I just pulled out most of my peas after five months of growth.
They produced wonderfully over that time but their production has dropped significantly in the past weeks. Plus I need to make room for the cucumbers.
Not every vegetable will produce forever. They all have limits to how long they are worth growing.
Just like not every product will be profitable forever.
Some products will last year.
Others might only last months.
Some might only last a few days.
That’s why you need to measure their performance and transition them to a closeout plan near the end of their useful lifecycle. It’s no big deal as long as you’ve been building up new products to replace them.
Looking at month-over-month order counts and sales is a good way to measure this. You’ll likely want to track it against their mid-life volume, that time when they were established and selling well.
You can also track how new customers are receiving them. It’s a more complex calculation but it can show you products that are good and bad at creating repeat customers, even if their volume is low.
To do that:
- Take the new customers who bought that product,
- track how those customers reorder, and
- see how those customers compare to your overall store performance.
If those products are producing under-performing repeat customers, you’ll want to transition them out sooner. You could be losing the chance to have those customers buy a better performing product (and come back to buy again).
Or if they are producing VIPs and superstars, you might keep them around even if the sales are low. These gateway products can be sleeper hits, ones that your most loyal customers use.
The First Product Analysis in Repeat Customer Insights measures how products bought by new customers perform over the customer’s lifecycle. It would be easy to take that analysis and run through the comparison to find products that should be transitioned out.
Use cohorts to find out who the best customers are in your Shopify store
Repeat Customer Insights will automatically group your customers into cohorts based on when they first purchased. This will let you see how the date customers bought would impact their behavior.