How to Plan Hour-by-Hour Spend for Black Friday & Cyber Monday

[00:00:00] One of the things that gets talked about a lot every year is this idea that like. Is Black Friday, cyber Monday, starting earlier. And it's like the biggest waste of energy news cycle ever. Because you can run your sale whenever the hell you want and if you have a big email list, you can certainly affect your own revenue.

[00:00:14] But customers shop on Black Friday and Cyber Monday. That is like the cultural behavioral tenet that you are not gonna change by changing your offer. And every year we see this revenue flow in the same way. The excitement and enthusiasm really begins on bla on. Thanksgiving where you can see Thanksgiving morning prior to all of us sitting down for dinner.

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[00:01:32] hello everyone. We're back for another jam session today. For chat through today, we're gonna talk about Black Friday, cyber Monday hourly tracking and planning.

[00:01:45] So we're gonna go through a little bit about the shape of each day. How that affects how we think about planning and executing within the context of that day. And Luke's gonna take you through exactly how we would manage and execute against, these numbers, but how many of you like, this is, this is a topic that comes up every Black Friday and Cyber Monday, like in your head, can picture the shape of revenue flow by day for Black Friday, cyber Monday.

[00:02:12] So we're gonna talk through this a little bit specifically how it affects media buyers and the allocation of our spend and actions. One of the things that it tends to wreak havoc on is how you expect. Your ad spend and revenue realization to pace and what it makes the perception of your ad account look like in the mornings, how you map this flow and expectation against your own brand's history as well.

[00:02:35] So I'm gonna, I'm gonna roll through some of the historical stuff since a lot of this will be things that you guys have seen. Okay. So just some, just some fun facts in terms of like a little bit about the overall impact of these days. Not that we all need to know that it's important, but historically we've seen November and December account force anywhere between 23 and 26% of brand revenue on aggregate.

[00:02:57] So you get about a quarter of the revenue in two months. That's growing a little bit, not too much. In terms of the total overall percentage, the total amount of revenue that we look at it was growing for sure in those periods, but the percentage always sort of stays about the same. There's about 23% of the revenue that comes from brands over the course of these two months.

[00:03:14] Last year was really weird because we had the month, the weekend was basically split in half between November and December. This year we just have one day. So we pick back up Sunday in in November, Monday still sits in December. This wreaks havoc on comps for year over year, for those months. So just keep that in mind as an upfront.

[00:03:34] So as we think about this, we're always moving from an annual plan that breaks down into a monthly set of expectations that breaks into a set of daily expectations. And then in this period of time, we actually go all the way to doing it down to the hour because there's so much. Revenue realization in this period of time.

[00:03:51] But that's always the tricky piece. We got three of the four days, if you call it Turkey five or whatever the hell they're calling it these days. We get four of the five days. Monday still sits in December. So your annual comps are gonna be a little bit weird, but okay. I wanna roll through the flow of like, when does revenue show up?

[00:04:06] One of the things that gets talked about a lot every year is this idea that like. Is Black Friday, cyber Monday, starting earlier. And it's like the biggest waste of energy news cycle ever. Because you can run your sale whenever the hell you want and if you have a big email list, you can certainly affect your own revenue.

[00:04:21] But customers shop on Black Friday and Cyber Monday. That is like the cultural behavioral tenet that you are not gonna change by changing your offer. And every year we see this revenue flow in the same way. The excitement and enthusiasm really begins on bla on. Thanksgiving where you can see Thanksgiving morning prior to all of us sitting down for dinner.

[00:04:41] We do do some shopping. Then there is a very clear lull during the periods where people are eating. You can see between about 2:00 PM and 7:00 PM everyone stops and consumes their food and then. Usually around this six, seven o'clock hour, the first emails start to hit and it's like Black Friday sale starts now.

[00:05:00] You're done eating. Come shop with us. And you see there's a peak that comes in this period of time and that looks like, wow, that's a big peak. There's a lot going on, but it's really not that impactful still. Thanksgiving as a meaningful moment. Now Black Friday, the day itself is really important to understand the flow of because it is very unique.

