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In this episode of the eCommerce Playbook Podcast, Taylor and Tony Chopp, the VP of Paid Media from Common Thread Collective, explore the shifting landscape of Google Ads and the challenges posed by the implementation of PMAX. With over 20 years of experience in digital advertising, Tony brings invaluable insights into how AI developments are reshaping the strategies for Google Ads, particularly with PMAX's impact on advertising effectiveness and budget allocation.

Tony breaks down the complexities of Google Shopping, the nuances of data feeds, and how brands can effectively navigate the ever-evolving digital advertising space. He also shares his journey from learning painful lessons in eCommerce advertising to becoming a data feed expert, making this session a goldmine for marketers looking to enhance their Google Ads proficiency.

Key topics covered include:

  • The transition to PMAX and its industry-wide repercussions.
  • Strategies for managing brand and non-brand PMAX campaigns to maximize ROI.
  • Analyzing recent shifts in ad spend distribution within the eCommerce sector.

This episode is packed with actionable advice and strategic insights to help you leverage Google Ads for your business advantage in the AI era. Don't miss out on understanding the current dynamics of digital advertising from one of the industry's seasoned experts!

Show Notes:

The Ecommerce Playbook mailbag is open — email us at to ask us any questions you might have about the world of ecomm.

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[00:00:00] Taylor: Welcome to another episode of the e commerce playbook podcast today. We're going tactical. We've booted Richard out of here. No philosophical nonsense. No interviewing the GQ giants. This is in the weeds solving for the great AI takeover of Google, turning it into a giant P max sloth. I don't even know what I'm trying to say, but I've got with me the VP of paid media from common thread collective, Tony chop here to help us decipher what on earth to do with Google.

Tony, how are you?

[00:00:31] Tony Chopp: I'm doing well, Taylor. Thanks for having me.

[00:00:34] Taylor: So Tony, you've spent what you'd like 20 years dealing with this whole Google ad product universe. Give us a little bit of the credentials here and why people should listen to you. Help us solve this problem that we're going to discuss.

[00:00:46] Tony Chopp: Well, you're giving away my age. So that's a good start. But yeah, I mean, I, I've been in the digital advertising world for coming up on 20 years. Now, early on in my career, I spent a ton of time in the Google ad space. I ran my own consulting agency for a bunch of years before coming to CTC in 2019.

To actually help CTC build up the Google ads function. So, yeah, deep, deep deep tactical platform knowledge on Google ads for sure. Specifically and just a little, little anecdotal story. How would actually. I think led to what's worked really well for me at CTC early on in my career with Google ads, I did a lot of lead generation stuff.

And then as I spun up my freelance business, one of my first clients was a large e commerce brand. That sold auto parts. And I actually didn't have a ton of experience with e commerce and Google shopping at the time. And I got I got fired in about two weeks from that deal. And I learned a really painful lesson at the time, which is.

How how, how different Google shopping specifically was and how it's related to data feeds and all the inputs that were required. And I sort of took that knock as or I should say that knock propelled me to get really deep in the weeds on The, the Google shopping products specifically and everything that orbits around it.

So for anybody that doesn't know Google shopping little picture ads at the top of the search results page that advertise products different Than google search which are all the text ads that show up on the search results page but yeah, so that sort of propelled me to to become I I Got to be I would consider myself a data feed expert and that was really just all about Getting the right inputs into google in order to make google shopping You as effective as possible in your calling from the early time at my early time at C.

  1. C. My some of the mantras that I would have about how we want to invest the majority of our dollars into Google shopping and get really good data feeds and really control how much we're spending on Google brand search, which is a topic I want to, we're for sure going to get into and then, And then PMAX came around about two years ago now and really through through us for through the whole industry for a loop as to how we, how we think about Google ads and, and the distribution of it amongst the different advertising inventory that is available.

So yeah, that's a little bit of a, the preamble for Tony.

[00:03:10] Taylor: Yeah, that's great. So we've brought you in today because over the last week with the release of this month's DTC index, we have been publishing some data. Around the impact that we've seen on PMAX in the ad environment generally. And if you follow me on social, you've seen that I put out a bunch of tweets lately, basically saying that Google is killing itself with PMAX.

And I want to lay the groundwork for this and then have a dialogue about what that means we do in light of this reality. So a couple of things that are data points. From the DTC index over this past month. One is that Google's share of wallet from the e commerce industry. And this data comes out of Vero.

