How 2 Top-Tier Strategists Actually Forecast Client Growth

[00:00:00] Luke Austin: Hey folks, welcome to the Ecommerce Playbook Podcast. I am going to be your host today in place of Richard Gaffin, and I've got a couple special guests for this episode that is gonna be something different than, than we've done before. And, and we're, we're excited for it. What, what we're going to be diving into today. It looking at how we forecast in our profit system daily targets for every single one of our clients, every single month of the year, and how we execute an action against that. And I have two of our top growth strategists who have landed the closest two forecasts across their client Profo portfolio year to date. to talk through how they have achieved that outcome with specific brand examples that, that we're gonna be walking through. So this is sort of a look behind the scenes, under the hood what that is going to look like.

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[00:01:39] Luke Austin: So before we jump in, want to introduce those folks. We have Lacie Geary and Brian Sakansky. Lacie, how you doing?

[00:01:46] Lacie Geary: Good. Thank you for having me. Excited to be on.

[00:01:51] Luke Austin: Excited as well. Brian, how about you?

[00:01:53] Brian Sakansky: Feeling great, Luke.

[00:01:55] Luke Austin: Great. We got some good energy for those listening as well. I apologize for what may come across as a bit of a nasally podcast episode. We got kids, kids back to school, school season, and these, these things happen. So what we're gonna do here is start out with a look aggregate across our client portfolio at forecast. Accuracy for the recent few months to sort of frame up the conversation. So, if you are watching this in some visual format, you'll see some visual guides pulled up. If not, we're gonna talk through them audibly. And the first thing we have up here is August forecast accuracy report across our core client portfolio where we can see revenue, actual versus target spend, actual versus target contribution margin, actual versus target for every single one of these clients.

And, in August we landed across our portfolio at minus 6% to revenue. Minus 1.34% to spend against Target and plus 1.01% to. Contribution margin, we'll toggle back a couple more months. In July, we landed plus 1.7% to revenue, minus 5.93% to spend, and plus 12% to contribution margin. And then June as another example, plus 0.14% to revenue, plus 0.66% to spend, and plus 4.6899999999999995% to contribution margin. This is the core outcome that we're focused on in. The profit system that we build out as the initial touch point with the brands that we work with. And then the ongoing execution is clarity against the business outcome and then accuracy against those forecast targets. Now what we also do is we look at this breakdown by growth strategists.

So the growth strategists are the quarterbacks of the team on our side who are building out the forecast and, and or orchestrating the team and execution against those targets. And so we have a breakdown. By each of our core strategists of actual revenue spending contribution margin to target, year to date.

And that's what's leading to this conversation where we can see where each of our core folks have landed. And specifically here we have Brian Sakansky who year to date has landed minus 2.42% to revenue forecast for his client portfolio, minus 0.91% to spend, and plus 8.8% to contribution margin. how do you feel about those numbers?

[00:04:25] Brian Sakansky: These are exactly what we aim for. I mean, if we can achieve more profitability against our target. On track to sales goals and spending the exact amount of money that we have, this is a great outcome. I would say in some cases, spending more would've taken it to the next level, but overall, really pumped with how we're progressing so far for the year.

[00:04:46] Luke Austin: Yeah, so frame that up for us a bit in terms of what your. In terms of what you're looking at and what you deem as good for where a forecast lands each month what, how, how do you frame that up? What, what's good in, in, in your mind and what's, what's acceptable versus unacceptable in terms of the outcome?

[00:05:04] Brian Sakansky: Yeah, so I mean it's very, of course, client specific. What are they trying to achieve, you know, from a profit perspective? Are they in growth mode? There's a whole, you know, variety of different instances, but usually like what we're trying to aim for is, you know, revenue is directionally helpful largely to make sure that your order volume is moving in the right direction, right?

Like, are you getting enough new customers, returning customers and making sure that the business and people are coming and purchasing on site. Spend obviously is, you know, one of the engines, if not the most majority engine for doing that. But then when I'm up above a contribution margin target, trying to make sure that I'm not too far ahead

[00:05:44] Luke Austin: owner

[00:05:44] Brian Sakansky: to where I could potentially reinvest those dollars, but ahead enough to stack some extra cash for the business so that can be redeployed into other areas.

[00:05:53] Luke Austin: Yeah, yeah. You bring up an a, a great point, which is how we, how we think about this as CTC is there are there are either challenges focused on volume or efficiency, right? There are that any forecast exists in the tension between some expectation around volume and some expectation around efficiency. And every given timeframe there is some consequence of an action either direction, right? So, taking more contribution margin in the short term, pulling back spend, impacting new customer revenue is going to have an impact to three months from now on what the business outcome is for the shorter term trade off of this, of this outcome.