[00:05:20] I want you to think about Black Friday and Cyber one day weekend as generally speaking, a horseshoe that begins in the morning of Black Friday and ends at the night of Cyber Monday. And then in between it kinda recreates that same you you pattern. So at the end of the day, you end up with this arc that goes from the morning of Black Friday.

[00:05:37] Cyber Monday is the biggest peak of the whole thing. This hour between about, this is MST time. So Mountain standard time from about seven to about 11 is the largest peak of the whole thing. The whole thing. So why is this so important? If you miss the morning of Black Friday, you miss, that means that your attentiveness to the spend and allocation of your budget needs to predate this peak.

[00:06:06] And this is one of the first things that screws people up is that you show up and you wake up Friday morning and you've spent a shit ton of money and the efficiency looks really bad. 5, 6, 7 am on Black. Friday morning, you're gonna spend a bunch of money and your row house is gonna be shitty. If you respond to it, you're gonna screw it up.

[00:06:22] So understanding this allocation and this peak that we're going hammer the morning of Black Friday, cyber Monday, and we're going to trail off the rest of the day from there is a really important understanding of that and to contextualize this against Thanksgiving, it's way bigger. It's way bigger than Thanksgiving.

[00:06:39] So we talked about like, ooh, yay, there's this exciting peak after Thanksgiving dinner. It's basically inconsequential, it's tiny in comparison to what happens on actual Black Friday, cyber Monday. You can see the peak of Black Friday, cyber Monday, about four times the size, about three and a half times the size of the peak of, of of Thanksgiving, and about four times the peak of the same time period, day over day.

[00:07:02] So way larger. As we get into Saturday, we see sort of a, a similar flow where again, we come morning, peak trail off starkly throughout the rest of the day. And it will easily beat Thursday. It's gonna be bigger than Thursday. Generally speaking, Saturday the peak will be about 50% of Friday and decline faster throughout the day.

[00:07:21] So if you want a very simple heuristic, Saturday beats Thanksgiving, but is half a Friday. That's like a very simple rule in aggregate across most of what we see in Black Friday, cyber Monday, Sunday. Again, here's that mini horseshoe within the bigger horseshoe. Saturday morning, Sunday peak. Okay. Opposite direction where it's a little bit slower lag throughout the day.

[00:07:42] Peak moves a little bit further out into the afternoon. This is normal for most Sundays. It looks similar to Saturday, but the peak is slightly later in the day. Revenue expectation for Saturday and Sunday are fairly similar. Now the big difference is Cyber Monday. Cyber Monday, the highs are back Monday peak is just shy of Fridays.

[00:07:59] So if you look at like 24,000 average revenue per hour was the peak that we saw on Black Friday, cyber Monday. Or on Black Friday, cyber Monday gets to about 20,000. It'll be very strong throughout the day. 30 to 40% better than the weekend peak. But the real key is the evening, and this is where people screw up, is that this period right here and working inside of an agency, I can tell you.

[00:08:20] There's this big joke that we all start making in Slack around four o'clock where everyone is panicking. It is like this day has gone to shit. My cyber Monday sucks and it's hold, hold, hold, hold, hold. The bump is coming. The bump is coming. The bump is coming, and this is where you get that last frenzy of energy at the very end of Monday, right?

[00:08:39] So peak Friday morning peak Sunday night. In between, we get down to about 50%, but if you behave. And you start looking at your revenue realization in any of these days in comparison, if you start comparison the revenue realization between Cyber Monday to Black Friday, you're gonna be like, my cyber Monday sucks.

[00:08:58] We're blowing this shit. What is happening? They pace very differently. In terms of when the revenue shows up in each of these days, which means my expectation of how my, the allocation of my media and the realization of my revenue needs to be lodged into an understanding so we don't alter our behavior relative to an expected norm.

[00:09:17] So this is really important. Now, what I would say is you need to see this data for your brand. Aggregate data is generally useful and specifically useless. Yours might be very different, and it might be different for some very specific reasons. So one of the things that I would encourage you to do is to, we're gonna give you an opportunity to do the, we will do this for you very simply with stat list.