So this is, you know, almost 6 billion in spend, which for our industry is about the largest data set that you could get your hands on in terms of the amount of media spend for e commerce specific brands. Here's something we have seen since may of 2023 through. End of April of this year. So over the last year in may of 2023, Google represented about 25 percent share of wallet with meta at about 70 percent share of wallet. And then the ancillary channels sort of fighting over the scraps of about 5 percent since that time meta has now gone up to In April, 80%, and almost the entire share has come from Google, which was down to about 16% in a month. So if you think about $6 billion in revenue, let's do, let's do a quick, some quick math here. So if I have $6 billion, okay, and I divide it by 12, that's roughly $500 million a month. Right. 500 million a month losing 10 percent share of that is roughly 50 million a month or 600 million a year. Is that right? 10 percent of 6 billion. Yep. So that's a monumental shift in the allocation of dollars. Now at the same time, what has happened is that P max as a percentage of total dollars. On Google. So how much of the Google dollars that exist are on PMAX has gone from about 25 percent to almost 40%. So as the increase of PMAX. Has happened inside of Google, the overall share of wallet has gone down. And my experience of this is that it's because Pmax obfuscates the results in a way that makes it really hard to decide whether it's working or not. And the way we've seen this show up is in that a lot of the incrementality studies that we have seen come out of our Pmax. Partners show that both PMAX has a, or all, all PMAX structures, both branded and non branded. And we're going to talk more about the distinction. They're have a lower incrementality than both previous or standard shopping and meta products as an example. And so, because of that confusion, people are moving their dollars out of this channel. So Tony, can you share a little bit as that, why do you think this is occurring? This data, and again, to be clear, this is not CTCs data. We're going to talk about this distinction. This isn't the results of our customers.

This is the result of our industry. So why do you think that that's happening?

[00:06:30] Tony Chopp: Yeah, so I think so. I want to I want to talk about this thing this brand thing. Because I think it's, I think it's really important. So I, I want to grab some numbers this morning in preparation for our podcast. Just to sort of set the table on the scope of what this means, what this category is.

of searches mean for Google. So, pull some data out of our MCC across our agency. We've spent for approximately 42 million a year to date on Google ads for CTC clients. Out of that 42 million, 9. 4 million, or 22%, 22. 6 percent has been spent on campaigns that are labeled brand. Okay, so 22 percent of the total spend goes into into brand.

Now, if we were to extrapolate that into the larger Google ads ecosystem. So Google ads in 2023 reported. Alphabet reported 237 billion in revenue for 2023, pardon me, 307 billion in revenue for 2023. 237 of that is from the ad, ads product. So 77 percent of Google revenue or Alphabet's revenue is from ads.

So if we were to take, if we were to assume that CTC's data set is a proxy for the whole data set, That you could go and say that approximately 54 billion of Google ads, total revenue. Is from this stack of brand, right? It's a lot. And so when I think about why, why is the platform, why does it feel like they fight us on this particular component of the mixture?

The story I'm telling myself is the reason why is because it represents a big chunk of the total revenue for the total thing, right? So that's like one contextual thing for me in. And that I like have to wrestle with when I think about like as an advertiser, what I, what I know is I want to be able to drive the most positively incremental investment with my dollars possible.

Right. And I go, well, why does it, why doesn't Google help me with the tools to do that? And then I go to the other side of the coin, I go, well, it's because of this, this brand piece of the puzzle is such a large portion of the, of the total financial. Puzzle for Google ads. One, one more piece, just to break down that, that ads revenue 237 billion.

Let's break that down into chunks as well. Uh, So 175 billion of that. Or approximately 74 percent is coming from Google search. Okay. So the search results page that's search shopping, that's advertising revenue that comes directly out of out of shopping ads and search ads. The remaining 26%.

13 percent is on YouTube and another 13 percent is on a Google network. So GDP display advertising. So the other piece of this, so there's the whole brand piece of the puzzle. Then the other piece of the puzzle, and I believe the impetus behind the why behind P max is that the search results page has a finite amount of inventory.

There's only a certain amount of searches. Yes, it's a lot. But still there's only a certain amount of searches. And I believe if I'm, if I'm sitting at the top of the Google ads leadership team, I'm looking for ways to expand the available inventory into these other channels. And I think this is a big component of why the push for PMAX has been so strong.

