0:00 Most e-commerce brands are looking at the wrong number. They look at rorowaz, they look at revenue, they look at me, but very few of them actually understand how cash moves inside an e-commerce business, what financial models to use, and how all of this ties directly into paid media. And that gap between what the ad account says and what the bank account says is where most brands get into trouble. Today, I'm going to walk you through every financial concept that you need to understand. This isn't theory. This isn't MBA stuff. This is core application that we use every single day with the eight and nine figure brands that we work with. Finance knowledge ends up being the bottleneck for a lot of agencies and a lot of founders because the ad account isn't the business. Platform metrics end up being a proxy for performance. Most teams end up misdiagnosing their problem because they think they have an ads problem or a media buying problem, but a lot of the time it's a measurement issue or it's a margin issue or it's a cash flow problem. Good paid media strategy should always reconcile directly to the P&L. If the ad account looks good, but the business isn't improving, something 1:00 is fundamentally broken. Better data should lead to better decisions and a lot of reporting done internally in large 9-f figureure businesses to seues as well as small six to seven figure businesses between an agency partnership. A lot of it is vanity. So, we're going to strip it away in this video. Firstly, we're going to cover the P&L. We're going to be going end to end on every component of the P&L and how it translates into direct to consumer e-commerce and changes the decisions that you make on a day-to-day basis. Then we're going to go into unit economics. We're going to break down everything in unit economics that is important for day-to-day decision-m as it ties into paid media and the business as a whole. We're then going to be touching on metrics. This is the metrics that actually matter. I'm not going to be giving you 20 different metrics that aren't actually going to move the needle or change your decisions. You want metrics that fundamentally change your behavior after you read them. We then have cash flow verse profit. This is something that most smaller founders don't understand well enough. I guarantee every agency that's either 1:55 watching this or an eight or nine figure marketing manager that's working with an agency. The agency doesn't understand how to properly integrate cash flow versus profit decision-making into the ad strategy. And so we're going to be breaking down exactly how you need to be doing this, where the complexity of cash flow gets introduced into an e-commerce business versus any other type of client that you're working with across paid ads. And then lastly, we're going to go and put it all together. We're going to loop the P&L into unit economics, into metrics, into cash flow versus profit, so that you can make better decisions and you can know everything that you need within finance for ecom. Starting off with the P&L, we need to start at the very top of the P&L, which is revenue. Now, there's two really important components to understand here with revenue. Number one, there is a difference between gross revenue and net revenue. And the differences in decision-making are enormous between them. So, we're going to break that down. Number two is a little bit more simple. A lot of people know this, but people don't think through it because they don't run a 10, 20, $30 million 2:47 business, which is that revenue is not profit. And so, you can have a $10 million business that's running at 5% net profit and you'll be making 500k per year in profit or income. Now, technically, this won't actually flow through to income in an e-commerce business cuz net profit does not equal cash flow. Or you could have a $5 million business that's at a 20% net margin, which is healthy in ecom. And that means that you're making $1 million in profit. I would much rather every single day of the week own this business over this one. And the reason being is that a $10 million business is a much more stressful asset to hold than a $5 million business. And this is doing double the profit. I think in agency land and in revenue land, a lot of people overprioritize just arbitrary revenue growth with the idea that margin will expand. For a lot of early stage founders, margin actually never ends up expanding and they just get themselves into a bigger and bigger and bigger business with the exact same amount of profit that they were making 3 to four years ago. And let me quickly expand on 3:47 that statement. What do I mean by people scale to expand margin, but it doesn't actually work? Well, the logic when you scale an e-commerce brand is that you have three buckets of expenses. So you have cost of delivery. You then have marketing. And we're going to break all of this down and I'll show you exactly what's in each of them. And then you have operating expenses. Now operating expenses should stay relatively fixed in an e-commerce brand because you don't need to expand people that heavily. So as you scale up, what should happen is operating expenses should remain stable. So the blue line here will be opex. Marketing will go up as revenue expands. Cost of delivery will go up as well. And then here's revenue at the top here. So when we then calculate out profit, what's actually happening to profit? It's going up over time. It's actually expanding as a percentage on the P&L because operating expenses are remaining flat. Now the issue is is that for pretty much every small e-commerce founder that I've worked with, and for context, in the first four years of the agency, we worked with nearly 300 7 4:49 figureure e-commerce businesses. So I have a lot of experience working across that size of business. And what almost always happens is that seven figure founders are just not good capital allocators. And so operating expenses actually ends up going up faster than me and cost of delivery and therefore profit remains flat. It remains stable as a dollar figure which is obviously not a position that you want to be in. Now let's get back to revenue and breaking down the P&L. When it comes to revenue, you have net revenue and you also have gross revenue. Now the difference here is that net revenue accounts for returns, refunds, chargebacks, sometimes a discount allowance as well, whereas gross is simply their cash collected on topline. Now you actually see this within Shopify, but in other platforms you won't. It's also important to note that the Shopify gross to net breakdown typically doesn't flow through into accounting softwares like Zero, like QuickBooks. And so you will only get a net or a cash read within a P&L accounting software. You won't get a gross read. And this becomes really 5:50 critical for using the P&L to actually make decisions. So when we look at gross to net, this is really the data that you want to be looking at. And the reason being is that if you just have net revenue at the bottom here and you're looking at this within your accounting software, let's say you have 100K one month and then you have 110K the next month. When you look at these two revenue numbers, there's not really much that you can substantiate out of it. You can go, okay, revenue increased. We don't really know why. We need now need to look elsewhere in the P&L. Let's go and look at marketing. Did marketing expenses increase? Let's go and look at operating expenses. Did we add another staff member that's driving some kind of revenue in the business? We have to start looking elsewhere. But the answer could actually be above this net revenue number. If we go and look above net revenue, what we might actually see is that gross revenue across these two months is the same. Maybe it's 120K here and 120K here. But when we then go down to refunds, refunds in this month were at 20K, but refunds in this month were only at 10. Then we go down to discounts. There was zero change in 6:53 discounts and maybe shipping charges. All shipping is free on this store. And so then when we look at the difference in revenue for this month, the difference in revenue is actually coming from refunds, which is a line item that doesn't get encapsulated in most accounting softwares if you're not actually pulling through the gross to net revenue dynamic into the software. So really, really important that anytime you're looking at revenue, we're not just looking at net, but we're looking at gross through to net to understand these different levers cuz I could give a hundred different examples of this. Okay, we could change the discount line item. So actually refunds were stable across both months but the core difference was that there was actually 10k in discounts in the prior month and so because we had some kind of discount running or discount code that didn't get encapsulated in the following month and therefore that's why we saw revenue expansion. These are fundamentally levers that exist within the business to increase profitability increase net revenue. If we can decrease refunds we make more money. If we can decrease discounts we make more money. If we can 7:48 increase the amount of shipping collected at checkout, we also make more money. And so you want to be looking at all three of these levers because often there actually is profit to be unlocked in better optimizing these three numbers. If you can push refunds down a little bit, if you can push discounts down a little bit, if you can collect a little bit more shipping at checkout, which most people can do, most people underolct at uh checkout, you can improve the P&L. Next layer of the P&L is cost of goods sold. This is where people make a massive mistake in direct to consumer ecom, which is that they don't encapsulate all the actual expenses associated with cost of goods sold. Cost of goods sold isn't just the cost that you paid to the manufacturer for the item, but it's the total landed cost of getting that product from the manufacturer to yourself, then into the customer's hands. And so we have the product cost. We then have importing taxes and duties. We then have the landed cost. So this encapsulates the freight to get it to your warehouse. And then sometimes included in here, sometimes categorized into shipping and fulfillment instead is the cost of 8:47 shipping to the actual customer. So this would be shipping charges. And this will also encapsulate uh import taxes and duties if you're shipping internationally. Tariffs in as well as an example. So sometimes you'll go and encapsulate that here and just count it in cogs. Sometimes you'll separate the definition to shipping and fulfillment. But overall both of these sit under a category called cost of delivery. And so whenever COOD is used or cost of delivery, it is encapsulating all of the cost of goods expenses and then all of the shipping and fulfillment expenses. And this is where people really mess up product margin versus gross margin. This definition is super misunderstood. When you say these numbers to people, you'll always get different answers. So let me run through an actual worked example. Let's say that you're selling a $100 t-shirt. What we will typically get from a brand is they'll say, "Yep, on this t-shirt or on this category, we have 70% gross margin." But what they're typically doing here is they're going to someone internal within the wider team if it's a 89 figure retailer or if it's a smaller business, they're just going and looking at their PO and they're 9:48 going, "What did we actually pay for this t-shirt to the manufacturer?" And we paid $30 per unit. And therefore, they're going, "Well, 100us 30 is 70. 70 divided by 100 equals 70%." Now, this is product margin. This is not gross margin. And why this is so critical is because this GM number will be used in setting KPI. If we know what the gross margin is, we therefore know what percentage allocation we should be putting towards marketing to be able to ensure that we sell through this product. Now, with 70% gross margin, we would honestly probably be fine spending up to 20, even 25% on marketing to drive sales here. However, if this is actually a much lower number and we don't know about it cuz we're getting given product margin rather than gross, well, all of a sudden we're driving this product at an unprofitable marketing efficiency. So, we then actually find out that it's $11 on average to ship this to a customer. It's then $4 in pick and pack fees at the warehouse. There's a 3% transaction fee here, which is actually something I missed in the cost of delivery expenses before, which is transaction fees. They 10:50 always need to be accounted for in cost of delivery because it is a cost to fulfill the product. You have to pay that transaction fee. A lot of people put transaction fees in operating expenses which is a mistake because the expense is variable with revenue. And so we have $3 on transaction fees. We actually also have tax implications here. So of this $100, we were actually including tax, which was $9, which is a flow through expense. So we need to remove that. We then have the actual cost of landing this product to our warehouse. So yes, it was $30 a unit, but the actual PO cost a few thousand to get to us and ship via air freight. And so if we then cut that down into a unit byunit cost, that's about an additional $4 per unit. And then the last thing here that we still haven't taken into the picture is an assumed refund or discount allowance. And this is absolutely critical in the fashion niche because in fashion refund rates can range from 10% in some cases I've seen up to 80%. And so gross margin substantially changes when 80% of the product is getting returned. And so we also need to factor in a refund or 11:50 chargeback allowance. And then let's also throw in a discount allowance too because people might be using uh coupon codes here at some particular rate. And so let's have $15 of allowance here because this allows