in relation to this which is what is the point of your ads. Okay, the point of your ads is to drive purchases particularly for direct response advertisers, performance marketers, e-commerce brands trying to drive sales right away. This wouldn't be true if you're running a big brand campaign, but there would be actually a way that it would be uh analogous to this, but whatever. We won't get distracted. If you're running purchase optimized ads on meta ads, the goal ought to be to drive purchases from your ads that were not otherwise going to happen. That is what we mean by the word incremental. Incremental in this case means you delivered an advertisement to somebody. They they uh were in some way moved to action by that ad. And I didn't say clicked very much on purpose because they may or may not have clicked on it. They removed action by that ad and they made a purchase in your store that they were not otherwise going to make and your ad caused the purchase. That is what we mean by the word incremental. And therefore, if you are presented with two optimization methods in meta ads, okay, and one of those optimization methods is called standard optimiz standard attribution or standard optimization. K purchase optimization and the other one is called incremental optimization. If those are your two choices, you should with if you know nothing else, opt into incremental because what is even the point of having something called standard attribution, the thing you want for your ads is incremental.
So why hasn't everybody done this right away from the beginning? And it's it's what I alluded to earlier. It's that in the earliest days of meta rolling out this tool, it just didn't work that well. uh it it seemed to perform generally speaking in the tools in the in the every test that we ran and every test that we saw just didn't work as well as standard optimization that that uh Meta had had for a very long time at driving incremental purchases okay whatever forget in platform reporting or whatever your triple whale dashboard if that's what your thing is you know like forget all those things just it's just you're it just didn't seem to perform as well at the inc uh in terms of driving incremental purchases doing the thing that it was supposed to do so so you kind of wonder even at that point why did Meta roll it out then the answer is I think that the same is why Meta rolls out anything they roll out, they I think pretty much always roll out tools a little bit before they really work perfectly. And that's because the thing Meta needs more than anything else to make their tools work as well as possible is data. And so what they do is they roll out the tool sometimes to some people, sometimes to everybody. They fund a bunch of tests. If you're a larger spending account, almost certainly you can get ad credits for your accounts and you can go spend a bunch of Meta's money on the ads and do that. And then meta of course from that not only gets people testing the tool and responding to it and gets uh you know subjective feedback about it but they also get the objective data of how it's working and they can download the tool and over time the tool tends to work really well. This is very much what happened with ASC if you remember this I it goes all the way back to when Metabot Instagram or when Facebook bought Instagram and you know in in those early days we would exclude Instagram from our placements because it just worked really really poorly but of course now you would never do that sort of thing. So they do this all the time. I don't think there's anything devious here. It's just the way that this is the way that they're going to get the information they need the data they need to make the tool work. And now it seems to me to work much better than it did before. And so in general that's the case.
But there was actually something that motivated for me um testing this again recently uh after it hadn't worked for a little while. And it was particularly one account that I was working on where it just seemed to me that no matter what we did, we could not get our bidcap campaigns to spend, my precious bidcap campaigns. And um and that didn't make any sense to me. It just didn't make any sense to me because they were spending fine for a little while and then when we first launched them they were you know like they're okay whatever like it was a fairly newer client at the beginning of this year but it just it didn't make any sense to me that the bidcap campaigns wouldn't work very well. Many people for a long time have been have said to me about my strategy of running bidcaps and if you know my content you know I I've loved using bidcaps for a long time. What many people said to me was well bidcaps are only going to spend on lowerfunnel traffic and a lot of times they don't spend at all and they're really volatile spend levels and all that. You know, at various times we found little bits and pieces here and there of things like that, but generally speaking, we didn't really have those problems. We buy with bitcaps all the time. I think there's some skill involved with it. We're good at it. We know kind of what we're trying to do there. And so, they worked really, really well for us. I didn't see an obvious volume drop off, especially for brands that were getting a good number of conversions. They were relatively stable for us. And it seemed to work well for a long time. We certainly didn't see any of this issue of it only targeting lowerfunnel traffic. It was clearly targeting for our accounts upperfunnel quote unquote. I mean, I don't even like that phrasing of this, but you know, new visitors who were not coming to the site before and getting them to buy.
