Average order value in Shopify, that metric by itself doesn't really tell you anything in terms of actionables off the back end. And so when you look at that number and 80 or 90, it's not really telling you much. And so you can break it down a step further. Hey, how's it going, everyone? So we're back again with Nathan. and he just been, getting blown up by all the comments and like people reaching out to us. we want to hear more about what's going on with PNLs, how to understand and demystify everything that CFOs talk about. and so when it comes to marketing, it's not just about running Google ads a certain way or Facebook ads a certain way. It's about actually understanding the business. and so Nathan's a really good resource for both me and other people at Solutions 8, to have chats about, more of the, back and finance side of things and how that kind of comes into, place with, marketing as a whole. now I think we're going to talk more about AOV. and when I think of AV, I just think of average order value, the type of customer and more of the psychology behind it. But, yeah, I just wanted to hear your thoughts on that and also welcome back and, yeah, let's jump right into it. Thank you. Thank you for having me back. Looking forward to it. I thought AV would be a good topic for this video because I think it encapsulates well, the lack of a deep understanding of e commerce analytics. by most e commerce operators, as well as even, performance marketers that are actually in the field. And this isn't to say that you need to have this deep of an understanding of each individual metric, but it should help you uncover that if you do have an AOV problem, or if you've tried to increase average order value in the past through a threshold or through a bundle, and it hasn't worked like what we're about to run through should hopefully contextualize why. All right. and give you a better understanding of all of the levers on the average order value and how complex it actually is so that you can make a more educated decision on how you're going to try to fix it or whether you even need to fix it within the context of the unit economics of your brand. So to start would be, average order value in Shopify. That metric by itself doesn't really tell you anything in terms of actionables off the back end. And so when you look at that number and 80 or 90. It's not really telling you much. And so you can break it down a step further and you can look at new customer AOV versus returning customer AOV. And that starts to tell you a little bit more because those two numbers are very different. And for almost every brand, they're different. And the reason they're different is because Of usually two parts. The first part is customers don't have the ability to return and spend more money because of the way that the product suite is set up. And so they might sell a wallet, but then the only product that anyone can come back and buy is like a pen. And so the returning customer average order value was really low, but the first time customer average order value was really high. Or vice versa, maybe they do have a really large skew of products and they have, I don't know, a thousand different products. What will always be the case is returning customers will have a higher AOV. And that's because they have increased purchasing power because they already trust the brand. They've experienced the brand, they liked it, they're coming back, they're willing to spend more. and so they're much more likely to be upsold and spend two, 300 on the initial 150. And so now you start to have a little bit more of a nuanced understanding of, okay. When we say increase AOV, we're really trying to increase either new customer AOV or returning customer AOV, and they're two very different problems because the consumer psychology on returning customers is very different from the consumer psychology on people that are just entering into the brand and the website. it goes even a step further to that, which is that AOV is a mean. So it's an average output of the dataset, but the average tells you nothing because it doesn't show you the cohort distribution of the customers over the, the cohort of customers over pricing. And so when you look at the actual cohort, your majority of brands, once again, you'll usually see that there's a bimodal distribution. And so average order value doesn't look like up to 80 and then back down on the other side. It'll be a peak at 40 and then a peak at 100. And so now if you think that there's a peak at 40 and a peak at 100 and you're trying to move an 80 AOV, you're not going to move it correctly because you don't understand where the cohorts sit. If you want to move 80 up to 100, and we've done this for multiple times for multiple brands, it's not by setting a 100 free shipping threshold, it's by setting a 50 free shipping threshold. And you get that doesn't. Why that doesn't make sense because you're sitting at way under what it currently is. But it's because we're moving the lower cohort up. And if we can drag that bottom cohort upwards to 60 to 70 dollars, then suddenly the average moves to 100. it's only through looking at cohort distributions and then breaking it down by new customer and returning customer that you can start to make really educated decisions on how you're actually pulling individual audiences and moving them around on that cohort graph. I guess more so a question for, agencies, because, I would think email marketing is probably more geared towards return, whereas pay is gonna be more geared towards, actual top of funnel traffic. have you had instances or have, said, Hey, like we need to increase our bottom of funnel on, let's say Facebook. Or, and that actually translates to, an increased AOV on, the top line numbers for return customers. Or do you think that's something that people should leave more so for like sales and email and that side of things? Yeah. for sure. I've seen it. it depends. It's very brand specific. generally as a marketer on paid ads, I would be KPI'ing yourselves around first time customer AOV. returning customer AOV is normally going to be predictive of where you're driving traffic to through emails. And so if you're driving traffic to lower end products or to individual product pages, you'll generally see lower AOVs. It doesn't allow the consumer to increase the discoverability of other products. so that's a really interesting insight in itself, which is that. Consumers that come from email are already highly likely to buy because they've already experienced the brand, they've made the click, they're very high intent. If you silo them into a single product, they're just going to buy the single product. But if you drop them onto a collection page where there's now 10 products, normally, in regular, buying psychology, you would go, that's too many options, they're not going to be able to choose. But in this instance, they're already super high intent. And so now, it's not going to go, they can't choose, it's going to go, how many are they going to choose? And so that's when you start to see an increase in like units per transaction within individual orders. And that's when you'll see the uplift in returning customer AOV. it makes sense. cause of the same mindset of, we're paying for all this traffic. Let's maximize the potential of the traffic, let's try to optimize for new customers, not repeat customers and trying to increase AOV. We have other channels for that, right? obviously you can run email sales, all that kind of stuff. Yeah. But I think one of the most interesting points too, that I think we can maybe, I guess just be aware of, is that when someone buys more of your product, depending on what business you have, so if it's a clothing brand, let's say, you