So it really is. there really is a, a constant trade off between volume and efficiency. That I think is, is a, is a good point to, to bring up. Okay. Let's jump over to you, Lacie. So, year to date plus 5.29% spend, plus 10% contribution margin. Plus 10%. I, I feel like we could we could debate who landed closer to forecast between you and Brian.

What, what would your, what would your case be? Lacie.

[00:06:59] Lacie Geary: I think overall this year has had a lot of macroeconomic challenges. So number one, just wanna say how proud I am of all of us in the work that we've done to get this close to forecast. I would even say, like in this instance for me. still could have pushed a little bit further. So I think both Brian and I probably could have pushed further to generate even more contribution margin in some instances.

[00:07:23] Luke Austin: Okay.

[00:07:23] Lacie Geary: just depends on the client and what their specific situation is, what their inventory position is, and what the margins are per product for that client.

[00:07:31] Luke Austin: Yeah, for sure. It's a good, good answer. Also a good way to skirt my, my direct sort of competition frame up against, against Brian. I would say you, you are 10, 10% ahead of cm. 8.8% ahead of cm. So if there's anything that we prioritize in terms of looking at the outcome against our clients, you, you may have an inch ahead in that regard, although. Brian, Brian was closer on the revenue, the revenue and spend expectation against against each of those. So, that's where Brian and Lacie have landed year to date. What we're gonna do now is we're going to jump in and look at two specific clients, one of Lacie's and one of Brian's. We're gonna pull up lists.

We're gonna pull up the things that we look at in the profit system and talk through what are the specific things that we look at and action against to achieve this sort of outcome in terms of performance against.

Forecast in this type of an expectation. And to to further set how we think about this. We believe that forecasting is an exercise in both planning and execution and our, it's inseparable in terms of the relationship between those two. We put a lot of emphasis on the planning side of things through our span, a ER model, through a retention model, through a VIN effect model, through the marketing calendar. Through integrating the cost, the planning's very important. The execution is equally as important once we set the plan to actually make it come to fruition. And so Lacie and Brian, have you both talk through and give us some examples of what are some of the key things that you have looked at for these two clients.

We'll look at in the planning process to help get the forecast as tight as it can be prior to then the execution phase, and what a couple of the core things that we look at in the execution phase. have helped to achieve the outcome that we have seen here. And let's start with Brian here.

So we've got one of one of Brian's clients up. We're not gonna share any brand, brand specific. This is in the home home goods category. And we're looking specifically at the month of August. So, Brian, frame this up a bit for us.

[00:09:33] Brian Sakansky: For sure. So in addition to this being a home goods business, they have a really large inventory of SKUs, so a very wide, you know, diverse catalog. Different ranges of average order values, different product categories, different cogs. So it's really important that, you know, ahead of the month, we're really clear about our expectations of sales in each of those individual categories based on not only the rolling trajectory, year over year and seasonal changes.

So all those things are considered, especially when framing up average order value, which you could see, right, 12% off or 13% off. Coming pretty close, but not quite on target because of how dynamic. A very large catalog can be. But more importantly, like what we're looking at here is, so the month of August has a really big moment for this category towards the end.

'cause it is dictated by map pricing. So there's only so many times of the year that we could actually run sales. So you could kind of see the trajectory, you know, kind of this line. And then it raises here at the end of the month to really drive the majority of our revenue and contribution margin as we close things out.

The week over week is pretty different. We have most of our sales coming in during the weekdays, pulling back on the weekends, which is just a classic day of the week effect for this particular brand. So being cognizant of what are the days, as well as the times of the month where we're gonna drive revenue, contribution margin, be able to spend into those efficiencies.

Was really key in terms of framing this up. And as I'd mentioned like the end of the, the month was a really key moment for US Labor Day being one of the five-ish or so big sale moments for this particular category, which allowed for us to overachieve on our contribution margin target as we closed up the month of August.

[00:11:19] Luke Austin: Great. That's, that's helpful framing. So you mentioned a couple things there that I want to, I want to dig into in terms of our planning process and some of the tools and frameworks that we utilize to help set the expectation on the front end. You'd mentioned. The day of week effect and how that's important for this client.

You mentioned the marketing calendar and how that plays into. The revenue expectations specific at the back half of the month. And then connected to both of those things. I think the spend a ER model in determining the budget allocation total for the month, we landed 2.6% to spend goal for August 6.3% ahead of revenue goal. We're basically right at a MER goal minus 2%, and new revenue is plus 0.6% to goal. So let's, let's maybe start there. When thinking about budget allocation and, and determining the optimal budget allocation for a specific, specific point in time, like for this brand in, in August what are, what are some of the things that we're looking at there to help us to land within this, this type of a range?

