10 Brutal Truths of eCommerce

In this episode, Nathan discusses 10 brutal truths of e-commerce for DTC brand owners. The first truth is that reducing ad spend is not the solution to higher operating expenses. Understanding how the P&L works and the flow of revenue is crucial. The second truth is that most accounts are either overspending or underspending, and finding the right balance is key. Attribution tends to overattribute bottom-of-funnel actions and underattribute top-of-funnel efforts. Customer repeat rates are largely influenced by merchandising and operations, not just marketing. Site intent is a better measure of success than click attribution. Buying the right products is more important than marketing for online retailers. Only a small percentage of creatives will scale. Strategies used by nine-figure e-commerce brands in the US can be applied to eight-figure brands in other geographies. Keeping operating expenses lean is essential for success. Focusing solely on cost of goods minimisation may not be the best solution, as cash conversion cycle also matters.

Takeaways

• Reducing ad spend is not the solution to high operating expenses in e-commerce.
• Finding the right balance between overspending and underspending is crucial for success.
• Attribution tends to overattribute bottom-of-funnel actions and underattribute top-of-funnel efforts.
• Customer repeat rates are influenced by merchandising and operations, not just marketing.
• Site intent is a better measure of success than click attribution.
• Buying the right products is more important than marketing for online retailers.
• Only a small percentage of creatives will scale in e-commerce.
• Strategies used by nine-figure e-commerce brands in the US can be applied to eight-figure brands in other geographies.
• Keeping operating expenses lean is essential for success in the DTC business model.
• Focusing solely on cost of goods minimization may not be the best solution, as cash conversion cycle also matters.

Chapters

00:00 The Misunderstanding of Reducing Ad Spend
05:21 The Balancing Act of Spending
07:18 The Attribution Challenge
10:01 The Influence of Merchandising and Operations on Customer Repeat Rates
11:56 The Importance of Site Intent
14:50 Buying vs. Marketing for Online Retailers
17:14 The Scaling Challenge of Creatives
19:10 Applying Strategies from Nine-Figure Brands to Eight-Figure Brands
22:05 The Significance of Lean Operating Expenses
24:09 The Complexity of Cost of Goods and Cash Conversion Cycle

Transcript

0:01

Welcome back to the Blues Brothers podcast. In this episode, I'll be running through 10 brutal truths of e commerce. So we've been slowly putting these together over the course of the last few weeks, which are brutal truths that I think a lot of DTC e commerce brand owners that are between seven to eight figures don't realize or eventually do realize at a certain point in their business. Starting off with number one, if you're operating expenses are relatively high, reducing ad spend typically isn't the solution. This comes down to a misunderstanding of how the P &L works for a direct to consumer brand. A lot of business owners, particularly seven figure e business owners don't understand how the e -commerce data CPL flows through. And so commonly when things go bad or the P &L turns red, the immediate solution that they drive for is to try to decrease marketing spend to generate more net profit at the bottom And the logic is, okay, we just went to negative $2 ,000 profit this month. Let's reduce ad spend by 2000 so that we go to net zero. However, that lacks the realization of how a DTC P &L works and how demand generation exists at the top, which flows through into contribution dollars, which have to cover operating expenses. And this is a concept that I end up finding myself running through with e-commerce owners quite a lot, almost weekly, which that at the top of the PNL, you have revenue, which then flows through into discounts, returns, where you then have net revenue. And let me actually pull up an ecommerce panel so that I can give an exact representation And so at the very top, you have gross revenue, you minus off discounts, returns, and then you add shipping and you have net revenue. You then go and minus off cogs, fulfillment and shipping and transaction fees, which is your variable costs that move in association with top line revenue changes. And you then get your gross margin. So as long as you can calculate down to gross margin, all you have to do from there is minus off your direct advertising and marketing expenses, which is typically your Facebook and Google ad spend. and you'll then get to contribution margin. Now you have to have enough contribution margin dollars to be able to cover your operating expenses or you end up with negative EBITDA. And so what a lot of brand owners try to do is reduce the direct marketing and advertising expenses so that they can get more contribution dollars, which then covers OPEX. However, in most instances, those direct marketing and advertising dollars are the generation point for the top line revenue. And so the top line revenue drops as a consequence. And I've seen this play out over 50 times probably with different e -commerce brands who have been very set on wanting to reduce advertising spend to be able to enable better profitability. And all that is done is negatively spiraled them downwards because top line revenue has dropped as a consequence. And so it's really important to understand that if marketing expenses has been used effectively to generate top line demand, when you pull that expense, you will see that flow through into top line. Now where sometimes you can get a negative bias in your understanding of this is that you could pull marketing expense and see the next month an immediate 2K improvement in profit. And so that falsely reinforces an assumption that you can pull spend and see an improvement in contribution dollars. But the reason why that