Okay, but then there was um a big well and and in the midst of this though, we should think for a second about the big caps seemed to be more volatile in one particular ad account. Let me finish the story. And so I just thought, let's just try this again. We haven't tried it for a little while. Let's try incremental attribution with cost caps. And what we found when we did this was that suddenly we were getting a bunch more spend than we than we were before. our spend actually uh like like 3 to 4xed for this account. Okay, it was spending very little money before it like it like tripled and this is not like a big spending account. It was spending in the low it was it was an offseason period of year. It's very seasonal account and so was in the offseason it's kind of the perfect time to test this sort of thing. It was only spending a couple grand a day and I thought like this account even though it's the offseason should be spending five to six grand a day at least, you know. So we we launched incremental attribution and when we did that the very first thing that happened was that our spend or when we launched incremental attribution our spend got right up to those numbers like like within a day very very quickly spend started happening. The problem was the performance was not actually awesome but it still showed me that oh we're getting more spend out this way materially more spend and so I'm going to stick with it for a little bit. And as I started to do that, I found over time that those campaigns performed extremely well relative to what was happening before this. And uh and as we've rolled it out into more and more accounts, we found uh we've found that incremental attribution basically in every account that we've rolled it out across. And I've got a you know, we're running 10 to 12 accounts at a time. You know, at this point, it has really worked awesome. It's worked great. And pretty much in every account, it has increased our spend and increased our performance, especially over over a couple weeks of of first rolling it out. And so that little trigger happened and suddenly we started finding that this worked really really well.
Now I want to think for a second about what problem incremental attribution solves. Okay, let's think again first principles about what the idea of the tool is. If you think about it right there was there's always been this proxy there's this question in your meta ad setup. You could you could you could uh for a long time opt into one day click 7-day click 7-day click one day view uh attribution. You could opt you could have engaged view um and you could you could have all these different ways of saying what do I want to count as a purchase in my uh in my optimization methodology. Okay. And there are all these different options. You are building a business. You need great team members in your business and you should find those team members in the Philippines with help from my friends at more staffing. More staffing is the staffing agency I have been using for a long time to build my team on my business. The majority of my team at this point is based in the Philippines. I could not be more thrilled with that on a lot of different levels. First quality of employee uh just great great contributors across every part of the organization that we have. I just I have no plans to build any business in the e-commerce space at this point without help from incredible people in the Philippines who've been working on e-commerce businesses for a long time who know what they're doing, who are really talented. And I've seen those kinds of contributions across every part of e-commerce businesses from marketing teams to designers and editors to you know media buyers to operations people to supply chain people just all over the place and more staffing is so well equipped to help you find those people in the Philippines because they were built on the back of a US-based e-commerce business that was working with Filipino talent that helped them unlock growth and and profitability at the peak of their business. So they understand what it looks like to locate, to onboard, to train, to keep connected to great talent from the Philippines. And they're going to help you do the same thing. The value proposition is really simple, right? Which that your money goes really far in the Philippines for finding great talent because you can hire way higher up the market in the Philippines for much less than it would cost to get the same level of talent, the same level of resume in the US. And more staffing can help you find those great people there. Go to more staffing.co.staffing.co co or find the link in my show notes. Tell them I sent you.
It's one of those things that Taylor Holiday pointed out a long time ago is like media buying has sort of gotten more confusing than ever because you you pull up your adsets and you go like, well, what do I do here? And I've look, I audited a lot of accounts, especially brands that are starting to spend more into the multiple hundreds of thousands a month. They just kind of have gotten there however they've gotten there. But lots of them are spending huge amounts of money with view attribution, probably not looking at click, you know, click specific conversions, etc. And so, one of the things I would tell them all the time is you should be optimizing for clickon conversions. And the reason I gave that piece of advice and the reason most media buyers have ever known who are any good at this have given that piece of advice and we kind of all agree there's just not a lot of talk on DDC Twitter or or wherever else about like view attribution versus click attribution. Occasionally someone will come in with a comment here and there but but basically everybody agrees you should be optimizing for click attribution for click optimization in your meta purchase optimized ads and the reason why is that we all agreed on something which is that there's a proxy for an incremental purchase and that proxy was a click. So what I mean is all along we always agreed we were trying to drive incremental purchases. That's always been what we're going for. Okay. But the problem is we didn't have a great way of saying give me only