5 Questions That Drive 80% of Your Growth

[00:00:00] Luke: So how we'll talk about the profit engine and the system here at CTC many times is in relation to. The different roles or functions or the people, right, that, that we're sort of stepping into. But I think it's a helpful sort of framing to think about, okay, what are, what are the key problems and the key questions, the key discussions and conversations that that this steps into that the system helps to, helps to answer.

[00:00:24] And so, how I would think about this is there's, from our perspective, there's five questions. That account for 80% of the time and the work that your marketing growth sort of team and workflow are currently accounting for, that it's all sort of downstream from these five questions and the way that.

[00:00:48] Different brands are answering these questions and the frameworks and the tool and tools and the software and the team structures and everything that I have in place in order to affect the answers and the outcomes of these five questions is all over the place. 

[00:01:01] Richard 1: Hey folks. Welcome to the E-Commerce Playbook Podcast. I'm your host, Richard Gaffen, director of Digital Product Strategy here at Common Thread Collective, and I'm joined yet again by our VP of E-Commerce strategy here at Common Thread. Mr. Luke Austin, the weatherman himself joining us live in the podcast studio in beautiful coast of Music, California.

[00:01:19] Luke, what's going on, man?

[00:01:21] Luke: Oh, the week is off to a pretty good start. I would say relative, I had a. The end of last week was a real, it's like one of those movies where it's just like every scene, it just keeps getting like worse for the, for the person. Like just great, great day on Friday, it was my birthday. Going home a little early after some work and workout. Just, I'm like five minutes from home and this guy just rolls into me at the stoplight, rear ends. Me just looking down his phone, just boom and just so like, okay, a bummer. Get home. My kids have been sick for a couple days doing, you know, had the works of what's, whatever's going around the recent virus.

[00:02:00] And so like an hour later it was like immediate just on the couch. Fever the whole, you know, the whole thing. So it was just like, it was like a weekend of looking at the, the dent in the back of the car while favoring, while the kids are barfing in their beds. It's like, alright, hey, let's, let's try next week.

[00:02:19] Let's, let's get next, next week going. So, it's off, off to a more positive trajectory.

[00:02:25] Richard: I'm glad to hear that everything's, seems like it's turning around for you. I definitely like when 

[00:02:30] it rains, it pours for sure. So whenever, if something like that happened, like I got, I dunno bumped into at a stop sign, I'd immediately start looking out for am I gonna get sick? You know, all that type of stuff.

[00:02:39] But, alright. Well today our topic of conversation is as it has been for a while now, our profit engine system. And what we wanna do is take like kind of a different angle on this, which is to talk about it through the lens of the questions that it answers. So, Luke kind of has prepared for us, I guess you could say like five key questions that every brand essentially has to ask themselves on a day to day or week to week basis.

[00:03:05] Those questions, I think, are answered in a unique. And I, I hazard to say, better way by our profit engine system. And so, Luke's gonna kind of walk us through that. So Luke, why don't you set this up for us? What are those questions? Kind of what are the context in which it's, those questions are asked now, and how does the profit engine kind of step into that?

[00:03:23] Luke: So how we'll talk about the profit engine and the system here at CTC many times is in relation to. The different roles or functions or the people, right, that, that we're sort of stepping into. But I think it's a helpful sort of framing to think about, okay, what are, what are the key problems and the key questions, the key discussions and conversations that that this steps into that the system helps to, helps to answer.

[00:03:48] And so, how I would think about this is there's, from our perspective, there's five questions. That account for 80% of the time and the work that your marketing growth sort of team and workflow are currently accounting for, that it's all sort of downstream from these five questions and the way that.

[00:04:12] Different brands are answering these questions and the frameworks and the tool and tools and the software and the team structures and everything that I have in place in order to affect the answers and the outcomes of these five questions is all over the place. Like there, there's just a wide level of variance as it relates to how direct to consumer brands answer these five questions that for every brand, these five questions account for a large portion of what the direction and the resourcing and the time orients around.

[00:04:38] Okay? So. That's sort of a lens at which we can, we can look at it. And so I'll, I'll kinda share them high level and we can go one by one and, and dig more into it. But the five questions sort of in this sequential order are one, what should my forecast be and what, what does each channel need to deliver in order to achieve that outcome?