[00:09:35] But if you don't, you can export this through Shopify or, or, or Meta, and you can plot the revenue by hour in a very similar graph. The other thing that I want you to do is I want you to, annotate this using when you sent out emails. So you're gonna grab a little circle and you are going to plot on the hours that you sent an email so that you understand why you created the revenue for your business.

[00:10:02] When it was created and why. So as you go back to build your revenue, hourly revenue expectation for this year, you don't look and go, what the heck? We just had a really shitty hour, and it just turns out you sent an email that hour last year you didn't this year, because that happens all the freaking time.

[00:10:17] I watch people panic and go into hysteria and she's like, oh, our email went out an hour later this year. Than previous years. And it's also important to understand like, when do we want to send emails relative to how this behavior shows up and when people are most attentive to it? Right. So with this plot, if you export this, show it, then you're going to have visibility to understand, okay, we have an expectation of when our revenue's gonna show up.

[00:10:39] We can plan our emails accordingly. And then. Because the rule is how many emails are you sending on Black Friday? The answer is, as many as it takes to get to the revenue. You are going to create an expectation of each of these revenue, these emails, to generate a certain amount of revenue in that hour.

[00:10:53] And if you're a header behind, you're gonna respond and adjust accordingly, right? Because that's the goal. Course correction is the plan. Not get it right on the first try, not We're sending a fixed number of things. It's an expectation of a goal. That course corrects relative to the expectation that shows up.

[00:11:08] So, Monday you'll see that overall the volume will be lower than Friday, but it absolutely mashes the weekend. So we see some brands Monday operates, perform Friday certainly happens, but in aggregate it's about 85% of what we see on Black Friday but well above the weekend. So this is Monday versus the weekend that you can see here.

[00:11:27] And then another question a lot of people have is Tuesday. Tuesday is sort of when people will like to extend their sale or try to drag it on, or giving Tuesday or whatever moment you would try and create. But the reality is the moment has passed, the culture has moved on. Now the good news is it's not a normal day expected to be significantly higher than a normal day, but you're looking at volumes approximately half of Monday.

[00:11:47] So if Saturday and Sunday are half of Friday and Monday's, 85% of Friday. Then Tuesday's gonna be a little bit less than Saturday, Sunday. Just think of it as like 85% of Saturday, Sunday. So as you're thinking about a general pacing, of course you can look at this for yourselves. If you're wildly out of whack of that some way your Saturday was way worse, your Tuesday was way worse.

[00:12:05] There's a good question of asking why, what are we doing different than everybody else? So those are some good rules to gut check in your head about that pacing.

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[00:13:10] I.

[00:13:10] And one of the things I want us to recognize, and this is sort of a lot where the principles broadly start to manifest themselves when we get into these kinds of moments, which is that you begin to dissect for yourself. Revenue is the byproduct of an action.

[00:13:23] What action did I take? What revenue did it generate? And therefore, if I want to generate future revenue, what actions do I need to insert in order to create that effect? And that's like the general principle of our system across the whole calendar year. And it just gets hyper concentrated into this period of time where actions in response times are very tight.

[00:13:42] If we think about, most of the time we spend money and the realization of revenue paces over let's say a 28 day period. There's a big tail on day one falls off, and then long tail running really beyond 28 days. In many cases. This is the same thing, just hyper concentrated into a 24 hour period where you're seeing the revenues, realization cycles tighten a lot.

[00:14:02] It's the smallest, delayed attribution period of the entire year. Most of the revenue you realize will be realized within the day of spend for Black Friday Cyber Monday. But it's just tightened cycles around the same philosophy throughout the whole thing. Luke, I'm gonna, I'm gonna kick it to you now to walk through like, all right, there's the shape of revenue, there's hourly expectation. What do we do about it? How do we make sure that we're getting where we need to go?

