The Math Behind Creative Hits (With Real Spend Data)

[00:00:00] Adrianne: All right. Hello, and welcome to this episode of the CTC Canon, where today we're gonna dive deeper into the CTC Canon as it relates to creative strategy. And really, this is our methodology for turning creative production, which can be this very ambiguous confusing, and frustrating kind of avenue of paid media into a much more predictable data-driven system that fuels efficient scale.

[00:00:25] What I hope to provide today is actually freedom. I think too many advta- advertisers really see creative production as this this beast that they just can't really get ahold of. They're constantly changing production partners. They're constantly changing their internal strategy. They're they're-- it feels, it feels to them like this beast that really can't be handled.

[00:00:51] And what our canon really provides and has provided our clients and our our own production system is the freedom to just understand that we have no idea what is going to perform, and therefore pr- a, therefore, a- Therefore, a predictable system actually outweighs any level of, quote-unquote, "creative strategy" that you could ever inject into your ad account.

[00:01:20] And, and really your ad account Meta being obviously the one that we're primarily spending on as advertisers should be this flywheel of production, not this, this channel that we over-resource against and overthink. Because that's where we get stuck as advertisers, is overthinking something that really we have no business outsmarting.

[00:01:43] And so, as I go through these numbers and, and this methodology, I hope that it provides freedom and really peels back a lot of the layers of confusion. So to arrive here, we analyzed five hundred and four stores across our Statlas data set of clients, which aggregate- aggregated into about three point three five billion in Meta ad spend on seven-day click attribution over the last three hundred and sixty-five days.

[00:02:11] Now what's also really interesting is I'm gonna include data in here from Meta and from Motion that solidify and validate this methodology. It's not just a CTC methodology that is siloed in our own thought universe. This is fully backed by the same patterns and the same data that Meta and Motion are, are seeing and producing w- in their own articles.

[00:02:35] So, really there's two parts to this philosophy and two parts that should go into every ad plan. So we think of an ad plan as the number of ads that you need for any given month. So that's part one, quantifying how many that ads that really is against your spend target. And then part two, determining how to allocate those ads across calendar moments, evergreen moments core products, creative types, so the format, whether it be branded videos, branded statics, or UGC videos or UGC statics, and then the producers.

[00:03:09] So getting very clear on the allocation of the number of ads needed against the spend target. Now, what we need to understand, and if, if this isn't clear this, this, this is central to this philosophy, and we cannot drill into any other part of the philosophy unless you agree or understand this core premise.

[00:03:33] Ad creative is a hits business, right? Just like music or movies or, or gambling, if you will, right? This is this- The idea that a small number of ads drive a very disproportionate share of all your results is something you have to believe in if you're gonna be an effective meta advertiser. Volume is the lever that is bending probability in the favor of the brands that are doing this.

[00:04:01] For the brands that are not doing this, it is bending the probability outside of your favor, right? So what's true across our Statlas dataset in the last three hundred and sixty-five days is that only seventy-four percent of ads got any spend at all. Twenty-three point eight, let's call it twenty-four percent, ever cleared a hundred dollars in spend.

[00:04:24] Very little. I mean, if you're working with an AOV above a hundred dollars, you're likely not even getting a purchase in that window, right? And then seven point two percent became real contributors, meaning they spent one K or more. And then one point eight percent became significant performers, meaning they spent five K or more.

[00:04:45] And then point nine percent became whales, right? Whales being those are the ads that drove a disproportionate share of all resort-- of all results So the raw hit rate you can call it and just simplify this from creation, ad creation to a whale is roughly one in a hundred. Now, let that free you from the idea that a disproportionate amount of creative strategy needs to go into producing a hundred ads.

[00:05:15] Because if one in a hundred is beco- is going to become a whale, who are you to predict which one of those hundred is going to perform? It's not about making better ads. In fact, the term better ad is so subjective to the person sitting in the seat of approval or creation. This is all about making enough ads where-- to where the math starts working in your favor, right?

