# Average Order Value, and how to calculate it

Your Shopify store’s Average Order Value (AOV) is one of the key metrics you want to keep track of.

### Average Order Value definition

Average Order Value shows how much each customer spends in an order, on average (hence the name).

It is calculated on orders in a date range so you’ll end up with some average customers, some high value customers, and some low value customers. Your store’s specific mix of different customer segments will determine what your AOV ends up at.

(That’s actually one way to increase the average order value: try to get more customers from the higher end to make more purchases).

It’s not as useful as customer lifecycle metrics like customer lifetime value (CLTV or LTV) but it’s much easier to calculate because it doesn’t require forecasting future revenue. That makes it a key metric for new stores who don’t have enough purchasing data to know what their customer lifetime value is.

### Calculating Average Order Value

Calculating your average order value in Shopify is quite easy. For this example, we’ll calculate the Average Order Value for April and May 2016 using the Sales by Month report in Shopify.

#### 1. Find total sales for the month

Using the Total Sales metric, you can see that April had \$4,473.91 and May had \$1,160.45 in total sales.

As an aside, May didn’t look to good. I’d consider digging deeper into the data to see why sales dropped that much.

#### 2. Find order count

Using the same report, Shopify shows us the number of orders for each month — 38 for April and 10 for May.

Which also explains why May did so poorly, this store didn’t have many orders.

#### 3. Divide total sales by order count

Now to find the Average Order Value we just divide the total sales by the order count.

April

`````` 4473.91
---------  = 117.74
38``````

May

`````` 1160.45
---------  = 116.04
10``````

### Drawing conclusions

Based on these two quick calculations we can draw a few conclusions:

• our AOV has dropped in May but not a significant amount
• our number of orders has dropped significantly so we’re not acquiring as many customers as April
• depending on the margin and any other costs, we have an upper limit of about \$116 per order
• each new customer we acquire should add \$116 in revenue on average
• at an order volume of 100 per month, we should make \$11,600 in total revenue or \$116,000 for 1000 orders per month

### Using Average Order Value with customer acquisition

One place where Average Order Value shines is with customer acquisition. You can use it to make sure that you’re acquiring customers at a low enough cost to still make a profit.

For example if your AOV is \$100, customer acquisition cost is \$10, and operating margin is 20%, then you’re making \$10 profit per order:

`\$100 - \$80 COGS (20% margin) - \$10 acquisition = \$10`

If customer acquisition increased to \$25, now you’re losing money on each order.

`\$100 - \$80 COGS (20% margin) - \$25 acquisition = -\$5`

But if you increased Average Order Value by the same \$15, you’re back in the black.

`\$115 - \$80 COGS (20% margin) - \$25 acquisition = \$10`

### Other ways to use Average Order Value

Average Order Value is a simple calculation so it can be used in a variety of different ways. You calculate and compare it for different time periods.

• for the month, like in the examples above
• for the year-to-date
• for the trailing 12 months

You can compare orders from different marketing channels.

• orders from organic SEO traffic

It is usually summarized across your entire customer base, but you can also calculate it for different segments of your customers

• new customers
• repeat customers
• geographic location (e.g. customers in the USA vs Canada)

One of my Shopify apps, Repeat Customer Insights, will even combine the average order value with the customer purchase latency which will tell you if repeat customers are spending more with each subsequent purchase or less.

### Average Order Value’s impact on conversions rates

Sometimes when you’re trying to optimization your conversion rate, you’ll be told to track Average Order Value too. They aren’t directly related but if your online store doesn’t watch them both, you could over-optimize and weaken one metric.

If you increase your conversion rate, you’d get additional orders each month. But if in the process of that you cause your Average Order Value to drop you could lose enough profit to eat into those additional orders and perhaps deeper.

So make sure to watch Average Order Value as you optimize your store and back off any changes that negatively impact your conversion rate. Similarly, watch your conversion rates when you’re increasing your AOV.