[00:12:19] Brian Sakansky: Yeah, so there's, there's a few considerations 'cause. This brand in particular has a very seasonal dynamic. So Labor Day in particular in the month of September is really the preparation for Q4. So you can notice that if you look at a lot of the contribution margin values for new customers, a lot of them are positive.

But actually in September we intentionally went in knowing that we're going to invest more in order growth. As a preparation for Q4. So that's a really, really key insight, but holding at a specific efficiency so we could drive the necessary order volume so that we had returning orders in Q4. So it's a very intentional move.

Now, the way we balance that though. Is by looking at what is the returning revenue constraint and how much con contribution margin dollars we're gonna be generating from that cohort. So on the initial screen, you saw that we came in at, you know, right around 55 60 K in contribution margin. To close the month, which is ahead of Target, so that was an intentional move to spend into that opportunity.

We closed the month overall ahead, but we set ourselves up for additional order volume, which is gonna get us ahead for Q4, which is after, as Lacie teed up a really challenging H one due to macro environments. We wanna make sure that we're ready for Q4 to really close out the year on a strong note.

[00:13:41] Luke Austin: Great. Okay. So, the, the first step here is really, is really actually thinking about the constraints that exist, right? First to frame up the forecast and planning and the constraints that in this dynamic of volume versus efficiency, there's a. Constraint relative to the, the necessary contribution margin dollars or, or overall profit dollars that the business needs to be able to cover fixed expenses and other obligations.

Right. That like is an immovable constraint that we need to be aware of so that we understand how much we can push on the volume side of things, right? So that's one of the initial, the, that's the initial step of the things that you looked at was understanding. How much contribution margin do we need to be able to cover those obligations for the business?

So then I know how much volume, how much I can push on the gas for the course of the month, knowing that it's gonna be important to ramp up in August into September to set us up for Q4. Is that right?

[00:14:38] Brian Sakansky: Exactly.

[00:14:40] Luke Austin: Okay. So, look, looking at that, we have the spend a UR model up here. For those listening, we'll talk through it.

Briefly. So in, in August, the spend expectation was $280,000 in spend at a two 90 9:00 AM ER, September two 50 k at a 2 81. And then October drops down, and then November ramps up to 3 46 K at a 3, 3 2. So you can sort of see the natural ramp up there in terms of the expectation for that month and how we're setting up the volume in July, in August, September, October, and then up into up into November. So Brian, just to sort of tie, tie a bow around this part of the conversation, then looked at the constraints relative to the business, the business obligations and the profitability necessary. Then from there the business goal is to push as much top line volume against that constraint. Is that the right framing for how the conversation's heading into August?

[00:15:40] Brian Sakansky: Yeah. And one thing I would add to just kind of, top off, the top line piece of it is it's really the order volume, right? Getting more people in the customer file. So it's not really driven by average order value per se. It's mainly driven by making sure we have new customers in the business so that we have a more dialed email SMS program.

Our pixels are more warmed up, et cetera, so that we can really knock it outta the park in Q4.

[00:16:05] Luke Austin: Great. Great. Okay, so looking at the constraints around profitability, expectations, looking at and then helping that that being the determining factor for how much volume we can push over the course of the month. And then the other piece that you had identified was day of week effect. Talk to us a bit more.

I'm gonna pull up here on stat list and we'll talk through it for, for those listening. Day of week effect. And and how we look at that across our portfolio. So set, set this up. How do you look at day of week effect? How do you use it to help us to land on daily target expectations? To be as accurate as possible.

[00:16:40] Brian Sakansky: Well, the nice thing is that Stats does a lot of the calculus for us. So this is a really big aid in terms of like speeding up the process and getting really precise around what is the percentages here, like the 29.07 for Monday. You know, 19.53, et cetera. But what we do observe, and if you look back historically, is that even if we do run ad spend over the weekend, Saturday, Sunday, this customer just does not shop at the same volume over the weekend as they do during the week.

So over time and very quickly, what we identified is that hey. We're actually generating negative contribution margin or lower efficiency spend over the weekend, so it's more advantageous for us to pull back before the weekend is and then push up leading into the week to make sure that we just maximize our outcome and stay on target for the month.

[00:17:34] Luke Austin: Yes. Yeah. And the day a week effect for this brand is, is, is quite dramatic as well. We, we see this for every brand. You have a natural sort of daily revenue behavior that you can expect in terms of how much volume you can push on specific days. Things that are impacted based on your category, your consumer behavior, your marketing calendar when you send out emails and SMSs.

But we, we. Consolidate all that into what we call the day of week effect, which is identifying relative to the average, so relative to what the average or the mean of the, of the daily revenue's gonna look like. What are the days that are above the average and what are the days below the average?