meta please only give me the purchases that are truly incremental and keep don't count the other ones. There wasn't a great way to do that except for third-party incrementality tests to sort of tune a model in some way or another. Well if you think about that the way that people got around that was by trying to define clickbased windows on which they would count a conversion. a one-day click or a 7-day click or something like that. Um, you know, a while back you could separate between view through conversions and engaged view conversions. The idea is that some conversions where people don't click but do make a purchase, those probably count for something even if the person didn't click. In fact, one there's sort of two challenges here to this. Well, let me just say like this. As you're making those decisions, you're trying to decide which of those proxies you want to use to signal incremental purchases to meta and to your reporting. And so what people have done for a long time is relied on a click for that. But there's really two problems with the idea of relying on a click as the proxy for incrementality. The first is not every click indicates incrementality. Anybody who's ever run a brand run a branded search ad knows this. And anybody who's ever been concerned that meta ads is disproportionately reaching lowfunnel traffic, quote unquote, is having this same concern. They're saying, "Wait a minute. Why would I want to optimize for a click when some clicks are actually not driving incremental purchases at all? that person was going to buy anyway. So the click doesn't increment uh doesn't indicate in incrementality. Okay. The second problem is not every incremental purchase follows a click. So problem number one, not every click indicates incrementality. Problem two, not every incremental purchase follows a click. And if you think about both of those problems and and that's, you know, that second one is really simple, which is that like what if I watch a minute and a half of your video, you know, get off of Instagram and then make a purchase the next day, but I don't click. Well, probably a good good chance that that that video view drove the purchase. Okay, I think this is a that's a relatively small issue in meta, but it is a real thing. And so both of those create this problems and our our historic solution to this for a long time at AF Growth and I think for a lot of advertisers has been optimized for click-on purchases, but then recognize that it probably doesn't count the full value of your spend. So for us, it was 7-day click optimization for a very long time. And when we would do 7-day click optimization, we would just make an adjustment up and say we're going to count the true value of the purchase as being more than that. You know, Meta and how I've referenced this a lot of times, but um but House and Common Thread Collective both released these big sort of meta analyses of incrementality studies showing basically the same result, which is that if you optimize for 7-day click, the true value contribution of your ads on average taken across all their accounts was about 10 to 20% higher than that number. So, if you drove $1,000 according to your ads, you actually or according to 7-day click optimization, you actually drove $1,100 to $1,200 in in true actual incremental revenue in your ad account. Okay. Uh, another way of doing that, the way we did that was we would measure on 28 day click, which is which ladders to about that same number. Okay? And so, you could look at that sort of window when you get there.
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All of that is proxy work. But then another big problem happened. Okay. So we would we would do that for a long time knowing that Meta underounted. But then another big shift happened and that happened in March of this year, March 2026. Okay. And that was that meta redefined what a click was. Meta used to refer to a click-based purchase as any purchase that followed any click on the ad at all. That could include somebody commenting on the ad, which would include a click at somewhere in the process, somebody making an image larger or a video larger on the ad, somebody sharing an ad, somebody clicking the Instagram account handle and then going to the Instagram account and then going to the website. that would count as a click, which is a very large like a lot of people do that. Okay, all of those things counted as a click and and uh or excuse me, all those used to count as a click, but then in March, all of the everything that used to be called a click besides an actual click on a link to your website. Okay? All of those things got rettagged as an engage through. And you could only optimize on engage through conversions on a one-day window. And so suddenly we're shifting all of our optimization from 7-day click to 7-day click plus one day engage through optimization. Now in the old days like I told you 7-day click optimization including all of those different various kinds of clicks they all counted okay that underounted the total contribution of your ads pretty significantly. Well now a lot of those actions only gave you one day of optimization data after that. And what we had found, we we've wrestled with this a bunch about sort of what the best way to handle this was. But what I have found is that basically since March, no matter how we've done it, no matter how we've approached this, I have found that our bidcap campaigns in particular, for some of our clients, not all of them, but for some of our clients, have been sort of the most stubborn they've ever been at getting them to spend. And it's been really challenging. So, uh, so we've we we haven't had like insane massive underperformance or anything like that for most of our brands for most times. Most of the performance has been fine since then. Okay. Not great, not terrible, but but fine with really good moments mixed with some down moments and whatever. Okay. Uh nothing nothing catastrophe or anything like that, but just it's felt like running the day-to-day like the bid caps, like I said, have been sort of stubborn. They just won't spend in the same way with the same consist consistency that they would did before.