[00:05:46] And so scrolling down here you can see the same pattern on Motion's twenty-twenty-six creative benchmark article that they put out. They, they measured five hundred and fifty thousand ads and one point three billion in meta ad spend from six thousand advertisers for this study, and Motion found that only five percent of ads became real winners.

[00:06:09] So roughly half received minimal or zero spend, and hit rate only increases with volume. So top advertisers ship twelve to nineteen plus new evergreen creatives per week and achieve hit rates more than double those of smaller accounts. So, so Motion's data validates and supports the data across our Statlas stores and, you can just take that part out. Okay. All right, cool. So if you understand and, okay. If you understand and are prepared to resource your team or your production partners against this idea of hit rate being one in 100, then what the ne-- then the next step to effective creative production for Meta is understanding the creative demand formula. So this is how we take a advertiser's monthly spend target and tell them exactly how many ads they need to make for the upcoming month against that spend target.

[00:07:08] You can do this if you have a yearly forecast, you could do this for the whole year and be set and understand, "Okay, in January, I need to make 20 ads. In February, I need to make 30 ads. March is peak season. We're launching this product. Production's gonna go up by X amount because we're gonna be spending X amount more."

[00:07:24] Right? So you're able to look ahead and plan ahead on production well into the future if you have an accurate forecast that you're that you're budgeting against. So the creative demand formula is is your target spend minus your current spend times your carry rate, I'm gonna go into each of these in a moment, divided by your expected spend per new ad.

[00:07:46] So, that will give you the number of new ads needed against the spend forecast that you have set for any given month so let me go over the definitions of these because they're very important. So your current spend is the estimated end-of-month spend. So how are we... You know, it's July twenty-seventh where are we going to land the month of July?

[00:08:07] That's your current spend. It's the month-to-date spend plus the Statlas calendar projection. Another fallback if you don't have this is just to take your month-to-date spend plus your daily run rate, adjusted for the day of week pacing and any planned moment spikes that you have. Your carry rate is your computed carry rate per ad, and then it's aggregated.

[00:08:28] So for every brand in your trailing sixty-day active inventory we measure whether it survives into the next month or not and how much of its spend it actually retains. So you're really measuring how many of these ads can live past this month, and that's your carry rate. And we're able to measure that directly with the ad-level data in Statlas in the Facebook overview report.

[00:08:52] And then expected dollar divided by new ad. So how much spend could you count on for every new ad that you launch? We measure the spend it absorbed in its first month. So the brand-level expected dollar per new ad is the average of those per ad outcomes distributed across whale, winner, testing, and then dust tiers.

[00:09:12] So then this formula tells you, tells you the gap between where your existing creative will land and where you need to be, and then divides that gap by the productivity of each new ad you introduce. And so what's really important is to really understand more about our carry rate by account relative tier.

[00:09:32] So but this is essentially the survival percent-- So this is essentially the survival percentage versus the spend retention percent, percentage. And these are tiers defined relative to each account's own mean. So basically, whales have a survival rate of eighty-two percent and they have a spend retention rate of seventy percent.

[00:09:56] Similarly, wha- winners have a survival rate of seventy-one percent, and then winners have a spend retention rate of ninety percent. So you're not-- The point of this is for you to understand that we're not treating every ad as equal carry rate. We understand that whales behave differently than winners, behave differently than testing, and re- and behave differently than dust, right?

[00:10:19] And so those are being factored into the ad plan for the upcoming month. I mean, you can see-- I, I know obviously accounts where whales are active for years on end. These are being factored in to a part of the spend plan because we can count on them. We can count on them, we can count on them taking a certain predicted percentage of the upcoming month's ad spend.

[00:10:42] So really, the net effect of this is that roughly seventy to seventy-five percent of your current spend carries forward on its own, and then the other twenty-five to thirty percent must come from new creative that you introduce, right? So brands that actively push budgets on existing winners can carry eighty-five to a hundred percent or more of prior spend forward.

[00:11:05] But the actual observed range is sixty-five to t- sixty-five percent to a hundred and twenty-two percent, with the highest carry rates belonging to brands that scale budgets on proven performers before reaching for new production. Actually, you can just take that whole part out that I just talked about because that's not the most helpful.