for about $5 in discounts to be used on average as well as about a 10% refund rate which is pretty standard within fashion. Now we go and add all these expenses up and we've got $46 in additional expenses to actually deliver on this product. That comes out to $76 in cost of delivery. So if we recalculate our gross margin here, which you do by taking price, you minus the costs and then you divide by the price, this equals 24%. Now, this is an incredibly extreme example where all of the additional variable costs here have significantly added out outweighed the unit cost. But you can see how there can be such a drastic difference between the assumed gross margin, which is product margin, and the actual gross margin within e-commerce. And it's because in e-commerce, you have all of these 12:52 associated additional variable cost that aren't there necessarily in brick and mortar retail. So, as we move down the P&L design here, we've gone through revenue, we've gone through cost of delivery, gross margin. Now, we're at marketing. Marketing is relatively straightforward, which is anything associated with marketing and advertising. The product falls into this bucket right here. So, this is anything on paid ads. This is any influencer payments. This is any events, this is any out of home. The big question here becomes does content production go into this bucket? And this is based on whether it is a variable expense or whether it is fixed within the business to meet the content demand. And so what typically happens through an e-commerce direct to consumer business is that content velocity or volume needs to flex throughout the year in conjunction with revenue expectations. And so a typical e-commerce brand will look flat through Q1. We'll have a spike at June for end of financial year sales. Will then build back up, have a big November, December, and then fall back off. And so your 13:53 creative production or amount of content entering into the ad account as well as obviously investment in influences, events, etc. needs to map to this. When you try to map creative to this flexing in demand, it becomes very difficult to do with just an in-house team because if you have four people, they're probably underworked here. They're probably substantially overworked here. And then this is probably the only time a year in which they have the right amount of work. And so because of that, it's not really an ideal model. So what you do instead is you have in-house here and then all of this additional flex up in creative volume requirements is typically done by agencies or you could pull in short-term hires that are just there to fulfill a 3-month period. Now these agency expenses that flex this is a variable expense that should go into your me. These fixed costs down here this should be associated with OPEX. This is a fixed expense that needs to be held for indefinitely into the future while content is king for being able to drive revenue. Now, as you then move into flexing this throughout the year, that's when you can make a variable. Now, some people would also argue that, 14:53 hey, let's just put all of this in the me bucket because all of this is revenue driving, which I also understand, but that's going to be where there's a little bit of custom design within how you're approaching the P&L at an individual brand level. Once we now go past ME, which is the second big expense bucket within an ecom brand, the biggest expense is typically cost of delivery. Second biggest expense is me. We now get to another margin, which is contribution margin. This is one of the best metrics for indexing performance over time. And I'll tell you why in a second. Now, contribution margin is relatively straightforward looking at this P&L design. It is total revenue minus cost of delivery minus all marketing expenses. And this will give you your contribution margin. Now, this can all be calculated as both a percentage and a dollar figure. So, revenue is 100%, you have cost of delivery at 30%, me at 20%, therefore your contribution margin is 50%. Now, why is this contribution margin number so helpful? Well, it's because if we're looking at it as a percentage, we are one step away from net profit. To get to net profit, all we 15:55 need to do over here is minus off OPEX. So if we know that opex in the business is kept relatively stable at let's say 10%. Well then that means that 50% minus 10% is 40% net. Now we will have a net target as a business. You might want to be holding 10% net margin or 20% or 30% net margin. You can then back math that into a contribution margin target. Right? So let me give you an example. Let's say you have a 20% net profit target within the business. Great. If you know your operating expenses will always sit at 15%. We then just need to work our way up the P&L. So over here we're starting at the bottom and we're working our way up and we can go okay net plus opex means our contribution margin needs to hit 35%. So we effectively have a contribution margin target that's really far up the P&L that ensures that we hit a net profit target. Same thing with dollar values too, right? So we might have a net profit target which is a million. We might have a million dollar in operating expenses. And so our contribution margin target is these two added together, which is $2 16:57 million. And so we know for the year we need to produce $2 million in contribution margin to be able to get a million dollars in net profit. Now, one further piece of clarification here is that you'll actually hear contribution margin being used, not in this definition. So technically, this definition is what's called contribution margin 3. Contribution margin one is product margin, which is what we talked about at the start. Now why people call this contribution margin one I have no idea. People are just making it complicated. Okay you can just call this product margin but sometimes people will call this CM1. CM2 is gross margin. So we also went through that at the start. This is including all variable expenses associated with cost of delivery. And then CM3 is exactly what we just went through here. This is typically called contribution margin. Just really important delineation because sometimes people will say contribution margin and they'll be referencing one of these other definitions which is a weird thing to do. I don't know why people do it, but just make sure you understand those definitions. The third largest expense bucket is operating expenses. Now, how 17:55 to think through what actually sits in operating expenses is very simple. It's just anything that doesn't go in cost of delivery or marketing. Now, the typical three big expense buckets here within direct to consumer is going to be people at number one. It's going to be software at number two, and then it's going to be some kind of office or fulfillment center here. Now it's important to delineate that actual product fulfillment like a 3PL or a warehouse the objective is to fulfill actually sits in cost of delivery. Same thing technically with warehouse staff. So if you have staff that are pickp packing and shipping product, you actually technically want that defined in cost of delivery. What you do is you take their salary and let's say take their salary per day. So maybe it's like $400 per day and then you divide by how many packages they ship per day. Let's say they manage 100. Well, then you would take a $4 per order expense and you would move that over to your cost of delivery in your actual accounting software. You can tag particular staff and your bookkeeper can do this and then they can reconcile into a custom P&L report that will have 18:57 warehousing staff in your cost of delivery. So, you'll have an accurate gross margin number on a month-by-month basis that encapsulates people that are actually fulfilling the orders. And then who you would want in operating expenses for people is everyone that's not associated directly with the actual fulfillment of orders. So this would be like your head of marketing, your head of operations, list goes on. Now the real key to operating expenses and where most 7 figureure e-commerce brands actually get this very very wrong is that they overinflate operating expenses believing that this is the way to grow the business. Cuz you commonly hear reinvest into the business. That's how you grow. But in e-commerce, the way that you reinvest into the business is actually to invest in marketing. This is the primary growth lever that exists within the P&L for a business like this. Going and simply hiring more people generally isn't a revenue generating exercise. Going and simply getting more software generally isn't a revenue driving exercise. Getting a bigger office generally isn't a revenue driving exercise. None of these expenses generally drive much revenue. Now people 19:56 are by far the greatest leverage that exists in any business. In fact, the ceiling of revenue within a business is generally the ceiling of the summation of skills and talent within the people that exist within that business. So, I'm very much so of the opinion that there is nothing more important on this entire P&L than the people line item. However, 7Figure e-commerce brands generally don't have the skill set to hire incredible people yet. Number one, they don't have a big enough business to attract incredible talent. Number two, they simply haven't hired, trained, and gone through enough interviews to be able to identify what those people look like. And I say that from personal experience. I've personally hired over 60 people in the last 5 years. And at the start, I had no idea what to look for. I was just going through interviews trying to figure it out. And over time, as you do more and more interviews, and to date, we've probably done near 500 to a,000 interviews. We have a pretty good idea of what a really good high performer looks like verse not. But when you're getting started, you don't. And so, people overinflate their people expense. They overinflate software 20:52 because they think this is going to drive revenue. They end up overinflating office and tertiary expenses, and it ends up destroying the P&L. So this is just a really important one to watch because honestly this is the in a larger business this is the CFO in a smaller business this is the owner's responsibility to be able to keep under control. So we can now run through the actual waterfall of the P&L here. So starting at the top and I'm going to use small numbers to keep this simple. We have $100 in revenue and let's just think about this as a daily revenue on a tiny business so it makes sense. Then we move down to cost of delivery which is $40. And so this business ends up with a $60 gross margin. Then the actual marketing expense here is 20% of revenue. They maintain a 20% me, which means that contribution margin is now $40. Operating expenses, these guys are keeping it at 20% as well, which is $20. Meaning all the way down the bottom here, we get to $20 in what we can define as net profit. Now, what you'll notice here is that I'm calling it net 21:52 profit here, but over here it's called IBIDA. The reason for that is that technically this $20 here isn't actually net profit. Net profit sits after we take out interest, tax, depreciation, and amotization. Now, a lot of words. If you're not familiar with finance, it's not really something that we need to get too deep into in this video. The only caveat that's really worth noting is that typically to fund an e-commerce business, most people rely financial tooling like loans. And the reason for that is it's very capital intensive. To actually be able to grow quickly, you need capital to make future inventory purchasing whilst also continuing to spend on media. And now with that, you have interest repayments on those loans. Question becomes, where does interest repayments go? A common mistake I've seen on a lot of seven figure and actually 8 figure P&Ls is that interest expenses will go into OPEX. This is not true. Interest should not go into OPEX. Now, the reason being is that interest actually isn't an operating expense. This is leverage to be able to accelerate the growth of the business. And therefore, if a buyer or a third 22:54 party wants to look at the true profit generation of this business, they do not want interest included in the IBITA number. Hence, you get interest before earnings, tax, depreciation, and amotization. Then your interest expenses go down here. And so, let's say that there was $10 in interest expenses associated with loans. Then you would have one last line item down the bottom here, which would be $10 in net profit. So there is technically two definitions. There's IBIDA, which is the capability of the business to generate earnings if it didn't have loans outstanding, which is what a buyer wants to understand because a buyer will just zero out the loans. And then net profit is the actual profit that the business ends up generating after these repayments are made. And this is the basic P&L structure at a high level. We can also, and this is a very valuable exercise that I'd always do, allocate percentages to each level of the P&L to understand relative percentages throughout the year because we want to be looking at these on a month-on-month basis to be able to understand how these percentages are changing. So, for example, our cost of 23:54 delivery is 40%, our gross margin is 60, our me is 20, our contribution margin is 40%, this is 20%, IBIDA is 20%, and then net profit is 10. And so then you can look at these percentages over time and go, are they expanding? Are they contracting? What is our target percentage allocations here? And this becomes how you can use the P&L effectively on a day-to-day or month-to-month basis to be able to make decisions. Okay. If me is creeping up, well, we know our marketing efficiency is declining and that's deteriorating and compressing the bottom of the P&L. So, we need to go and fix that. If our gross margin is compressing, we need to look