[00:14:23] And you can talk a little bit about how we manage this moment. Yeah. So I'm gonna take a moment to zoom out. First, we're gonna get to the hourly pacing and how we've solved for this. But before I get there, I'm gonna take zoom out just for like five minutes on what is going to feed the hourly expectation for us in terms of how we're backing into what the daily and hourly expectations are.

[00:14:47] Many of you may be familiar with our spending power model or spin a MER model, but I think it's important. This came up in some of the conversation already of how we're accounting for. The month as a whole. So in, in the spending power model or spending R model, we've got one of these examples up here for a brand.

[00:15:03] And it's accounting for the seasonality impact of these moments, right? To, to an extent where the output of the spending power model for November is spending twice as much as October at basically the same a MER efficiency, right? Because of the seasonality impact that we anticipate, right? So. The spending power model is gonna get us to what is the optimal total budget allocation for that point in time?

[00:15:26] Accounting for the seasonality impact, and that's the starting point before. Before we even start decomposing this down into daily or hourly targets, is the monthly expectation. Take into account the seasonality and understanding what my total budget should be for that, for that period of time. And that's why we're able to scale up substantially into November.

[00:15:44] And in this case about two x amount, the amount of span at a very similar A MER efficiency and December has a similar, similar story to it. So we start with the spending power model. This is the optimal total budget allocation. That's the purpose of this, this tool. And then from here, before we look at the hourly pacing we have the monthly budget allocation, and then we back into the daily the daily expectation of that.

[00:16:09] And for. In forming the daily expectation, that's where our event effect model comes into play, right? So we have the monthly expectation from the spinning power model. Now we have to get back into daily targets. That's gonna be done by the event effect model. And these are a couple examples here of those, how these events play out, where we have all our historical marketing moment events tagged for the brand, and we can see across product launches, promotions, seasonal events, cyber Monday, black Friday.

[00:16:36] Cyber week, what the impact of these individual moments are on increased A MER efficiency and then increased returning customer revenue as a percentage of total, because that's, that's what we see when there's a big moment, right? We know our A, we're, we know we're gonna be able to spend more at a similar A MER efficiency, right?

[00:16:53] We're gonna be able to spend twice as much in November at the same am ER as we were in October. The same holds true on a daily basis relative to these moments, and we also know. That our returning customer revenue as a percentage of our total revenue is gonna be higher than it, than it normally is.

[00:17:07] And so the event effect model helps us to back into what that daily expectation is. And so you can see here. For this brand, cyber Monday and Black Friday, these are the specific impacts of those moments on a, on a daily basis. So on Cyber Monday, we can expect an A 35% improvement on our A MER efficiency relative to a normal day and the ability to spend at a higher volume, and then our returning customer revenue is gonna have a different relationship as well.

[00:17:35] This is projecting out 379% increase above our baseline relative to our returning customer revenue. So if normally our returning customer revenue relative to our new customer revenue is one to one, this is gonna be 3.8 x higher in terms of the amount of returning customer revenue we're gonna bring in on that specific day.

[00:17:53] So. The marketing calendar events are, we're looking at the spending power model. Here's our total budget allocation. The event effect model is looking at each of those individual days and what the expectation should be on the daily level based on that marketing calendar moment. Now we can get into the hourly decomposition, right?

[00:18:13] Monthly, daily, hourly targets. And that is where. The our hourly report comes into play where we take what's been informed by the spending power model and then the event effect model based on the marketing calendar. And we decompose that down into hourly targets that we track against throughout the day to see how far we are pacing ahead or behind at the expectation that that has been set.

[00:18:39] So to bring up a couple points as it relates to the hourly target tracker. What we'll do in terms of setting hourly targets. Is, we'll take that daily target that we have set and then we'll look at how the revenue shape for this individual brand has been in, in historical time periods, right? So for Black Friday, what was the revenue shape for the specific brand?

[00:19:01] And then set the hourly revenue targets accordingly so that we can pace against it. So these are where these, these two conversations converge, right? The shape of the revenue. For the brand specifically is then how the hourly targets get set and we can track, we can track against them. So the example I have up here is Black Friday of last year, so November 29th, 2024 for this specific footwear brand is what we are looking at.