[00:11:23] Okay. Plus, I just read it. Of all new ads spend Okay, so a little bit more about what the data says about expected spend per ad and why this matters when we're calculating your carry rate. So we know that whales are only going to be about one percent of the share of the new ads you produce. If you make a hundred new ads, one of those might be a whale.

[00:11:46] However, they'll be forty-one percent of the all-new ad spend, okay? So the number of ads is just dis-- is totally disproportionate to the actual percent of ad spend that they claim in the ad account. Same with winners. Five out of a hundred you might find five out of a hundred ads are winners, yet those winners will take thirty-four percent of all new ad spend in the ad account.

[00:12:10] So that's factored into your carry rate as well. Okay. So, carry rate just to close out this section, carry rate is how we calculate your number of new ads needed against an upcoming spend target. And then what's really important to understand is the creative score metrics that go into evaluating the health of any given ad account.

[00:12:35] So there's five metrics, each mapped to a specific variable in the math and three metrics specifically drive carry rate. So you could be a brand that is on benchmark for carry rate, meaning seventy-five percent or more of your existing ad foundation are going to carry into the next month. That's a healthy carry rate.

[00:12:57] You could also be a brand that is experiencing a thirty percent carry rate. Because your creative score metrics are extremely low, your creative health is poor, and therefore your carry rate is also poor. So the three metrics driving carry rate are your evergreen share. So this is the percentage of ads running consistently for more than thirty days.

[00:13:19] Your spend degradation, this is your average week-over-week spend change after the ad launches. So does the ad improve in spend and efficiency and volume, or does the ad degrade in spend over time after it's launched, and how quickly that happens? And then your ad concentration. The-- So the percent of total spend sitting in the top five ads.

[00:13:42] The higher this is, obviously the more risk is introduced, right? So if a very, very high percentage of your total spend is sitting in your top five ads, that introduces more risk that your account could quickly degrade if one thing were to happen to one of those ads. A product goes out of stock, the ad the ad, A product goes out of stock, you lose rights maybe to that creator's handle.

[00:14:09] Someone on your team says that you have to retire that ad for so and so reason, right? So, hold on one second.

[00:14:37] Okay. So, we've covered three of the five creative s- score metrics, and I'm just gonna go over really quickly exactly how each of these impact carry rate. So your evergreen share directly measures the survival rate. So an ad running thirty days is by definition an ad that survived, which means the higher evergreen share you have, the higher carry rate you have, which means a smaller gap for new creative production to fill.

[00:15:03] Spend degradation measures your spend retention, so how much of a surviving ad spend holds up as it ages. So a brand showing thirty-nine percent spend degradation has surviving ads bleeding almost forty percent of their spend every week. Therefore, their carry rate is going to be very low a- and because their spend degradation is very is very high, right?

[00:15:25] And then ad concentration deter- determines your spend mix. So whale heavy accounts carry at fifty-nine percent benchmark tier, while mid-tier distributed, distributed ad accounts carry at a sixty-four to ninety-two percent tier. So high concentration means your carry rate is hostage to a handful of ads.

[00:15:44] And then low concentration, which means low concentration means your carry rate is a lot more resilient. So then there's two metrics that are going to drive the expected spend per new ad that you launch. You have your zero revenue rate, which is the percent of ads generating zero revenue in the period, and then you have your ROAS degradation, which is the average week-over-week efficiency change after launch.

[00:16:09] So zero revenue rate is by far the most direct predictor of how efficiently new creative converts into spend. For example, a brand that a brand at thirty percent produces creative that algorithm wants to distribute, and then a brand at sixty-five percent needs two to three times more ads to fill the same spend gap.

[00:16:28] So the higher your zero revenue rate is, the higher your production necessity is gonna be because the worse your carry rate is. Or sorry, the the lower your expected spend per new ad is and then ROAS degradation really modifies the expected value of new creative over time. So a brand with five percent ROAS degradation has winners that stay efficient as they age and they can really carry forward into future inventory and performance.

