/growth

Win-Back Campaign Reference

Purpose: Recover cancelled or long-dormant users with a recency-weighted offer sequence, multi-touch cadence, and a reactivation metric tied to Pulse. Distinguishes voluntary from involuntary cancels.

Scope Boundary

• growth winback: Cancelled / long-dormant user recovery (this document).
• growth reengagement (elsewhere): Still-active dormant user re-activation. Default. Winback is a deeper recovery path.
• growth churn (elsewhere): Churn prevention before cancellation.
• Growth (elsewhere): New-user acquisition campaigns. Winback is recovery, not acquisition.
• Prose (elsewhere): Campaign copy (notification). Winback designs the plan; Prose writes the words.
• gateway (elsewhere): Delivery infrastructure.
• Pulse (elsewhere): Reactivation metric and funnel reporting.

Voluntary vs Involuntary Cancels

Involuntary (payment / card failure)  →  Route to dunning first
                                         Clean card issue, attempt re-charge
                                         Separate from winback flow

Voluntary (active choice to leave)    →  Winback candidate
                                         Segment by cancel reason
                                         Apply recency-weighted offer

Dunning handles involuntary. Winback handles voluntary only.

Recency Cohorts

Rule: offer strength scales with recency inverse — stronger for colder. Acquisition-level economics apply to cold winback.

Segmentation Dimensions

For each recency cohort, further segment by:

1. Cancel reason (if captured): price / features / unused / support / switched competitor.
2. Plan tier at cancel: free / paid-base / paid-premium / enterprise.
3. Lifetime value at cancel: LTV tier (top / mid / low).
4. Engagement peak: power user vs. casual vs. never-activated.
5. Primary use case: what feature they used most.
6. Channel preference: email-only / push-allowed / SMS opted-in.

Never send the same message to all cohorts. A power user who left for price needs different copy than a never-activated user who left for lack of understanding.

Offer Design

Avoid: bribes with no context, identical discount for everyone, discount that undercuts current paying users' price.

Multi-Touch Cadence Example (Warm cohort, price objection)

Day 0   (cancel)   : offboarding email confirming cancel, low-key "come back" link
Day 3   : value reminder email — top 3 features they used
Day 7   : offer — "30% off for 3 months, start where you left off"
Day 14  : feature-launch push (if relevant release since cancel)
Day 21  : final soft touch email — success story from similar user
Day 30  : stop cadence; move to Cool cohort if no return

Quiet period: 60 days before any further contact

Frequency cap: no more than 1 marketing touch / 3 days in winback.

Deliverability and Suppression

• Global suppression: honored-opt-out list never gets winback.
• Complaint list: spam-reporters never get winback.
• Hard-bounce list: invalid addresses suppressed.
• Winback fatigue suppression: user who's been through 2 full winback cycles without returning → 180-day cooldown.
• Regulatory: CAN-SPAM (unsubscribe ≤ 10 business days), GDPR (legitimate interest balancing test), CASL Canada (consent required), Japan APPI.

Route compliance checks to Cloak/Canon[regulatory] for regulated regions.

Reactivation Metric

Reactivation Rate = returned_users / winback_recipients (per cohort, per campaign)

Benchmarks (typical SaaS):

• Fresh cohort: 15-30%
• Warm: 8-15%
• Cool: 3-8%
• Cold: 1-3%
• Frozen: <1%

Downstream: track LTV of reactivated users vs original LTV. Sticky reactivation means reactivated LTV ≥ 60% of original. Lower than that suggests price-incentive-only returns who churn again.

Offer Cannibalization Check

Before shipping a winback offer, verify:

• Current paying users cannot easily discover and exploit the winback discount.
• Serial cancel-rejoin gaming is rate-limited (one winback offer per 365 days).
• Offer does not undercut a more expensive plan and drive current users to downgrade.

Output Template

## Win-Back Campaign: [Name]

### Target Segment
- **Recency cohort**: [Fresh / Warm / Cool / Cold / Frozen]
- **Size**: [N users]
- **Primary cancel reason**: [price / features / etc.]
- **Secondary segmentation**: [plan tier, LTV tier, channel preference]

### Offer
- **Type**: [discount / extended trial / feature access / migration help / pause]
- **Strength**: [% or value]
- **Duration**: [days / months]
- **Justification**: matched to cancel reason and cohort economics

### Cadence
| Day | Channel | Content goal | CTA |
|-----|---------|--------------|-----|
| 0 | email | offboarding confirm | "we'll be here" |
| 3 | email | value reminder | "see what's new" |
| 7 | email | offer | "[offer CTA]" |
| ... | ... | ... | ... |

### Compliance
- [ ] Global suppression respected
- [ ] Hard-bounce / complaint lists applied
- [ ] Unsubscribe ≤ 10 business days
- [ ] Regional regulation verified (CAN-SPAM / GDPR / CASL / APPI)

### Metrics
- **Primary**: Reactivation rate (benchmark: [cohort-specific])
- **Secondary**: Reactivated-user 90-day retention, reactivated LTV vs original
- **Guardrail**: current-user cannibalization < 1%, unsubscribe rate < 2%

### Handoffs
- Prose `notification`: copy per touch
- gateway: email / push / SMS delivery
- Pulse: reactivation event + funnel
- Experiment: A/B test offer strength and copy
- Cloak / Canon[regulatory]: regulatory review
- Growth: ensure no overlap with active promos

Anti-Patterns

Deliverable Contract

When winback completes, emit:

• Segment definition (recency cohort × reason × tier × LTV × channel).
• Offer design matched to cohort and reason.
• Cadence table (day × channel × content × CTA).
• Compliance checklist (suppression, regulation, unsubscribe).
• Metrics plan (reactivation rate, 90-day retention, LTV, guardrails).
• Cannibalization check.
• Handoffs: Prose, gateway, Pulse, Experiment, Cloak/Canon[regulatory], Growth.

References

• Reforge — Winback Playbook
• Andrew Chen — "The Cold-Start Problem" (cohort recovery)
• Sean Ellis — Hacking Growth (winback loops)
• CAN-SPAM / GDPR / CASL / APPI regulatory references
• Customer.io, Braze, Iterable — winback automation patterns
• SaaS Metrics Benchmarks (OpenView, KeyBanc) — reactivation rates by recency