ends up occurring is because you might have a 60 % daily revenue allocation towards returning customers and 40 % of first time customers. And so you're only going to see the hit on the first time customer P &L, which 99 % of business owners are tracking and don't even know how to track. And so you will only see the revenue dip end up presenting itself once the lagging customer acquisition catches up within the cohort, the retention cohort that builds over time. And so it might take three, six, 12 months for it to actually present itself materially within top line revenue, but it will present itself. And then you'll end up chasing your tail because you've had a degradation in the returning PNL, which is very hard to improve without ramping up customer acquisition again, and waiting three to six months for repeat purchases to come off the back of new customers being acquired. And so brands often end up putting themselves in a really bad position over the long term by pulling marketing spend. without understanding the long -term consequences and how their customer return rates are flowing into a repeat panel. So number one was if operating expenses are high, reducing ad spend typically isn't the solution to generating more contribution dollars to cover OPEX unless you're being incredibly inefficient with your current marketing spend. Number two, which ties into number one, is you're either overspending or underspending. I've almost never seen an account that is perfectly spending the right amount. And what I mean by that is let's go with the underspending accounts. A lot of e -commerce business owners fail to, as usual, understand the P &L, but more importantly, understand the leverage that a direct -to -consumer e-commerce business has. And the leverage is that you can operate incredibly lean, which allows you to spend enormous volumes of revenue on marketing and advertising. And so a really strong D2C P &L looks like a 40 % allocation towards advertising and marketing, a 8 to 10 % allocation towards OPEX, and then about a 25 to 30 % allocation towards cost of delivery, which is cost of goods sold transaction fees, and then shipping and fulfillment. And then you end up and I can't remember what numbers I said, but you end up with about 15 to 25 % EBITDA with those ratios in place. And that comes from operating really lean on operating expenses, and then maximizing spend that you're putting through into Facebook and Google to rapidly acquire customers and then ideally retain them over Most people don't understand that you can go that aggressive in terms of acquisition. And so they end up significantly under spending and wondering why they're not growing rapidly when they're trying to maintain a 5 % allocation towards direct advertising and marketing. And then on the other side of things, there's a lot of overspending going on where brands are inefficiently spending throughout their marketing campaigns through lack of understanding or a push towards diversity across channels. And so you see this a lot on search campaigns, where brands are 20 to 30 % of their spend on search, which is just a complete over allocation and overspend and miss spend of resources. Where really that spend could either better be going into generating top of funnel awareness on Facebook or going into shopping campaigns, which is further down the funnel on Google. And both instances, you'll likely see better efficiency out of that existing spend. Number three. is attribution will always over attribute bottom of funnel and under attribute top of funnel. And this is something that I went into a lot of depth in in a previous podcast, talking about how to structure accounts to incentivize better profitability of a business. And the really the core message within that was that when you look at campaigns and direct reported attributed revenue, they are not a direct reflection of where you should be allocating resources. Because These platforms are terrible at attributing backwards to first click. And you can do this by going into your GA4, going into conversion paths, do an export, and then you can run basic formulas within Excel, or you can make your own script, which sorts all of the first click within the conversion pathway revenue. So you can start to do first click attribution. First click attribution isn't natively available anymore within GA4, within Google. within Meta, but if you run a custom script, you can generate that data. When you go and generate that data, what you find is that it isn't really that useful anyway. And that's why all these platforms removed it was because when you try to look backwards in time, a few clicks, every step you go back, you lose 90 % of the cohort because the attribution is so terrible as you're trying to step back through customer journeys. And so any... channel that's generating top of funnel awareness or top of funnel traffic that's then flowing through into a conversion seven to 14 days later, it's super unlikely that that channel will get any degree of attribution. And you see this if you run cold targeting campaigns on Meta, but you exclude website visitors and you exclude any other custom audience that shows any degree of intent. What you'll see almost overnight is ROAS will drop to sub one, but as you start to scale that campaign up, revenue increases linearly. or proportionally to that ad spend. And it's incredibly profitable to do so. Now, if you're looking at direct attribution and platform, that wouldn't be a strategy that you'd roll out. But if you're indexing towards actual profitability on the backend, that's a strategy that starts to make a lot of sense. Number four, the next week's podcast, we'll go into a lot more detail on this, is that customer repeat rates are almost entirely out of the control of marketers. And that's not to say that there is an incrementality in email flows and campaigns. I do believe there is. And I believe that a business that is doing $100 ,000 in top line per