[00:19:27] And what we're able to see here is I'm looking at comparing my hourly pace, pacing against the targets that I have set for that day. Broken down by last year's hourly pacing. That's how we're looking at it. Okay, so here's my, the targets I have for the day, but then the pacing is broken down by the shape, how the shape of the revenue was shown last year.

[00:19:47] So whatever my target is for this full day. The hourly targets are based on the shape that I can spec expect based on the pacing last year. And so you can see the visualization of that on the top here, right where we can see actual planned and in the last year line and how we're following that.

[00:20:03] So in this case. The last year and the plan line are following each other, right? In terms of the shape of them. So the, I'm, I'm planning for a similar shape of revenue, and then this dark blue, dark teal line is the actual pacing against that. So what you can see is early on in the day, we're pacing really tight, really close up to about the three 4:00 AM hour.

[00:20:25] And then this year, this year, what we, or last year, what we started to see is a five and 6:00 AM hour. Paced ahead relative to the year prior, but then you can see the, the afternoon hours are then what dropped down and we tailed off in having a similar, a similar day. And we have the, the hourly metrics book broken down for each of the metrics.

[00:20:43] Revenue spend, new orders. The efficiency on each of the platforms, the vol, the spin volume on each of the ad platforms, and we're seeing for each hour how we're pacing a goal and, and can catch early on when a gap starts to surface against the expectation. And then know where we may need to course correct to get back on track.

[00:21:03] And, and one of the areas here for this brand last year. These hourly revenue numbers. You can see the 12 1 2 and 3:00 PM hours is when we started to really pace behind the expectation, minus 17% behind the goal, minus 17, minus 15%, minus 19%, and on down the line. And so what we had to do as a result to course correct, that is start to push more budget and bridge, bridge the volume gap to goal, right?

[00:21:29] And so you can start to see some of these hours where we are pacing. 40% had to spend 40%, 27% had to spend, 12% had to spend. We were starting to push more volume because we had underspent some of these morning hours, and that was what was leading to the miss in terms of the volume. So early course correction, to make sure that we don't miss out on the day's pacing is ultimately what we're after here to make sure that we don't stack.

[00:21:52] Once you stack two or three hours, and if they're meaningfully behind the expectation, it's a really deep hole to dig out of for the rest of the day. Right. So spending power model, event effect model to the daily expectation and then hourly pacing is following last year's shape of revenue so that we can make sure we're pacing on track to that level. The other thing I wanna show is like, so to the point of like how your ad account is gonna look and how you don't want to react to it. Like, lemme show you something. Can I share my screen real fast? Look so like. Your spend allocation, and this is the thing I hear people talk about all the time.

[00:22:35] They, they'll be like, Meta's broken. It's overspending against shitty performance in the morning on Black Friday. What's gonna happen? I'm just telling you right now, the spend allocation is going to proceed those bumps. So imagine I showed you the curve of Black Friday peak 7:00 AM nine to 9:00 AM.

[00:22:53] Trail off your spend is going to spend earlier than that. So you're gonna see peak around this hour, like five to 7:00 AM and it's gonna look dog shit. It's gonna look horrible in your ad account and you're gonna freak out. And this is where you screw it up. This is why this expectation is so important, is because when you look at it, and if you look in whatever attribution system you're looking, nothing has like a 20 minute time lag to purchase.

[00:23:16] Like that's just not. Anywhere what's gonna happen. And if you look at ROAS by hour, it just goes up, up, up, up, up, up as you spend, right? All throughout the day because you're realizing revenue off of the morning spend. The morning spend, the volume of spend in the morning is critical. If you lose the morning volume, it's actually really, really hard to make up value later.

[00:23:40] Now alternatively, you could look at Cyber Monday and see like a, a similar distribution of spend that spikes again preceding the peak. And so this is where it's like you have to anchor yourself into your flow of revenue by hour. When did I send emails? So that's another thing I watch people do all the time.

