Let’s look at a high-value customer segment for your Shopify store.
You’re aware that there’s a cost to get each customer. It may be direct costs from advertising or indirect ones like spending time on SEO or content marketing.
Whatever the source, those costs can be pretty high. Every additional dollar spent acquiring a customer is profit taken away from your store.
And it hurts even more when you lose a customer after their first purchase. You invested all that money into acquiring them, they place one order, and then they are gone.
That’s what this segment today is going to help you with.
You’re going to learn how to segment your customers so you can find the ones that are at a high risk of leaving (or who already left).
Customers with a Frequency of 1 order will be your one-time customers, the ones who you’ve spent the most money on to acquire.
Combining that with customers with a Recency in the past, you’ll be able to find who could be ready for another purchase.
You can do this using the Shopify Customer admin panel like before but by adding two filters and sorting. Shopify doesn’t let you sort by two columns at once so the filters will help to restrict the customers shown.
- Visit your Shopify Customer admin panel and add a filter of "Number of orders is equal to 1"
- Add a second filter for customers who Placed an order on or before 6 months ago. You’ll need to change the date you use.
- Now sort your customers by the last order
What you can do with these customers is to load them into an email marketing service and send them a campaign called a Win-Back. This campaign is designed to try to get them to come back to your store and make another purchase.
You’ll probably want to include a lot of trust-building elements because they might not be familiar with your brand any more. Maybe even include an incentive for them like a discount or bonus product.
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.