into why that's the case. Is this a discounting issue, a returns issue? like what above the P&L is causing the gross margin compression. So the way to look at this is that if a target percentage or a target number on this P&L is not hitting target, the fault is everything above it. So if we're not hitting our IBIDA target, it's an issue with either or all operating expenses me cost of delivery. If we're not hitting our contribution margin target, it's an issue with me and cost of delivery. If we're not hitting our gross margin 24:55 target, it's an issue with cost of delivery or revenue. Because remember, revenue isn't just net revenue, but it's also gross. And so there's a few different levers in here that we need to look at as well. So this is how you troubleshoot the P&L. If you're not hitting numbers that you want, you want to look upwards and look at the levers that exist there that we need to pull on and that we need to diagnose. So that is the P&L explained. Moving into unit economics. So unit economics, how unit economics differs from the P&L is the P&L is a zoomed out view of the entire business. Unit economics is diving into a specific unit. Now what this would typically look like in retail is we would be looking at a single unit. And so if we're selling a t-shirt, we would be looking at this t-shirt and breaking down what is the price, what is the cost of goods sold, what is the cost to acquire a customer for this t-shirt, and therefore what is the net profit on this individual unit. Now, in e-commerce, in direct to consumer, this actually changes a little bit. And we're actually looking at baskets. And so when we talk about unit economics, we're actually typically talking about the basket 25:51 because an average cart doesn't just have one unit in it. Most people will buy 1.5 things or 1.7 things. That's called your units per transaction. And so because of that, we want to encapsulate multiple different products into any unit economic calculation. So the single most important component of unit economics is something that we haven't spoken about yet, which is CAC. This is your cost to acquire a customer. It's one of the most important metrics on acquisition and it's a metric that most brands calculate completely wrong. How you calculate this is you take total advertising spend over any given time period. So this could be on a daily level, a weekly level, a monthly level. And then we divide by the total amount of new customers that we acquired in that period. This is not the same as CPA in the platform because CPA is running off attributed numbers and will end up showing you a better number than is actually reflective within the business. And then people will also try to delineate CAC down to a channel by channel level, which is also impossible because you're relying on attribution. and attribution has a plethora of issues which is why we have this whole finance 26:52 video together because attribution is just unreliable. Now the first question that I typically get when I pull a trailing CAC calculation for most businesses is okay well what is a good CAC? You have access to over 68 n figure brands. I've personally consulted on well over a thousand brands to date. I have a pretty good reference what a good CAC looks like. The answer to what a good CAC is is that it's fundamentally actually the wrong question because CAC means nothing without contextualizing it to a pairing metric. And that pairing metric is gross profit on first purchase because you could have a $100 cost to acquire a customer. But if you're making $10,000 on the order, this is an unbelievable deal. You're paying $100 and you're making $10,000 on the order. That's insane. And so this could be like super high ticket furniture as an example. Or vice versa, you could be super low ticket selling lollies online, which is probably not a very good niche, and you're making $20 in GP. This is a terrible exchange. You're actually losing $80 on each new customer acquired here. And so, you need to understand 27:52 what is your gross profit on first purchase, and it's really important on first purchase. Cuz what people will do here is they'll take their average order value, which on Shopify, let's say it's $100, and then they'll take their gross profit percentage, which is typically wrong, calculated wrong. We spent a lot of time going through that and they'll go, "Okay, our gross profit on average is 70%. Therefore, we have a $70 GP, so we're happy with $35 CAC." Well, is this on new customers? Because returning customers always have a higher average order value, which pulls your average order value number up. And so, if you actually delineate down into new customers, you might find that this is actually 90 and that your GP is actually even lower because maybe you have more discount orientated front-end offers. And so your GP compresses all the way down to maybe 50. And so now your CAC targets are completely wrong in conjunction with your true GP. And so this is really just the important of data integrity within the business. These numbers need to be calculated correctly. You need to trust the calculations or else you're just going to scale off fundamentally flawed 28:52 metrics. So as a part of unit economics, let's go into pricing strategy because pricing becomes an enormous lever for profitability of the business particularly when products are underpriced. So, as a new e-commerce brand, what people will typically do is they will use keystone pricing. Now, I think anyone that's ever run a business or started an ecom brand has done this, which is that you take your cost of product, so you go to the manufacturer, product cost $10, and you just double it. This is what's called keystone pricing. So, as an example, a $6 cost of goods just gets 2xed and becomes a $12 price. So many people price this way. I reckon 40% of the startup market just prices in this way. This is probably the worst way you could ever price. Now, it's because this cost of goods doesn't encapsulate all the variable expenses associated with fulfillment. And so, you end up with way more compressed margins than just 50%. I think the reason why people use Keystone pricing is number one, it's simplicity, but number two, the fact that people don't want to overpric. People think that margin is bad. We can't have too much margin or else we're just ripping people off. But 29:53 because of that, they don't take into consideration all of the expenses associated to actually fulfill within a business. And so because of that, people underpric and they can never actually scale. Whereas the actual cost to grow a business in all of the variable expenses associated with fulfillment as well as all the marketing expenses associated and then operating expenses taking up 15%. It ends up being a lot. And so you end up needing to price way higher than just a doubling using keystone pricing. So the next pricing model that people jump to is IMU pricing, which is initial markup pricing. So this is effectively the same thing as Keystone, but rather than doing a 2x, maybe we do a 3x or we do a 4x or a 5x. So we're effectively taking the cost of goods once again, and we're just applying a multiple to this number. Now, that might seem better, right? You're like, well, Nathan said that the big issue with Keystone is you're not increasing by enough. So if we just increase to 34 5x, then surely that fixes the issue. It doesn't fix the issue because this is just an arbitrary multiple on a product cost, which has nothing to do with the price elasticity 30:50 of demand within the market. It has nothing to do with the competitors and it has nothing to do with the actual cost structure associated with delivering that particular product. And so, yes, we could just 4x it now and the price is $24. Amazing. But this might be substantially overpriced compared to competitors. This might still not encapsulate enough margin to be able to actually fulfill on this business model. And so, all of these things have to be taken into consideration. The real core takeaways here is that you want to use waterfall pricing from bottom to top to be able to identify the price that you need to actually price the product to make money. And then from there, you make the decision of do we even sell this product? So here's all the expenses associated with actually delivering on the product. We need to start at the bottom. So what is our actual contribution profit target here? Okay, is it 20%, 30%, 40% based on our existing P&L understanding and how much operating expenses we have. So you could really start all the way down the bottom here, right? And take this a step further and say that our net profit target is 10%. We know that our 31:47 operating expenses 10%. Therefore, our contribution target is going to be 20%. Okay, great. Now we need to start moving up. How much do we think it's going to cost to acquire a customer on this product? Now, based on our understanding, based on the ad account, based on other product, we think our CAC is going to sit at $30. Now, what's the return allowance? This is also called a shrink allowance, which is that we're allowing for shrink in discounts, returns, etc. Well, we probably want a 3% return allowance, probably a 3% discount allowance. Shipping and fulfillment on this product, we've gone, we've reached out to Opost or the shipping courier, and we know that this is going to be $11. Then, we have the cost of goods, which we know is $6 over here. And now we can work our way all the way up to pricing. So, we need to be priced at 30 + 11 + 6 plus 3% 3% of this total price. And then we need to come out to a 20% contribution margin. And so we can run all of this math, which I'm not going to do for the sake of this video, but let's say this takes us up to a $100 price cuz 100 - 6 - 11 takes us down to about 85. Then we minus another 6% which takes us down to 79. Take us 32:47 off another 30 that takes us to 49. And so down the bottom here, we have a $49 contribution profit, which is actually a really high contribution margin, way above our actual target. So if we just keep reworking these numbers, I believe this should come out to probably like a $70 price. So to hit this contribution margin target with this CAC with these unit economics, we come out to a $70 price at the top. This is how you price correctly and you then go and you do competitor research. And guess what? If this $70 price is ridiculous, if everyone else is pricing at $30, $40, well either number one, we need to figure out, can we position into a blue ocean where no one's actually selling a premium version of this product? Can we position this as premium? Can we sell at this price? And if we can't, we don't sell the product. The unit economics don't work end to end. If we can't hit our profitability targets by selling this product any less than $70, no one will buy it at $70. Let's cut the product entirely and not sell it. So that is how you need to be thinking through pricing strategy. Now you need to understand the unit economics of discounting. This is where most brands 33:47 destroy their margin without even realizing it. Now I'll give you a really quick worked example. So if we have a $100 average order value or product price, this means we're going to come out to a $40 gross margin. Now what we can do here to calculate our break even return on ad spend. So what return on ad spend do we need to be to break even is we take our gross margin which is 40%. So break even return on ad spend equals 1 divided by 40%. And this equals 2.5. So we need to achieve at least a 2.5 return on ad spend to break even and therefore make money. So this is the lowest we can be. Great. This is a really important number for not only your internal team and your agency to know because if let's say an ad set or a campaign is below this you're losing money. It's really important to understand what this number actually sits at, but more important to understand where this number sits at during a discount period. So, if we take this exact same example, you're on 30% discount. So, you get slashed to a $70 price. $70 price, your cost of goods stays the same. And so, we have our $60 cost of goods here. That then comes out 34:48 to a $10 gross margin. If we then recalculate our break even return here, our break even return becomes 1 / 10%, which is 10. So, our break even return on ad spend, the efficiency that we need to operate is 5x what it was up here off just a 30% off discount, which is crazy. And it's because discounting exponentially increases the break even return or the efficiency that needs to be hit within paid media. And so, anytime you're discounting, it is really important to run this exact calculation to be able to understand what efficiency level we need to be at. Now, all of this math can also be done based on a CAC or a CPA number. So rather than doing this division to calculate break even return, all you do is this gross margin number is your break even CAC. So your break even CAC just simply equals gross margin. So here break even CAC is 40. Here break even CAC is 10. Obviously a $10 CAC is absolutely insane. You're probably never going to hit that across paid platforms. Therefore, this discount will never work for acquiring new customers. So this shouldn't go out publicly. Now this isn't to say that you can't discount. You can't do blank discounts. Of course you can. You just 35:48 need to understand how it affects the efficiency targets within paid and whether you can actually hit those efficiency targets. You always need to just run that math which is that if we're going to do a 20% off discount, how does our efficiency on paid media need to change to maintain the same level of profitability or improve profitability? And if it's insane, if it's like we need to go from a 2x row to a 12, like well that is physically impossible. The discount isn't going to create that much of an uplift in demand and conversion rates. Therefore, we need to rethink the discount approach and what we're actually doing