Win-back flows: 12 patterns that earn their place

The most common way a win-back program goes wrong is the trigger itself. Teams reach for hasn't opened an email in 90 days because it's easy to build. It's also a garbage signal. Apple Mail Privacy Protection inflates opens for over half the market, and 90 days is a round number someone pulled out of a deck in 2014. Use a real behavioural signal or don't bother.

For a subscription product, lapse is no login in N days. For a marketplace, it's no purchase plus no session start. For a content product, it's no consumption event plus no app open. Pick what reflects actual product value. And tune N to the natural cadence of the thing — 14 days for food delivery, 9 months for annual travel booking. A round number is not a cadence.

Lapsed users are not one audience. There are at least three, and tiering them is how you avoid sending a cheery please come back to someone who cancelled last week over a billing dispute.

Tier 1 — recently lapsed, historically high engagement. Most likely to return. Light touch, high-value reminder, short sequence of two to three messages across one to two weeks.
Tier 2 — medium-term lapsed, moderate historical engagement. Needs a real reason: a product update, a new feature, something that's changed. Slower sequence — three to five messages across four to six weeks.
Tier 3 — long-lapsed or cancelled. Usually the largest audience and the lowest reactivation rate. Most of these users should end up suppressed. The win-back attempt is a final qualification before sunset, not a real conversion play.

Sequence length scales with tier. Anything more than five messages per tier is counterproductive — you're burning deliverability on people who aren't coming back and calling it optimism.

The Orbit Win-Back Playbook skill generates the tier definitions, the sequence per tier, and the sunset policy — tuned to your lapse definition and your product's natural cadence.

1. The "here's what you missed" digest. Three to five things: new features, popular content, community milestones. Works for content-heavy and community products. Skip it for transactional products — you'll sound out of touch with a shopping cart.

2. The "what changed since you left" update. Single biggest change since the user lapsed. Lands best when the change addresses a common complaint. Lead with the change. The ask to return is a footer, not a headline.

3. The personalised usage memory. Their last listen, their favourite item back in stock, how long since their last workout. Requires a real data model — the generic version of this reads as mildly surveillance-adjacent, not personal. More on where this tips over in the personalisation guide.

4. The low-friction re-entry. One-click resume, one-click restart, skip the password reset. The finding that surprises most teams: removing password friction alone can lift Tier 1 reactivation two to three times over. Users don't always leave because they lost interest. Sometimes they left because they couldn't be bothered to log in.

5. The direct discount. The default move for most teams. Works for Tier 2 and 3, and the level matters more than the offer. 10% won't move anyone who stopped caring. 30% signals desperation and teaches your base to wait out campaigns. 15–25%, tied to a specific product or category, is the zone that works without training bad behaviour.

6. The "what went wrong" survey. A single open-ended question, nothing else. Reactivation conversion is low. The value is elsewhere — as product research, it's some of the most honest feedback you'll ever get. Slot it late in the Tier 3 sequence. The users who respond are doing you a favour.

7. The behaviour-based trigger. Not a campaign — an automation. If a lapsed user does anything at all (opens, clicks, visits a page), fire a targeted flow the same day. Intent-in-the-moment is a much stronger signal than the lapse itself, and this is the pattern most teams forget to build.

8. The peer-behaviour nudge. Users like you are now doing X. Social proof for reactivation. Needs a real user model behind it. Popular with other users as generic filler reads as weak and vaguely manipulative.

9. The "we'll miss you" note. Direct from the team, signed by a real person, brief, no discount. Usually the last message before sunset. Works because it breaks the pattern of every other marketing email the user has received, and because the subtext — this might be the last one — is true.

10. The preference-change invitation. Too many emails? Tell us what you'd prefer. Preserves the subscriber relationship without forcing reactivation. A subscriber who opts down in frequency is worth considerably more to your sender reputation than one who marks you as spam because you kept sending anyway.

11. The seasonal tie-in. Align the moment with a natural re-evaluation point: new year, quarter end, seasonal product relevance, annual usage anniversary. Higher inherent relevance. Less forced than a cold where have you been.

12. The channel-switch. Move lapsed email subscribers to a lighter-weight channel — push, SMS, in-app only — instead of forcing more email they've stopped opening. Lower complaint rate, preserved relationship, often re-engages users who were tired of the email cadence specifically. The constraint, always, is consent: you can't port an email subscriber to SMS without a separate SMS opt-in, and that's the end of the conversation.

Every win-back program needs an explicit sunset policy. The rule that says: this user is done, stop sending them marketing. Without one, the lapsed list grows indefinitely and your sender reputation drags down with it, because ISPs weight engagement-per-send and your engagement-per-send is bleeding.

A policy that works. After the win-back sequence completes, if the user takes no engagement action — open, click, login, purchase, session start — remove them from marketing. Transactional still flows. A final goodbye email gives them one link back, and re-opt-in is always available via a product surface. That's it. Not complicated. Just written down.

The number to watch is list churn. Healthy programs sunset 1–3% of the list each month. Programs that sunset nothing end up with lists that are 40% dead weight inside 18 months. The deliverability guide covers how list hygiene compounds into sender reputation, and the Deliverability Management skill runs the full diagnostic when you want to check if yours is already bleeding.

The primary metric is reactivation rate: share of the sequence audience that took a defined reactivation action inside the measurement window. Define the action specifically. Completed a purchase is not the same as opened any email. Measure both if you want, but the purchase number is the one that decides whether the program earns its seat.

Watch three secondaries. Complaint rate — should stay under 0.1% even though this audience is ambivalent and will naturally push higher than a warm cohort. Unsubscribe rate — will run higher than your baseline, and that's healthy. It's the sunset working in the open. And downstream LTV of reactivated users — do they stick for 30+ days, or do they churn again inside a fortnight? Reactivation that doesn't retain is a vanity metric with extra steps.

The trap worth naming: measuring the open or click rate of the sequence itself and declaring the program broken when the numbers look rough. Opens on this audience will sit at 30–40% of your normal baseline. They're supposed to. Use reactivation as the headline and judge the program on that, not on sequence engagement stripped of context.