So the whole, the whole conversation for me orbits around the elephant in the room of how big of a component brand search is for the Google ads business. And the other piece of the puzzle, which is Google the Google ads platform, continue to try to find ways to monetize they call them surfaces other than the search results page.


[00:10:33] Taylor: So this is 

[00:10:33] Tony Chopp: the picture? 

[00:10:35] Taylor: so I think, I think it's a brilliant breakdown that analyzes the incentive structures that we're dealing with. And I try my best to avoid tinfoil hatting this process to now just say that, well, metas are, I mean, Google is trying to intentionally force you into a thing without your conscious awareness of it. But I do think that the danger here is, this reminds me a little bit of like, you Did you ever hear the AOL statistic that like towards the end of AOL's era, that like a lot of the subscriptions were just like old people who didn't know how to cancel or had even potentially passed away where it was just like they were benefiting from lock in on an idea that no longer actually served the customer. And so like when I put out that tweet the other day talking about how I think one of the things that Google should do is ban competitive brand term bidding, people were like, It will never happen. And if that's true, if it becomes too big of a hurdle to actually act in the interest, the mutual benefit of your customers, I think that's when a business is really in trouble. Is when they've, they would have to take a step too far back in order to do the right thing. And so they begin to move into ways. So, so one, I think there's just this whole interesting thing about brand search being the ultimate tax on a product that I like that has maybe ever existed in human history, where it's just like, you used to have a thing that you controlled that you were in the right to show up first organically for. And now anybody is allowed to place themselves into that line of results. In a way that forces you to bid then organically on your own content. So I think that's, that's super interesting. And then the second thing you're describing, which is that the problem with search or let's specifically the search engines results page is that it's immensely finite. Even though there are Infinity terms, the core ones where value, where people want to compete for the attention are finite. And so what happens is in any auction based search environment where the inventory is fixed and then the supply of advertisers is not all of the profits tend to get competed down to nothing. Someone is willing to pay a little bit more and a little bit more and a little bit more. Pay, push out the payback period a little further and a little further and a little further and take up more and more of that real estate till eventually there's nobody making money on that page anymore. And that's, what's happened as our industry has matured is that a lot of these categories, jeans, t shirts, whatever, they all get competed down to nothing. And so the value capture there just sort of dissolves over time. So both of those are important dynamics to think about. In which Google now has to solve for creating a product that allows them to go further. So if those are the two constrained inventories, Tony search and brand, what are Google's unconstrained ad products where they have an interest in people pushing towards.

[00:13:27] Tony Chopp: Yeah, I mean, YouTube is the obvious one that they, you know, we've been watching them try to unlock it for a bunch of years now. And simultaneously, like, we've had a bunch of explorations into YouTube as well, which which have been challenging to measure, I think is the easiest way to easiest way to explain it.

And then the other piece of inventory that that I think PMAX goes into that as advertisers, we haven't been super excited about for the forever, which is the Google display network. And those are the 2 places where, where PMAX really expands into, but I want to circle back to something else that you said, which I think is.

The, the PMAX, the PMAX puzzle, when it goes into search ads one of the things that we see all the time from performance max in we got search terms reports out of performance max six months or so ago is that expansion into competitive terms. So it's one of the first places we'll see PMAX go into into quote unquote, non brand search on the flip side of that coin, one of the struggles we've been fighting against with a bunch of our advertisers who are in many ways potentially over reliant on brand search is the cost of that traffic increasing.

And it's a, it's a tricky puzzle. There's no doubt about it. And it's, and there are difficult conversations to have in our client partnerships when when we're faced with something like a question, like, why is my CPC on my brand search traffic rising so significantly year over year? Why am I not able to access the same level of return that I was in years past?