So as, as Brian mentioned for this, for this brand, the strongest day of the week is Monday. On Monday we can expect 29% more volume at our efficiency target than the average day. So 29% higher than, than the mean. day of the week for this brand is Sunday, Saturday, and Sunday are really close, minus 48% and minus 49%.

So again, against the average daily revenue. and Sunday are gonna be 48, 40 9% less, and Monday is gonna be 29% higher than then Tuesday's gonna be 19% higher. This is a wild swing, right? Because the, it's really the difference in the delta of those two numbers, which is Monday, 29% higher, Sunday 49% lower.

You have a 70 to 80% swing in terms of the volume that you can expect to drive within any either one of those days at the same efficiency target. is a, which is a substantial difference in, in the business outcome. So let's use that to pivot. For a couple minutes here and then we're gonna jump over to, to, to Lacie.

Let's pivot to talking about the execution against the plan which is equally as important as all these considerations we talked about in building the plan, we identified the constraints around the profitability, how much volume we can push on span and new customer revenue, the day of week effect, and helping to plan out the peak moments.

We talked about the marketing calendar as well. So we have this plan. We have a really good plan. We've considered a lot of things. Now we have to go and make the plan a reality. You have to execute against it to make it happen. What are some of the core things that led to the execution leading to this outcome?

[00:19:51] Brian Sakansky: Yeah, so I think one of the most like blaring things when I look at a retrospective for this month is you have, you follow the progression. The first three weeks of the month and then it really picks up for Labor Day. But actually like the plan drops off for that Saturday Sunday, which follows the day of the week effect.

So when we did the same sale moment last year, Saturday, Sunday, actually were not as productive. This year when it came to execution, what we found very quickly is things took off on that Saturday, Sunday. So we were able to actually lean in, spend more against our plan, generate more revenue and contribution margin dollars as a result of it.

So going back to what you said, Luke, about like expectation versus like execution. We expected based on year over year trajectory, historical numbers, et cetera, that we would actually plan very similarly to how we normally operate that we'd pull, pull back, ad spend and that we actually found in the moment that we need to push here.

That's what we did and actually led to a better outcome. So tactically, you know, we had to stay flexible knowing that it was a really key promo moment for the brand. And it actually worked to our benefit and tied up the month really nicely. And allowed for us since Labor Day fell, you know, day one or two of the following month, allowed for us to actually keep up that ad spend to go straight into September on a strong note as well.

So that's a key thing. One other thing that I'll call out to Luke, if you wanna just scroll down. Is you'll see very quickly, right? So we started the month with a plan to spend much closer to 20 k in YouTube spend. But that expectation very quickly proved, and you could see very obviously, that the returns weren't there.

And this happens from time to time, right? We come in with an expectation that a channel's gonna perform much, much stronger. But it turned out that we actually needed to pivot very quickly. So we reallocated the spend into Google, which after delayed attribution is actually gonna land much closer to that IO as target since it meets the 30 day window to close up.

And we were able to push more into Facebook and Pinterest, which were both ahead of their IO as target. So in terms of expectation versus our execution, these were some key pivots that we had to make mid month after data started coming in. And it led to a really good outcome to close out the month for this brand.

[00:22:10] Luke Austin: That's great. So we are looking at. So one, we had daily targets. So going back to the first point around, were we able to push more on Saturday and Sunday for the launch than expected, help build that momentum. We had daily targets for total revenue, total ad spend, total contribution margin that we had set. What, what were the signals based on the plan that enabled you and the team to then go execute against driving more volume? What, what were the, what were the initial signals that you saw and identified as, yes, this is an indication that we should push more than we had originally planned to, to increase the, the business outcome.

[00:22:46] Brian Sakansky: There's a few of them one of which is acquisition, A MER. Another one is the ROAS of the channels. We also had a healthy amount of returning order volume. Hitting as well. And so when you start to unpack all the things that are that are progressing during that timeframe, it's just really key to look at all these things simultaneously to say that, Hey, we're on a good track here.

Let's keep pushing. Especially since we had buffer to, to allow us for do that. And like I said before, this is a really key moment. For us when it comes to acquiring order volume ahead of Q4. So the more we can do that, as long as we stay ahead of our contribution margin target that gives us room to push accordingly.

[00:23:31] Luke Austin: That's great. And so, I pulled up the, the Sunday and Monday here, which were a couple of those, I think initial days right? That we were looking at where the returning revenue for those two days was 41% ahead of forecast. So substantial beat on the returning revenue for those couple days, which brought in more contribution margin 'cause that's the most profitable customer cohort we have.

Right? So more contribution margin, which then allows us to be confident in being able to push more ad spend volume, sort of what we talked about in the planning. Our A MER was very close to target as well, and so we were able to push more, more ad spend during, during that period. Which, which makes total sense.