can pair other products together in the remarketing side of it. So the hero product might be like, a shirt or, pants, whatever the case may be, bundle that all together. And then on the return you have, like you said, that full collection, to where they say, oh, complete the, the look by getting, this, and this. and then it makes a lot of sense from a returning standpoint versus, just purely going after the same customer again and again, because clothing is extremely competitive. and so I think it makes a lot of sense on just trying to get the entry point AOV up, because I assume if someone buys more on the first time order, they're going to buy more on the second time order if it's, a product like that. And this is a really common misconception that I see a lot, which is, Okay, you shouldn't optimize for the highest average order value on first purchase because that's smaller end product that's only 40 that might drive better LTV. Not true. Like it's never true. it's so rarely the case because if you're looking at lifetime contribution margin, you're not If you maximize first order contribution margin, most instances, that's 50 percent of the lifetime anyway. And so if you can make sure you're getting as much revenue or as much margin on that first order, that's significantly going to inflate the LTV of that product. And so it's very rarely the case that you'll go, okay, a 40 product is going to drive better LTV than an 80 product. Just maximize for average order value on first purchase, because that scenario is so unlikely. Okay. and then what you were talking about there was really like the next level of average order value, which I don't think many people look at, but intuitively a lot of people understand it, which is that to increase average order value, we need to have more items in cart. We need to have people buying more, we need them buying two, or we need them putting other products into their carts that have increases. Fundamentally, you can calculate average order value at an individual unit level. Based on average unit retail, which is the average price of a product, times units per transaction, which is how many products are in the cart, plus 1 minus return rates, plus 1 minus discount rates, so that's just taking returns off, taking discounts off, and then plus shipping collected. Because within e commerce, you also collect shipping. And so that's a part of the average order value. equation and the final number that you get. And so when you start to look at those five levers, because anytime you have a metric and you're trying to move it, it all depends on the levers that are the subsets of that metric. Shipping collected, not really much control over returns, not really much control over discounts. You can control, and that's what we talked about in the last video. So I would make sure you're not discounting too heavily. average unit retail, so the price, you've got control of that, but most brands don't want to move their pricing. And also, it's risky because of the elasticity of demand that might exist with their current price. And so that's, that is a lever, I understand that you can change that, but not a huge one. And so what you're ultimately left with is units per transaction. If you want to increase average order value, you need to increase units per transaction. And so if you can track units per transaction as an Ecom operator as well, and then you can KPI around that's going to be the predictor of what your average order value ends up looking like. and then you can get really nuanced with this, was like, I just feel my brain exploding with information, topics to talk about, but no, it makes sense. I think from a implementation standpoint, something as simple as with the mindset, like you just said of like increasing the overall products that you're trying to get someone to have added to their cart. I'm trying to increase the amount of investment they have put into the actual company, because yeah, like for some reason people think Oh no, they spent more money, so they're not going to spend more on the second transaction. It's like people's money with you is investing in like your company. Is not a finite number, It's variable. You don't know the situation of the person. You don't know if this is going to be like, they're testing it out and then they want to get more. it could be a one off by we don't have that information, right? So why not just maximize that first initial touch point? And then just by the basis of psychology, if someone's more invested in your brand itself. They're going to buy again, if it's a good product and that's the key, obviously is having a good product, but you still get that, from a initial marketing standpoint, you get that profit up front and then you can use that to increase, scale, wherever the case may be, just makes things a lot easier. And then the return AOV is obviously a whole nother, area, like you were talking about, that's more of, like you could say the icing on top of your leverage points. to focus on outside of just the, paid marketing set of things. completely makes sense. But, I can just see how, we can rabbit hole on this for hours and hours. maybe we'll have another though, talking about AOV and like sales. I think that might be cool. but yeah. Anything else you wanted to add to, the topic of AOV? No, the only one is you made a really interesting point there and I might actually go and pull some data on it, which is that, what you said was. the higher price the item that, consumer buys on first purchase, the higher likelihood of repeat purchase rates being higher. and I think that's actually a really interesting concept because technically speaking, the higher price an item is across a brand, generally speaking, the more value the product's driving, because pricing of a product is generally indicative of the value of the product. And so if people are buying a more valuable product, it generally should drive them more value. And so then they should likely. Repeated higher purchase rates. And so I'm actually going to pull data on that to see if that actually holds across like 10 to 20 different brands. But that's really interesting is drive people to the premium product. Cause if they experienced the premium product, they're more likely to buy it now because they had a better experience. it all depends on your business model too, right? If you have a consumable, then makes a lot of sense. If you have a one off buy, then probably doesn't make as much sense. So I think that's another caveat to add to the equation is. Making sure it's the right business for that to actually be possible. But, yeah, I think it makes a lot of sense. So a lot of levers to pull outside of just marketing, not just in the marketing side of things. So if you're a business owner and you're like, Hey, I want to try to squeeze more. I don't think this agency is doing X, Y, Z, or, there's something that I want to change. Then, cause I know I have a lot of business owners that say I want to change something. Like we need to move something. We need to have an adjustment. It's like focus on these concepts to then change the back end of the business. And then have that trickle out to, for example, the marketing side of it. I think that makes a lot of sense. Yeah. So anyways, thanks again guys. And we'll probably have some more videos coming out here soon, whenever you guys want to learn more about financial stuff and have your head explode, Nathan's the guy for you. where can they find you? blue sense digital on YouTube. So I'll give you the link. It'll be in the description, blues brothers podcast. If you want to listen to that long format and then my LinkedIn, which is Nathan Padreo, alright, perfect. Thanks again. See you guys. Thanks Caden..