So, I implemented the test that I told you about earlier for that one account. And if you think about this, the idea has always been that the bank account is the only attribution method that really matters. That's like been our mantra for forever. Okay? And if you go back to this idea that what I want is incremental conversions and and I know that there's limitations to using a click as the proxy for that no matter how you define a click. Okay, then I actually never had a solution to this problem that I really really loved. It was always flawed in various ways. It was always frustrating in various ways. So, okay, what then do you do about that problem? And that's where I thought, okay, why don't I retest for this one account and see if incremental attribution could solve it. And that is what we launched and that was the thing that became definitive for us in a whole bunch of ways.
I have been advertising Intelligjam on this podcast for a long time and it is getting better all the time. Really amazing piece of software that is just one of those core pieces of software that basically every serious operator has in their e-commerce software stack at this point that I know of. And that's because if you are testing things on your website, you should be testing things that really do move the needle on your website. And Intelligjam allows you to do that while tying into your COGS data so that you can actually see the output of every test you do, not just at the level of conversion rate or average order value, but at the level of profit per visit, which is the most important thing, but it goes way beyond all of that at this point. You can not only test all the needlemoving stuff that we talk about a lot, you know, price, free shipping threshold, all kinds of different offer tests, and of course, all the regular testing they're doing all the time. That's all great in Intel Gems, really extremely useful. But they're also doing all kinds of additional things with the tool to make it more useful all the time. You can now do post-purchase upsells in Intell. You can do pre-purchase upsells in Intel gems with cart upsells and check in checkout upsells. You can start testing checkout. You can um now have like AI powered changes to your website to start testing. So you can so you can actually just do use natural language to start making some of these changes. It's just it's just one of those tools that is already awesome and getting better constantly. And like I said, if you're a serious e-commerce operator really trying to build a business for profit, Intelligjam should be in your toolkit. Go check it out right now. Go to intelligjms.io, use the code fair 20 f months and get started testing today. Test the things that really do move the needle in your business.
So, let's talk then about why incremental attribution is such a good solve for this problem. Because ultimately, if all of the click metrics we're using were already proxies and that got blown up in a new way in February in a way that made everything worse. What it does is it puts a fine point on the fact that we never really wanted to use click attribution anyway. What we wanted was to be able to to optimize for incremental attribution. And what incremental attribution does is kind of genius. Basically, incremental attribution, the way that it works, instead of relying on just a couple of click or view based behaviors, what incremental attribution does is using the boatloads of conversion lift studies, probably millions that Meta has to get some sense of what actions preede a purchase. Maybe at the user level, like literally maybe down to like what actions you take before purchasing. I don't really know that. I'm just speculating here. But they have a lot of data, right? They can have a sense of what actions for all of where their pixel measures things a user takes on platform and off that precede a purchase driven by an ad according to the conversion lift studies that they have. And then they can use that to build a machine learning based predictive model of what an incremental purchase from an ad is after seeing clicking whatever. Now ad now I'm sure a click on the ad weighs heavily in that machine learning algorithm, right? I'm sure it does. Of course, right? It has to matter a lot. But it's not the only thing. And how it factors in relative to other things, I don't know. I will never know and neither will you. But the basic idea that Meta says, forget trying to use these proxy metrics. Instead, let us build a machine learning based approach to measuring what things people do that lead to purchase. I mean, that to me is a better approach anyway. And so, as long as the tool does what it says it does, I have no interest in looking back. I I have no interest in turning back to any clickbased attribution or viewbased attribution or anything else. I would like there to be a machine learning based attribution based on this. And this is where like the countless conversion lift studies powered by meta along the way is kind of a genius move because what it allows you to do, what allows them to do is collect boatloads of randomized control trials about what leads to a purchase from ads on their platform and then to use those to inform models. If you listen to any of the incrementality companies talk about the way an MM and an incremental incrementality test interact, this is exactly what they're talking about. what they will all say the smart ones I've seen Olivia mentioned this tweet about this for house is is like and you know Cody Plofferson tweeted about this the other day that basically and an MM that a lot of people like love to rely on like North Beam or whatever is not tuned correctly. It is some kind of algorithmic approach you know a modeled approach to how or to what actions are are driving purchases across a bunch of different ad platforms. Okay. But what the people from house will say and and I I think rightly so is that when you tune your mm with incrementality studies, it gets more accurate. And so incrementality studies uh help make the modeling more beneficial. Well, Meta has exactly that. They can build a model of what likely led to a purchase and then they can tune that model based on not only your CLS's, conversion lift studies, not only other brands like you, but millions of conversion lift studies across millions of advertisers over a whole bunch of time. And that is what you want. You you another thing everybody will tell you about incrementality studies is that you get three incrementality studies and they all tell you really different things. And so any one of them is not that useful. Actually, the thing that's really useful is a bunch of incrementality studies in the aggregate and then having that tell you something about modeling and all of that regress to the mean. So, this gets into statistical nerdom a little bit, but like it is it is a very helpful way of thinking about this problem. And so, as much as meta is actually able to do that, incre incremental attribution is great.
