Customer Analytics That Go Beyond Average Order Value (AOV)

Customers are all the same, right? Can’t we just pull metrics from our customer analytics and build strategies using averages? Perhaps. But what happens when you start digging deeper into the averages? Customers know they aren’t average and they don’t expect to be treated as such.
Let’s look at how we can unpack metrics based on average order value (AOV). Before we get into a statistics course, I just want to point out the difference of average (mean) versus median. A median can eliminate outliers on the high or low end of your data set since it’s simply the middle value. However, if you have a shifted bell curve, you can end up with a median above or below the average. In a perfect world they would be the same number.
Here’s an interesting look at how the AOV compares to the median order value for a retailer’s customer base. Notice how different the AOV is from the median in upper revenue deciles. This indicates we have outliers pushing the average way up, while the values converge to approximately the same number around deciles 4 to 9.

Now back to customer AOV… Your customers are different, but they can be grouped by several different similarities. Simply by looking at AOV by customer decile, you can start to identify shoppers with the highest likelihood to become your next best customers before they make their second purchase. In the chart below, you can see how the top three (3) deciles produce an AOV between $ 105-164 which could be used to put an automated campaign in place to nurture first-time buyers to a second purchase, bolstering your best customers segment.

Another way to look at AOV would be to track it over time. By plotting AOV by week, you can spot trends and then break down buyers from that period to identify trends in products or categories. In the example below, we can see that the AOV for the year is $ 115 but it varies from $ 82 to $ 149 throughout the year. That’s an 82% jump and when you look at the people who made their first purchase during that AOV peak; the customer’s average lifetime value (LTV) based on a first purchase in March/April jumps from $ 163 to $ 296, another 82% increase. Coincidence? Not really, once you do the math.

Hopefully this gives you a perspective on AOV that you never considered before. We need to stop thinking about our customers as one big mob of people. By using a customer analytics platform like Listrak CRM, we can help show you the secrets that lie within your customer data.

Mike Hartman
Senior Director of Product Strategy, Strategic Planning

Listrak Insights | Marketing Strategies, Insights and Trends

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