36 Cycle Retention Report
Track long-term subscription retention across 36 renewal cycles to visualize your complete retention curve and understand cumulative subscriber lifetime.
The 36 Cycle Retention Report provides a long-horizon view of subscription retention, tracking cohorts through up to 36 renewal cycles. While the 6 Cycle Retention Report offers granular per-cycle breakdowns, this report focuses on the cumulative outcome — how many subscriptions from each cohort successfully renewed at each cycle point. This makes it ideal for understanding long-term retention trends, projecting lifetime value, and benchmarking retention improvements over time.
What This Report Includes
This report tracks all recurring subscription offers from their initial sale through 36 successive renewal cycles, based on the date the subscription was originally ordered.
Subscriptions Included:
- Recurring subscription offers only
- Tracks each subscription through 36 successive renewal cycles (R1–R36)
- Only successful (non-declined) sale and capture transactions with a completion or skip date count toward retention
- Test orders are excluded
- Date range is based on Subscribed Date (when the subscription was originally created)
Why This Matters: Short-term retention reports only tell part of the story. Many subscription businesses see the most critical churn in the first few cycles, but long-term retention data reveals whether your subscribers become loyal, committed customers or continue to attrite over time. The shape of your 36-cycle curve is one of the strongest predictors of business sustainability.
Report Metrics
Subscriptions
The total count of recurring subscription offers in the cohort. This serves as the denominator for all Overall Success Rate calculations across every cycle.
Each renewal cycle includes the following two metrics:
Success
The count of subscriptions that were successfully charged at this renewal cycle. This represents the subscribers who made it to and through this specific billing point.
Overall Success Rate
The percentage of the original cohort that successfully renewed at this cycle, calculated as Success divided by Subscriptions. This gives you a true cumulative view — at R12, for example, this tells you what percentage of your original subscribers were still successfully renewing one year in (for monthly billing).
Available Dimensions
Use these dimensions to slice and filter your 36-cycle retention data for deeper analysis.
| Dimension | Description |
|---|---|
| Subscribed Date | The date the subscription was created |
| Subscribed Hour | Hour of day when the subscription was created (0–23) |
| Subscribed Day Of Week | Day of the week the subscription was created |
| Subscribed Week | ISO week number of subscription creation |
| Subscribed Month | Month and year of subscription creation |
| Subscribed Year | Year the subscription was created |
| Customer ID | The customer's ID in the system |
| Customer Email | The customer's email address |
| Customer Information | Combined customer details (name, email, phone) for searching |
| Connection | The connection (CRM instance) associated with the customer |
| Order ID | The unique order identifier |
| Order Offer ID | The unique identifier for a specific offer within an order |
| Offer Status | The current status of the offer |
| Connection Offer Status | The offer status as defined by the connection |
| Subscription Billing Status | Current billing status of the subscription |
| Days To Cancel | Number of days between subscription creation and cancellation |
| Cancel Reason | The reason provided for cancellation |
| Is Blacklist | Whether the customer is on the blacklist |
| Is Gift | Whether the order was marked as a gift |
| Offer | The offer associated with the subscription |
| Offer Name | Display name of the offer |
| Offer Code | The unique offer code |
| Primary Offer Category | Primary category assigned to the offer |
| Secondary Offer Category | Secondary category assigned to the offer |
| Campaign | The campaign associated with the order |
| Primary Campaign Category | Primary category assigned to the campaign |
| Secondary Campaign Category | Secondary category assigned to the campaign |
| Charge Frequency | How often the subscription is billed |
| Is Prepaid Offer | Whether the offer is a prepaid subscription |
| Discount Code | Discount or coupon code applied to the order |
| Discount Name | Display name of the applied discount |
| Merchant | The merchant account used for processing |
| Merchant Group | The merchant group the merchant belongs to |
