Win-back Timing model
The problem with 90-day win-back campaigns
Most brands wait until a customer hasn't bought in 90 days before running a win-back campaign. LiftSignals data consistently shows this is too late — by 90 days, win-back success rates typically fall below 10%.
The optimal win-back window — the period when a lapsed customer is most receptive to re-engagement — is typically 35–65 days after their last purchase, depending on their individual purchase rhythm.
How the model works
The Win-back Timing model calculates the optimal re-engagement window for each customer individually, based on:
- Their personal average purchase gap (not the store average)
- How their previous gaps have varied over time
- Historical response patterns from similar customers who received win-back messages
- Current churn score trajectory
Win-back window status
| Status | Meaning | Action |
|---|---|---|
| Not yet open | Customer is within their normal purchase rhythm | No action — they're not overdue yet |
| Window opening soon | Optimal window starts within 7 days | Prepare your win-back message now |
| Window open | Customer is currently in their highest-receptivity period | Send win-back message today — this is the optimal moment |
| Window closing | Less than 5 days before win-back probability drops significantly | Last chance — send today if you haven't already |
| Window closed | Optimal period has passed — harder to win back now | Lower-priority — try a bigger incentive |
Viewing win-back windows
- Grow screen — Shows all customers with currently open win-back windows
- Customer Profile → Intelligence tab — Shows this specific customer's window status and days remaining
- Audiences — Filter by
winback_window = opento build a targeted daily export
Best practice: Create a daily scheduled export of the "Win-back window open" audience to Klaviyo or Attentive. As customers enter and exit their window, the export automatically stays current without any manual work.
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