month and is not running regular email campaigns and doesn't have correct flows set up, that they are losing out on incremental revenue. However, the incrementality that you probably believe might be there or that might be sold to you by retention or email agencies, I don't believe actually exists. And the reason for that is that customer repeat rates or retention within a business is fundamentally built into the merchandising, the operations or dash and the vertical in which that business operates within. If you're a CPG brand, automatically you're gonna have better repeat rates than any furniture It's just built into the business model. No matter how hard that furniture brand goes with spending advertising dollars on remarketing existing customers and having intricate retention strategies in place through loyalty programs and the list goes on the CPG brand not trying at all will automatically have better profit contribution growth over the course of the first three to 12 months. Now, is that to say their loyalty program and implementation of retention tactics don't have a material uplift. Absolutely. But the material uplift that I think a lot of people are sold on within the retention industry doesn't really exist. And I think there's an opportunity for a service line here, which goes into how can you operationally or change your merchandising suite in a way that's going to facilitate higher customer repeat rates. And a fantastic way to do that is have samples within existing orders. And so it's a material, it's a physical change. It's not a digital change that's going to enable better cross -sellability of that product post purchase. Number five is site intent is a better measurement for success than click attribution. And so what I mean by this is there are a lot of softwares coming out now that measure site intent rather than direct click attribution on the website. And so this means that if you get a click from a TikTok campaign, you're measuring how much time is spent on site, as well as how many different pages are moved to by that traffic. And you can use that as a signal for intent as to how likely those individual users are to convert off the back. As you can generalize ratios of time on site into add to cart ratios into conversion rates. to be able to predict how well a platform or a new campaign is going to perform prior to conversions actually occurring and at the very entry point of these customer journeys starting to play out. And so if you have quite extensive customer journeys that might take 10 to 20 days, you can start to predict the conversion without having to wait the lag of 10 to 20 days to see whether a campaign's actually performing well. And I think this is also really helpful. when it comes to testing out new sales channels like TikTok. If you have average onsite time of two seconds out of a TikTok click in comparison to a MetaClick where you're having an average time onsite of 44 seconds on a first click, you can start to predict that the conversion rates and the profitability of TikTok as a platform is going to be significantly worse than Meta. Not only that, if you're looking at paying per second of attention, on the brand, you're getting a much better ROI out of Meta as a platform. And so being able to delineate down to intention on site rather than relying on click attribution, which is a lagging indicator. And that's the primary issue here when it comes to attribution on long customer journeys is that you have to run an experiment and then you have to wait for a lagging indicator, which is going to be the attribution down the line. This is the same issue with incrementality testing. which is that you run an incremental test, which is a large fluctuation within budgets or a new campaign type. And you then need to keep all variables constant and measure top line revenue or efficiency changes across the entire marketing strategy. But you have to wait two to four weeks to actually see the results because you need to wait for those conversions to actually go through a path and then convert. But if you can look at attention or if you can look at intention right at the start of customer journey, you can start to predict very early on and reduce a lot of wasted spend within accounts. Number six is buying is more important than marketing for online retailers. And the reason this was put in is it ties back into the P and L discussion at the start and adds an additional caveat. And so I said that an ideal direct to consumer profit and loss statement looks like a very low percentage allocation towards operating expenses. generally a high single digit allocation. So eight to nine, maybe up to 12%. You then have an ability to have 25 to 35% gross margin. And you can then allocate a very large proportion of the P &L towards direct advertising and marketing to grow customer acquisition. Now with the retailers that are retailing other people's products, this P &L looks very different. You can still maintain relatively lean operating expenses. However, your gross margin shrinks substantially. And so your allocation towards cost of delivery, instead of being 25 to 30%, ends up looking closer to 70, potentially all the way up at 80%. And now your dynamics change substantially because you cannot operate at a 30 to 40 % MER. That needs to be squeezed down to five, 10% max. And so how is that even possible? to scale a DTC brand if you have such low allocation towards marketing. And the way that it becomes possible is that the demand generation isn't being done by you as a brand. The demand generation and the advertising dollars are being spent by the brands that you're stocking. And so as a stockist, the value actually comes in you buying the right products and stocking the right products to where demand generation already exists within the market, and then you're entering to capture it at very low cost. And so that's where shopping campaigns start capturing bottom of funnel traffic for very low cost