We Analyzed $1.5 Billion in Meta Spend. Here's What We Found.

its outcome, highly effective.

Within several percentage points of achieving its outcome, at the portfolio scale.

“And I think this is going to be a really important, a really important part of this conversation”

is that the things that we are, the things that we're talking about that are true at the portfolio scale, there is obviously differences within any individual account. But we have to hold these ideas, these ideas and tension, that it can be true for the portfolio, that Minrose is very likely to achieve the setting that it is set to you. While at the same time, there's an individual account variance.

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Hey folks, welcome to the e-commerce playbook podcast. I'm your host Richard Gaff and Director of Digital Product Strategy here at Common Threat Collective. And I'm joined today by the chopper, Mr. Tony Chopper, who is our, and you just told

“me this, but you should have to remind me again, what is your official title, Tony?”

Vice-president, media investment. Vice-president, media investment, which for our purposes here today means that he knows everything about paid media, and what we were discussing right before we hit record here was the fact that is we've sort of connected cloud and RAI tools for our own MCP.

We've been able to develop analysis at an incredible rate of speed here or an incredible

volume, rather. And so there's lots of information coming through and we've had a ton of opportunity to explore questions that we haven't really been able to explore in the same way before. And so one thing that we've been kind of going over recently is analyzing how platforms behave against bidding strategies and what we mean by that is if you set, say, a, I don't know,

ROS target in meta, does meta actually deliver against that outcome and how close does it actually get to that target ROS in, in actual fact and similar for like a cost cap or

“a CPA target, how close is it getting to those things?”

And so we wanted to talk through a little bit of that research today about Tony, why don't you give us some background on some of this research that we've been doing and and some of the conclusions we've come to. Yeah, quick, just quick time out. My internet is real choppy. Can you guys hear me, okay? Yeah, you're good right now.

Cool, yeah. Nice to see you again, Richard. Hope you guys are still enjoying it somewhere up there in Portland. Yeah, it's been, you know, this year's been a really fascinating, fascinating time. I've been at this for a long time and, well, earlier this year, we, we, we got set up with Claude. So we have a corporate Claude and we, we connected Claude

to the statless database via an MCP in it's kind of always been a dream of mine to be

able to really ask some of these these questions at scale on top of this, this incredible database that we have of all of our, all of our e-commerce customers. And to your point, like for a long time forever at CTC, we've believed we've had a strong belief in called cost control, media buying and that takes a lot of different shapes, but in essence, media buying can be volume based or can be cost constrained cost constrained. And we have been long

been advocates for for the latter for forcing the media to achieve some sort of financial outcome in order to earn its delivery. So and contained within that sort of sphere, all of the platforms give us multiple options for each of these pathways for volume based bidding and for cost controlled bidding. And so the questions that we've been exploring and trying to scratch at with our with our broad database is how well do they work? If we don't

per acquisition target CPA or if we tell meta, give us a 2.0 min or us or Google a 2.5 target CPA. How effective is that setting that we give to the platform? And are there any differences and nuances between the different options that are available to us? And are those differences or nuances? How are those differences and your nuances useful for us on the media investment side? And useful for us to, you know, share our perspective internally at CTC, like in

the canon and how we operate in ultimately with our audience as well. So that's kind

“of the setup. And there's been, I think, so pretty interesting takeaways so far. Yeah.”

Well, so let's, let's just then jump right into into the results and maybe we talk a little bit about like this setup of some of these experiments like what exactly, what's like the, I don't know, the sample size, what exactly are we testing like talk to that a little bit? Yeah. Yeah. So the, the first one we looked at was was from meta and we, the report was generated earlier in the summer, back in July. And we looked at a chunk of investment

between beginning of March and the end of June. We looked at 300 approximately 320 meta accounts

and just under $1.5 billion in media spend. So that was the sample size of the, the

meta survey and the meta survey came with the, the fascinating and on the right on the nose title of due cost controls work. Did they actually have any impact? And the, the big takeaway from the research and what would be happy to share the entire reports is, it's pretty dense. But the big takeaway, the punchline, if you will, is Minrose is highly effective at achieving its outcome, highly effective. But within several percentage points of achieving

“its outcome at at the portfolio scale. And I think this is going to be a really important,”

really important part of this conversation is that the things that we are, the things that we're talking about that are true at the portfolio scale, there is obviously differences within any individual account. But we have to hold these ideas, these ideas and tension that it's, it can be true for the portfolio that Minrose is very likely to achieve the setting that it, it is that it is set to you. While at the same time, there's individual account

variants, we can hold these two ideas at the same time. So Minrose, highly effective at achieving its target, cost per result, very much less so effective. On, on average, across our data set, the cost per result goal only achieved its target less than half of the time. So in one sense,

