Should “lapsed customers” be segmented by context before entering a win-back flow?

I’m pressure-testing a lifecycle recovery framework and would love input from people running real Klaviyo flows.

The basic question:

Should customers who appear “lapsed” be treated differently based on context before entering the same win-back flow?

For example:

• 45 days since purchase + bought 1 unit + recently engaged
→ recovery candidate

• 45 days since purchase + bought 3 units
→ may not actually be due yet

• overdue + recent support/refund issue
→ resolve the service issue first

• overdue + email undeliverable
→ reachability problem, not another-email problem

I mapped the idea in the attached illustration.

Important: all numbers in the image are synthetic. This is a methodology demo, not a client result.

I’m also looking for one Shopify/Klaviyo merchant willing to pressure-test this on one real lifecycle flow.

I’ll do the initial review for $0.

One anonymized screenshot/export is enough to start — no full store access or customer identities needed.

If anyone here runs a real replenishment or lapsed-customer flow and is open to testing it, I’d be interested to compare the framework against what actually happens in your store.