The value of repeat customers has been measured and studied for decades in various places.
Today I want to show you a quick, back-of-the-napkin way to calculate this for your average customer and then how you can what-if to see the impact of different changes.
You'll need only two metrics, both of which are supplied by Repeat Customer Insights in the Store Analysis. You can calculate them yourself if you don't have the app.
- Average Order Value (AOV)
- Average orders per customer
I'll use the metrics from my demo in this example.
- Average Order Value (AOV): $171.01
- Average orders per customer: 1.34
Calculate the value of the average repeat customer
What this calculation does is assume you have an average customer who places an average number of reorders. I'll show the calculation first and then explain how it works.
value = AOV * Average orders per customer value = $171.01 * 1.34 value = $229.15
One way to think about this is, Average orders per customer is a range from one to infinity. Every customer has at least one order (their first order) but some will have repeat orders.
For the demo data, this means customers have the first order and about 1 out of 3 customers have later orders (the .34 part). That whole thing can be multiplied by the Average Order Value to figure out how much the orders are worth.
For example, these metrics describe this scenario.
- Customer A has one $171 order
- Customer B has one $171 order
- Customer C has two $171 orders
So each repeat customer is worth about $229 to this store. $171 when they first order and maybe $58 in additional orders. Compare that to one-time customers who are worth $171.
It would make sense to spend $58 per customer to get 1/3rd of them to place a second order.
What I like to think about next is adjusting the values.
- What if you increased AOV by $20?
- What if you could get your Average orders per customer to increase 0.3?
- What if order sizes increase but there are less orders per customer?
- What if you heavily discounted which dropped AOV by $40, but got 0.5 more orders per customer?
Each of those what-ifs should only take a minute to re-calculate, but can give you a lot of information for planning out your longer-term strategies and offers.
This is a simple formula. There are more complex ones that can give more precise answers, but this has the beauty of fitting onto an actual napkin and only needs two business metrics to work out.
Start noticing seasonal spikes in customer behavior
Cohort reports let you detect seasonal spikes as well as long-term retention cycles. Repeat Customer Insights can automatically create cohorts for your Shopify store, going back to your very first order.