By figuring out your Returns Rate, you'll have an idea of how many returns you'd need to process each month.
The only other thing you need to forecast your returns each month is your monthly order volume.
(Repeat Customer Insights can automatically calculate your Average Order Volume over a year if you don't want to go through a bunch of order date by hand)
If January had 1,000 orders and your return rate averages at 5%, that's 50 returns you'll have to handle. 1 or 2 per day. Not a big deal but something you'd want a process for.
But 10,000 orders per month with a 10% returns rate would be 1,000 orders per month or over 30 returns per day. Now you need staff or even an outsourced returns processing system.
At that level it could be profitable to spend some resources to reduce your Returns Rate too.
There'll be some carry over from month-to-month (e.g. November purchase, returned in January) but much of it will be leveled out over time.
Eric Davis
Segment your customers to find the diamonds in the rough
Not all customers are equal but it is difficult to dig through all of your data to find the best customers.
Repeat Customer Insights will automatically analyze your Shopify customers to find the best ones. With over 150 segments applied automatically, it gives your store the analytics power of the big stores but without requiring a data scientist on staff.