[00:04:58] Budget allocation, what is the optimal spend allocation across channels to, to be able to hit that forecast? Then what creative output and production plan is necessary to be able to fuel that media allocation that was just said, and then what is the right full funnel meta strategy and daily optimization. Plan in order to achieve that outcome. And finally, what's the gap versus our forecast and what are the specific actions that we're taking to close it today? So this sort of progression of what should my forecast be? What's the right budget allocation across channels? What is the creative output and production plan?

[00:05:35] What is the right full funnel? Meta, meta strategy and daily optimization? And then on a day-to-day basis, what's the gap against that forecast and what are the specific actions necessary needed to to bridge, to bridge that gap? Imagine for those of you listening, all of these questions hit to some extent, and you can probably think, think back to earlier today where you were having some conversation or some decisions were needed to be made in relation to one or all five of these questions and that, and that is the case for direct consumer.

[00:06:03] E-commerce brands, particularly in this in this revenue range, 10 to a hundred million plus is like, these five questions are gonna encompass a lot of the, the, the thought and the decision making and the team resourcing and the tools, et cetera that you deploy in order to achieve the outcomes that you're aiming for.

[00:06:19] Richard: Yeah, so let's talk about how, how these questions are usually answered at this point. Not in terms of of course, what the exact answer is, but like what's the method that the average brand that comes to us, let's say before onboarding to our system, how are they answering these questions?

[00:06:36] Luke: So starting, starting with the first, which is under this umbrella of forecasting, what should my forecast be and what does each channel need need to deliver to be able to enable that outcome? The question of what are there, there are probably a hundred different ways we could and have seen these questions being answered in, in different brands, which like state the obvious, which is why we've created the system.

[00:07:00] We have to be able to like understand. The different ways different brands are doing this and be able to identify what works well and what doesn't, and sort of piece that together into the, into the optimal thing. But as it relates to the forecasting, I'll give like a couple examples for each of these.

[00:07:11] 'cause we could, again, we could give a hundred examples of how brands are doing them, but the ones that we'll see most commonly as it relates to forecasting first is you'll have it's very common that the forecast lives within a separate function than your marketing team. So the forecasting process lives with under the umbrella of the finance organization or, or something separate to the marketing team.

[00:07:38] Right. And how you'll see this come about is. The forecast most times will look like a spreadsheet or an Excel doc or or maybe it's a, it's a cool tool that's been created in, in a, in a, in a software solution, et cetera. But it orients around it orients around metrics that live outside of the context of.

[00:08:00] The marketing activities that the team is taking on a day basis. So this is the most, the most common thing that we'll see, right, whatever sort of in format it lives in is see a bunch of numbers in a, in a, in a sheet that ladder up to some forecast using some methodology and, we'll, there's like a million different ways of how all the methodologies come together, but like the key point is lives outside the context of the marketing.

[00:08:23] Activities, the marketing calendar, the email send plan, the actions that are gonna be taken on the media channels. The new creative that's going to be launched, it's actually gonna fuel the media spend. It's just completely disconnected, right? It said numbers in a sheet. So why? Why is that a problem? Two main reasons.

[00:08:38] One. Is the folks that are responsible for the day-to-day actions to be able to drive the outcome are completely disconnected from the planning process, right? So you don't have, you don't have buy-in at the level of someone that's, that, that's owning the outcome, right? They, they're being handed it a forecasting and not building through the actions that are gonna be taken.

[00:08:58] And that's and that's problematic for I think obvious, obvious reasons. When that disconnect. When that disconnect hap happens. And then. The, the other thing it leads to is whatever the forecasting methodology and inputs are whether it be traffic conversionary, a OV split by day with some seasonal year, year effect, right?

[00:09:18] Or new customer revenue, returning customer revenue a OV, and then orders by each by day. Spend against ACOs or add to sales or MER by day, which backs into your revenue, right? Like, those are just like three different sort of high level ways that it could be done, whatever, whatever that mode is.

[00:09:38] What it leads to is a forecast expectation that's disconnected from the marketing actions. And then when you're off track of forecast, what it leads to is, okay, we're not hitting the revenue number, so. What's necessary is to alter one of the metrics that's being used as an input, and let's say it's a visitor's conversion rate, a OV.