And then to the second point you brought up, looking at the efficiency of each of the channels reallocating budget, we had initial plan and budget allocation and ROAS target set based on incrementality. So I ROAS target three each channel and we were able to see. Which are underperforming and which are under and overperforming for each channel reallocate the media dollars in real time to make more of the initial budget that we had set as well. It's great. Okay. Planning execution. So much more we can talk about here. Brian, anything else worth noting relative to this August forecast before we switch gears to Lacie?

[00:24:44] Brian Sakansky: No, the, the only thing that I would just kind of top things off with is, you know, all these different metrics that we look at. I think it's really easy to fixate on like a MER, right, as a benchmark, but keeping in context the. Contribution margin that gets generated from returning revenue or the volume at play.

Like all these things, intermix, which is why this dashboard has all these different metrics is really helpful to make, okay, here's the best possible decision based on all the inputs, and let's go. Let's go execute accordingly.

[00:25:13] Luke Austin: Yes. Yeah. Is a great point, which is why contribution margin is at the top of the dashboard here, and it's the biggest metric that exists in this hierarchy is because that is contribution margin dollars, not the percentage, not the efficiency ratio, but the actual contribution margin dollars generated.

Having clarity of the cost, clarity of the contribution margin outcome. the core signal that we are looking at to be able to make these decisions. Everything else ladders up to that in some priority order, but to your point, a MER is not, the source is not the source of truth. Just to spend the, the budget allocation that is not the, the source of truth, contribution, margin landing at or above the expectation is, and everything else exists as levers to pull in service of that outcome.

So yeah, it's a great, it's a great call out. Lacie. Jumping over to you. So I think what we're gonna look at is for one of your brands that's in the apparel category a year to date, look at their forecast against Target and, and, and what that's looked like. So similar sort of structures. Brian, let's talk about a few of the things in the planning process that have led to the outcome that we've seen and a few of the things, and then in the execution against that to be able to enable the forecast.

So give us, give us a bit of context first on. This client and where they have been at against their business expectation year to date.

[00:26:35] Lacie Geary: For sure. I think first things first, the context is important. So we have all of our modeling, which is great, but the modeling is based off of historicals

[00:26:44] Luke Austin: Yep.

[00:26:44] Lacie Geary: brand came to us, it was like late spring 2024, and whenever they came in, they were spending unprofitably. They had a lot of inefficiency in their paid media. we knew to a certain degree that we were gonna come in and completely change their spending power. The model was gonna completely change as we started working with them. So by the end of last year that happened, we introduced a lot of creator content into the fold. It was a game changer for meta acquisition and scalability. So all of a sudden, whenever it came to planning this year. We had to factor in how far ahead of the model did we pace with all of these changes in spending power? And then apply that to this year in order to understand like, where do we think this brand can go? So that's the high level context here, because. We wanted to create a couple scenarios, which that's the great thing about stat list. You can create your baseline growth scenario, then you can create a stretch scenario. So this is their stretch high scenario, and we are 0.1% above year to date, which is really awesome. We're five, almost 6% ahead of contribution margin because we've actually been able to scale more and improve their spending power even more. So

[00:27:57] Luke Austin: Ads. We can do that.

[00:27:58] Lacie Geary: level background and yeah.

[00:28:02] Luke Austin: great.

[00:28:02] Speaker 2: Want more conversions, more repeat purchases. Of course you do. The trick is picking a provider that helps you do more with less yapo reviews help shoppers say yes faster with AI powered summaries and filters that answer their questions before they bounce. Driving real results like pers 25% jump in onsite conversions and yapo loyalty keeps those shoppers coming back with rewards that feel personal.

Perks they actually care about and smart segmentation that inspires action fueling outcomes like RMS Beauty's 66% boost in repeat purchase rate. And third, love's 56% lift in revenue per user Interested in learning more yacht PO is offering 10% off annual reviews and loyalty plans through September. Just mentioned common Thread Collective on your demo .

[00:28:49] Luke Austin: Let's, let's take a pause there real quick 'cause I think it's an important important piece before we dive into the specifics. Is that what you mentioned? Is. Forecast is always going to be wrong. It's important for us to know in which direction the forecast is. The, the important thing is that it highlights where the actions can be taken, and similarly, the models that we help to inform the forecast are all looking at the historical data. And so being able to understand the adjustments that we can make. To those models. What are the, what are the tweaks to the inputs to be able to get us to an expectation when the business is improving or growing is really important, right?

Otherwise, we just forecast sort of perpetual stagnation, like just sort of like, you have the model just sort of forecast like, here's how the business has been, here's how it's gonna continue to be, where that's not the goal at all, right? The goal is how do we continue to improve the business outcome? Then how do we have, how do we have an approach that allows us, allows us to do that? And in this case, I, I, yeah, I'm, I'm like tempted to refresh here and see if anything happens. Point, 0.1% ahead of forecast is pretty, is a pretty tight outcome. So, so Lacie, talk to us about some of the things in the planning process over the course of this year that have been important to be able to build a, a helpful and accurate plan and forecast for this, this brand.