with very high intent. And so you end up with CPAs that are incredibly strong to facilitate a 5 % M .E.R. The same thing with running dynamic ads on Meta. You can run dynamic catalogs and you can just capture existing demand. A good example of this is that any brand that we work with that stocks Nike shoes, we sit at a 10 to 20 return on ad spend or a 10 to 20 M .E And the reason for that is that all of the brand awareness, all of the demand generation already exists and is continuing to be generated by the millions a month that Nike is spending on advertising and sponsorships, if not tens to hundreds of millions of dollars a month. And we're simply coming in and capturing that existing demand and getting in the bottom of funnel traffic. And so if you are a stockist or an online retailer, understand that buying the right products ends up being much more important. than the marketing that you're actually running. Number seven is 95 % of creatives you've launched won't scale. And there's a really easy way to validate this within any single account. And you can run this and validate it on your own account right now. And the way to do that is do an export within Meta of day, ad name, and then spend. And you'll be able to look at every single individual ad that ran historically and the associated spend with that You can then pull that into a Google Sheet and do some if, unique ads, and you can look at the individual spend that went through each unique ad. And what you can start to delineate from there is the average amount of spend that goes through a creative. You can look at one standard deviation higher than that mean, and you can deem that as high performance. And you can look at the percentage of high performance that exists within the entire data set of all ads that's run within a meta account. And what you'll end up finding is that percentage will sit anywhere from 3 % on the very top end 8%, which means that only between three to 8 % of creatives that are launched within an average meta account actually see statistical deviation of one standard deviation above the mean spent. So that quote unquote, a high performer, I wouldn't even deem them as a really high performer. That simply means in most instances that you can get four to $5 ,000 of spend through that creative. But if you want to get$50 ,000 or $100 ,000 of spent to a creative, that kind of creative appears 0.5 % of the time. And so you need to test 200 unique ads before you find a creative that can truly scale. And I think that concept is lost amongst most smaller end DTC e -commerce businesses where the amount of unique ads that are active within their account is so low. Number eight is nine figure e -commerce strategies in the US market. need to be applied to eight figure brands within Australia and other geographies that have lower population sizes. And the reason for this is that a lot of e-commerce brands within Australia don't realize that the top end advertising spend thresholds within Australia as a geo is 10 to 15 X lower than what you can achieve in America. And so you end up with all of the issues that nine figure brands in America start running into. but you run into those issues a lot faster within Australia and at a lot lower revenue caps. And I think because you look at US strategies on these larger brands that are being run on nine figure brands, and you have the core understanding that that really only translates for a nine figure brand, so you don't translate it to your own is a crucial mistake. An example of this is that if you run a Facebook account within Australia at about 100 to $150 ,000 a month, you run through the entire addressable conversion optimization market on meta, within about six to eight months, if you're optimizing for conversions and purchases, your total addressable market ends up tapping out at about nine to 11 million, depending on your specific customer demographic. And so what that ends up meaning is that once you run through that entire audience, you just start reserving to the same existing users. And so if you're trying to get net new reach or net new eyeballs, it's unachievable through continuing to spend on meta as a platform through conversion based optimization. So what is the solution? You can look into running brand awareness at a very low percentage allocation to try to get net new reach on a rolling basis. You can look into optimizing to add to cards rather than purchases. And so it slightly loosens the target demographic of audience that you could be targeting. and enables once again, net new eyeballs and net new reach. You might have to expand into YouTube as a new sales channel where you're not gonna see direct attributed revenue, but you are going to see a net ROI over a long time horizon because YouTube is incredibly top of funnel. But once again, platforms will under attribute on a click basis top of funnel campaigns. So you will actually see that flow through into bottom line, but you have to be able to take the leap to run that as an extensive high budget test for a three to four month period. And you have to start looking at other strategies as well. That nine figure brands in the US are running. If you are an eight figure brand in Australia, as getting above a 100 to $150,000 a month spend threshold for e-commerce brands starts to become very, very difficult in the Australian geo. Number nine, and this might be fairly obvious based on what we've ran through so far is that the DTC business model only works if you keep operating expenses lean. Otherwise, competitors will outbid and outperform And this becomes very obvious if you simplify it down really to just Google as a platform. We don't even have to look at meta, but the same concept directly translates and applies onto meta, which is that on Google, whoever pays the most ranks in the number one position. Now there's quality score components, there's relevancy score components, it's going to add additional nuance to that statement. But