[00:09:58] Okay, so conversion rate and a OV are holding, but we're, we relied on visitors so that that's why we're missing revenue. Let's go drive visitors. Well, you can't drive visitors in isolation, right? Because if you're looking for like run a traffic campaign, you get a bunch of visitors, low conversion rate, no one's actually gonna do that.

[00:10:15] But what what happens is, like visitors in conversion rate and a OV, they all, they're all interconnected in this way that like you don't have a. Increased visitors lever. Lever, right? Like you have a send another email campaign lever, you have a build more creative into the meta ad account and deploy more budget.

[00:10:31] Like those are the actual levers. And so you're trying to translate between the metrics that are in the sheet that are disconnected from the marketing actions. And what could end up happening is like you drove more visitors or you improved your add to sales ratio because that was where the gap was, but you didn't actually hit your forecast outcome, right?

[00:10:49] Those were just like the they weren't built around the marketing actions, right? So the, in this first bucket of what should my forecast be, what does each channel need to deliver to be able to get us to that outcome? Those, those are some of the most common things we'll see, which is that the finance and the marketing functions live completely separate.

[00:11:07] And then it leads to the actions we're taking on a day-to-day basis, being subservient to whatever individual metrics live in isolation in this forecasting sheet that aren't actually connected to the actions. 

[00:11:18] Richard: All right, that makes sense. So the, the forecasting, like you're saying, sorry, the forecasting is already disconnected from the marketing actions. And then even then, the set of KPIs that the marketing team is judged by, that sort of forms the middle layer, maybe that communication substrate between the CFO and the marketing team.

[00:11:36] Those are also vague and don't actually guide you towards anything that's, or don't actually guide you towards anything that's going to have a meaningful impact on your goals. So. If that's sort of, obviously there's a particular solve for, have we? We have with that, but I think it would be more interesting to, let's keep going down this kind of road of, like for our second question, how is that, how does that play out?

[00:11:58] Luke: Okay, so second question, which is under the budget allocation. Umbrella. What is the optimal spend allocation across channels to be able to hit that forecast? Right. So let's say we've answered the forecast question and, and in this conversation we're not really talking about how we do each of these things, right?

[00:12:16] We're sort of like, we're sort of teasing out what the, what the, what the challenges are that, that we've seen and we'll, we'll kind. Doing that. I think to sort of a, you know, aggravate ag aggravate the issue maybe a little bit more. But the, the budget allocation, so what is the optimal spend allocation?

[00:12:32] So, so this comes in two forms. One is. You need a total budget allocation for said time period typically on a monthly basis and then out to the quarter to the year, right? But you need to understand how much total ad dollars are necessary to, is sort of the right allocation to start with for that given point in time period.

[00:12:50] And then the second step from there, which is like done in the forecasting process and should be done, accounting for seasonality, the degradation of your efficiency. A lot of things we could talk about, about like what you should take into account and not a. Static MER or add to sales ratio, right? Like, so all that, given you have your total budget.

[00:13:07] Now what you need to do is you need to allocate that across ch channels and tactics, right? So we have this total number. What is the right way for us to think about how much spend goes to meta acquisition and Google non-brand and Google brand and TikTok acquisition and Pinterest and on down the line.

[00:13:24] So, again, about a hundred different ways we could talk about how we have seen this be done. Every direct to consumer e-commerce brand does this and everyone does it slightly differently, which is which is just incredible behavior really. If you, if you think that like there's, there's not more consensus around what, what the right approach here is.

[00:13:45] I think the most sort of rudimentary way would be start with a sort of year, year over year budget allocation percentage by channel, right? So meta's typically 65, 35 between these two channels, right? And that's kinda what we were at the year previously. What we saw is that a couple months ago we went more 60 40, a little heavier on Google and it didn't seem to help things.

[00:14:08] So we're gonna go back to the 65, 35. Right. And that may, that may sound really simple, but is it's happening in, in, in a lot of cases. Right? If sort of just like, let's try to try to correlate the budget allocation based on the trends and what, what it sort of gets at too is this. And making a drastic, a more drastic shift from, you know, call it sixty five, thirty five, between two channels to to a 40, 60 split.

[00:14:33] And going like the, the, the opposite way in terms of the, which channel is getting the majority of spend, it's a pretty dramatic impact to the, to the, to the media spend, right? So it sort of gets at this like, okay, let's, we're gonna. Make incremental improvements and sort of ladder, ladder up versus let's take some, some bigger swings and I think is a challenge of like the maturity level of businesses and, and what they're, what they're willing and able to do.

