You can use Shopify's updated customer list to get a rough idea of your loyal customers.
First you'll need to decide how to measure their loyalty. For that you can mimic the RFM model and look at:
- How recently they ordered: say the last 90 days
- How frequently they ordered: say 10 times
- How much money they've spent: say $500
Using Shopify's fields that'll be the query:
last_order_date >= 90_days_ago AND number_of_orders >= 10 AND amount_spent >= 500
The only problem is where did I get those numbers?
I just made them up.
90 days might be good, but your store might have longer cycles where customers go 300+ days in-between orders.
10 orders might be excessive and take a decade or it might be too low and only account for two months of ordering by a customer.
$500 might be completely off too, that might be 20x your Average Order Value or 1/10th of what a single order is.
To figure out what numbers work for you, you'll have to spend the time to analyze your customer data. You might be able to make guesses but it's going to be difficult to narrow down what loyalty means for your store.
Plus it'll change from year-to-year as your store and customers change.
That's why the full RFM model used by Repeat Customer Insights is better. It'll automatically figure out what values to use for your store and adjust them everyday as new orders come in.
Starting with Shopify's segments to get an idea about your customer data makes sense. Just be careful making decisions based on it without having a proper analysis done.
Optimize your promotion timing to save money and attention
Repeat Customer Insights will analyze a ton of customer behavior data for you, including their buying cycles.
If you knew exactly when the majority of your customers were ready to buy again, you can increase your orders and profit just by tweaking your message timing.