So it's, it's tricky, 

[00:15:04] Taylor: So, so I want to, I want to say this back cause this is a really important point. So you're saying that when people use P max. Draws them into competitive bidding

on other people's brand terms,

which has a secondary effect for that brand, which it drives up the CPC on their own terms. Because now there's more people competing against their space. So this is really potentially a vicious cycle where the increase of the utilization of PMAX increases because brands are no longer choosing all the terms that they bid on. They're giving Google more free reign. And this is an important, I think maybe just to set up. What is PMAX? PMAX is sort of Google's attempt at all placements where they just, you give them free reign of delivery against Any available search term, any available ad inventory that they deemed to achieve your business objective. So draw them into competitive search forces, the other brands that increase bid price on branded search decreases the value of brand search over time, right? Like that is a pattern we've seen play out in a number of spaces. And there's nothing that people hate more spending a bunch of money on their own branded search terms. But there's also the thing that they might only hate more is seeing a competitor show up first on their own brand term. And so therein lies the tension of choice. Do you accept the lower return, pay the tax, or do you cede the real estate to a competitor?

[00:16:27] Tony Chopp: Yeah, and I think we, we ask and answer those questions all the time and you know, at a performance agency with a bunch of resources and a bunch of knowledge, like, we, we try, we work to get as clear as possible about where we're allocating the dollars. And this is where P max becomes challenging. Right?

And I think this is probably it makes sense for, it makes sense for us to get into some of the tactics that we're using on the P max side to try to, to try to control for this. So for example, we'll have. Our, our most common tactic is to have two versions of PMAX. We'll have a brand versus a non brand PMAX campaign.

But we, we want explicitly, we want our brand search campaigns to cover the brand ecosystem so that we can be thoughtful and control the CPC as opposed to having PMAX just do all that work, but that's just us. That's just a a super in depth performance media agency. 

[00:17:27] Taylor: Well, So that,

[00:17:28] Tony Chopp: the 80 percent of the advertisers that turn on a Google ads account and fire up P max and let it rip.

[00:17:34] Taylor: that's right. That's right. So what you're getting to is okay. In light of this reality, where P max, and here's the thing I want to say that I actually, I'm going to assert some goodwill here towards Google's actual attempts is that My genuine belief is that the sequence of advertising, when you tell an ad algorithm to optimize for lowest cost of conversion would be obviously and logically consistent to move first through the highest intense signal that exists, which would be branded search. Remarketing all of those low hanging fruits would be the initial action point to drive the lowest cost for per conversion. And so in many ways it's, it's logically consistent and actually consistent with what you've asked the system to do for them to move through those things first. And oftentimes the reason people don't ever reach the next tranche of spend is because they stop and don't have the patience to allow that system to then prospect out further beyond that lowest hanging fruit. And that's, that's a problem that media buyers have generally. That is, it's a very, very difficult thing to predict, to understand. So in light of that, one of the things that we try to do and you're describing it, and this is maybe now how we can set up. Okay. How do we combat that is to try to isolate the stages of action, basically to say, okay, we're going to take all that branded search and we're going to make it its own isolated campaign that we control and lever against. And now we're going to use. Brand exclusions in the PMAX to try to focus beyond onto that next tranche, where we have a different target than we do with the brand search to try and separate them out and isolate that. Is that fair?

[00:19:21] Tony Chopp: Yeah, that's exactly right. Yeah. And I think that the important part of it is different targets for the different tactics, right? And 

also. And you mentioned, you touched on this earlier, but where, where our CDC's measurement philosophy is continuing to all this developing a deeper understanding of incrementality and and so the reason for different targets by different tactics has a connection back to the incrementality.


[00:19:49] Taylor: That's exactly right. And what we're seeing is that branded PMAX or is the lowest incremental action. So let's say, Okay. Well, you have an incrementality multiple of like 20%, meaning that 20 percent of the platform attributed revenue is incremental. I think you, you have a big customer right now that you just saw 14%, right?

It was the incremental brand. So, so what you're trying to say then is, well, in order to get to. My target, if my actual break even target is like two to one, well, you actually have to almost be like seven times that like 14 to one would be the actual incremental target. So it creates a different expectation of results for that campaign.

[00:20:26] Tony Chopp: yes, and I'm going to connect back to what you said about what advertisers hate, hate, they hate paying the Google tax on brand the most. The second thing they hate is seeing a competitor squeeze into that space. Right? Okay. So now here's, Now with this client that you mentioned that we're working on right now, where we have a good understanding of the incrementality of brand, which leads us to, so in this particular client brand CAC target is approximately 12 backing out of our incrementality non brand 97.

We'll go pay for that. Super, super incremental. We want all of that. In fact, we had We had a big buying moment recently around Mother's Day. This is a gifting brand where we actually saw we saw fantastic results from our non brand campaigns. CAC came in at like 60. We think we can spend maybe twice as much in Father's Day, maybe more.