[00:14:57] And so what, what that leads to then I think is like another approach is. Leveraging is leveraging tools MTA or different attribution model tools to be able to give a sense of what the right budget allocation is. Well, which will give probably a, a more informed allocation than just looking at sort of historical, historical percentages and doing it that way.

[00:15:20] And we'll look at, okay, based on my rocker box, MTA, based on my based on my. Triple whale, north beam, whatever on down the line. Like what is the efficiency I'm seeing per channel, right? And if I rebalance, like if I'm seeing a, A 1.8 x in this channel, X amount of span, but a 1.6 x on this channel, this amount of span, I'm gonna try to shift, you know, 10 or 15% of the budget from channel eight to channel B so that the 1.8 becomes a 1.7 and the 1.6.

[00:15:46] Becomes a 1.7, right? And there's like an imbalance there. So let's sort of rebalance them in terms of the efficiency. I can get a little less here, a little more there. All in sort of service of the efficiency target and rebalance that way using. Again, MTA attribution model, et cetera, to sort of, I identify what the efficiency threshold is and then re and then rebalance, rebalance from there.

[00:16:07] And then the and then the other one that I'll, that I'll pull out, which I think is important is is a, an experimentation informed budget allocation. Which is going to be that we are going to use the budget allocation, that's the best source of truth right now available to us, and use experimentation to improve that over time.

[00:16:30] And the, the tools and the models that are, that are gonna be helpful in that pursuit are an MMM to understand a really good starting point allocation. This is really important, especially for brands that have been like running for a number of years and have, like, they currently have a budget allocation.

[00:16:45] Is this right or wrong? Is it like, are we like plus or minus 2% optimized? Or like plus or minus 20 to 30%, you know, needs optimization? So like MMM for the beginning allocation and then incrementality. Geo holdout testing as the experimentation ongoing to improve that allocation over time. And any new channels that are entered into the media mix are first assessed via geo holdout test and then scaled into more broadly from there and on down the line.

[00:17:12] And so those are just three of like the different, different approaches of the, many, of the many options within this sort of budget allocation umbrella. But what I'll say is. Between those three and then any of the other options and workflows that exist out there, it's going to lead to a really different allocation of your media mix and not like.

[00:17:32] Cool. Our meta Google split was 60 40 and now it's, and now it's 65. 35. Like the, what it's going to lead to in many cases is, okay, it was 60 40 and it should be 80 20, right? Like it's, it's meaningful changes in terms of the amount of money you're spending. And for most brands, 20% of your revenue is going straight to that meta and Google, right?

[00:17:54] Right. Like that's, it's your, it's your highest cost. And so. The, the workflow and the tooling and the framework around budget allocation around each of these things. But it's just, it just has such critical importance on what the the outcome of your business is, is, is going to be.

[00:18:12] Richard: Yeah, so actually maybe it would make more sense than to just like on each of these, just dive into what our solution is or like how the way that we do, like the way that we answer a question too, like fundamentally changes your approach.

[00:18:24] Luke: Yes. Yeah, for sure. And, and so for number two, like in that, the third, the third sort of bucket that I. Highlighted m what What we do is we build on an MMM as a starting point and we'll use that to inform the initial channel allocations. And then in terms of setting the efficiency targets per channels, we have a database of incrementality tests that we run across hundreds of brands that are starting points for what the true incremental impact is for each of your channel and tactics.

[00:18:51] So we'll use that to set the ROAS target expectation from day one 'cause it's the best source of truth we have. And then we'll use experimentation through geo holdout testing. We'll build a testing roadmap for meta testing, meta acquisition first, then testing into TikTok acquisition as a new channel.

[00:19:06] Then App Oven, the Google non-brand, right? Based on the impact of each of those channels and the amount of spend that you have, we'll test into each one of those channels. We'll get an incrementality. Result and incrementality factor back. And once we have that, that'll be the newly informed source of truth for that channel to set the budget allocation, efficiency targets.

[00:19:24] And we keep iterating that over time. So MMM do incrementality starting point factors to a testing roadmap that then updates the factors over time so that they become stronger and stronger indications of reality.