[00:16:57] Whereas a brand with a very high ROAS degradation is going to need an outsized amount of ads and because they have a low creative health score. So the creative score really makes the difference between accounts super drastic. You could see-- you could have a brand spending two hundred K a month on Meta with a really great aggregate creative score, needing, only needing forty ads, forty new ads a month.

[00:17:24] And then you could have a different brand also spending two hundred K a month on Meta with a really poor creative score, and they need two hundred ads a month in order to find winners. So, that said, there are essentially this looks wrong, Corey. It says the three levers, but there's only two.

[00:17:49] Oh, lever... Hold on one-- Sorry, one second. The three levers. Mine historical winners make better ads. Oh, no, no. The th- the... I'll call this the third lever, the catalog lever

[00:18:03] Okay. So, so we've talked about hit rate, we've talked about understanding your carry rate, and we've talked about understanding your creative score and how that impacts the number of ads you need against a spend forecast. Now, there's three-- there's only three levers that can impact the actual performance of your ad account.

[00:18:23] And so continuously pulling on these three levers in a systematic way that gives you the number of new ads that you need every month is how you how you win. How you honestly compete against all the other brands that are doing this better than you. So lever one, mining historical winners, winners.

[00:18:42] So this is the work you should be doing before asking for or producing anything new. Revive last year's top performers, revive the last thirty days' top performers, reenable paused winners, launch existing creative to new landing pages. I promise you there's gold in there that people just sit on, and they always think it has to be about new ads.

[00:19:01] Lever two, make better ads, not just more ads. So, Hold on one second. Let me think

[00:19:17] Okay, number two is make better ads, not just more ads. So volume's sake pr-production just for volume's sake is gonna get you nowhere. That's really the first layer to understanding and committing to the process. But, but the second layer to that is understanding how to make better ads and what for.

[00:19:35] So we think of this at CTC as product, persona, pain point, and then where's the ad going, the URL. So the combination of those four inputs should imp- should create ads that are actually going to fuel the right products in the right places. So I'll say that again. It's product, persona, pain point, and then URL.

[00:19:54] So what product are you making the ad for? Who are you talking to? What is the pain point that you're addressing? And then where is the ad going? If those four inputs can create a diverse set of ads across formats, so videos and statics, and also across IDs, actual entity ID in the ad account, you're gonna be in a really good spot as it relates to quality and not just volume.

[00:20:18] The third layer. So, the third layer and lever is the catalog layer. Catalogs... Catalog ads are so overlooked across so many brands. And the truth about them is, is that they run on different math than other ad types, and they run on a different cadence. And they need to be carved out before the formula applies.

[00:20:38] So when we're, when we're creating an ad plan for a CTC client, we're taking out the catalog layer from production. Those should not be included in the number of net new ad units that you need for an upcoming month. These are just inventory, right? So every other section of this canon treats an ad as an actual creative identity, whereas catalog ads typically, especially with high SKU count brands, are routinely the highest ROAS line item in an ad account and routinely the, the most under-discussed in creative ad planning because they don't actually get briefed, designed, or tagged the way that other creative ads do.

[00:21:16] They just get configured, right? So twelve percent. Hold on one second

[00:21:41] Our catalog shared queries by archetype

[00:21:56] All right. I'm just gonna go into this part 'cause I don't really understand that part

[00:22:20] Okay. So, so catalog ads we know inherently have different math than other ad types. And that's for two reasons really. Number one is creative identity. So, mm, no, that's not what I wanted to say. Compliance, ad frequency, 17, get replaced, production

[00:22:43] Okay. So catalog ads inherently have different math than all other ad types. And what we just talked about, the creative demand formula and all the metrics associated with it are about ads that have creative identi-identities that fatigue, get replaced, and need monthly production to actually fuel them, right?

[00:23:00] Whereas catalog ads invert all three of these assumptions. They persist, they recombine, and they compound very fast. The carry rate of catalog ads is effectively a hundred percent across any aggregate data, data that you look at, as long as the feed and the product sets persist. So the unit is the product set plus the dynamic overlay configuration.