We see a huge amount of opportunity there, but this brand search campaign that we're we need to hold it at about a 12 CAC to keep, to keep in line with the incrementality. You know, what pops out of that? About 80 percent search impression share, not 90, not a hundred, meaning we are giving up intentionally a certain amount of that real estate to competitors through, through either direct search campaigns or through PMAX campaigns that are just squeezing their way in.

We're doing it intentionally, and we're doing it on the back of an incrementality measure to say, like, it's actually not worth it for us to go and try to squeeze this extra 10 or 15 percent of the brand search available brand search impression share. That's a tricky conversation to have, but based on the math and how we arrive at the targets.

It's, it is the answer.

[00:22:07] Taylor: Well, and this is where I think people have to be really thoughtful about business strategy because it is the right answer for the short term financial reality. But if you are seeding. Positive incremental contribution margin to a competitor, there is an argument to be made that defending that real estate, even at a loss is beneficial.

And those are the really hard choices that I think businesses have to make in these scenarios and why there is no right answer to this problem. And so when people espouse publicly like, Oh, you just do XYZ, it's just, it misses the, Complexity of this from a pure business strategy and financial decision making standpoint.

So that's really hard. So I want to go to the next phase here, because we're talking about The distinction between brand versus not brand. But I would also say that we have seen different incrementality and therefore potentially different strategies designed around placement as well. So we talked about Google's desire to leverage their largest available inventory in the DSP around display network and YouTube. But how are we currently handling the value of those placements versus You're what you started this whole conversation with, which is shopping, which seems to be still the gold standard in terms of incremental impact is categorical brand search. How are we at CTC currently handling this? Are we isolating feed only PMAX brand exclusion?

Are we not, what is the best plan right now as it relates to how we're thinking about placements for PMAX.

[00:23:41] Tony Chopp: We are still doing feed only. It's getting, it's getting more and more challenging to execute in the platform. It's a, it's a place where I think the, the platform doesn't quote the platform as if it was a thing doesn't want us to do feed only. But we are continuing to find ways to, I guess, hack it would probably be the best way to say it, to get to a feed only shopping campaign.

The other thing that is so sort of interesting in the dialogue between us and our, our agency partners and what we're sort of hearing from Google a year or two ago the message was, Hey, throw everything into PMAX, consolidate, consolidate, consolidate. And actually we're, we're starting to have conversations and hear, hear things from them that that are more akin to the way things used to be, which is if having dedicated campaigns for all the inventory types.

So having dedicated campaigns for search, dedicated campaigns for display, dedicated, dedicated campaigns for YouTube, and I would say that. That remains our best practice that if we have an, if we have an intentional thing that we want to go after, we do that in a dedicated campaign as opposed to having everything smashed up together into one PMAX.

So I'll give you a, for example we, one of the things that I'm doing regularly across the accounts that I'm associated with is my non brand, our non brand PMAX campaigns. We'll mine the search terms report and when we spot good search terms in there that we want to go after We'll go and then build a non brand search campaign to specifically target that that group of traffic So it's almost like when we get our PMAX campaign set up In a way that we feel is the best in the current environment It's almost like thinking about them as a place to farm or source or potentially look for ideas that we can then go build in specific tactical campaigns in the Google ads account represented by a specific set of economic targets related to the funnel that we're going after, et cetera, et cetera.

I think the

best way to think about PMAX is like. Get it, get it, get it as sharp as possible. And then what you learn out of the P max, whether it's through search terms or audiences that pop up or whatever else, use that to deploy into specific campaign types.

[00:25:57] Taylor: yeah, and this is really good. I, and I think this is where these platforms fundamentally miss. Their strategic recommendations to e commerce in particular, which is that there's so much specificity as it relates to the marginal value of each unit, as well as the inventory position of each unit that has to go into being able to have eyes into both the target result, as well as the volume of results that you need to generate over time. And so one of the things right now, That I've seen is in terms of how deep you break out the types around optimization. So you're saying campaign types, this could be around an individual skew. This could

be around a category of skews.

This could be around. Right. Those are all three different ways that I would say how specific you get relates to how big your budget is, how many purchases are going to occur on that, how much search volume exists as the opportunity, because you don't want to be whittling these campaigns down to where you're getting two purchases per week.

