Subscription Lifecycle

You optimize every stage of the subscription journey: trial → paid → renewal → cancellation recovery → win-back.

The Subscription Lifecycle

Install → Trial start → [Trial period] → Conversion → Renewal → ... → Cancel → Win-back
            ↓                               ↓              ↓           ↓
         No convert                    Voluntary       Involuntary   Lapsed
         (nurture)                     (exit survey)   (dunning)     (campaign)

Key Metrics at Each Stage

Stage 1 — Trial Optimization

Trial Length

Test: Monthly apps with a 7-day trial vs. 14-day trial — conversion rate may drop slightly but LTV often increases.

Trial Nurture Sequence

Send in-app (or push) messages during the trial to drive activation:

Day 0: Welcome — "Your trial has started. Here's how to get the most from it."
Day 1: Core feature highlight — "Try [key feature] today"
Day 3: Progress / social proof — "Users who do X get 3× better results"
Day 5 (7-day trial): Urgency — "2 days left in your trial"
Day 6: Value recap — "Here's what you've done / could do with premium"
Day 7: Last day — "Your trial ends today"

Rule: Messages should show value, not just create pressure.

Trial End — Conversion Moment

At trial end, show a paywall that:

• Recaps what the user achieved during the trial
• Shows the most-used premium features
• Offers 3 plan options (monthly / annual / lifetime if applicable)
• Highlights savings on annual ("Save 40%")

See monetization-strategy for paywall design details.

Stage 2 — Reducing Voluntary Churn

Why Users Cancel (and How to Fix It)

The Cancellation Flow

When a user initiates cancellation (iOS — ManagedSubscriptionGroup):

1. Offer a pause before full cancel: "Pause for 1–3 months instead of cancelling"
2. Show value recap: "You've used [feature] X times this month"
3. Offer a discount: Only as last resort — 20–30% off for 3 months
4. Exit survey: Always ask "Why are you cancelling?" (1 tap, not an essay)

Cancellation exit survey options:

• Too expensive
• Not using it enough
• Missing a feature I need
• Switching to a competitor
• Technical issues
• Just taking a break

Engagement Signals to Watch

Users at high churn risk:

• Sessions < 1 per week (down from higher baseline)
• Core feature not used in 14+ days
• Push notifications disabled
• Last session > 7 days ago

Trigger a re-engagement push or in-app message before they cancel.

Stage 3 — Involuntary Churn (Failed Payments)

Involuntary churn accounts for 20–40% of all subscription cancellations.

Dunning Strategy

Grace period:

• iOS: 6 days (configurable up to 16 in App Store Connect)
• Android: 3 days (configurable)

Maximize grace period length — every extra day recovers more subscribers.

RevenueCat Integration

RevenueCat handles dunning automatically. Key settings:

• Enable Billing Retry (iOS) / Account Hold (Android)
• Configure grace period to maximum allowed
• Use RevenueCat webhooks to trigger in-app messaging at each failure event

See revenuecat.md integration guide.

Stage 4 — Win-Back Campaigns

Target lapsed subscribers (cancelled or expired in last 30–90 days).

Win-Back Offer Ladder

Start with the softest offer; escalate only if no response:

Week 1 after lapse:  "We miss you" — highlight new features added since they left
Week 3:              "Come back for 30% off your first month back"
Week 6:              "3 months at 50% off — best offer we'll make"
Week 12+:            Archive — low conversion probability

Win-Back Channels

StoreKit 2 Win-Back Offers (iOS 18+)

Apple natively supports win-back subscription offers for lapsed subscribers:

• Set up in App Store Connect → Subscriptions → Win-Back Offers
• Presented automatically in the App Store to eligible lapsed users
• No additional code needed beyond StoreKit 2 integration

Output Format

Subscription Health Report

Lifecycle Metrics ([period]):

Trial start rate:    [X]%  (benchmark: >20%)
Trial conversion:    [X]%  (benchmark: 25-40%)
M1 renewal:          [X]%  (benchmark: >70%)
Monthly churn:       [X]%  (benchmark: <5%)
Dunning recovery:    [X]%  (benchmark: >30%)
Win-back rate:       [X]%  (benchmark: 5-15%)

LTV (estimated):    $[N]
MRR:                $[N]

Top issues:
1. [Stage] — [metric] is [X]% vs benchmark [Y]% — [recommended fix]
2. [Stage] — [metric] is [X]% vs benchmark [Y]% — [recommended fix]

Priority action:
[Single highest-leverage change to implement this week]

Related Skills

• monetization-strategy — Paywall design, pricing tiers, trial setup
• retention-optimization — Engagement strategy to reduce voluntary churn
• app-analytics — Track the metrics above with Firebase + RevenueCat
• onboarding-optimization — Fix early-stage drop-off that prevents trial starts
• rating-prompt-strategy — Satisfied subscribers are your best raters