[00:30:09] Lacie Geary: for sure. So the first thing we did, and it might be helpful to go to the new model, the new customer model within the plan,

[00:30:17] Luke Austin: Great. So we're, yeah, we're toggling over. There's toggling over a spending power model in status. Okay. Yep.

[00:30:22] Lacie Geary: Yep. The first thing that we wanted to start

[00:30:25] Luke Austin: New

[00:30:25] Lacie Geary: here

[00:30:26] Luke Austin: won't be

[00:30:26] Lacie Geary: just taking that percentage over model assumption and baking it in. So what you'll notice is all the way to the right, we have that percentage over model for the first half of the year, it's like up significantly, and we were able to hit that and beat that. And the reason why it's up that high is because we didn't start with them till. Late spring, so we knew the impact of the model was gonna be even double what we saw versus the impact of the model in the back half of the year. So that's why you'll see like the averages are like 30 or 25, whereas in like Q3 ish Q4, it's only like 1317. It's because we had to adjust that on a month by month basis based off of where. the model is pulling historicals.

[00:31:10] Luke Austin: Yes.

[00:31:10] Lacie Geary: that was super, super important. And then the other part here is you'll notice there are specific months, like February for example, where the model was up significantly, and that's where we had to bake in additional moments or things that are like newer into the calendar that maybe we didn't have in years past. So those were definitely like the starting places that we had to incorporate into this to get that baseline understanding of what's achievable.

[00:31:35] Luke Austin: That's great. Okay. Yeah. So the percentage of remodel is, is an interesting conversation, which, to the, to the previous point, our initial. Role with the customers that we work with is we're, our goal is to give them clarity on what is most likely to happen. That is, that is what we want to, that is the first conversation we want to have is in building out the models and the profit system.

This is a scenario of what's most likely to happen based on the current business performance. Then there exists some gap between what's likely to happen and then what we all would like to happen for the business. Right. And the bridge between those two things is strategy is the thing that we're, that we're focused on. The percentage over model input that we have built into the spinning power model helps us to understand if we are doing, we are improving or degrading against the current business trajectory, right? So percentage over model is positive. That means we are producing a stronger business outcome than the historical performance of the business would warrant. If it's a negative percentage over model, then that is leading to a worse outcome than the current trajectory of the business. And so a way to identify like. These changes we made to the media mix, are they leading to a percentage, positive percentage model or negative? The changes to the marketing calendar, to the website and the product from the merchandising, right?

Like how, how are these things contributing to the overall trajectory of the business relative to its current state? And so when we see percentage over model, 30% higher, 20%, 6% higher, to your point, Lacie, what that's indicating is that the business is improving against what the historical performance of the business would, would warrant us to expect, and it helps us to quantify what that outcome. Would be. Now you brought up another, another point, which I think is which is an interesting one, I I wanna dig into around the around the budget allocation and how we thought about that during some of these months. So Brian talked to us about how for that brand in August, the home gets brand that we looked at.

The first step was identifying what is the minimum necessary. sort of fi fixed cost obligation that we need to produce profit for, right? To then understand how hard we can push on the acquisition side of things in relation to that in the spending power model for for those that are aware, we have sort of three out of the box optimizations, max contribution margin max, lifetime contribution margin, and max revenue.

Each of these are different layers of getting outta business objective. You wanna maximize contribution margin in month. One from your new customers. If you wanna maximize revenue from new customers in month one at break even contribution margin. But Lacie, you have a specific budget allocation set for each of these months.

Talk to us about what are some of the constraints and goals that you considered in determining the optimal budget allocation against these business targets?

[00:34:23] Lacie Geary: Yes, yes. So for this apparel brand. years past, there has been some inventory difficulty where they have maybe overdone it on inventory and then contracted too far on inventory. So this year we took the swing. We invested in a larger amount of inventory, and this plan helps them get through that. At the maximum contribution margin that they're looking for per item based on the product inventory forecast. I think what's interesting in this case is that if you go back to the Home Dash, you'll see that the, the Red Months are actually like sale months. And it's funny because historically they relied a lot on sales, whereas now we have this great acquisition churning pipeline that's increasing their evergreen months above expectation. So what's happening here is that you'll look at this and be like, man, you could spend more and make more contribution margin. But the problem is, is that we're selling out of inventory too fast. that's the main constraint is inventory and just making sure that we're not. it and actually chopping down on the margin expectation that we set for the year based on the inventory that we've ordered. So that's the main constraint that we're operating off of here. And the spend just backs into that at the contribution margin that we're happy with in order to reinvest into years to come.