Here's one of my predictions in this episode. One of my predictions is that eventually there will be no distinction between standard and incremental attribution that in instead it will just be incremental only and and advertisers will go nuts if they take away if meta takes away clickbait attribution or whatever else as an optimization method they will go crazy and yet like many things where advertisers go crazy but meta makes them make the decision it's actually the right decision for advertisers in in a lot of cases and I think this is this is one of those now I don't I don't have any inside information there it's just a guess but that's what I think.
So when I go to my clients now and say we were optimizing for incremental attribution. It's just been really really beneficial. We've found all kinds of great things coming from this. First of all, more spend. Secondly, better performance. Those things have just been off the bat really really good right away. We have seen what other people have seen as well, which is some different ads rise to the surface in these than previously. We we do seem to see pretty good reach. I haven't measured this closely yet. We've been using it. We started doing this by replacing our volume, our bidcap campaigns, like I said, because we're having a specific challenge with those. replacing those with cost cap incremental campaigns and I'm going to talk more about that in a minute too and that has been really good. Every single brand for which we have done that we have not gone back to vidcap standard optimization campaigns because the incremental campaigns have performed so much better and it's it's very clearly not just because of the cost caps. It's it's definitely both. There's a lot of reasons I think. Uh but it's it's such an overwhelming difference especially compared to anything we've seen before. Certainly I have tested cost caps relative to bidc caps in the past when you know when I've had little challenges here and there with an account or with an advertiser really wants to try some or a client wants to try something different. We have never seen anything like this where the performance is so drastically difference at the level of volume and performance. I I just I think there's the cost cap element of it may or may not be helping dynamic bidding with cost cap versus bidcaps. I don't know maybe helping in some accounts in some way. I'm not sure but uh there's there's no way it explains that the total differences that we've been seeing. We haven't measured super closely yet, but I'm just here to tell you across every account where we've done it, it has made a meaning meaningful difference pretty much right away.
There's all kinds of other benefits here. One of them is that I feel less pressure to get really sharp exclusions here because even the idea of excluding existing customers, the whole premise of that is that existing customer click-based purchases are not actually that incremental. And that's always what I have believed about this. I've always held retention ads to higher standards than prospecting ads. But if it is a that has always been a guess based on click-based proxy signals for incrementality, what happens if an incremental campaign can just like make can just know the difference based on modeling of what actions led to a purchase? Well, then maybe you don't even need to exclude existing customers quite the same way anymore. We're not I'm not sure on that yet, but certainly for some of my clients, large skew scar set clients with lots of product drops, lots of moments, we've seen pretty good success so far. Basically combining up new and existing customers. Meta has also rolled out their customer life cycle optimization now where you can specifically tell Meta we want more new versus more existing customers. So that could be a factor here as well. I haven't really tested that yet, so I don't have any information, but anyway, the point being it's been really really good.
Now, what about cost caps versus bidcaps? So, you you've heard me say for a long time that bid caps have been uh something I really love because I like the idea of bidding on a threshold, not an average. This has always been my argument. There's a certain CAC threshold that I want and above that CAC threshold, I don't want I don't like that cost caps can dynamically bid. Costocals can dynamically bid above that target. Even though I I theoretically like the idea that Meta has a bit of freedom to go explore new audiences with that, I think that's a great idea in theory. It's just really expensive. And so, and so what about that? Well, uh, my answer to that right now is that I have always thought this was a relatively minor distinction. I really have. Like I, you know, I've put out content about it because there is a choice to make here. But when somebody comes to me, when when people come to me with accounts and they say, "Hey, can you audit this account?" And I see it's running on a bunch of cost caps. I don't go tell them, "Turn off all your cost cap campaigns and rebuild them as bidcap campaigns." Like, I just don't think the distinction is big enough to warrant that. I'm happy. I I think details matter. So, I'm I'll make content about anything that I think is good. and we're going to we've always opted into bid caps, but for me it has never been a central distinction that I care the most about it. Like 90 to 95% of the job is done when you go to manual bids versus auto bids and I've said that for forever. My friends at kinship, I used to coach them for a long you know one of their media buyers for a long time and sort of work with them and like I you know they've I think run cost caps for forever. Had Jack Rubin from Pretty and Fig on here. They've run cost caps forever and been happy to tell what they've done. I think CTC does that. I refer them business. It's just not actually the biggest deal in the world to me. The big distinction to me is manual versus auto bids.
