Lapsed Shopper Win-Back Campaign

Example output

Lapsed shopper win-back campaign — Briar & Bloom Herbal Tea

Lapse-depth segmentation
Rather than treat all 12,000 lapsed members identically, split by depth:
1. Recently lapsed (120-180 days, likely the largest share of the 12,000): still fairly warm; a smaller nudge is probably sufficient, and over-discounting this group wastes budget on people likely to return with a lighter prompt.
2. Deeply lapsed (180+ days): a weaker relationship to revive; justifies a stronger incentive since the risk of losing them permanently is higher and a light touch is less likely to work.
[Confirm the actual split between these two bands in your 12,000 before finalizing budget allocation — the read below assumes a roughly even split, adjust once you have the real numbers.]

Win-back message framework
Reference the prior relationship directly — these are not cold shoppers:
- Recently lapsed: "We've missed you" tone, referencing their past habit lightly (e.g. "your usual order") without an aggressive discount — a light nudge plus a reason to reconsider (new flavor, seasonal relevance) may be enough.
- Deeply lapsed: a more direct "come back" message with a stronger incentive, acknowledging plainly that it's been a while rather than pretending no time has passed.

Incentive mechanics by lapse depth
- Recently lapsed: a modest reminder offer, sized to nudge rather than fund the whole purchase decision.
- Deeply lapsed: a larger incentive, justified because the alternative is likely permanent loss of the household, not a delayed return.
Model both incentive levels against your $30,000 budget once the actual segment split is confirmed — the deeper-lapse group should get a meaningfully larger per-person incentive even if it's the smaller list.

Channel plan
- Email and app push: the primary channel for both segments, since these are former loyalty members with existing contact permissions.
- Retail media retargeting: if your retail media platform supports audience upload, layer in retargeting ads to the deeply lapsed segment specifically, since they need more touchpoints than a single email is likely to deliver.
- Sequence: lead with owned channels (email/app) in week 1, layer paid retargeting for non-openers/non-clickers from week 2 onward.

Re-lapse monitoring plan
- Track purchase behavior for won-back members at 30, 60, and 90 days post-campaign — a member who redeems the win-back offer once and never returns again is not a durable win, and should be flagged for a different, lighter-touch nurture track rather than another deep discount next time.
- Build a simple internal flag for "won back, at risk of re-lapse" so this same 12,000-scale problem doesn't quietly rebuild in another six months.

KPIs
- Reactivation rate by lapse-depth segment (not blended across both).
- Cost per reactivated member, checked against the $30,000 budget by segment.
- 90-day repeat rate among reactivated members — the metric that actually separates a real win-back from a one-time redemption.
- Net base health: reactivated members minus any newly-lapsing members in the same window, since a win-back campaign that ignores newly lapsing members is treating a symptom, not the pattern.

Want me to model the exact incentive split once you confirm the recently-lapsed versus deeply-lapsed breakdown within the 12,000?