[00:19:37] Richard: Great. And then I should also say too, because I think it would make sense to just say it now, to circle back to the first one, like the way that then we would then approach that idea of connecting the forecasting to the marketing is by actually doing the forecasting ourselves as the people who are in charge of sort of directing your marketing output or having like some control over the execution of your marketing calendar.

[00:20:00] We are also the people who are developing the forecast. Therefore, there's like a very clear connection between the people who are doing the work and the people who are making the forecast. It's, in fact, it's the same person which I is, you know, as far as I can tell, is the most efficient way to bring those two things together.

[00:20:15] So, I just wanted to make sure we doubled back on that,

[00:20:17] Luke: And, and to add on the building blocks of the forecast are the marketing actions and calendar events that we're taking, right? And so every marketing moment and product launch and sale and email that you send out, all of these actions we're modeling against those individual actions. And they have an impact on the forecast outcome, right?

[00:20:37] So, so that we can assess and go back and say like, okay, this. On, we missed forecast on this day. What specific metric did it come from? Right? And then it was relation to this marketing action or this calendar event, right? That, that is then something we can go and actually action against versus like, okay, we're reli on visitors, what now, you know, relative to the forecast.

[00:20:58] So the, we're doing, yes, we're building the forecast, and then the building blocks of the forecast are built around the actual marketing actions and events.

[00:21:07] Richard: Okay. So let's, let's roll on to question three and talk a little bit about A, how it's generally being answered right now, and B, how we would answer it. And the, the third question as we set up already is. Creative strategy and really creative demand, right?

[00:21:20] Like given the set of, or the budget allocation that we've determined, how much ad creative are we actually going to need to support that? So how is that question current currently being addressed? Generally,

[00:21:31] Luke: Yeah, so. And this, this is still one that the so on, on creative strategy. What I'll say is the more work that we've done around this I think is it's, it makes it clear why this is a really tough one to, to, to crack. Like it's a, it's really complicated thing how metas algorithm works and the power law. Three to 5% of your ads are gonna drive 70 to 80% of your account spend. Right? So, like that, that's, that's what we see across our data set. And that's the, that, that's the reality for account. So I think that's why this, this topic of creative strategy is still so challenging. We're like, we see brands making 10 to 20 new ads a month, and we see brands making 2000 ads, new ads a month. and not being that, not like one's a $2 million brand and one's a $200 million brand, right? It's like the, the, the amount, the error bars and creative output and the expectations around it for brands of a pretty similar size is just so wide still that these, these conversations we have, there's stuff to work through on, on either side, and that's what we see, which is brands making hundreds or thousands of ads a month, brands making 20 or 30, which making an extra 10 is really, is really challenging to, is really challenging to do.

[00:22:52] So, there's sort of two, two main threads under creative strategy. One is. What is the total necessary creative output, like numerical output? Like how many new ads do I need on meta? Right? And then what is the production plan against that number? Right? So like what type of ad and format and for what specific products and marketing moments, right?

[00:23:13] Like what is the right allocation of that, of that numerical output? And so for, for creative strategy I, I would say this one probably has the least, least defined tooling and workflow as it relates to understanding what the necessary number of ads is, right? I think it's, it's typically. It goes along the lines of looking at, okay, how much did we, how many ads did we make last year?

[00:23:37] In a similar time period, were we spending a similar amount? Okay, so we could probably, that's probably the amount that we need this, this time around. Or, you know, we, we usually make 40, 50 new ads a month. We're gonna scale spend a little bit, so let's try to make 10 more that, that's, that's the most typical sort of like, understanding of what, what the necessary creative output is.

[00:23:58] And and then from there, what, what we've, what we've seen and where the conversations land for us is what I referenced earlier, which is this understanding that creative on meta behaves like, like outliers do, which is you have a very small percentage of the, of your creative output account for a very high percentage of your spend.

[00:24:20] And so what this game becomes creatively is. Most brands are gambling when it comes to creative output, and the brands that have more predictability in their business and are driving more upside are playing a probability game rather than gambling. Is is really what the data frames up in terms of how to think about creative and how and how meta and how meta approaches it.

[00:24:45] And so how that works is. When you understand what your outlier rate is, right? So what how many ads it'll take you to find an outlier that'll produce X amount of media spend, right? Then you understand as your media spend grows you also have ads that are dying off each month. So we'll call this the, your sort of turnover rate of your ads, right?

