Is Increasing Your Average Order Value (AOV) the Solution?

Caden: 00:00:11

Average order value in Shopify, that metric by itself doesn't

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really tell you anything in terms

of actionables off the back end.

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And so when you look at that number and 80

or 90, it's not really telling you much.

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And so you can break

it down a step further.

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Hey, how's it going, everyone?

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So we're back again with Nathan.

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and he just been, getting blown

up by all the comments and

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like people reaching out to us.

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we want to hear more about what's going

on with PNLs, how to understand and

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demystify everything that CFOs talk about.

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and so when it comes to marketing, it's

not just about running Google ads a

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certain way or Facebook ads a certain way.

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It's about actually

understanding the business.

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and so Nathan's a really good resource

for both me and other people at

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Solutions 8, to have chats about,

more of the, back and finance side

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of things and how that kind of comes

into, place with, marketing as a whole.

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now I think we're going

to talk more about AOV.

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and when I think of AV, I just think of

average order value, the type of customer

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and more of the psychology behind it.

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But, yeah, I just wanted to hear your

thoughts on that and also welcome back

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and, yeah, let's jump right into it.

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Thank you.

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Thank you for having me back.

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Looking forward to it.

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I thought AV would be a good topic

for this video because I think it

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encapsulates well, the lack of a deep

understanding of e commerce analytics.

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by most e commerce operators, as

well as even, performance marketers

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that are actually in the field.

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And this isn't to say that you need

to have this deep of an understanding

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of each individual metric, but it

should help you uncover that if you

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do have an AOV problem, or if you've

tried to increase average order value

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in the past through a threshold or

through a bundle, and it hasn't worked

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like what we're about to run through

should hopefully contextualize why.

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All right.

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and give you a better understanding of all

of the levers on the average order value

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and how complex it actually is so that you

can make a more educated decision on how

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you're going to try to fix it or whether

you even need to fix it within the context

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of the unit economics of your brand.

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So to start would be, average

order value in Shopify.

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That metric by itself doesn't

really tell you anything in terms

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of actionables off the back end.

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And so when you look at

that number and 80 or 90.

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It's not really telling you much.

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And so you can break it down a step

further and you can look at new customer

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AOV versus returning customer AOV.

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And that starts to tell you a

little bit more because those

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two numbers are very different.

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And for almost every

brand, they're different.

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And the reason they're different

is because Of usually two parts.

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The first part is customers don't

have the ability to return and

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spend more money because of the way

that the product suite is set up.

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And so they might sell a wallet, but

then the only product that anyone

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can come back and buy is like a pen.

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And so the returning customer

average order value was really

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low, but the first time customer

average order value was really high.

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Or vice versa, maybe they do have a really

large skew of products and they have, I

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don't know, a thousand different products.

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What will always be the case is returning

customers will have a higher AOV.

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And that's because they have

increased purchasing power because

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they already trust the brand.

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They've experienced the brand,

they liked it, they're coming back,

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they're willing to spend more.

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and so they're much more

likely to be upsold and spend

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two, 300 on the initial 150.

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And so now you start to have a little bit

more of a nuanced understanding of, okay.

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When we say increase AOV, we're really

trying to increase either new customer

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AOV or returning customer AOV, and they're

two very different problems because the

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consumer psychology on returning customers

is very different from the consumer

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psychology on people that are just

entering into the brand and the website.

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it goes even a step further to

that, which is that AOV is a mean.

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So it's an average output of the dataset,

but the average tells you nothing

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because it doesn't show you the cohort

distribution of the customers over the,

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the cohort of customers over pricing.

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And so when you look at the actual

cohort, your majority of brands,

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once again, you'll usually see that

there's a bimodal distribution.

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And so average order value

doesn't look like up to 80 and

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then back down on the other side.

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It'll be a peak at 40

and then a peak at 100.

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And so now if you think that there's a

peak at 40 and a peak at 100 and you're

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trying to move an 80 AOV, you're not

going to move it correctly because you

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don't understand where the cohorts sit.

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If you want to move 80 up to 100, and

we've done this for multiple times for

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multiple brands, it's not by setting

a 100 free shipping threshold, it's by

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setting a 50 free shipping threshold.

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And you get that doesn't.

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Why that doesn't make sense because you're

sitting at way under what it currently is.

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But it's because we're

moving the lower cohort up.

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And if we can drag that bottom cohort

upwards to 60 to 70 dollars, then

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suddenly the average moves to 100.