with this offer. And so, let me give you some other options. Well, bundling is a very big one. Everyone knows this. This is pretty generic, which is that if you bundle, you get economies of scale because you might go from one unit in the cart, too. But this doesn't increase your shipping and fulfillment cost from 1 to two. Generally, you will get maybe a 20% inflation in the shipping and fulfillment cost of the product. And so, therefore, you actually get better gross margin when you bundle. And you can give that margin away to the customer, and it 36:39 doesn't affect your GM percentage. Bundling also increases average order value substantially, which allows for you to have a higher cost of acquiring a customer on the platform and still make more money. And so bundling is still a really effective way to provide a discount to the end consumer, provide an offer that seems to have a value discrepancy in the market that allows someone to get over the line and buy, but it is beneficial to you in regards to the unit economics of that bundle. Another example here is a gift with purchase. And so this is where you just need to become good at calculating unit economics correctly on offers because this is what allows you to validate whether an offer will work. It allows you to bake in the assumptions and then you can go and actually run it in public. So an example of this would be if you buy two beach towels, you get a free bag that actually holds the beach towel. Now the beach towels might be $100 each is what they're priced at and they're pretty high margin. Let's say 70% or something. So you go and when people buy two, it's $200, but they get a free bag. And you can say the free bag is valued at or sold on the website at 37:38 maybe $50, $60. You can price it really high. It can be seen as a premium bag, but the reality is is that the cost of goods on this bag for you is maybe $4. And so you're going to forgo $4 of margin to get an extra $100 in revenue. Really good exchange. Okay, your gross margin is pretty much going to stay the exact same as a percentage, but you're doubling average order value by giving this free bag away. So gift with purchase ends up working really well if the offer is crafted well and if the gift is relatively low cost. And then the last is straight uh discounting which I just told you compresses margin a lot and you have to be really careful about. But the caveat here is that you can do this on grade C inventory. We'll talk about stages of inventory later in this video and we'll break down actual strategies to be able to move inventory and focus on cash versus net profit and the marketing strategies associated. But just as a call out, if you are going to do flat discounting, you want to do it on inventory that isn't moving. And then you can move that inventory back into cash. Even if it is at break even, it doesn't really matter because the inventory wasn't going to sell anyway. 38:37 Now, I can't talk about unit economics and finance without talking about LTV and repeat purchase rates. And the reason this is so critical is because acquisition is expensive. Fundamentally, it is expensive to acquire customers. Particularly if we start going into an industry like CPG, consumer package goods, you're not going to probably even be profitable on first purchase. And the reason being is that you just have competitors that will outspend you, outbid you at auction on Meta, on Google, and they can go and pay $200 to acquire a customer because they have this massive lifetime value that they can then realize on second, third purchase. And if you don't have that, you will lose because your competitors will just spend more than. And so lifetime value becomes a critical component in profitability of most business models. I can give you a completely different example of this outside of e-commerce as a whole, which is actually the agency model, which is something that I'm very familiar with. In the agency model, most agencies won't run profitable on first purchase or first invoice on month one. Most agencies will run at a 3 to six month CAC payback period. So they will spend X 39:35 amount to be able to get a client, whether that's associated with marketing, sales costs, etc., etc., networking, events, and then once they have a client, they will only start making money after 3 to 6 months due to the CAC. Same thing in CPG, same thing in fashion, retail, etc. Except in these other industries, you need to carefully and meticulously understand what your LTV actually is so that you can operate that model profitably. Because if you are an agency, let's say, and you don't understand all the associated cost to get the customer and you miscalculate CAC or you miscalculate LTV, you are actually in a very different profitability position and you can really negatively impact yourself. So, let's run through a quick example. Let's say you're doing 200k a month in revenue. of that 200k a month 140,000 is new customer revenue and let's say this is coming from 50k in ad spend that then means you have $60,000 in RC revenue and let's say that the cost here is like 2.5k which is associated clavio costs and maybe an agency associated with driving repeat revenue now your new customer profit contribution which isn't 40:36 a metric that we've gone through yet but it's just contribution margin but we're doing it on new customer revenue only this is 140 minus 50 So, we have $90,000, but we obviously also need to minus cost of delivery and gross margin. So, let's assume a 50% gross margin. That means that this is going to come to 70 - 50. This is going to be $20,000 in profit contribution that we're making each month on new customers. Now, what about RC revenue? Well, 30 - 27, this is 27,500 on return. And so this business, which is a pretty typical business in terms of new customer revenue to returning customer revenue percentages at this kind of size, this business is making more on returning customers in profit per month than they are on new. And this is super typical because majority of your profit ends up coming from returning customers. Now, why is that the case? Well, because it's very hard to get a new customer. You have to pay money to get them. Returning customers come back due to the product, the experience, and the brand affiliation. So you actually don't need to spend much at all on getting a returning customer and they drive tons of profit 41:38 contribution in the business. Now once you start getting into this position, that's where you start needing to understand, well, can we actually push up new customers even harder and subsidize this acquisition cost with all the profit that we're making on returning and continue to grow the business that way. And that's where I just want to provide a massive hesitation to most people, which is that most people calculate LTV wrong. Number one, they will calculate LTV based on just infinity. And so when we look at lifetime value, uh, as you extend the time period in which you're looking at how much a customer is worth to you, it increases forever. And so we can look at how much a customer is worth to us after 6 months and it might be $100. And then we can look at 12 months and it might be 110. Then we can look at 18 months, it might be $120. And as you just keep extending that time horizon, LTV increases forever. Now it does somewhat asotope. So it will look something like this. But still, if we measure from here to here, there is still an increase. And so what you want to be very careful of is not just looking at an LTV calculation based on total customer data 42:35 over forever and instead you want to restrict it to a particular time period. Now a good way to do this is to look at 90day or 180day LTV. The second delineation you want to make is you want to go to LTGP. You want to be looking at gross profit, not value. Now, LTV in the traditional value sense actually is lifetime gross profit. When we measure this against software because this is a software metric and in software, lifetime value is typically very close to lifetime gross profit and therefore it's the same thing. But in e-commerce, we want to make this clear delineation because some people and a lot of softwares actually will give you LTV as a revenue number. And so we want to understand what the gross profit are of these customers at 90 180 days and then we can use that to be able to understand what we can actually pay to acquire a customer. Now, let's take unit economics and apply it at a product level. So, on product level economics, let's say you have a hoodie that you sell and you sell it at $90 retail with a $21. So, you have a hoodie at $90, cost of goods 21. So, you have gross margin of $69. Our cost to acquire a customer through the 43:36 hoodie on our advantage plus scaling campaign is $45 right now. So, that's our CPA. We're just going to call it CAC. So, our contribution margin here is $24. Now, we have a t-shirt that's priced way less. Cost of goods is about the same. Actually, our gross margin is only 27, but we have a CAC of 15 and we have a contribution margin of $12. So, right now, the hoodie is driving 2x the contribution margin to the business per sale. So, this firstly is an important number for us to be across. Okay, understanding what actual products within the portfolio is driving us the most contribution margin when we break our unit economics down at a product level. The second component that becomes important here is understanding how we should structure our campaigns accordingly. Should we be splitting these out? Because if we're using a bidding strategy on Meta, Google, Tik Tok, which is maximize conversions, and this is the default bidding strategy on every advertising platform. When you use maximize conversions, what it's optimizing for is the lowest CPA. So, whatever product is driving the lowest 44:36 CPA, whatever ad is driving the lowest CPA, that will get prioritized, that will get the spend. Now, if we look at this example here, the t-shirt actually has the lower CPA. And so, Tik Tok, Meta, Google will distribute all your spend here, but this product is driving a lower contribution margin per sale. We would actually prefer Meta to put all of our spend up here. Yes, it's going to cost us a little bit more money, but we're going to drive more contribution margin per product sold. So this is the better place to put cash right now. Maximize conversions won't do that. Now you can fix this in the platforms in a number of ways. You can have segmentation across product categories based on product level economics which is really important to do. You can change the bidding strategy to maximize for conversion value and therefore we will actually prioritize this because it has a better rorowaz. This actually has a worse rorowaz too. So maximize conversion value won't fix this issue either. So segmentation is the way that you actually need to fix this. Now the other reason why this is an important exercise is particularly in fashion what you were trying to do is sell through 45:33 all of your product highest contribution margin possible. What we need to start thinking about in this instance is this t-shirt will this sell anyway without us even pushing it in paid cuz the cost to acquire is so low here that it seems like there is some kind of virality component. there is some kind of product market fit that's just getting this t-shirt to sell kind of regardless of our paid media spend because this is so hyperefficient. So the question we need to ask particularly if we're an omni channel business with retail stores or we're just a very large business in general is would people have bought this product anyway if we didn't spend? And if that's the case well then guess what let's not spend. Let's then take our contribution margin up on this order by $15 to $27. and let's actually reallocate all the spend to the hoodie which might not be selling naturally or organically and we need the paid spend to be able to drive sellrough rate. So this is where product level economics becomes incredibly important. It's something you should be breaking down. You can obviously build Google sheets around this. Have visibility build it into your decision-m. Now moving into 46:34 the metrics that matter. How we think through this internally is through a pyramid. We have platform level metrics down the bottom. We then move into finance grade metrics which we've been covering a lot in this video. And then up the top we move into incrementality testing which probably isn't applicable for 80% of people watching this but for the 20% that's doing over $10 million a month that has a presence in the US or multiple different markets might be omni channel this is going to be critical for ensuring measurement within the business and it's going to tie into understanding how finance ties into actual platform metrics. So if we start down the bottom we have rorowaz CPA CTR multi-touch attribution like triple whale etc. Now why is rorowaz down the bottom of the pyramid? Why is rorowaz not good? The reason why return on ad spend isn't a good metric is not because calculating ROI is bad, calculating return on investment is a great thing to do. The reason why rorowaz is unreliable is because it relies on attribution. And attribution is fundamentally an unknowable reality where you're trying to connect correlation within platforms 47:35 with faulty data to be able to prove causation. And what do I mean by all that complex language? When someone gets served an ad and then they click on the ad and then they go to the website and they purchase. You might think that this is causation that this ad click caused the purchase. But in a lot of cases particularly in large omni channel retailers that actually is not the case. This is correlation and in fact all attribution is just correlation. We are saying that these two events are correlated. The traditional way to explain correlation versus causation is that at the same time throughout the year, swimming deaths go up and ice cream sales go up. And you go, well, is swimming deaths causing ice cream sales? Is ice cream sales causing swimming deaths? No, they're not causal. They're correlated to summer. When it is summer, more people die when they're swimming in the ocean and more people buy ice cream. And it's the same thing here. Ad clicks is not necessarily causal to purchasing. It is simply correlated. And so because of this, return on ad spend ends up lacking validity and congruency to the P&L. What you see a lot of the time is 48:37 that people will go and say, "Rooraz is unbelievable. Wow, but my business is dying. What is going on?" And it is because rorowaz has a few dynamics to it. Number one, because of the way that it attributes, it will always overattribute to the bottom of funnel. Because people that for example might see a billboard up here and this is obviously a super extreme example but let's say someone sees a billboard and they become aware of uh the brand. They then see a TV ad which reinforces that they actually really want to buy your stuff because there was an influencer in there who they connect with. Then eventually they get an ad on Facebook. They click on the ad and they buy. Now did that ad on Facebook cause them to buy? Probably not. Like yes it got it over the edge at that specific moment but they were going to buy regardless at the next point of activation. It was the billboard and the TV that actually warmed them up at the top of funnel but these got no attribution. Now, it's the same thing across platforms. And so, a really evident example of this actually right now for us, and this might change depending on when you're watching this video, is Tik Tok to Meta to Google. 