| Card Bin Number | First six digits of the card number identifying the issuing bank |
| Card Type | Card brand (e.g., Visa, Mastercard, Amex) |
| Card Issuer | The bank or institution that issued the card |
| Card Category | Category of the card (e.g., Consumer, Business) |
| Card Country | Country where the card was issued |
| Is Prepaid Card | Whether the card is a prepaid card |
| Ship Country | Shipping destination country |
| Ship State | Shipping destination state or province |
Key Business Insights
1. Retention Curve Visualization
Plot the Overall Success Rate from R1 through R36 to see your complete retention curve:
R1: 65% R2: 55% R3: 48% R6: 35% R12: 22% R24: 14% R36: 10%- Steep early curve → Most attrition in first cycles; focus retention efforts early
- Long flat tail → Subscribers who survive early cycles become loyal; invest in getting past the "danger zone"
- Linear decline → Steady churn across lifecycle; systematic retention issues
2. Cohort Comparison
Compare retention curves across different acquisition periods:
- Are recent cohorts retaining better than older ones? Your product and retention programs are improving
- Are recent cohorts retaining worse? Something has changed — investigate offer changes, traffic quality, or operational shifts
3. Lifetime Value Projection
Use the retention curve to project revenue:
Expected Lifetime Cycles = Sum of all Overall Success Rates (as decimals)For example, if your R1–R12 rates sum to 4.5, each subscriber generates roughly 4.5 cycles of revenue on average over their first year.
4. Break-Even Analysis
Knowing your average revenue per cycle and customer acquisition cost, identify where on the retention curve subscribers become profitable:
- If CAC requires 3 successful cycles to recover, your R3 Overall Success Rate tells you what percentage of acquired customers will break even
Optimization Strategies
Flatten the Early Curve
- Improve new subscriber onboarding
- Set clear renewal expectations at purchase
- Send pre-renewal engagement communications
- Offer first-renewal incentives for high-risk segments
Extend the Long Tail
- Build loyalty programs that reward tenure
- Introduce exclusive benefits for long-term subscribers
- Proactively address satisfaction issues before they cause cancellation
- Optimize dunning to prevent involuntary churn at every cycle
Benchmark Improvement
- Track this report monthly to measure the impact of retention initiatives
- Compare curves before and after specific program launches
- Segment by offer, traffic source, or customer demographics to find your highest-value acquisition channels
Pro Tips
- Monthly Billing Mapping: For monthly subscriptions, R12 = 1 year, R24 = 2 years, R36 = 3 years — making it easy to frame retention in business terms
- Filter by Offer: Different subscription products may have dramatically different retention curves. Use filters to analyze each offer separately
- Pair with CLV Report: Cross-reference retention cycle data with the Customer LTV Report to understand revenue contribution at each lifecycle stage
- Data Maturity: Older cohorts will have data across more cycles. Recent cohorts will show high rates at early cycles with data tapering off at later cycles — this is expected, not a problem
Frequently Asked Questions
Q: Why do later cycles show lower numbers or no data for recent date ranges?
A: This is expected. If you select subscriptions ordered 6 months ago with monthly billing, data will only exist through approximately R6. Later cycles haven't occurred yet. For a complete 36-cycle view, select cohorts ordered at least 36 billing periods ago.
Q: How does this differ from the 6 Cycle Retention Report?
A: The 6 Cycle Retention Report provides detailed per-cycle breakdowns (pending, cancellation, dunning, failed, skip, success) for cycles R1–R6, making it ideal for diagnosing why subscribers churn at each early stage. This report extends the view to 36 cycles but focuses only on success counts and overall success rates, giving you the long-term retention curve without the per-cycle operational detail. Use the 6 Cycle report for early-lifecycle diagnostics; use this report for long-term retention trends and lifetime value projections.
Q: What does a "good" retention curve look like?
A: This varies significantly by industry and product type. Generally, a curve that flattens (rate of decline slows) at later cycles indicates you're reaching a stable, loyal subscriber base. If your curve continues to decline linearly or steepens at later cycles, long-term retention may be a concern.
Updated 6 days ago