It's going to be still really difficult to optimize around it, but you want to get to buckets ideally around an aggregate marginal result. Where you can have an idea of what the target efficiency outcome is for those campaign structures and where there's going to be enough volume to get through the recommended optimization phase.

Right? Like, so those are the things to consider in terms of the width of the account. But other than that, it is specific around feet only. What about the other setting that they've introduced? Yeah. That we are debating all the time is around NCA. So new customer acquisition. So this is a setting inside of PMAX that I struggle with this as well, because search in many ways, isn't exclusive to obviously just your just new customers. So how are we thinking about the utilization of when and where to use NCA? We've also seen this have a dramatic impact on incrementality and not always positively like in all every direction. So how are you thinking about when to use NCA and when not to?

[00:27:45] Tony Chopp: Okay. So first of all, let's talk about the weird thing about NCA structurally for how it's wired up. So the way, the way NCA works in the Google ads account is you add an arbitrary value to there's a setting to add an arbitrary value for new customer. Now the platform will give you a little bit of information based on AOB and what they think that arbitrary value should be.

But the point is you're adding an arbitrary value. So Let's say it's say it's 20. Now, what it does is it makes the conversion value reporting and Google ads weird, right? Okay. We'll use simple math. Let's say you sold something for a hundred dollars. And it was a new customer and you send a new customers worth 20.

Google ads is now going to report that as 120. So you've baked in conversion value that isn't actually part of that transaction. That's now we, that's weird. Look at your face. It's, it's super weird. Now, the way that we've manipulated this is we'll add a really small number. For the new customer acquisition value, like a dollar or something like that.

Sort of try to give a little signal, but not overly inflate the conversion value. So it's not the, the weirdness of it is the, the ability for it to inflate the conversion, the reported conversion value in a Google ads account is a watch out. And we've seen 

[00:29:09] Taylor: Now, is that, is that because they're using that value to inform optimization? And so the higher value is a signal to go after those kinds of people. Like what, what is the actual logic there in the algorithm in terms of why Matt is or why Google's doing it though?

[00:29:22] Tony Chopp: Yeah. I mean, I think all of their not all of their, like outside of the sort of, target CPA. So they're like they're CAC related bidding methodologies. They are value related. So there's maximized conversion value at target ROAS. So by, by saying this new customer associated with these audiences, X, Y, Z has a higher value.

It is tilting the scale of the algorithm. To attempt to find higher value customers for me, it's the thing that's problematic about it is adding like not real conversion value into the reporting. And that can mess with a bunch of measurement down the line. So it's something that we, the way that we do it at CTC, if we're going to set it up, is we'll use a really small value in there, like a dollar.

But still even still, like if you're having 20, 000 or 30, 000 conversions a month, You're, you're adding an arbitrary value in there. So I, I'm not like overall, I'm not as bullish on the functionality of NCA. I'm more excited about the olive branch that was, that they gave us about a year ago in April of 2023 for the brand exclusion lists and PMAX that, that was, that's more important to me than the NCA bidding from what I've seen.

[00:30:37] Taylor: Yeah, this is really interesting. I got off call today. With our meta rep, and he said that meta has a goal that currently 6 percent of the ad dollars are spent on value optimization. They have an internal goal to get that to 35 percent by the end of 2025, and that's going to include the release of new products. Around profit optimization, these things. And I, I feel like this is the shift that these platforms are going to make because of what the market is demanding from them. And so you're seeing Google, I feel like they're like going back on a lot of their initial setup to undo it all to go back to, okay, we hear you, we see it, but that's just sort of my way of setting up.

Like, what do you think happens from here? Where does this go in terms of what is Google going to do about this?

[00:31:27] Tony Chopp: Well, so I'm, I'm going up to their annual summit Google marketing live tomorrow, where they talk about all their new ad ad products. And I'm assuming this podcast isn't going to be released for a couple of days, so I'm going to talk about some of the stuff that we expect to see. I think they're ahead of the game.

I know they're ahead of the game on bid for profit. So it's, it's going, we've been in a handful of betas for a couple of accounts. And it's going to be part of the conversation for Google Marketing Live tomorrow. It's something that they're really excited about and releasing. And I think this is where, like, as an e commerce advertiser that's really close to this product, I think this is where Google has the advantage and where our, our alignment as an e commerce agency.