49:29 Now, this isn't applicable for everyone. This is a very unique circumstance, but it at least gets the point across, which is that we're finding at the moment for some very large retail brands that Tik Tok is actually underattributing substantially because it's getting impressions. It's getting in front of people in new markets, but they don't actually click off the platform much. or if they do click off the platform, they click off, they look at the product page, but they don't buy. Then once we have them in the pixel, Meta goes and follows up and retargets them. And we end up capturing a lot of increased demand on Meta when we increase our Tik Tok spend. And then finally, people that still haven't bought after Tik Tok and Meta, they end up going to Google. They search for the brand name, they click and buy. And so when we increase Tik Tok spend, our meta rorowaz goes up and our Google rorowaz goes up. Tik Tok doesn't. If we're using rorowaz as the indicator for performance and budget allocation across the business particularly and this is where this becomes a very large issue is when this is reporting up to a seuite a seuite will see return on ad 50:24 spend numbers across these different channels and go okay tik tok we should cut it's not driving returns meta is okay let's decrease budget and team let's put more budget into Google that would be a fundamentally terrible idea because what we're effectively saying there is let's cut all the top of funnel generation and move to just bottom of funnel bottom of funnel will stop working unless there is top ofunnel generation. And so rorowaz ends up misleading people in terms of decision-m unless there's a lot of additional nuance in understanding what is actually driving impact in the business. And so we need to go to better measurement systems to be able to actually encapsulate this, understand it, and then communicate it to a seauite or if you're a small business just to you as the founder. Now we could go on and on about the other limitations of attribution and return on ad spend here, but this is fundamentally the crux of why this metric misleads you in terms of decision-making. So then we move one stage up in the pyramid and we get to financial grade KPIs. Now these are metrics like acquisition me. You can throw me in here as well. We've got profit contribution which we've ran 51:19 through. We have CAC which we've ran through. So these are all metrics that aren't relying on the inplatform attributed numbers to be able to calculate them, but instead they're using the actual financial metrics that exist within the business. So the actual amount of new customers that you're acquiring, the actual new customer revenue, and then we're dividing by the actual ad spend. So this is all metrics that aren't relying on any kind of correlation calculation but instead are directly associated to financial metric. And so because of that the reliability is much better as we move up the pyramid reliability improves. However, speed decreases and so what ends up being the case with these metrics is them going up and down. You need to look at this on slightly longer time periods to be able to make correct decisions. Whereas you will get faster feedback loops generally speaking on your inplatform metrics. So why would we even use this bottom half of the pyramid at all? Why would we even look at rorowaz CPA? They are helpful in directional campaign feedback and ad feedback within the siloed platform. So what we do not want to do, what would be a big mistake is comparing a rorowaz 52:20 number on a Google campaign to a rorowaz number on a meta campaign because they have different attribution models. They're sitting at different points in the funnel. They're driving different incremental impact to the business. If we took both of the campaigns and we pushed budget up, one of them would drive excess return compared to the other irrespective of the rorowaz number on the campaign. So these are helpful directionally within the own platform. So if we're looking at two meta campaigns next to each other, we can compare rorowaz, we can use that to make decisions. But if we start comparing platforms, if we start zooming out and making larger business level decisions based on these numbers, that's where we can start to mislead ourselves and go into using low reliability, low data integrity level metric. And then all the way up the top here, we have incrementality testing. We won't dive into this in too much detail in this video, but the crux of the way that this works is that you take an area, generally the whole country. You split down by states. In Australia, you have to split down by commuting zones rather than states because there's not enough 53:12 state selection. And from there, you hold out a particular area. Now, typically it might even be two states. So, we can go and grab two different states that are next to each other. And then we hold them out. Now, a hold out means that we increase spend everywhere else except here. and we see what is the differential or we can just increase spend here in the control group or we can cut spend entirely. So we have a lot of different options in terms of test design here. But the idea is that when we isolate a large control verse treatment group, we can start to measure the incrementality of changing different campaign types. And so we might go and take that Tik Tok campaign I was talking about before that doesn't seem to be doing well and we might double budgets in these states. And then over a 30-day period, we measure the revenue realization difference over that 30 days and maybe new customer revenue doubles. And so as a function of that we can take the lift in new customer revenue against the control. We can do an incremental return on ad spend calculation and we end up getting a very accurate read on the impact that these campaigns are making. Now that is an unbelievably 54:07 simplified explanation of how this test design actually works. It's actually a lot more complicated. I could make a 2-hour video just on the data science and approach to building incrementality tests which I think we actually might do at some point. That is the crux of the idea as to how it works. I do not recommend that you go away from this video and think, "Oh, that was a really interesting idea. Let me just make a Google sheet and start doubling budgets in states." If you do that, you won't get good results. It'll pretty much always say states aren't incremental because the test design isn't set up correctly. You'll end up way overspending or under spending. You won't get statistically relevant results. You need at least a fundamental understanding of data science to be able to start to approach this portion of the pyramid. Um, but that is ultimately the most reliable option. It's just very slow. You can't run a lot of them and you're quite restricted. Now, I said before that I was a little bit hesitant, put me in here. And the reason why I was a little bit hesitant is that me is revenue divided by ad spend. Sometimes people will do this the other way round 54:59 and they'll do ad spend divided by revenue which will give you a percentage number. This instead will give you a multiple number. And so if we for example have $100 in revenue and $50 in ad spend, our me would be a two. So every dollar we spend on ad spend we get in revenue. You could also look at this as an ROI calculation. Now, this looks really good and this looks like a good way to index the performance of total spend across all of our media channels against total revenue. But the reason why it's fundamentally a terrible metric for indexing the performance of paid media over time is that it includes a large bucket of revenue that has very little to do with paid ad, which is returning customer revenue. And so, we really want to strip returning customer revenue out of this calculation because we don't want marketing taking credit for all these returning customers that would have returned anywhere. So that's why we always want to delineate all of our finance grade metrics into new customerbased metric. And so rather than looking at me, we want to look at a me, which is new customer revenue divided by ad spend. And this might actually give us in this example a 1.4, which might 55:56 not actually be profitable at all for us. And so we might want to be rethinking our whole acquisition strategy based on this delineation to a better number. Now, there is a metric that's better than everything that I just put down in the finance grade section of that pyramid. because I wanted to spend some time on it by itself and give you benchmarks. Now, this is LTGP to CAC, similar to what we talked about before when we had CAC and I said that we needed a pairing metric to be able to contextualize it. This is contextualizing those two numbers. So, we're taking the gross profit on a customer and we're dividing by the cost to acquire that customer. And this will give us an integer. And so, as an example, if we make $100 on a customer, it costs us $33 to actually get that customer. This would be 100 / 33, which is 3.33 LTG picac. Now, where we need to be really careful with this metric is that once again, just having an unrestricted time on lifetime value is a terrible idea cuz this can be measured across 6 years and so we end up way overspending but we don't actually realize this cash for like 4 years into the future. And so you want to put a time constraint here. 56:52 Now generally what we will do is we will measure this across two time horizons. We'll measure it across 30-day LTGP to CAC and we will do 90day LTGP to CAC and then sometimes we'll do 365 days as well depending on how aggressive the acquisition strategy is. Now, as benchmarks here, what we want to be seeing on either of these metrics, depending on how aggressive the acquisition is in the business, is that there is multiple different levels that you can be at. So, you can be at sub one, you can be at 1 to two, you can be at 2 to three, you can be at 3 plus. If you're under a one, this is generally speaking a terrible position to be in because it means that you are actually losing money on acquisition. You are losing profit because you're paying more to acquire a customer than the gross profit on first purchase that you're making or within the first 90 days. You have to have incredible retention after this point to be able to support losses on acquisition. Most brands that I audit that are losing on acquisition do not have good enough retention to support it. So this typically is not an actual acquisition strategy most of the time. This is poor efficiency on acquisition. 