[00:23:57] Last hour was dog shit. Last year we crushed this hour. What happened? Oh, we sent the email at nine versus eight. And so now all of a sudden everyone's freaking out. We running around like chickens with our heads cut off. You need to know what hour did you make every send? How many cents would we have?

[00:24:11] What was the impact on what kind of revenue? Okay. That sets my baseline of expectation. If I make any changes to that plan, I've gotta expect changes to the realization. But the sooner you can get eyes on it, and especially around the volume of efficiency that you're getting and really understanding like what is a good 7:00 AM efficiency.

[00:24:28] Like that question to understand whether you're a header behind is really important because it's not gonna be your target. This is the key. It's not gonna be, so you almost have to build these little mini delayed attribution multipliers from the hours across the day, right? To start to set for yourself what is a good 7:00 AM because it's gonna look bad.

[00:24:48] And if you respond to that or you don't know how to respond, you could be doing awesome and miss an opportunity to go press on the gas or you could be doing horribly. You just don't know. And so setting some sort of contextualized expectation is really important throughout those hours. And that's where we, the thing that we'll try to focus on is we commit to the volume, especially early on and in the first, first half of the day.

[00:25:13] And you could even zoom out like it on Thursday and Friday of, of Cyber Week. Cyber weekend. Like we're going to commit to the volume to get there because the lag on efficiency in terms of what the platform is gonna be reporting. We know that these dynamics e exist, so especially they like Cyber Monday.

[00:25:29] What the phrase we'll use, hold the line. We're committed to the volume, especially for that first half of the day, where we're tracking total revenue, new customer revenue, returning customer revenue, and total spend, right? And making sure that we are getting to the volume necessary in terms of the on platform reported efficiency for.

[00:25:45] Meta or Google brand for the first six hours of that day it, it, it really is not gonna be helpful in the, in the decision making. The volume is what's gonna be necessary. And so us having transparency to the volume and how we're pacing against it, and whether we're over underspending, the expectation is the, is the most important thing.

[00:26:03] The other thing to remember is you have to think about this by channel two, which is to say that if we think about meta as primarily demand creation in most cases, and Google is primarily demand capture, again, I'm speaking more about search, not necessarily YouTube or sort of non categorical P max, but like then you have to think that the cycles are the same.

[00:26:20] So the the revenue are the spend distribution in Google. Follows a lot closer to the revenue realization 'cause it's like the tightest. It is the very bottom of the funnel. Last click action in many cases for the shopping event. So you'll see the peak spend hours in Google be really tight to the revenue, whereas meta precedes it.

[00:26:37] And so I think there's just little lags to these things that what you expect from Google is to be a lot closer to the revenue realization, whereas Meta's gonna proceed it. And so if you go back and look at your spend by channel, you'll see a little microcosm of how much the lag is in the normal universe shrunk down into a single day.

[00:26:55] And so it's kind of cool to see like, how much did my spend realization map to my revenue realization? In every channel. And how, what does that tell me about where it is in the funnel in terms of its creation of demand versus generation of demand?

[00:27:09] The other thing that's really important is to make sure that you don't, that when you map the targets that you obviously are using, not the f same Friday dates, you're obviously using the Black Friday day itself, and if you have multiple days. Chart multiple days, like the more that you can get the broadest revenue possible.

[00:27:26] Ask yourself questions about how comparable is this data? Am I running the same sale? Am I running the same emails? Do I have the same influencers posting? Whatever all the things that you are, that you're doing, the more annotation you can put on top of that shape, the more you can think about what you're doing and whether the actions are working or not.

[00:27:41] So I do think that. Anytime you try and model something, a model is useful in so much that the future is like the past, right? The second, that's not the case. In any substantial way, your behavior changes, the product mix changes than it is more inherent or, or more obligatory to you to start to.

[00:28:04] Deconstruct what might be different and why, and then to orient around wider error bars, like I think that's another thing to think about when you think about what is right or what do I expect to happen. A lot of times people want that to be a number, but I think about it as a confidence interval relative to the consistency of the underlying behavior.