[00:25:05] So you have ads that are dying off each month or each week, and so you can see that coming down. So you can really. Start to understand we have this much media spend, we're gonna see this much churn in our ads, right? Like there's, these are gonna turn over and die off, and this is our outlier hit rate. And when an ad does become an outlier, how much it spends, then it becomes a math problem to, to, to back into.

[00:25:26] You need X amount of, of budget on meta based on the budget allocation we did earlier. So based on that, you're gonna have this many ads die off. You gotta replenish those and you're gonna spend a little bit more than you were at previously. So you need more of these. So that's the amount of ads that you need to be, be able to spend that much dollars.

[00:25:41] And then this is the and then this is the output necessary based on the outlier rate or the hit rate of where of those ads that are actually gonna spend for you. And, and, and what it'll do is. It, it increases the volume threshold for a lot of brands so that you can start to play a probability game rather than play a gambling game, right?

[00:26:01] Which is ideally you can just launch your 40 ads and they end up, you end up finding, you know, you get lucky and your outlier rate that month, month is 10% rather than 5% and like you made it work, but it the. Next month or two months from now, it's not gonna work. Right. So like you, that's, that's what the, in terms of the creative strategy in terms of understanding the output necessary, it's understanding the probability of finding the ads that you need to, to replenish your spend, and then being able to create an ecosystem of, of.

[00:26:37] Vendors, internal resources. What we'll say is the brands that are successful successfully finding creative output at high volumes and with diverse output of those creative IDs are working with three or more different vendors for creative, whether that be an internal person who's doing some creative.

[00:26:56] Agency one that's doing some creative and agency two that's doing another type of creative. But the brands that are successfully doing high volume of diverse creative and able to have created this ecosystem are working with three, three or more vendors to be able to support that. That's what we see consistently.

[00:27:10] Richard 1: Alright folks. As you may notice I am wearing different clothes. So is Luke. He's in a different space altogether. The the internet at the CTC offices ironically keeps crapping out on us. So we're rerecording here, but we were on 0.3 around creative strategy talking about kind of the five questions here.

[00:27:28] And so let's move on to, to question four, which, is around the the way that we've approached meta management. So again, what we're setting up here is the way that it's commonly approached and then the way that the profit system steps in and does it differently and better. So, Luke, tell us a little bit about kind of the more commonplace approach to meta management.

[00:27:46] Luke 2: So meta management. So this question of what is the right full funnel meta strategy and daily optimization workflow against the outcome that we're after. So the first thing that's worth talking about is the amount of time that gets spent in building. Slash trafficking assets to meta, right? So let's say that we have the perfect plan. We have a, a high amount of creative volume, and we've produced against that high amount of creative volume. So we have all the assets needed. Now the last bottleneck becomes, we gotta get all those things live in the meta ad account, right?

[00:28:22] And they have to go live in the right structure against the right landing pages with the right copy and headlines, et cetera, right? Like the whole setup has to be there. And. It's very typical for there to be some lag between asset completed to live and ad account in the workflow for, for for brands ranging anywhere from cool, we can get it live tomorrow, which is like typically pretty quick to great.

[00:28:44] That should be live next week Wednesday. Right. And anywhere sort of in, be in between, in between that. What that takes away from is the time spent on higher level activities than building out meta campaign shells and, and waiting for assets to upload to meta server and go, go live within the ad unit.

[00:29:05] So, that's the, that's the first thing to solve within this workflow is how are you con condensing the time from asset created, ready to go live to its live in ad account, actually producing an outcome for your, for your business. And to do that, you have to reduce the amount of labor and the lag time against building the asset in the ad account. And. There's, there's different ways that this can be, that this can be approached, but how we, how we have approached this is building what we call push to build which is a technology that lives within stat list that connects directly to the finalized. Digital asset management system, Google Drive, Dropbox, et cetera, and can take the finalized assets based on whatever the folder and file structure is, and map those against the specific product types and campaigns that they need to be built within platform.

[00:29:49] And one click push to build from the completed asset into ready to go live in the Meta Hat account in seconds, not hours, not days. And so it allows us to get the assets live as quickly as possible. And and then also take away again, the hour spent in that sort of laborious building work as it relates to the management of the Mead account.