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it's only through looking at cohort

distributions and then breaking it

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down by new customer and returning

customer that you can start to make

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really educated decisions on how you're

actually pulling individual audiences and

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moving them around on that cohort graph.

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I guess more so a question for, agencies,

because, I would think email marketing

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is probably more geared towards return,

whereas pay is gonna be more geared

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towards, actual top of funnel traffic.

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have you had instances or have, said,

Hey, like we need to increase our

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bottom of funnel on, let's say Facebook.

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Or, and that actually translates

to, an increased AOV on, the top

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line numbers for return customers.

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Or do you think that's something that

people should leave more so for like

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sales and email and that side of things?

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Yeah.

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for sure.

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I've seen it.

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it depends.

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It's very brand specific.

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generally as a marketer on paid

ads, I would be KPI'ing yourselves

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around first time customer AOV.

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returning customer AOV is normally

going to be predictive of where you're

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driving traffic to through emails.

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And so if you're driving traffic to lower

end products or to individual product

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pages, you'll generally see lower AOVs.

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It doesn't allow the consumer to increase

the discoverability of other products.

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so that's a really interesting

insight in itself, which is that.

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Consumers that come from email are already

highly likely to buy because they've

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already experienced the brand, they've

made the click, they're very high intent.

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If you silo them into a single

product, they're just going

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to buy the single product.

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But if you drop them onto a collection

page where there's now 10 products,

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normally, in regular, buying psychology,

you would go, that's too many options,

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they're not going to be able to choose.

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But in this instance, they're

already super high intent.

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And so now, it's not going to go,

they can't choose, it's going to go,

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how many are they going to choose?

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And so that's when you start to

see an increase in like units per

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transaction within individual orders.

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And that's when you'll see the

uplift in returning customer AOV.

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it makes sense.

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cause of the same mindset of,

we're paying for all this traffic.

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Let's maximize the potential of

the traffic, let's try to optimize

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for new customers, not repeat

customers and trying to increase AOV.

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We have other channels for that, right?

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obviously you can run email

sales, all that kind of stuff.

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Yeah.

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But I think one of the most interesting

points too, that I think we can maybe,

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I guess just be aware of, is that when

someone buys more of your product,

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depending on what business you have,

so if it's a clothing brand, let's

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say, you can pair other products

together in the remarketing side of it.

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So the hero product might be like,

a shirt or, pants, whatever the case

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may be, bundle that all together.

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And then on the return you have, like

you said, that full collection, to

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where they say, oh, complete the,

the look by getting, this, and this.

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and then it makes a lot of sense

from a returning standpoint versus,

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just purely going after the same

customer again and again, because

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clothing is extremely competitive.

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and so I think it makes a lot of sense

on just trying to get the entry point

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AOV up, because I assume if someone buys

more on the first time order, they're

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going to buy more on the second time

order if it's, a product like that.

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And this is a really common misconception

that I see a lot, which is, Okay, you

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shouldn't optimize for the highest

average order value on first purchase

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because that's smaller end product that's

only 40 that might drive better LTV.

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Not true.

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Like it's never true.

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it's so rarely the case because if you're

looking at lifetime contribution margin,

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you're not If you maximize first order

contribution margin, most instances,

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that's 50 percent of the lifetime anyway.

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And so if you can make sure you're getting

as much revenue or as much margin on

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that first order, that's significantly

going to inflate the LTV of that product.

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And so it's very rarely the case that

you'll go, okay, a 40 product is going

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to drive better LTV than an 80 product.

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Just maximize for average order

value on first purchase, because

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that scenario is so unlikely.

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Okay.

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and then what you were talking about

there was really like the next level of

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average order value, which I don't think

many people look at, but intuitively a

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lot of people understand it, which is

that to increase average order value,

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we need to have more items in cart.

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We need to have people buying more,

we need them buying two, or we need

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them putting other products into

their carts that have increases.

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Fundamentally, you can calculate average

order value at an individual unit level.

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Based on average unit retail, which

is the average price of a product,

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times units per transaction, which

is how many products are in the cart,

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plus 1 minus return rates, plus 1

minus discount rates, so that's just

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taking returns off, taking discounts

off, and then plus shipping collected.

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Because within e commerce,

you also collect shipping.

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And so that's a part of

the average order value.

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equation and the final

number that you get.

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And so when you start to look at

those five levers, because anytime

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you have a metric and you're trying to

move it, it all depends on the levers

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that are the subsets of that metric.

