How do you prioritize win-back customers once they are already overdue?

I’m pressure-testing a retention assumption with real Shopify/Klaviyo operators.

Suppose a product normally has a ~45-day reorder cycle.

You now have four customers who are all past or near that window.

Do you treat them similarly, or do you prioritize using signals such as:

• previous order count
• customer value
• recent email/SMS engagement
• product/SKU
• discount behavior
• refund/complaint history
• subscription/eligibility status

My hypothesis is that “overdue” alone may be too weak a signal, and that the more useful decision is:

Who is actually worth a win-back action first?

But I also want to test the opposite possibility — that existing Klaviyo segmentation/RFM/cohort logic already solves this well enough and another prioritization layer adds little value.

I’m looking for 3 real Shopify/Klaviyo operators willing to pressure-test this with ONE real repeat-purchase product.

To start, I only need:

1. Product/category
2. Approximate reorder window
3. How you currently make this decision

If we go one step further, any customer-level examples must be fully anonymized — no names, emails, phone numbers or other identifying information.

I’m especially interested in firsthand operator experience, including cases where the existing Klaviyo setup already solves this problem.