[00:30:12] That's the last thing, that's the last thing that we wanna do. Now, when we think about the setup of the meta campaigns, though, there, there's a few inputs that are really critical to get right on the front end. And the core two will be bid and budget. So, let's assume for the sake of this conversation that the campaigns are being run with some sort of cost control strategy in place, right? Rather than highest volume or highest, highest value within the accounts. And so sort of whole subset of conversations there, but let's say we're after a specific marginal outcome for our business, and so we're only gonna spin media against. That that accepted marginal threshold, which is gonna result in some sort of cost control, roas goal, cost cap, bid cap, whatever it might be, but some sort of constraint on the efficiency of the campaigns. Really, the levers that you have and the inputs as the signal to, to the platform are the bid and the budget that you have set because the volume and the efficiency is gonna be constrained. Against against those inputs, this is where the connection to the broader system becomes really important as well, right?

[00:31:16] Because you have to answer the question, what is the right bid for this specific campaign that we have going live? And what informs that bid? What needs to inform that bid is one, the total business forecast for that month. So you're gonna have business level new customer revenue ad spend, a MER expectations. You're going to have incrementality reads for each of your channels, right? And those incrementality factors as a result of those channel tests are gonna inform the necessary how much a specific platform is over under reporting relative to this true impact. And that'll be the connective tissue between.

[00:31:53] What the business goal is, what the true incremental impact is, and then what the bid that needs to be set for that specific campaign within that specific platform is. And once you have that infrastructure, right, once it's connected to the broader system, and you can push to build and remove the manual, the manual hours required in that process, now you have a campaign that is set up against a bid that reflects your business objective and you spend all the time focusing on. The assets, the output, the ROAS targets, the business strategy, and as much time pulled away from manual building process and manual day-to-day optimization, let's tweak this bid up, let's adjust this budget from $600 a day to $675 a day. Right. Like that, that is, that is not the highest leverage category of activities.

[00:32:42] Richard 1: Yeah, so I mean, it sounds like the actually, hold on. You're, you're echoing like crazy on your end. Cancellation on,

[00:32:53] all right. Go on, go on mute for a sec while I ask this. No, no, actually, you're good. Just then check, check, check. Weird. Okay, cool. Yeah, so it sounds like the, to summarize, basically it's like the, the answer to this question is, or the difference maker here is like, we do push to build and everybody else does, doesn't.

[00:33:11] So there's like the, the, the, all of the kind of like tedious elements of meta ad building, those are all automated within our system. So you can just essentially press a button and then. The ads get built so you can focus on other things. So I think like then, then maybe it would make sense to move on to the, our fifth question then, which is around growth strategy, basically, which is around the day-to-day tracking of whether or not you are performing against the metrics that you're, the goals that you've set for yourself and whether or not you're tracking towards the forecast that you've given.

[00:33:42] So talk a little bit about how this goes how like, sort of the daily management happens, like within your average eCom and then how we do it.

[00:33:50] Luke 2: Yeah, so that's right. We have, we have these, of the five steps, we have sort of four accounted for related to the business forecast, budget allocation, credit strategy, meta management. So we have all the, all the tools in place now. What we're going to do is now we're going to execute against the forecast that we have created. And what we know about ev, what we know about every forecast is that it's going to be wrong, right? In one direction or the other. And so the useful forecasts are the ones that tell us where we are off so that we can course correct most quickly and effectively based on the specific area. In which we're off course what this looks like in different workflows and organizations. It's a couple examples. Might take the form of a weekly business review as sort of a, like a, a nemesis we could call out here in sort of this workflow, right? Which is like it, we do weekly meetings as well. Like we, so I'm not, but this like idea of a weekly business review of. This is the space in which we are gonna pull together all five to seven to 10 team members that are touching this system.

[00:34:57] Right? Like the whole thing we just talked about typically is like a, a group of several people across different work streams, different tools, a lot of times different agencies or vendors in combination with the internal team. So we're gonna pull those people together in a, in a weekly business review and and try to have a dialogue around. What we're going to do to move the business forward. What happens in those spaces is like we teed up the conversation, 80% of the time is spent on trying to understand what the heck's happening in the business right now. Right? Like, what is the gap? What's working, what's not, what's the thing to solve? And so the weekly business review is this idea of let's, let's get all these people together, let's get all the stakeholders together, and let's have each person report on their area. And then based on the input, let's all collaborate and try to come to consensus together on the, on the key actions to resolve, right?