“we have a bidding strategy, like if you think about it, we're media, uh, as a media investor,”

I want to go and give the money to the platform and have a certain level of confidence that the outcome that I need, I'm going to get, right? And what we've learned from this initial past with

meta is that if we're going to make a bet somewhere, Minrose is the bet to make. And this ultimately

has informed CDC's meta canon and how we think about applying our account structure in our bidding principles, because while there's no guarantees on an individual case by case basis, we can be quite sure and quite confident that this is the right initial bet to make. Yeah. So the idea then being, obviously, we've been advocates for cost controls for a long time, but that was sort of under the, because we can test the assumption that met as cost control product,

let's say, actually works properly. And so there's like a little bit of an element here of cost per result does not deliver the way that it ought to deliver and Minrose does. And so that's simple level, that's the preferred method or is there more nuanced to it or most paid social teams run dozens, hundreds, even thousands of ads. They haven't been able to experiment with landing pages at the same scale because traditional AB testing makes the team wait for every

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“Yeah. I think that's a fair sort of way to interpret it and just let it sink in your mind. I think”

just kind of zoom out a second. The lowest bidding product is the newer bidding product. It's

the newer optimization option in meta and in Google. The cost cap or target CPA were earlier forms of cost control bidding so you can think about the ROS or essentially value bidding as the newer technology. Also, if you think about the mechanics of how the ultimately the bidding engine works in cost control bidding, whether TCPA or cost cap, there's essentially a ceiling that the system is trying to operate under. It's trying to ensure that all of the conversions

sit below this threshold. In a ROS outcome, the cost per conversion can vary based on the AOV to create the marginal outcome. So there's one way to think about it is there's more flexibility available to the system to go find high value buyers that achieve like a higher basket, a higher

cart size, and ultimately create more value. But the cost, the cost per purchase, might actually

be higher on that particular order. But the ROS will achieve the outcome. So the way that I think about it is that the ROS bidding options give the algorithms more flexibility to go find different types of buyers where the cost constraint bidding options are going to be more constrained effectively. Yeah, interesting. Okay, let's switch over to Google then and talk a little bit about a result there because they're similar. And then, yeah, talk a little bit about that and

“the upshot of it. Yeah, I think this is where this is where things got really interesting, right?”

So the Google study is the more recent one that we just that we just put together. So we're looking at a big chunk data. So 24 months worth of data back to June of 2024 through May of this year, 134 stores in the sample size and just over $100 million in qualified spent. So very interesting that the result of the analysis on the Google set, which is does Google adhere to the targets that we give it in the platform are very similar to them. In the sense that

T-ROS target ROS bidding is actually achieving above its target 1.3 x the time. So more often than not T-ROS is actually running above the target. T-CPA is the exact opposite. It's running below its target at a factor of 0.8. Okay, so I think, wow, we have again, this is back to like,

there's going to be, you're always going to have variants at the individual level. But if you

will, if you're going to compose a canon for how to do media investing and you're going to, and for your brand, if you're thinking about a place to start, it is it is 100% advisable to use ROS bidding options either on meta or on Google and you are absolutely more likely to have the outcome that you need as a media buyer to say, I need, I needed two to one return on this media investment or I lose money. And I think one of the things that's, that's really, I think here's

a thing, Richard, that I think is hard about media buy. Okay, there's lots of things that are

“hard about media investing. But here's, here's the thing that I think it really, you're really”

cuts on. You can either produce a lot of value or you can destroy value. Yeah, right? And if you think about that, like, one, one of the things that we do at CTC is we get really sharp about how how businesses make money. We understand the P&L, we understand the cost profile, we understand we understand the customer, and we, we use all of that business acumen about how e-commerce businesses make money and our specific client, how they make money. And we get to an acquisition

target and we fold into incrementality and our understanding of the incremental contribution of

the channel. And then that leads us to a target for the channel. So, it may be our for a business is 2.0. The incrementality of meta-seventy click is 1.2. Therefore, our on-platform target for meta is 1.8. Okay. Now, but think about that. We've just, we've, like, threaded this needle. Like, this is the number where if we, this is the number we believe gives us the maximum amount of