generally speaking, if you're willing to pay $20 a click, you'll rank number one. No matter how bad your relevancy is, matter how bad your quality score is. You pay enough, you'll rank at the top. And so what that ends up meaning is whoever can pay the most to acquire a customer, wins. And this applies into really any business model as well. It's the agency that has the best retention, can go out and pay the highest CAC and beat the whole competition at acquiring customers in the agency model because they have the best lifetime contribution profits that they can pay to do so. The exact same thing applies in D2C. Whoever has the most margin on their product, or more specifically, whoever has the leanest operating expenses, the greatest gross margin, and therefore the largest allocation possible towards direct advertising and marketing, is able to go out and spend more than everyone else to acquire customers. And so they can end up sweeping out all the competition by simply ranking number one for all relevant key terms on Google, having the best placements across meta for all of the highest and 10 audiences, because they will always come into the auction with the highest bid. And so if you can pay to acquire customers at higher levels than all of the competition, you will end up growing and outperforming all of the competition. And so you could almost look at it as your competitors operating expenses are your opportunity. Anytime your competitors are inflating operating expenses, it's giving you percentage points on the P &L to go and be more aggressive than them. And then number 10 is focusing on cost of goods minimization is usually the wrong solution for a lot of direct to consumer brands. And so this once again ties into the last thing that I was talking about, which is that we want to be leaning out OPEX, but then as a consequence with that line of thinking, you also start to go down the route of, well, let's also lean down cost of delivery. And absolutely, there's optimizations available in minimizing cost of goods sold, particularly looking at your product portfolio and focusing on products with the highest GP. There's also optimization available in shipping and delivery, looking at a postcode analysis across your delivery and looking at net shipping. So that's shipping collected minus shipping paid and seeing where you're actually taking a loss and then optimizing those shipping collected at checkout accordingly. But focusing on simply driving down cost of goods as a proportion of revenue. can end up being the wrong solution for some brands because the other side of the coin here is that you typically have to have larger MOQs and higher inventory orders. And what that ends up doing is lengthening your cash conversion cycle. And we have a video on this on the BlueSense YouTube channel, but fundamentally all the business can be derived down to at least inventory -based businesses can be derived down to how short is your cash conversion cycle? Because the shorter you can make your cash conversion cycle, the faster you can take bootstrapped cash, turn it back into higher levels of cash, put it back into inventory and then continue that cycle moving forward into growth. You can model out your cash conversion cycle into the future. And you can actually see that you're limited on growth by the length of that cash conversion cycle. If your cash conversion cycle is six months, there's only so many doublings you can do throughout a two year period. Whereas if you can bring that down, you can double much faster just due to the cash available. after spitting out inventory into cash. And so in a lot of instances, you can look at minimizing cost of goods, but as a consequence, it's actually going to extend cash conversion cycles, where instead the negotiation tactic with the supplier might instead be to be floating terms to where you can actually have a negative cash conversion cycle. where you were taking a loan and then also floating terms with the supplier. And so you're not even paying for inventory until after it's been sold. And that shortening of cash conversion cycle enables further rapid growth, which enables a position where you can actually negotiate your cost of goods down because you're at higher, you're at higher sell-through rates due to the ability to foresee the cash conversion cycle is more important than getting an extra one to $2 in margin. on your individual products and squeezing an extra one to 2 % there. And so it's having the ability to contextualize cash conversion cycle as well within your future demand planning, as well as your future projected growth rates. So to conclude this podcast, number one, if your op ex is high, reducing spend typically isn't the solution, because you need to be generating enough contribution dollars to be covering operating expenses. Number two, almost all brands are either overspending or under spending. Identify which one or which bucket you're in and look to rectify and come as close as possible to efficiency. Number three is that attribution will always favor bottom of funnel and under favor top of funnel. Number four is customer repeat rates almost entirely out of the control of marketers and are in the control of merchandising and operations of the business. Number five is site intent is generally a better measurement for success than click attribution as click attribution is a lagging indicator. Number six is that buying is more important than marketing for online retailers and stockists. Number seven is that 95 % of creatives that you launch will not work and will not scale. Number eight is that nine figure e-commerce strategies in the US need to be applied to eight figure brands in Australia. Number nine is the D2C business model only works if you keep operating expenses lean. Otherwise, competitors can outbid and outperform you. And then lastly, focusing on cost of goods minimization is sometimes the wrong solution as cash conversion cycle matters.