[00:35:47] Which is like the idea, which I think, which I think makes sense. The challenge. The challenge with that is that it's, it's the outcome of that sort of discussion tends to bias around whatever questions were asked or not asked in that space, but whatever group of people that's present are not present, right?

[00:36:05] It's not a really defined sort of outcome and workflow. It's like, here's, here's what we see. Here's the thing inside that this person uncovered this week, that maybe this week was, they sort of took a different lens on it. And it's not structured in that way. And then it's, it's really laborious as well.

[00:36:19] Like it requires getting multiple people together for hours in these spaces to try to dissect the info. And, and back into it that way. So that's sort of one one, one example that we could, that we could hold up. Maybe some of you have experience of the weekly business review and all, all the joys that those sorts of spaces can entail.

[00:36:38] The other which, which would represent I think a more structured view would be some sort of organizational wide daily. Spreadsheet or daily output or daily message that gets sent via email or Slack that is pacing a forecast. And, and typically from the finance team or someone on the analytics team, right?

[00:36:56] Which is like, here's how we're pacing into the forecast that we sent yesterday. Here it is. So like, so everyone's aware. And going back to the bucket one, we, we talked about that can take all sorts of shapes, right? Daily revenue. And that's it, right? Or traffic conversion rate, a OV yesterday and the revenue that it backed out against or whatever the metrics are that it's, that they're oriented around. And like we talked about in that in the whole forecasting bucket, the challenge with that is it's sort of like a, it's tossed up into the ether of like, here's the, here's the here's the pacing to forecast that lives outside of the specific marketing actions and the, and the levers that need to be pulled.

[00:37:33] And it's like. What's someone going to do with this, right? Like where does the accountability live in relation to effecting this conversion rate number that was read yesterday, but like month to date is plus 10%. So like, how do we think about this? Right? So. The daily gap to close. What we're, what we're focused on as much as possible is reducing the time from insight to action as it relates to how we're pacing against the forecast.

[00:37:55] And so, what we do is we build out the business forecast on a monthly, yearly basis, but we break it down into daily targets for every single customer cohort and every single channel. And so. What we're, what we're able to see is on any given day the profit engineer, this one person's responsible for the workflow is able to identify and see where we are pacing against every single one of these critical business and marketing metrics.

[00:38:21] So it's over 35 metrics from revenue spend MER to new customer revenue, new orders, returning, returning orders, and then down to the channel level, right? Meta, Google, email, et cetera. How we're pacing against each one of those. And we can see red and green for every single metric where we're off and they're prioritized with contribution margin being at the top, then revenue and spend, then the ch, then the customer core performance, then the channel performance so that we sequence down and understand what, what levers need to be pulled in relation to the core business outcome, which is the contribution contribution margin goal. And so. Again, what's necessary for this workflow to exist is Targets. The forecast is built around specific marketing actions and levers that can be pulled. We can see we're pacing behind on contribution margin because our new customer acquisition efficiency is pacing below target, and that is specifically because Facebook acquisition is 17% below the IRO ops expectation this month. Great. We have clarity on the action. To go solve as it relates to the business objective and the specific channel we're gonna go after. And it took us 10 seconds to get there, identified by one person, and then the gap is being closed because we can get new creative and push to build within minutes in the ad account to help increase the efficiency, right?

[00:39:33] And so this sort of fifth bucket. Of growth strategy or closing against the daily gap spans across this workflow and really ties everything together, which is we have the infrastructure, we have the plan now every day we are going to review how we're pacing against the goal, identify where we're off course and course correct based on that specific area.

[00:39:52] Richard 1: Yeah, I mean, I think a, a way to summarize it is that the the most tedious beatings of the week that also are like the most important quote unquote. Those meetings you know how there's the cliche about this meeting could have been an email. This system turns those meetings into literally an email that you receive every day that drives action on a daily basis.

[00:40:10] And so, removing I think one of the sort of least, the least valuable, but most important feeling types of meetings that people tend to have in these businesses. So we're gonna wrap up here. Thank you all for joining us.

[00:40:22] Again, sorry about the little break. You got a transformation halfway through, so there's a little bit of excitement for you, but we'll talk to you next time. Take care.