57:53 So this is simply a fact that your ads in your acquisition funnel isn't good enough and this is a bad position to be in. Some people 0.01% 01% of people can get away with this and they have the finance capability and the modeling to be able to actually uh operate at this scale and they have really good LTV. Most people can't do this. You do not want to be below a one on 30-day or 90day. It is worth noting that being below a one isn't necessarily just a CAC issue. It isn't necessarily just poor efficiency on acquiring, but it could be poor uh gross profit. So, if you only have like, let's say, less than $70 in gross profit on first order, that's probably a problem. you just don't have enough gross profit to be able to substantiate acquisition at scale on a paid platform. We then have 1 to2. This also isn't a great position to be in for most people. Now, if you're in CPG and you have really good retention dynamics, and I'll give you some benchmarks on that later on, then you can operate in this area. But for most people with mediocre retention, that's okay. And if you think your retention is good, it's usually mediocre. You will know if you have excellent retention because the 58:49 numbers become very evident and you can push acquisition like crazy. So, one to a two. You also generally don't want to be here. This is generally not good. Dash average if you're really wanting aggressive growth. If you're financing hard, if you have investors and you need to just uh throttle up revenue, sure you can scale on this, but it's not ideal. Two to three, this is optimal. This is where you want to be. This is a great zone. You should be scaling up budgets. Now, to give you a little bit of context here, what does a two elig look like? Well, if you have $100 in gross profit on first purchase, that's simply a CAC of 50. And so take whatever your gross profit number is on first order, divide by two, and that's what your CAC would need to be to hit this optimal range, to hit the bottom end of the optimal range. Now, greater than a three, this is actually also a big mistake. Being less than a one is is a mistake. Being greater than a three is a mistake because this means you're just leaving money on the table. You could scale very aggressively here, be unbelievably profitable, and you're probably underleveraging paid media or whatever marketing channels you're using to drive 59:44 this efficiency. Now, let's add two quick notes here before we move on. Note number one regarding attribution and incrementality and everything that we discussed on the pyramid. Uh when it comes to attribution, what you want to make sure of is that you're not using view through conversions in the platforms. And so when you're looking at meta specifically, you want to be making sure that you're using 7-day click as your optimization or your reporting. This is going to give you much tighter congruency to acquisition me. In fact, in most businesses when you look at their acquisition me and then you look at their 7-day click rorowaz on meta, it is super correlated. And that's because it doesn't include all these view through conversions that is overattributing in the platform. For those that don't know what a view through conversion is, it's when a user sees your ad on Facebook, doesn't click, but then buys within 24 hours, Meta can claim the conversion. And a lot of those people are going to buy anyway. They're existing customers. The list goes on. And so, you want to be not including them in your reporting. You also don't want to be including existing customers. 1:00:38 As I said before, existing customers aren't that incremental on the platform and so you don't want to be overspending here. You want to go to breakdown audience segments and look at where your spend's going. Often people are putting way too much spend to existing customers and their frequency is way too high. So you want to pull out the frequency column and you want to make sure that over the last 7 days it's under an eight. Any higher than an eight and you're definitely overspending because you're serving to existing customers more than eight times a month which is not incremental. So there's a big existing customer trap on the platforms. The platforms always want to spend here because they know they can overattribute and they always want to expand their attribution windows because they know they can overattribute. And if they can attribute more revenue, you will spend more. Now, as a bit of a formula here, cuz I get this question a lot, even from 700 800 million brands, I get this question when when we come in and talk to them and have calls with them, which is what percentage should we be allocating to existing customers? You're saying that existing customers aren't 1:01:28 that incremental. Well, so then what percent should we be allocating of our budget? Should it be 20%, 30%, 40%? Well, because 80% of our revenue as a large 9 figure brand is coming from existing customers because we have almost full market saturation in Australia. So, what are we doing? The question isn't percentage. Thinking about percentage allocation of ad spend to existing customers is just a bad way to look at it. What we instead want to look at is total amount of existing customers. So, how many existing customers do we have? How many times do we want to show them an ad? And then from there, we can calculate how much we need to spend. Because as long as we know the CPM, we can get the total spend per month. So, I'll give you the formula and I'll give you an example, which is let's say you have 300,000 existing customers and you want to serve how many ads to them. Let's say you want to serve three times a month. Then you just times by your CPM. So, go into the platform, do an audience segment breakdown, look at what's your CPM on existing customers, and let's say it is $2.50. Now, that's super low. It's probably going to be a lot higher than that, but 1:02:25 let's just say that for the sake of this example, that means that you're going to have to spend $2,250 per month on existing customers to hit them three times. Now, you can go and change these variables and that will change the outcome and tell you how much to spend. Reality is you need to spend way less than you actually think. Most people think, "Oh, we're a massive brand. We have multiple millions, if not tens of millions of customers. We need to spend hundreds of thousands a month targeting them." You typically don't. You could hit them with a three to six frequency and you could just spend 10 maybe on the upper side $30 $40,000 a month and you're completely fine. I see tiny businesses spending $40,000 a month on existing customers. And so this is the math. This is what you want to be doing. Let's move on to the final topic here on metrics that matter, which is the profit frontier. As a founder or a head of digital or head of marketing, the question you need to be able to answer is if we were to spend an extra $10,000 next month, where would we put that budget? where would we get the best incremental impact of that media spend? Most people don't know that answer 1:03:20 reliably enough. They don't know actually where they should be allocating their spend and therefore they get into a position where they continue to drive spend up across platforms but they don't see incremental returns. And so how you need to be thinking through this problem is what's called the next best dollar. And so we want to have all of our platforms, let's say Meta, Google, Tik Tok, add in a bunch of other channels if you're spending on them. Ideally, you shouldn't be spending on a bunch of tertiary channels, but let's say you are. And then if we just take spend here, we want to take Meta up to the level of spend in which we stop getting returns that we couldn't get on the other platform. So, let's say this is the current allocation of spend. Okay? Maybe we're like 100,000 here, 50,000 here, 70,000 here. What we want to know is if we went and put an extra 10,000 into Tik Tok off the top here, what revenue return would we get of this $10,000? Same thing for Google, same thing for Meta. And this is what we're constantly trying to solve for because ultimately to grow the business we need to continue allocating more marketing dollars across the current marketing 1:04:17 channels and we need to do it in the most efficient way possible. The only way to really understand this is to unfortunately run incrementality tests. We would want to for example go and put 10 into meta but do it in a controlled incrementality test where we can get a read on what this is. Same thing for Google, same thing for Tik Tok. Now we can also just do this intuitively over time. You could use MM as well, some marketing mix models to be able to identify where you should be putting media spend at a lower revenue threshold like seven figure brands. This should be relatively intuitive if you're a good performance marketer. But this is ultimately the problem that you should be solving for. And you should also be thinking about this inverse. And so could we pull 10,000 out of Google, reallocate it to Meta, and get a better ROI? Maybe this 10,000 here is only driving us a 2x, but we could go and put another 10,000 into Meta, and it would give us a 4x on new customer revenue. And so we should be rebalancing budgets and reallocating and scaling across here based on incremental returns and the profit frontier. And so the profit frontier is that you want to go all the 1:05:13 way up to the point in which you're making no more profit past this nominal dollar in spend. And so you want to find the point in which your acquisition me becomes the break even point. And once you hit that break even point incrementally that's where you stop spending. And you're doing that across all channels at all times. And only until you've reached the profit frontier on all of these three primary channels do you go and move on to adding in additional channels. So cash flow verse profit. Profit doesn't equal cash. And that's ultimately why paid media within e-commerce is way more complex than in a service-based business or than in a SAS business or particularly in the info space. And it's because when you scale up, you need to commit cash to future inventory purchasing which substantially restricts the actual dividends that could be yielded within the business. And so if you see an e-commerce business doing 100k in profit, reality is founders probably taking no money. Even a million dollars in profit, $2 million in profit, respective to the total revenue and growth rate, there may be actually no profit available at the end of the day cuz it all gets reinvested 1:06:12 into future inventory buying. So let's say that the P&L here shows $2 million in profit per year, but the balance sheet has $3 million on it. So the balance sheet will show you the assets of the business. The assets in e-commerce is typically unsold inventory. Now, there could be buildings on here if they own the office, if they own the warehouse, etc. But typically for most businesses, we're just talking about inventory sitting on the balance sheet as well as cash sitting on the balance sheet. So, the reality of this business right here is that they are not in a good position. The brand actually has negative cash flow depending on how we're looking this across time and how the cash is actually moving. But if they made $2 million in profit, but $3 million in inventory didn't sell, well, they actually made no money. They would actually be cash flow negative. They would be down a million in cash because yes, they made 2 mil, but they bought 3 mil in inventory and it never moved. Not good. So, this is where we get into the inventory death spiral or what can also be called as skew rationalization. So, all of your inventory has a grade 1:07:13 associated to it. Most people are probably aware of this, but the marketers and the performance marketers watching this aren't. And so this will become incredibly helpful in making paid media decisions and tying this into how we should be approaching the ad account. Grade A is fast moving inventory. This is inventory that is selling quickly that we honestly don't need to worry about. We need to just be thinking about how do we not go out of stock. Grade B inventory is medium sell to rate. This is slowm moving sell to rate and then this is not moving at all. Now, Shopify actually auto ranks your inventory anyway. As long as the inventory is within Shopify, you can actually see this yourself. I think it's under the products tab. Now, the key here really is that people will do product launches because product launches are one of the best levers, one of the best ways to scale an ecom brand. Ultimately, you have brands like Grunes, like AG1, like IM8. All of these brands have gotten enormous, hundreds of millions of dollars, close to a billion dollars with just one product. But that is misleading you in terms of how most e-commerce 1:08:13 brands need to grow because those brands have done so well because they're in the supplement space. And in the supplement space, you have a very unique advantage which is that you can reposition your product into technically like different products. And so if you're selling a multivitamin, you can say that that multivitamin helps with gut health, but it also helps with hair health, but it also helps with all these other problems. And so because of that, you have a really large total addressable market that you can reposition the product into. With most brands, you cannot reposition your product enough to gain a large total addressable market. So you need to do future product launches. Now when you do that, what ends up happening is they don't work. A lot of product launches fail. And so they either land into grade B, grade C, or you get an initial pop from organic and existing customers and you can sell through maybe the first 30 40% of inventory and then it doesn't move at all. And so then you get stuck in a situation which is that every time you're trying to grow through product expansion, you were just adding more cash onto the balance sheet that is 1:09:04 restricting the cash position of the business and the ability for you to scale. This is where skew rationalization becomes incredibly important, which is that as new products are introduced into the product suite, you need to be thinking about how can we rationalize our skew count down always to be able to decrease the amount of available products, to be able to decrease the amount of inventory on hand. There also needs to be some congruency here between the marketing team and the finance team. And this is where an enormous mistake is made, not only on agency side, but internally a lot of the time, which is that let's play through an example of this, which is that you go and you launch a new product. it doesn't do very well. Okay, it works on the organic list. You get a bit of a pop out of it. Maybe you do 100K, but you ordered a million dollars worth in sell value and then because of that, it ends up over here in grade D or grade C. It's barely moving. You look at the sell through rate and you go, we currently have 400 days of inventory on hand, which means it's going to take 400 days for us to sell through all this product, which isn't good. Okay, we want 1:09:58 to move this back to cash as soon as possible. Now, what will normally happen is the CFO or the owner or the manager or whatever it is, will look at this and go, "Ah, that's annoying. and then try to solution it themselves. But a lot of the time, we can actually just solve this through paid media. Okay, we can take this product that didn't do too well and we can start pushing spend behind it on paid