[00:28:24] So, in other words, if I'm running the same sale, the same emails with the same product mix at the same scale, my confidence interval on the expected result is gonna be tighter. And so what I'm looking for is gonna be more consistent. If I'm running a new set of products with a new information, then I'm gonna have a wider range of expectation, and I'm gonna have to orient my behavior.

[00:28:43] Two, what do I do? In all of these ranges, it requires more planning because you need to be more flexible when you're less confident. So that's another thing to think about. Like my level of certainty underlines the breadth of my planning. The more certain I am about a result, the less backup plans I need, the less certain I am, the more backup plans I need.

[00:29:02] So that's always another thing to think about too, is. Does the data allow me confidence in the result? If so, okay, let's proceed. If not, then I spend probably more time on, less time trying to guess and more on contingency of what I do if I'm wrong, 'cause I'm likely to be wrong. We spent a lot of time on modeling and like I, the thing that it can distract people into thinking is that like we're playing a giant game of guessing m and ms in a jar, and we care about like the modeling shit I do not care about.

[00:29:28] What I care about is can I know how, how fast can I know I'm wrong so that I can fix it? And like, this is all about an exercise and execution way more than it is. Like my model's perfect, like there are infinite variables here. And so I want to just give myself visibility into. Is the thing that I thought was going to happen happening?

[00:29:45] If no, what can I do about it? So we always talk about having backup emails, backup offers, backup campaigns so that when that first email you fired off for some reason, flopped for whatever reason, then all of a sudden I'm not like, well, we had three emails planned and one of 'em just was shitty. No, no, no.

[00:30:02] You have n emails planned, which is the number required to get to my revenue goal. That's your email plan., what we will do though on the meta side, like to the point of creating optionality, having extra emails, bank, et cetera, is have scaling campaigns for meta built out, set up, duplicated, turned off. They're already through approval and review. 'cause the worst, the worst feeling is you're in the middle of Black Friday and things are firing and you would need to get something, you need to get some more spin going and yeah, you have to default to accelerated delivery 'cause duplicating campaign and it sitting in review for two hours during prime time.

[00:30:35] So. Having those campaigns sitting there a lot of budget on them. And then likely, likely in a, in a highest volume format so that they can just begin delivering immediately as backup is, is the supplement that we'll have to get additional spend through a conversion optimized campaign. And I'll just say like, I just don't think there's any day in the world that is more built for bid cast with inflated budgets than this weekend.

[00:30:56] Like just trying to guess at the available volume is just a fool's errand. It's just a fool's errand. Like I just do not know how you could possibly anticipate exactly how much budget is available to you at your target price that day. Like I just don't know how anybody could represent that they know that answer.

[00:31:11] And so I think that's why. Like even meta recently just published a bunch of stuffs about, and that like their, their willingness is to like put it at a million dollars because part of the auction input is like the available liquidity, like that meta cares about spending a lot of money and if you signal that you have available liquidity, that is a factor in the auction.

[00:31:30] So having the, the like million dollar bid cap inflated budget is like definitely a strategy. The thing I would just caution is that. You wanna know a place where you're really gonna pay fucking attention is in the ad set with a million dollars on a bid cap, right? So like this is all relative to your own comfort and risk profile.

[00:31:47] But that liquidity is an input that on a day like this, meta values for sure in terms of thinking about budgets because they want to spend the money. And if they can find a bid that works and there's lots of liquidity there, you are gonna get, it's gonna work really well.

[00:32:02] And then of course, this is what we do. Like, we're here to help you guys build this plan, model an action against it. So if building the full profit system and seeing the targets, 'cause what you won't get if you set up SAT lists is you won't get the forecast. You won't see your targets expectation, you'll be able to look at it last year

[00:32:16] no problem. If you wanna be able to get down to a daily expectation of everything and get the targets included, that's the work that we actually do. Luke, anything else on your end? Nothing to add. Cool. And excited to jam. Good to have you guys. Appreciate you. Thank you all for your time.

[00:32:30]