[00:23:21] And there's so many ways to take your catalog ads and actually enhance them for potentially better, better performance. And recently, Meta's done a lot of studies on these about dynamic dynamic catalog video ads, for example or even just simple, you know, sticker or motion overlays on your catalog feed.

[00:23:39] A lot of things you can just do with AI or through AI partners. But what's really important is to always carve out your catalog spend. So what we do we exclude that from the creative demand calculation. It's tracked as a separate line, and the formula computes how many creative ads any brand needs exclusive of the catalog layer

[00:24:01] Many, many advertisers have looked at the catalog layer as a long tail retention layer historically, which is great for, you know, it still is very, very true. It serves your lapsed customer files, your site visitor files, abandoned cart, you know, what other folks might call middle of funnel or bottom of funnel audiences.

[00:24:20] However, it's under leveraged as an acquisition en-engine. So broad audience, DABA, and Advantage Plus with catalog specifically with broad audience-- Or one second

[00:24:48] However, catalog ads are really, really under leveraged as an acquisition lever, and the brands that are figuring out how to do strategically use it as an acquisition engine are, are winning right now. So that's running your acq- your-- So that's running your catalog ads with broad audience DABA and Advantage+ with catalog across your whole, whole portfolio and being strategic about those product sets and those specific catalogs that you're running

[00:25:20] Okay, this is just so much about catalog. Blah, blah, blah, blah. Do you want me to talk about this?

[00:25:29] To close it out. Yes. Yes, I do. The creative audit. No, I think I'll close it out with this, but I just... I've never seen this part before. Sorry, I know you sent it to me before. I just was, like, in back to backs. The audit is the work we do on a brand's own data.

[00:25:48] Where does this account stand today? What's the spend target? What does the marketing calendar look like? What products matter, and what's already in the account? Jordan

[00:26:01] Part two approvable rather than assumed

[00:26:09] I'm not gonna go through that. I don't really know what we're saying there or asking for. The allocation system From volume to plan, the creative demand model gives you a number. The allocation system tells you where to aim it. For every ad you produce, you must answer four questions in sequence. How you answer each one matters

[00:26:37] Moments versus evergreen marketing calendar. Oh my goodness. Product allocation

[00:26:46] Holy shit, this

[00:26:53] is long. Open spectrum gets to file, producer allocation, unified workflow. Okay, I like this. I'll close it. Building this as a skill

[00:27:09] Okay. So now that we have a very clear idea of why hit rate matters, how our carry rate informs the number of ads we should be producing, how our creative health score impacts our respective carry rate it all comes back to the unified workflow that put these pieces together. So the creative demand system ties everything into a single operating commitment really, that all of the best meta advertisers are subscribing to.

[00:27:43] So it's really just five steps and then committing to that on a monthly basis for both your evergreen production and your moment-based production. So number one is total demand. Running the creative demand formula with your sixty-day carry rate and expected dollar per ad from the audit.

[00:28:01] Moments versus evergreen. So score the historical calendar through promo and LTV. Back-calculate ad counts from expected incremental spend and protect your evergreen foundation. So no-- do not over-index on moment production and neglect your evergreen pipeline. Number three, products. Pr- moments follow the moment.

[00:28:19] So evergreen, use your product matrix, role assignment and weighted distribution across the products that matter most. And then angles and treatmet- treatments. So format split from motion. Write the month's angles and multiply across the brand's treatments meaning what should our video production look like?

[00:28:37] What should our static production look like? What should our UGC production look like? And then ultimately at the, at the very bottom layer of this workflow is assigning these things to producers. So who is producing this number of moment ads this month? Who's producing this number of evergreen ads this month?

[00:28:54] And getting really clear on who's making what. Get those into the pipeline and get them into the ad account on a regular basis. Don't let over resourcing against approvals or, don't-- Sorry, take that part out. Don't fall trap to the idea that over analyzing or over-strategizing a single ad is going to get you the outcome you need. Rather just commit to the system, get the ads in the ad account, and you will find the winners because the math is in your favor.

[00:29:28] Okay, that's it