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Shipping collected, not really

much control over returns, not

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really much control over discounts.

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You can control, and that's what

we talked about in the last video.

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So I would make sure you're

not discounting too heavily.

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average unit retail, so the price,

you've got control of that, but most

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brands don't want to move their pricing.

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And also, it's risky because of

the elasticity of demand that might

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exist with their current price.

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And so that's, that is a lever,

I understand that you can

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change that, but not a huge one.

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And so what you're ultimately left

with is units per transaction.

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If you want to increase average

order value, you need to

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increase units per transaction.

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And so if you can track units per

transaction as an Ecom operator as

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well, and then you can KPI around that's

going to be the predictor of what your

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average order value ends up looking like.

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and then you can get really nuanced with

this, was like, I just feel my brain

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exploding with information, topics to

talk about, but no, it makes sense.

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I think from a implementation standpoint,

something as simple as with the mindset,

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like you just said of like increasing the

overall products that you're trying to

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get someone to have added to their cart.

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I'm trying to increase the amount of

investment they have put into the actual

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company, because yeah, like for some

reason people think Oh no, they spent

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more money, so they're not going to

spend more on the second transaction.

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It's like people's money with you

is investing in like your company.

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Is not a finite number, It's variable.

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You don't know the

situation of the person.

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You don't know if this is going

to be like, they're testing it out

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and then they want to get more.

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it could be a one off by we don't

have that information, right?

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So why not just maximize that

first initial touch point?

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And then just by the basis of

psychology, if someone's more

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invested in your brand itself.

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They're going to buy again, if it's

a good product and that's the key,

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obviously is having a good product,

but you still get that, from a initial

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marketing standpoint, you get that profit

up front and then you can use that to

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increase, scale, wherever the case may

be, just makes things a lot easier.

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And then the return AOV is obviously a

whole nother, area, like you were talking

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about, that's more of, like you could say

the icing on top of your leverage points.

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to focus on outside of just the,

paid marketing set of things.

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completely makes sense.

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But, I can just see how, we can rabbit

hole on this for hours and hours.

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maybe we'll have another though,

talking about AOV and like sales.

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I think that might be cool.

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but yeah.

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Anything else you wanted to

add to, the topic of AOV?

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No, the only one is you made a really

interesting point there and I might

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actually go and pull some data on

it, which is that, what you said was.

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the higher price the item that,

consumer buys on first purchase,

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the higher likelihood of repeat

purchase rates being higher.

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and I think that's actually a really

interesting concept because technically

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speaking, the higher price an item is

across a brand, generally speaking,

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the more value the product's driving,

because pricing of a product is generally

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indicative of the value of the product.

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And so if people are buying a more

valuable product, it generally

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should drive them more value.

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And so then they should likely.

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Repeated higher purchase rates.

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And so I'm actually going to pull data

on that to see if that actually holds

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across like 10 to 20 different brands.

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But that's really interesting is

drive people to the premium product.

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Cause if they experienced the premium

product, they're more likely to buy it

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now because they had a better experience.

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it all depends on your

business model too, right?

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If you have a consumable,

then makes a lot of sense.

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If you have a one off buy, then

probably doesn't make as much sense.

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So I think that's another caveat

to add to the equation is.

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Making sure it's the right business

for that to actually be possible.

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But, yeah, I think it

makes a lot of sense.

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So a lot of levers to pull outside

of just marketing, not just in

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the marketing side of things.

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So if you're a business owner and you're

like, Hey, I want to try to squeeze more.

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I don't think this agency is

doing X, Y, Z, or, there's

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something that I want to change.

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Then, cause I know I have a

lot of business owners that

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say I want to change something.

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Like we need to move something.

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We need to have an adjustment.

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It's like focus on these concepts to

then change the back end of the business.

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And then have that trickle out to,

for example, the marketing side of it.

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I think that makes a lot of sense.

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Yeah.

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So anyways, thanks again guys.

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And we'll probably have some more

videos coming out here soon, whenever

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you guys want to learn more about

financial stuff and have your head

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explode, Nathan's the guy for you.

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where can they find you?

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blue sense digital on YouTube.

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So I'll give you the link.

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It'll be in the description,

blues brothers podcast.

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If you want to listen to that long

format and then my LinkedIn, which

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is Nathan Padreo, alright, perfect.

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Thanks again.

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See you guys.

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Thanks Caden..