So why do I run cost caps for incremental attribution? Simple, because you can't run bid caps with incremental attribution. At least you couldn't last I checked. And maybe they will roll that out at some point. I don't know. So for now, we're happy to use cost caps for that. We tend to set them a little low because I'm assuming that there are going to be more purchases above my CAC average, which is what a cost cap is when I'm running incremental or when I'm running cost caps and and I don't want those. So we'll set them a little bit more conservatively than sort of a true target and just see if there's a little bit of money to shave there. On the other hand, what every uh incrementality test I've seen of incremental attribution campaigns has shown is that uh they under reportport their true value. And uh there's I'm not quite ready to say that yet, but I think there's some evidence of that in some of the accounts that I'm looking at now. And so it is possibly the case that um that while the cost cap pushes me to be a little more conservative, the incrementality factor on incremental optimization pushes me to be a little more aggressive and maybe we'll we'll end up right in the middle. So we'll see. There's some details. I'm sure I'll have more content in this in the future, but the basic point is here, incremental attribution can and should do the, you know, the thing or or hopefully should do the thing you always wanted your optimization method to do in the first place, which is drive incremental purchases and to have that determination be based on the actual actions users take that that predict a causal relationship between your ad and the purchase. That is always the thing you wanted. And it appears to me from the testing that we have right now that that today those campaigns are really showing are really showing that that does that. And so we're really excited about it and we're now doing it also starting to take over our highest value campaigns as well. That's sort of the next step. Again I'll have more content on this in the future. Right now I'm telling you to go test it. I think it's been working really really well. I wouldn't be surprised if I record it again in a month and said I am now telling you this is absolutely SOP for everything we do. to tell you any account I've you know I've got a couple accounts on boarding over the next few weeks as we kind of have our have our book of business filled up. I'm just telling you right now like we're going to launch those with incremental campaigns. We've been doing that with newer accounts, higher uh older accounts, higher spending, lower spending accounts with more and less organic reach. If you are an account with a wide skew set, if you are an account with some organic presence in some way in in these kinds of cases, if you're spending a lot of money, these are the brands where I think you especially have a great case for incremental attribution. I would strongly strongly recommend um I would strongly recommend you test it especially in those cases, but really I think you should do it for everyone. I've got accounts that are very early in their life cycle that we're testing this for.
All right, that's it for today. I think I hope that has been helpful to you as an initial guide to this. Yeah, that's the way we're approaching it. Thanks so much for watching and for listening. Big thanks to my sponsors at More Staffing and Intelligjs for sponsoring this episode. If you have thoughts or questions, I would love your comments on this episode. Tell me what you thought. Have you tested this? Leave a comment. Uh so I can see what you're seeing and see what you're saying about that. Um and I I read and reply to every single one of those. And uh and share this with a friend. If there's somebody who you think would get value out of this, who's running meta ads and who you think should be testing this too, share this with them. That's actually the number one way you could say thanks to me. If you like my content, you can go to my website if you want to work with us, afgrowth.com. Fill out the intake form. We're we're full right now, but at some point we'll have we'll have uh more space. And so let me know if you're interested in working with us some whether it's now or later. I might have a good referral for you if I don't have um uh any space for you right now. And then uh email me podcastfgrowth.com to tell me any more thoughts you have on this episode. Thanks so much for watching or for listening. I have a bunch of great episodes coming up. You should subscribe wherever you're doing this. I actually have a new little idea that I'm doing which is for a little while I'm going to bring back a bunch of my favorite guests from this podcast in a sort of recurring capacity. So, I'm working on who that's going to be, but I got a couple people who have sort of opted into saying, "Yeah, I'll come back every two, three months and just get some of the best guests I have and really hit it across a wide range of e-commerce topics that hit different parts of the business." Operations people, measurement people, meta ads people, you know, whatever, all of these different things to talk about sort of what's going on so you can stay up on it all in one place all the time in kind of a structured way. So, subscribe wherever you're watching or listening. Don't miss that. Thanks again. I'll talk to you next time.