media at break even or maybe even a slight loss. Dedicate isolated into its own adfunnel. So, it doesn't even have to sit on the website. It can sit separately. We can push it through whitelisting pages. What we've also done for a client is we've actually taken their grade D inventory and we've pushed it into a new country that we knew would perform well. we could discount heavily, wouldn't erode the brand equity within the primary market, and then we can just move all this stock using paid and turn it back into cash. Now, people don't have this conversation enough with the paid media team because the paid media team, the agency, is always KPI on profit, and this can be really detrimental. If we're trying to just maximize the profit position of the business, what ends up 1:10:51 happening is all of our spend will actually go up here and we'll end up really messing the business up because they'll have all this great BCD inventory that doesn't actually get prioritized in paid media at all cuz it doesn't have a good ROI, a good row, a good efficiency. We need to push grade BCD inventory in paid to be able to turn it back into cash. This is where you do need an understanding of the inventory position of the business so that we can make better decisions on paid for the overall health of the business. All right, we can't talk about finance without talking about cash conversion cycles. The actual formula for cash conversion cycle is DIIO plus DSO minus DPO. So days in inventory, days sales outstanding, days of payable outstanding. Now this is a 20-minute video on itself. In fact, we've actually put out a lot of content on cash conversion cycles, how to calculate it, how to measure it, what's good, what's bad, etc. So instead of going too deep here, I instead just want to explain the top level concept so that if you're in marketing, you can understand how this actually relates into the business and where you might need to be understanding 1:11:44 of these components. If you actually own the business or you're a CFO, I recommend watching our other videos that go into a little bit more detail on this topic. But the fundamental idea here is that if you sell 10 units of product and you make $50 in gross profit here, and once again, I'm just making numbers up, but this will make sense. What ends up happening here is because you only have $50 left in your hand, you can only then go and buy 11 units on your next purchase order. And then you'll make $55 in gross profit. And then this will allow you to maybe buy 12 units on the next order. And then this goes on and on and on. And so the limiter in this business is not the actual selling of the product. It isn't marketing. It isn't ROI on Facebook ads. It's the fact that they're just cash limited in their ability to buy future inventory because the amount of gross profit that is generated off this purchasing only allows a slight increase in future purchasing. Now, what you need to also add in here is let's say that there is a 90-day lead time from putting the inventory in to actually arriving at your warehouse to when you can start selling. And let's assume that you have 1:12:41 very poor terms with the manufacturer cuz these POS are so small. So, you actually have to put the money down 90 days prior to the actual inventory coming. then you're in a terrible position because you have to buy these 11 units after you sell these units to get the cash. And so you actually then have to go out of stock for 90 days here cuz once you have this cash, then you can buy the units, then you can actually go and sell again. And so what you would want to do here in this example is you would want to negotiate on better supplier terms so you aren't out of stock for 90 days. And so you might actually negotiate that you only need to pay 20% upfront here. And so after you sell two units, you have enough money to put in your next order. And then as you're selling through these other units, you're going through this 90-day period. Then once these actually get shipped, you pay the rest. And so maybe the shipping time is 20 days. You're actually only out of stock for 20 days rather than 90. Now, another thing that you could do is you could reduce the lead time from the manufacturer. So rather than it taking 90 days, you could try get a different manufacturer that 1:13:34 can reduce this down to maybe 30. And then that fixes the whole problem in itself. Or the last one is you use uh some kind of inventory financing. And so you actually take a loan out to pay for this inventory so that you can sell through, get this profit. This profit pays down the loan as you're going. And then this inventory comes. You then start selling this inventory. You open up another loan and this loan pays for the next purchase. And so you can get ahead by opening up some kind of financing. Now the issue is that financing is very expensive. When companies are loaning, you'll pretty much always have to put yourself up as collateral as well. And it's super risky. anytime you're introducing a lot of debt into the business, you're banking on the fact that you could sell these future units at an efficiency that's going to allow you to pay down the loan. And so if you are agency side and you're working with like seven figure businesses, they're almost always using some kind of financing to be able to actually grow. Um, and you need to take into consideration that rapid growth for these types of businesses usually actually isn't possible. The limiter isn't on how quick we can 1:14:28 increase ad spend or how efficient the ads are. The limiter is the cash conversion cycle. And so I have actually seen single-handedly probably five times now sevenf figureure businesses that have gone to an agency. The agency has absolutely crushed it. They've ramp spend from $20,000 a month to $200,000 a month. They haven't actually had any visibility into any of this with the client. The client in the background to fuel this growth has gone and taken millions of dollars out in inventory financing to be able to fuel the growth to be able to buy all the future inventory required to hit that kind of tripling per year in growth rate. And then as they've done that, their interest repayments get so large and the ads start becoming inefficient to where net margins get squeezed down to zero. And now, yes, we've taken a business from doing $2 million a year to $7 million a year. Like, amazing. Good job, agency. But the business has gone from cash flow positive founders actually taking an income to the business is near zero on net profit after all the interest repayments and the compression in marketing efficiency as they've achieved that additional scale. And so 1:15:27 this is why this is so important for at least people to be across so that they can understand that you just like can't triple an ecom business in a year. You just can't because the cash requirements on inventory are just so enormous. And so you either need a lot of self-funding. So the person starting the business needs to have multi-millions liquid. They need funding from someone who's providing the multi-millions or they need to go into some kind of financing. Otherwise, you just can't scale inventory orders fast enough to keep up with the scale that you want to achieve within the business. And a lot of the time where this gets a little bit dangerous is that uh people will pull marketing efficiency down to achieve larger scale but to do that it yes it accelerates the growth rate but it also increases the amount of debt that the brand needs to take on which actually compresses margins down to zero. And so you would actually be better off growing slightly slower at a slightly lower me. So a better efficiency, less marketing spend, having less interest repayments and making way more money rather than just trying to arbitrarily accelerate your growth rate but increasing interest 1:16:25 payments and making marketing efficiency worse. So that's just where you need to be very very careful in your financial modeling. Now this is where ultimately there starts to become a CFO verse CMO disconnect in a lot of businesses in this core decision which is let's run through an example. February arrives and inventory from November is still unsold. Maybe there was some new products in here that didn't do so well and they've fallen into grade C and D inventory. Now, most CFOs will actually look at this and go, "Okay, we need to cut media spend because we actually don't have enough cash right now to be able to fuel the current marketing spend in Feb through to April." And so, let's go and take our marketing expenses and cut them by 40%. And now this is quite logical when you're just opening up and looking at the P&L because when you look at the P&L uh cost of delivery might be 30%, marketing might be 25% and then opex is 15 and so profit in this business is at 30%. Now when revenue suddenly decreases in Feb and we actually don't have a lot of cash available me might go up and 1:17:26 spike to 30% which starts compressing profitability down and profitability dips to 25%. Now naturally the reaction from the CFO should be this has gotten out of control. ME has accelerated up. We need to cut marketing spend. Marketing team cut your budgets. Now there's two issues here. Number one is that in this business it might very much so be the fact that the marketing is driving the revenue. And so this compression in marketing efficiency is an efficiency issue on the current media spend. We shouldn't be cutting media spend because if we cut media spend, revenue will dip further. And so you can get into these uh cyclical situations where marketing spend drops, revenue drops, profitability decreases. To fix profitability, marketing spend needs to drop even more. And you keep dropping marketing spend to try to fix the issue, but it doesn't fix it. The other issue is that to fix this grade CN inventory issue for November, what we actually need to do is quite counterintuitive. We need to increase marketing spend even further because we need to sell out of the CND inventory and it's not going to be profitable to do so. And so what we actually need to do here is we need to 1:18:26 take me that's now inflated to 30% and we need to say hey you know we actually need to move this in the short term to 35%. And this additional 5% will be purely for driving all the CND inventory so that we can turn this back into cash which is going to give us a more a better position from a cash perspective which is going to allow us to get back into the old revenue position. So let's then put it all together. First place to start is in forecasting. Forecasting is critical for anything financial related because it allows us to set our KPIs and our expectations that we're then measuring off on an ongoing basis to be able to call scribe. Anytime you are forecasting, the number one rule of forecasting in e-commerce direct to consumer is that you always need to forecast new customer revenue separate to returning customer revenue. And the reason being is that both of these revenue buckets have different underlying levers that impact the realization of the revenue. So for new customers, this is primarily going to be marketing. Now, this might be just advertising spend for some brands. This might be advertising spend plus events and influencers. This might advertising 1:19:26 plus influencers plus other tertiary channels as well. When it comes to returning customer revenue, yes, advertising spend is going to drive a little bit of returning customer revenue. Yes, an influencer activation might drive a little bit of returning customer revenue, but primarily returning customers is going to come from uh product launches. It's going to come from marketing events like discount periods and it's going to come from other activations that are going to prop up and give returning customers a reason to come back. There is also obviously direct communication channels in here as well like email and SMS. These are different inputs compared to over here. Therefore, when we are forecasting, what are we doing? We're actually just forecasting inputs and therefore getting an output which is the forecast or the budget. And so we need to look backwards into the inputs to be able to then determine how we're actually getting the final number. For returning customers, you want to look at all of your returning customer cohorts. So every month back to let's go Jan 2021 all the way to Feb 2021. And this goes on and on and on all the way to today. There was a 1:20:27 certain amount of new customers that you acquired. Maybe back here it was 100, then it was 110, then it was 150. All of these customers repeat at a certain rate over time. And you can see this in your cohort analysis. And so people might come back at 7% in the first month, then 6%, then 4%, then two, then one, and then ultimately it asotopes down to usually a pretty small number. What you can then do is you can take all of these old cohorts and the amount of customers that you acquired then, and you can go, okay, well, they're about to enter into month 32 of them being a customer. What is the repeat rate on average of someone after month 32? And maybe it is 0.1%. So then you take your 100, you times by 0.1%. You then times by whatever your average order value is on returning customers, which let's say it's $100. And so we would expect this cohort to give us $1 in returning customer revenue next month. And then we do that for the next cohort and the next cohort and the next cohort and every single cohort that we've had in the past. And this will then give us a realistic extrapolation of what we should expect returning customers to contribute to next month. 