Can be greater than ever before with the Google ads platform using as they mature into a bidding type that's bid for profit and built on top of the fact that so much of the advertising is driven off of data feeds in our ability to submit cost of goods or profit related data through the feed.

I, let me just say this, Taylor. This is the future. The future that I believe is right around the corner for us. A PMAX campaign clean as a whistle. So non brand we're super confident in it. The Google ads account has a lot of shape to it in its structure outside of P max. So our brand campaigns are really tight.

Our non brand search campaigns are really tight. Everything's really tight. P max non brand, super clean bid for profit. And we go in there and we, when we look at the data, we say, Hey, this thing's got a, there's no holes. We can poke in it. Right? It's clean. It's non brand. And it's. And it's creating a margin outcome at the product level that is at or above what we see from our advertising on Metta, our new customer advertising on Metta.

We're going to shovel money at that campaign. We're going to shovel money at it all the way up to the absolute limit of diminishing returns. And I think this is where, this is where to me, Google has Google has for me, and in my worldview is as an e commerce advertiser. So it's like, I, their platform is much bigger than what, what I, what we care about.

Right. But for me, I envision this world where I'm, I have this really high level of confidence that this campaign is positively incremental that I understand the economics of it and that I can see that information, the platform. And not only can I see that information platform, but more important for me than for me to see it is for the machine learning algorithm, the bidding algorithm to be operating, making decisions off of profit.

Holy good. Oh my goodness. Am I going to shovel money at those campaigns?

[00:34:19] Taylor: And this is exactly, this is where the, I'm going to read a message I got from a GM and operator at one of the largest U S private equity firms. About this exact topic. He sent me a message. He says, this is a message to say, thank you for your podcast and content. They've been a daily friend for the past eight months.

While I worked on one of the largest U S private equity companies, managing DTC brands and e commerce GM businesses operationally and globally. I worked with finance and marketing to implement what we call crow ass contribution margin return on ad spend measured on a weekly and progressively daily basis.

The critical component was aligning finance to provide feeds for product slash order level COGS data, shipping and fulfillment and across border taxes, tear down to get a cash return on the spend we could optimize for long story short, stumbling across your podcast gave me the confidence that I was onto the right thing and to push for change.

Thank you. This is what's happening and where the world is going inside of every major organization is that people want to understand how much money they're making on their ads at a unit level, at a margin level, and then the game is not to optimize for revenue anymore. And so this is where it's all headed.

And I think that in the meantime, we still. As media buyers and operators and agency owners or brand op, like have a responsibility to understand and hold for ourselves, the business objective that we are there to drive and to mangle and wrangle these products into serving it. So Tony, any last thoughts you'll leave people with as they head out to try and wrangle the AI.

[00:35:54] Tony Chopp: Yeah. I mean, I think, you know, there's a couple other tools that we're exploring and partnerships that we're exploring around the incrementality of brand and when to show an ad and when not to show an ad give us a call if you want to learn, learn more about those ideas, but we're, we're like, you know, Taylor every dollar every day producing cash, I think to your point 

about like the way the game has changed, like, Everything that we talk about is not about it's about how we produce cash today, 

From this media spend that happens.

So, and I think the only other thing I'm going to add is. All of the investment in the ad platforms, both meta and Google is going into these new products. All, all of their resources, all of medicine the vast majority of medicine, investment and engineering is going into advantage plus the vast majority of Google's investment in engineering is going performance vaccine.

And these tools are going to be a really important part of our portfolio. They are now, and they will continue to be in the future. So it's not like. I'm not going to get up here and say, Hey, listen, we're going back to standard shopping, right? We got to figure out how to, we got to continue to figure out how to align ourselves, direction with the platform and with the platforms.

And at the same time, make sure that we're representing how do we generate cash today for, for our customers? So I think using brand exclusions on PMAX, making sure, making sure that it's as clean as it possibly can be, making sure you have your account built out robustly. You don't want just one PMAX campaign in there.

And then come talk to us about this bid for profit stuff. Cause we're, we're part of some early betas or go investigate it on the internet yourself and I think you'll be in good shape.

[00:37:30] Taylor: Thank you all for tuning in. Appreciate the time. See you next time on the commerce playbook podcast. Thanks Tony.

[00:37:36] Tony Chopp: Thanks.