[00:35:47] Luke Austin: Great. Yeah. Such, such a great point. The, the inventory consideration as another input to how hard can we push on the acquisition engine and what the constraint is that exists there. Is, is, is fascinating and, and really important. So, we talked about a couple things in the planning section.

Lacie, anything else in regards to the planning process and initially setting the forecast that are important to highlight here before we transition to talking about some of the execution that has enabled us to land within this delta.

[00:36:14] Lacie Geary: Yeah. I think the main thing outside of just spending power is making sure that you have a very deep understanding of what was the product mix like last year? Like what drove a lot of the revenue? Was it a specific. Button up collection. Was it specific pant collection? Because what another thing with like, just making sure you're covering all your bases on the risk side is evaluating each and every month and making sure that you don't have any substantial gaps, whereas like, say March last year, button ups made up. 80% of your revenue, but this year the button up inventory and the plan for the button up collection isn't as substantial. So those were the other pieces that went into the planning process just to make sure that we completely eliminated any risk and that we had the content that we needed to hit the plan for the specific items we wanted to sell through.

[00:37:05] Luke Austin: That's great. That's great. So inventory considerations as a whole to understand how much we can push on the media spin and drive acquisition, and then. The product mix to then understand the downstream impacts of the creative output necessary. How the product mix is gonna change the ME on the website to be able to enable that.

That plan. Great. Okay. Talk to us about the execution then on the other side, we lock in the forecast, we lock in the plan. Now we have to go and make it a reality. What are some of the key ingredients that have led to making that happen for this brand?

[00:37:38] Lacie Geary: Yeah, for this one in particular, I think what's really great is that. apparel brand, the quality of their products and the look and feel of them translate extremely well into creator content. And a big part of our plan for this year was to scale significantly into paid media and acquisition.

And that had everything to do with the volume of creator content we could get into the account. So what we had to do is we had to use the creative demand planning. Understand how many ads we would need in order to hit up to our spend plan, and then make sure that we had enough creator content to hit that plan. Shout out to Adrianne's creative team on this. That has helped in addition, and even the owners have created amazing videos, so that part of the execution was crucial in getting these evergreen days above target and getting us to that 0.1% overall for the plan.

[00:38:34] Luke Austin: That's, that's great. And we don't, we don't have a visual up here, but what we've, what we, what Lacie's referencing is the fourth of our model. So we have spinning power model, retention model, event effect model. And the creative demand model, creative demand model helps us understand, to Lacie's point. Against this, the budget allocation for that specific time period in the year. What is the total creative output volume necessary to be able to hit those targets and to under, and to be able to quantify exactly how much, how many creators do we need? Do we need 80 new ads or do we need 800 new ads?

And by the way, we've seen both numbers pretty consistently. And every brain is, is somewhere in the, is somewhere in that, that range. And so think what's, sort of surfacing in the things that you're bringing up. Lacie is one, understanding where the current business trajectory is at, and then understanding where we'd like to be against that as the first, as the first point in any of these conversations, right?

Here's the, here's what's likely to happen. Here's where we'd like to be. Okay? Now. There's a couple key constraints and considerations we have to have, and knowing how much we can push against the light, the what we like to happen scenario, the higher scenario, right? Inventory being a big part of it, the contribution margin and the profit necessary to cover you know, fixed expenses and obligations within the, the current time period, which Lacie and Brian both. Illustrated. And then with that, what is the creative volume and the product mix necessary against against those creatives to be able to drive that outcome forward And all these things cascading on one another to be able to get from planning process all the way down to execution and ensuring that.

The things that are running in the Meta Ads account actually ladder up to what the business objective is and the inventory we have available. Right. Like, the connecting, the connecting these dots is, is challenging. It really is challenging. It requires a system that takes all that into account, but it's crucial to make sure that the plan that we have to creative output, that we have actually maps to the business outcome that we want.

Right.

[00:40:33] Lacie Geary: Exactly, and

[00:40:34] Luke Austin: So it could be like, yeah.

[00:40:36] Lacie Geary: crucial to that, like we've got the content, we've got that, we've got the whole system executing how we need it to. The second part to this, and this is something that's become more expansive in C'S network just recently, is the product level reporting. Pulling in your ad performance by product, your efficiency per product, your revenue, and how that's pacing to forecast. That has been extremely crucial for this brand because we come into moments where we have a piece of creator content that's smashing and it's actually selling through too fast. At a margin, like it's getting to the point where we actually need to increase ROAS targets. In order to maximize the margin because it's selling through so fast. So you've pulled this up, which is great. One thing we folded into here is their percent to forecast. It's an import range from their product level forecasting so that we can tier things out and understand, okay, if a product is labeled tier one, let's hit the gas like we are behind forecast. We have to pump harder if it drops to a tier three. This product is selling way too fast. We actually wanna take as much margin as we can. Let's increase ROAS targets. Let's slow the pace and, and just max out. So that has been super important part of making sure we're hitting forecast, but then maximizing across our opportunities day by day.