“opportunity to invest. Okay. We have the most aggressive bid. You know, I think Taylor's mentioned”

the, you know, Zuckerberg quote about the person that's willing to spend the most to acquire the

customer as the person who will acquire the customer. So, we're always pushing, always pushing the

math to say how low can we set the target and still make money because that's going to make us the most aggressive in the auction, the most competitive in the auction is going to make us the most likely to get in front of the in front of that user, right? How low can we go? Now, the result of pushing that target as low as mathematically possible to, with a threshold of, you know, breaking you in or make a little bit of seat profit per order, whatever it is that we come to, is that on the

other end of that on the other side of that is lose money on every order. No. So, this is what I mean when I say like the, the confidence that we have when we go and say meta, give me a 2.0 for Google, give me a 1.8 to your us, our confidence and in the systems ability to deliver that outcome is

“paramount for us to be able to do to our job. And that's why I think this, you know, for forever,”

I've had, you know, anecdotal experiences with using this bidding strategy or that bidding strategy and again, individual circumstances will continue to vary, but it gives me a great deal of confidence in the CTC cannon, the principle of, this is where we start with media with media buying for our projects. Yeah. But I mean, the thing you make an important point because there's some rest a little bit is that like in order to, because it's a risk, pay media is a risk. There's an

incredible amount of precision that needs to go into finding what that number is. And then of course,

like you're saying, that has to be balanced with that you have to make that number, I mean, we're talking about T-RUS specifically, as low as possible in order to spend as much as you possibly can before you start to lose money. And so it's all about writing this line between those two

“things. And in order to get to what that line is and not fall over the edge, you have to have”

a ton of tools in place. You talk about a mentality, of course, like having confidence in the product itself to actually do what it says it's going to do, all of those things have to be in place in order for you to write that line the way that we like to write it, which is why we do, you know, produce these volumes and volumes of of reported research and whatever, just to make sure that the data is that the feedback we're getting from media is accurate, I guess. Yeah. Yeah. Yeah,

just, I want to double click on like just re-emphasizing like the reason why the math to arrive at how low can we push the target is because all of the media platforms are auctioned. It's worth participating in an auction against other advertisers. So the better, like, from from top to bottom, the the more the more what's the word I want to use. The better the DNA of the business. Yeah. So like subscription brands are like the sort of the one the poster child for this.

Thanks. So much LTV. They often can and do and are willing to acquire customers. I break even and potentially even a loss. So this is really good business DNA that allows for, you know, a really aggressive sort of front end advertising strategy. That's business business, business make up, incrementality, understanding the contribution of the channel. All of these things lead to our a posture of us having a high level of confidence in entering that auction as

competitively as possible. Yeah. That doesn't make sense. And this is something that we've been discussing recently with joy. We've been discussing for a long time, too. Of like, there's it maybe it's like it's not necessarily that a business's DNA needs to be good versus bad as much as like there's certain types of business DNA that are to continue the analogy,

brands and industries where we're paid media in this environment works well. And so you mentioned

“the script like a high LTV brand because because you win, if you can if you can afford to lose”

money on first purchase, that's a great way to win and it gives you the opportunity to spend more

money to bid higher in the auction to win more options and so forth. But is that a fair way to think about it like there's certain types of businesses, there's certain types of DNA that work with paid media well and it's our job and a lot of this research is identifying how your business can fit in with this environment. Yes. Yeah. Yeah. 100%. Yeah. It's all part of like one big cohesive hole, right? So you know, understanding your business DNA, understanding having really good understanding

of a measurement stack, you know, and for for us at CTC, it's MMM and incrementality and connecting like my title as media investors sort of like indicative of like what what we actually do is we deploy capital to create a return. And the tools of the trade are incrementality and MMM and on the business of financial planning side like the spend and the MDR model and returning customer model helps us understand the the spending power of a business and then ultimately when we get into the platforms,

you know, the bidding settings like what what what what tool do we use like we use, you know, so use a metaphor of tools like we can kind of think about like the older versions, the TCP is the cost caps is like maybe a little bit more older tools, a little bit more rough around

“the edges and I think what we're seeing from the data is that the newer tools that the minerals,”

the T-Ros are sharper, they're more it's more of a scalpel, it's more predictable. And that's really important to me as a media investor that's walking the line on, you know, how do we deploy this,

you know, we richer we sit, we sit across a $800 million media investment across our portfolio

clients like it's almost a billion dollars broke like how do we how do we deploy that confident and I think that's that's where we're that's more we're pleased to be able to do this this type of portfolio wide research. But I want to hit I want to hit one other topic on this because I think there's some interesting, there's some interesting sort of things that are happening around the sort of little flourishes around the bidding systems and so I want to I want to call out

something on the Google side so pretty much that's logged into a Google ads account Dave recently over the last several months you've seen a notification in the account that's changing their bidding mechanism for they're saying they're saying it's going to be more consistent, predictable performance against TCPA and T-Ross bidding including when budgets change so I've had some some laughs about this with our our Google agency partner except a sort of like

what do you mean more consistent predictable like isn't the isn't this the promise of the bidding like the TCPA thing like already like isn't that what you're saying that was sort of like