1:21:27 This number ends up being usually within about 10% accuracy. To get it within 1 to 2%, you do two things. Number one, you bake on seasonality. And so you look at uh average seasonality in the last 3 years across the calendar year and you just apply a factor based on returning customer revenue seasonality. Number one. Number two is you then go and superimpose marketing events that are going to substantially change these numbers. So obviously if you have a major marketing event that's going to occur this year that didn't occur last year, there's going to be revenue driven from that. You want to figure out what is your uh expected revenue realization and then you add that into the forecast. Then on new customer revenue. Now in paid ads, this is relatively straightforward when you have larger media makes for if you have other channels like influencers etc. This is where you have to build your own modeling around this. And this is obviously where modeling and finance and data science becomes pretty critical once you once you achieve scale as an 8 to9 figure brand. To keep it simple for paid ads, what you want to do is you want to take your acquisition me on the 1:22:23 y- axis. You want to take spend on the x- axis and you want to plot the last let's for the sake of this video say one year of daily data. What you'll see is that every day there is a certain acquisition me that is associated to that day. And what should end up happening is you should have something like this. Now if you go and put a logarithmic regression or a linear regression whatever has the best fit for the model you will get an average of the expected efficiency at a certain spend level. Now you will have outliers like these outliers over here. These are typically sales periods. So, we want to actually remove these from the data set. We also know that if we're only going to be spending a minimum of $1,000 a month, we could also just remove anything under $1,000 a month out of the model, too. And that's going to improve the accuracy of modeling on these higherend spends. Then, what you're also going to have is all of these over here are going to be November and Black Friday periods that are significantly overinflating the actual efficiency that you would expect during BAU. So, you want to go and remove all these two. And then what you'll get is this line through all of 1:23:18 the days last year at certain spend at certain efficiency. And then you know, okay, if we go and spend $8,000 a day here, we know roughly what efficiency we should expect. And this is how you model out spend and new customer revenue expectations. You would actually back propagate from your new customer goal. So if you wanted to get like let's say $100,000 in new customer revenue, uh, and let's say you want to do it at a 4 a.m., you would just go to a four on the graph, which might be here. You would go across and you go, "Okay, it's right here. Can we spend enough to get a 4 AM in this much revenue? And the answer might be no. Okay. Well, we fundamentally have an issue yet. We need to rethink what we're going to do differently this year to generate outsized returns compared to the average of last year. Are we going to do some kind of marketing event? Is there going to be a new product launch? Is there going to be a new channel? Are we tripling creative production? Like what actual input or lever is going to generate this outcome? And this is ultimately the exercise of forecasting. The exercise of forecasting is to look at the realistic expectation against the 1:24:11 target. There's going to be a delta. There's always going to be a delta. the board wants you to hit 50 million. You do this and you go, the math says we can only hit 40 million. And then you look at, well, what are the inputs required to achieve that $10 million difference? We talked about the profit frontier. We talked about how funnels overattribute at the bottom, underattribute at the top. But I want to reinforce this idea because it's a really common mistake in budget allocation, which is that you will always see the best rorowaz at the bottom. You will always see the worst rorowaz at the top. And so if you have a meta campaign that's attributing at a 2x and you have a Google campaign that's attributing at a 6x, don't simply go and put more budget here. This is going to be overattributing because it sits at the bottom of funnel. It might have branded key terms. It might be retargeting. Even if you have a bunch of exclusions in place, probably bottom of funnel and you're actually going to see better incremental impact putting budgets here. Obviously, always do this within a controlled test. Make sure that you're on top of whether this is actually true or not for your particular 1:25:03 business. But be very careful with rorowaz reads in the platform because it's going to usually make you overallocate to bottom of funnel efforts and then you'll wonder why you're not growing when you're increasing budgets. One thing that we haven't touched on at all here and this starts to get a little bit outside of finance but I think it's a really important mention which is brand at 1 million to I would actually argue probably 20 million. You can just brute force revenue through performance marketing. Okay, performance marketing through ads can get you here very easily. You put $1 in, you get $4 out, and then you continue to scale. But eventually, what usually ends up happening is you hit diminishing returns, which is that as you try to put more spend into these platforms, as you try to start pushing past $30,000 a day, $40,000 a day in ad spend, you just can't get any further. And the way to go further is through some kind of brand effect. And I say this from personal experience myself. Obviously, in the early days, we worked with three 500 7 figure brands, either full-time or in some kind of consulting capacity. And these days we currently work with over 1:26:01 68 and 9 figure brands and close to 10 figure brands as well. And so we have seen both sides of the spectrum. All these small brands that are very reliant on performance marketing and all of these large retail brands that aren't reliant on performance marketing at all. And in fact, there's actually a huge opportunity in performance marketing because they don't do it very well. And this is due to the brand that they have within the platform. You can open up and I do this all the time. You can open up one fashion ad account that's doing maybe $8 million a year and you can look at all the core metrics in the Facebook ad account. the click-through rates, the CPMs, the CPCs, the conversion rate, and then I can go and open up another fashion ad account of a business doing $300 million a year. And the crazy thing is that the ad account over here has better metrics on everything. They have better CPMs. They have better click-through rates. They have better CPCs. They have better rows. Everything is better. And you go, how is that even possible? They're doing like 20x the volume. They're doing 20x the ad spend. That just doesn't make sense because as you scale paid media, you hit 1:26:52 diminishing returns. So, why are they not seeing all their numbers degrade? And it's because of this overarching brand effect that they have in the market. They have so much market saturation. They have so many associations that have been built through external marketing efforts that sit outside of the ad account that inside the ad account it looks really good. But it's because of everything that they're doing outside of the ad account that makes it look good. And so I can go in any day on a brand that every single person knows and run ads and I'll have incredible clickthrough rates cuz everyone knows who they are. But if I go in on a brand that no one knows who they are and I'm trying to push, obviously the performance marketing has to be a lot better and that's why you hit diminishing returns. And so also just when you're thinking about marketing expense allocation, I would always be having some kind of budget towards branding efforts. And by branding efforts, it's making associations within the market that is going to put you in front of the customer where they are. And so if your customers are commonly in a particular area or at a particular event or looking 1:27:42 at particular things, that's where you want to show up to be able to build associations. I'll give you two personal examples of this, which is that I've recently bought running gear from two different brands. I bought from 2xU which is an Australian brand. It's actually a client of ours and then another brand which is 247 represent. And the reason I bought from this brand was because all of the running influencers that I follow, all the people that I watch YouTube videos of every week, all the people that I follow on Instagram, they are all either sponsored by 247 or they just wear it. They make associations with it. And so because of that, that natural association that's been made within market of where I end up showing up on the content that I consume is the reason why I bought it. Had nothing to do with quality, had nothing to do with anything except for the fact that I follow all these running influencers, ended up following the founder, following his story, watching podcasts of him, and that's ultimately what pushed me to the purchase. I would argue that all of those uh influencer deals, all of the branding exercises, them showing up to run clubs, etc., that probably doesn't 1:28:39 have direct profitable ROI. They're probably not getting the coupon code that the influencer has at checkout, which I don't think they even do, but let's say they did do it. Probably not a profitable exchange, but is the overarching branding effect of making those associations that ends up pushing tons of people to purchase. On 2XU, it's the branding of premium. Now, 2XU's products are incredibly premium. I think they're probably one of the highest quality products in Australia in this market. But honestly, I don't think that even matters for me in terms of my purchasing decision. I didn't purchase because I knew the product was quality cuz I bought online. I hadn't seen it. I bought because of the perception of quality and so it is the brand perception that they have built that this is the highest quality uh activewear clothing in Australia that is causing me to buy. Now once again was this through some kind of performance marketing ad? No. Was this through a Google ad? No. It was through the overarching associations that they make. It's through the messaging that they have and it's through the way that they show up in the creative as well particularly in the campaign shoots that 1:29:35 makes the perception that it is super high quality which ultimately drove me towards that conversion. And so both of these purchases likely wouldn't have happened through any kind of performance marketing effort. They actually occurred through brand which is why that we can't understate this and we need to have it as a portion of the video because it is unbelievably important particularly as you continue to scale and it should be thought through as a budget allocation of an expense on the P&L. So wrapping this up, if there are five things that you should be walking away with as key takeaways to take forward in your business or working with a client, it is number one, know your gross margin and know how to calculate it correctly. You need to understand variable costs. You need to understand the difference between product margin and gross margin. You need to understand how that also then flows through into contribution margin. Number two is you need to understand the definitions and you need to have live dashboards that track acquisition me profit contribution ideally LTGP to CAC not just being over here tracking rorowaz on a day-to-day basis and having weekly rorowaz reports 1:30:32 this is not productive at all for core decision-m and moving the business forward the third is that you want to be separating all new verse returning customer metrics you want to be tracking new customer economics acquisition me new customer profit contribution new customer revenue, new customer cohort size separate from returning because ultimately the levers underlying them are different. This also obviously applies into what we were just talking about around forecasting. Number four, you want to understand the difference between a cash verse a P&L play. It might very much so be the case within the business that the current limiter isn't marketing spend or marketing efficiency, but it's the cash conversion cycle. And so there is no point in arbitrarily pushing budgets up and trying to scale if it's just going to cause an increase in interest expenses on the P&L and a compression in me. There also needs to be constant communication between either the internal marketing team or you and the agency as to the inventory position within the business across the different SKUs so that there can be strategies employed to be able to actually decrease 1:31:34 profitability, decrease acquisition me, decrease efficiency, but prioritize the turnover of inventory into cash to make the business overall healthier. And then number five is that you want to be using the P&L and all of these other financial tools to be able to identify the constraint in the business. And so when you can understand how to read the P&L and structure it out, you can understand how to KPI at each level. And then when you start falling below KPI, you can look above that level in the P&L to understand, okay, what has changed? What levers are there? And then how can we pull on those levers to rectify and course correct back to where the target actually is. If you made it this far, thanks for watching for an hour and a half. And if you are an e-commerce brand doing over $5 million a year, there'll be a link somewhere in the bio to reach there'll be a link somewhere below in the description to reach out and get a free audit from ourselves where we'll run you through all of this financial modeling, but we'll actually apply it to your business. And if you're a performance marketer that's gotten this far, please reach out. We're always 1:32:34 hiring for a play of performance marketers. Click on the website, reach out to us somehow. You could also email hiring bluesdigital.com.au