[00:41:54] Luke Austin: Yeah, that's great. And what, what we've got up here is our product matrix report that as Lisa mentioned, pulls in, by individual product or product category, the revenue orders and ad spend for each of our channels against each of those product categories. And we distill that into two main reports.

One is a Pareto matrix, which helps us to be able to see the distribution of orders that come from each of the core products and product categories. So, what are the products that are leading to the top 20% of sales volume, the middle 60, and then the bottom 20%, and being able to look at the distribution of where the sales are coming from on, on a product and category level. And then the product MVP report, which layers on. Ad spend investment against each of those products backs into contribution margin for each individual product or product category, and then helps us to identify things like which, which products are potentially, are we underserving the opportunity against those based on the profitability they're driving versus the volume against them. Which products are sort of core growth drivers of the business, which products are underperforming or categories are underperforming that we should think about reinvesting or reallocating the dollars away from? So topic for another conversation. We can go so deep here, but it draws the through line of we start with a plan of what is likely to happen, bridge the gap to what we would like to happen. And then within the context of that, consider the inventory, consider the business cash obligations to be able to understand then what products we can push on and how aggressively we can push on each one. And then what the creative demand and the media plan is against each of those pieces. And then we track against it in real time to see what's actually coming through and what's materializing and make adjustments against each of those. That then helps to inform the forecast for the coming month. And it's a virtuous cycle that allows us to land plus 0.1% to revenue forecast over the course of year to date still, dunno how much I believe that number, but it's here.

So,

[00:43:53] Brian Sakansky: Oh, come on, LA Lacie's. Got it. Lacie's Got it.

[00:43:58] Luke Austin: Alright, so I think that wraps it up. Got to our top growth strategists here who have landed closest to forecast, year to date across their client portfolio, portfolio sharing in the planning process, execution process, or the key considerations that led to that outcome. Brian, Lacie, anything else that you would like to leave? The folks listening with.

[00:44:19] Brian Sakansky: I would say key summary for me is something you said, Luke, around, you know, we go into the month with a plan.

[00:44:26] Luke Austin: I

[00:44:27] Brian Sakansky: With the forecast. That's our expectation. But really what the system is designed to do is to give us insight into the metrics that we need to then adjust for and make a plan for in order to keep getting better over time.

Like the methodology in the system is just as much, if not the most important thing, then actually hitting the number at the end of the month. Not to say that targets are not important, but the system that we're operating on is so crucial. So even looking at this and seeing laces. Client, you know, as an example, is just like so much food for thought about, oh, how can we then adjust on my book of business for certain things going forward?

It's just this, you know, reinforcing cycle that produces so many learnings over time and just makes everybody smarter over time.

[00:45:13] Lacie Geary: For sure.

[00:45:14] Luke Austin: great.

[00:45:15] Lacie Geary: for my side, I think the biggest takeaway is if you can have all the tools to understand where your challenges are, where your risks are. Then you can create a plan that not only hits your forecast, but also it allows you to contingency plan against your risks. So that chart looked really pretty like, oh, like everything went great, but like there was a lot of work that was done with all the modeling and what we saw to say, okay, we have a risk here. can create a contingency plan if that happens, and I think that's another like beautiful part of all the tools and stats is that you can foresee challenges and you can pre-plan for them and then you can implement your plan B or whatever you need to do to make sure you're executing to hit the target no matter what happens.

[00:46:04] Luke Austin: Yeah, it's great. It's a great point. And I would just, I would just add, once we lock in a forecast at the beginning of every month, we don't change that forecast. And so what it does is it sets the expectation and the obligation of this is what we're committing to. This is the forecast that we're going to go make happen now.

It's an obligation to go get after and the changes in terms of the merchandising, the product focus and the creative output and the media playing against it. And we can go on down the line of the changes and the different levers that we can, that we can adjust in pursuit of that. But the, the revenue forecast is set.

We align on the obligation, and then what it does is gives us clarity on where we're ahead or behind to then be able to go, make, make the adjustments. Like, like you said, Lacie, so. great. Thank you all for taking the time. If you still stuck around, this is a longer episode than normal. But but so much good stuff here, Lacie.

Bryan, thanks for joining. And we will likely do this again sometime soon, maybe with Lacie and Brian again, or maybe with an up and comer that lands closer to forecast. We will see.

[00:47:05] Lacie Geary: Thank you for having us Loop.

[00:47:07] Brian Sakansky: Yeah. Thank you Luke.