“isn't it like isn't this how it's been supposed to work but anyway I think it's I think it's”

the the language that we're hearing back from our partners is that it's it's really a function of campaigns in Google that are limited by budget Google Google it gives us a really cool indicator in the platform that is we don't we don't see it anywhere else where it will throw a flag that's is limited by budget aka if you have your T-Ross set to tune you have your budget set to $1,000 day or whatever else after the system processes for some like the time it will give you a flag to

say hey you could actually turn up the budget here and maintain the same result now what what's happened it what can happen and what we've seen happen is you go to that same campaign you know triple the budget or whatever else and then the the the return it's really unpredictable okay and that so back to this whole like the spirit of this whole conversation like what what's really valuable to me as a media investor's predictability so what we're hearing from Google is that we can expect

more predictability specifically around campaigns that are limited by budget and specifically

around increasing that budget which to me is like Hallelujah that's that's amazing okay so that that's

like one little embellishment around this this whole this whole universe around bidding and predictability and expectation there's another thing that I've that I've seen recently that I'm that I'm I'm pretty excited about and I think it's it's like a different it's a different take on the same idea and it's

ecosystem and it was it's pretty cool it's like give the campaign a daily budget and then TikTok

“the GMV Max campaign has an option to a budget scaling option so it is said simply if at target”

scale budget right and then you can set there's like different settings you can set the interval like look at it like check like five times a day and scale up by 10 or 20% so it's all kind of configurable but the premise is pretty simple it's if the system for whatever reason finds a pocket up demand go and scale into it if you're at the target right and I think the the what what this solves for is if the fear in the apprehension and sometimes the the challenge in this whole world

is like on the meta and Google side what the platforms want is budget liquidity they want a big

daily budget right okay what I want as a media buyer is predictability confidence that my media investment is going to return at this level because I'm threatened to needle here Richard one way creates a bunch of order volume and contribution margin the other way torches it hey so

“meta Google they want these big like daily budgets for budget liquidity that's how the system works”

I talked to you before about like minerals and tiros bidding having opportunity to go from more like higher value buyers on a higher caq blah blah blah blah budget liquidity is the thing TikTok is approaching it a little bit differently where they're saying like hey you don't have to give us unlimited budget liquidity you tell us the target you tell us how much we can roll this budget up if we find a pocket of demand in the next day the budget resets back down to

that sort of normal baseline so I really I really like that mechanism and again we saw it in GMV Max ads a couple months ago and we're starting to see it percolate into the the web ad side as well but I think it's another sort of cut of this whole idea around what are the platforms need in order to be successful what do I need to be successful as a media investor and you know how how do we how do we put it all together no cool so let's let's quickly I mean if we got a lot of

take away some out of this but just just to make sure we're summarized here use tier us minerals don't use cost caps that's that's the canon stance right now yeah yeah I don't like I hate these I hate I don't I struggle with like black and white things like the foundation the found if you're going to build a media media platform or your foundation should be rose rose based bidding value based bidding okay we have in our canon we actually have some language around bid surface expansion

through bid caps specifically okay so I just want you to think about the takeaway needs to be use rose bidding as your core it's not like hey don't ever do anything else okay I don't want to be that dramatic body I want to be I want to say use rose bidding at your core because it is it is across the portfolio the most likely to help you thread that needle it's right all right well well you you heard the man so I think I think we'll we'll cap it there but the idea is

the the headline is that minerals tier us work the way they say they will work or even better in some circumstances there are maybe circumstances which the other bid types make sense but in this

particular case this is what we've we've discovered and as we again like this an incredible

volume of research coming out of of the CTC think tank so we'll have plenty more to share with you

“and go over with Tony so one more thing I want to say that is if you want to join us and join Tony”

Chop himself for a in-person workshop on building out your paid media account and thinking through some of these things that in-person workshop is next Wednesday September the second Tony will be there to break down a meta-ad accounts kind of run through his stance on paid media so please join us for that you can check out a link either on our website or in the show notes for tickets to that event but anyway I just wanted to say that and I think Tony anything else you want to

hear here oh that's it for this one we'll see you next time Richard with way more a bunch more analysis reports let's write with hundreds of thousands of words of analysis in between the next time so we shall see but all right folks thank you again for joining us and we'll see you all next