Subscription retention cohorts
Understanding which customers stick around (and for how long) tells you more than just counting who’s still paying. Subscription Retention Cohorts show you exactly how well you retain subscribers from each customer group over time, helping you spot patterns in both customer loyalty and potential red flags that need attention.
What makes this report different
Most retention tracking just counts heads month over month. Subscription Retention Cohorts takes a deeper look by grouping customers based on when they first subscribed, then showing you exactly how each group’s retention evolves over time. Even better, it focuses solely on activated subscriptions - customers who’ve completed their trials and started paying - giving you a clear picture of true customer behavior without trial noise clouding the data.
Report components
Your retention story in numbers
The main visualization breaks down your subscriber retention by monthly cohorts:
- Each row represents a month’s worth of new subscribers, showing you their complete retention journey
- The “New subscribers” column tells you how many customers activated in that month
- Month-by-month percentages show exactly how many stayed subscribed
- A natural “stair step” pattern emerges as newer cohorts have less history to display
Two ways to view your data
Toggle between two powerful perspectives:
Relative View Shows percentages of original subscribers retained, making it easy to compare cohort performance regardless of size. This view helps you spot patterns in customer behavior and identify which groups of customers tend to stick around longer.
Absolute View Displays actual subscriber counts, helping you understand the real scale of retention changes. When cohort sizes vary significantly (like during seasonal peaks), this view gives you the complete picture of your subscriber base.
Understanding your numbers
How cohorts work
Each cohort begins when customers activate their subscriptions - meaning they’ve completed their trial and started paying. This focus on activated subscriptions gives you a clearer signal about true customer behavior, helping you separate serious customers from trial browsers.
A few things to keep in mind:
Month 0 percentages below 100% show immediate departures - customers who left in the same month they subscribed. This often signals potential mismatches between customer expectations and your app’s reality.
Frozen shops (those who haven’t paid their Shopify bills) temporarily drop out of their cohorts until they return to active status. This helps you maintain accurate retention tracking even when shops face temporary payment issues.
Reading the patterns
Your retention data tells multiple stories:
Early drop-offs often signal onboarding challenges or customer fit issues. If you’re seeing steep declines in the first few months, it might be time to review your customer acquisition strategy or early-stage customer success processes.
Stabilization points show you where retention levels out. This helps you identify your core customer base and set realistic expectations for long-term retention.
Seasonal variations become clear when you compare cohorts from different times of year. Understanding these patterns helps you plan resources and strategies around natural business cycles.
Making the most of this report
Smart analysis
Get more value from your cohort data:
Filter for Insights Use billing provider filters to compare retention between payment systems, or segment filters to identify your most stable customer types. This granular view helps you focus your retention efforts where they’ll have the biggest impact.
Track Changes Over Time The 12-month view shows you complete retention curves, helping you identify both quick wins and long-term opportunities for improvement.
Compare Cohort Sizes Watch how retention patterns change between smaller and larger cohorts. Sometimes what works for one group size doesn’t scale well to others.
Pro tips
Level up your retention analysis:
Watch for patterns in early-month retention - this often signals how well you’re qualifying customers during trials and onboarding.
Compare cohorts before and after major product changes using Journal to measure the impact on customer retention.
Look for your “stabilization point” - the month where retention typically levels off. This helps you set realistic expectations and plan interventions before customers reach critical drop-off points.
Remember: Understanding retention patterns helps you focus your efforts where they matter most - whether that’s improving early-stage customer success, adjusting your target market, or enhancing features that keep customers engaged long-term.
Frequently Asked Questions
Understanding Subscription Retention Cohorts
What's the difference between subscription retention cohorts and logo retention cohorts?
• Subscription retention cohorts: Track paying customers who maintain active subscriptions
• Logo retention cohorts: Track customers who keep your app installed (regardless of payment status)
A customer can retain your app (logo) but cancel their subscription, or maintain their subscription through different payment phases.
Why do cohorts start with activated subscriptions instead of trial starts?
Starting with activated subscriptions gives you cleaner retention data by focusing on customers who've already demonstrated buying intent. This eliminates trial browsers and shows true subscriber behavior patterns, making retention metrics more actionable for subscription business decisions.
How are frozen shops handled in subscription retention cohorts?
Frozen shops (due to unpaid Shopify bills) are temporarily removed from their cohorts until they reactivate. You can choose to:
• Include frozen events: Treats freezing like cancellation and unfreezing like reactivation
• Exclude frozen events: Shows retention of continuously paying customers only
Including frozen events provides complete subscription continuity visibility.
Calculations and Data
How is subscription retention calculated for each cohort?
For each subscription cohort (month), we track:
1. Total customers who first subscribed that month
2. How many still have active subscriptions in subsequent months
3. Retention % = (Still subscribed ÷ Original subscribers) × 100
The calculation factors in reactivations - customers who cancelled and later resubscribed are counted as retained for their original cohort.
Why might Month 0 show below 100% retention?
Month 0 percentages below 100% indicate customers who subscribed and cancelled within the same month. This can signal:
• Poor onboarding experience
• Misaligned customer expectations
• Payment or technical issues
• Wrong target market fit
High Month 0 churn often points to problems in the trial-to-paid conversion process.
Why do different cohorts show different retention patterns?
Cohort variations can result from:
• Seasonal customer behavior (holiday vs regular periods)
• Product changes or improvements between cohorts
• Different marketing channels or campaigns
• Economic conditions affecting specific periods
• Changes in pricing or onboarding processes
Comparing cohorts helps identify which factors drive better retention.
Strategy and Analysis
What's the difference between relative and absolute view?
• Relative view: Shows percentages of original cohort size - best for comparing cohort performance regardless of size
• Absolute view: Shows actual subscriber counts - best for understanding business impact and scale
Use relative for trend analysis and absolute for revenue planning.
How far back does subscription retention cohort data go?
Subscription retention cohort data goes back to when customers first started activating subscriptions in Mantle. The cohort table shows up to 12 or 24 months of retention tracking depending on your selected time period, with 'Months since first subscription' tracking up to that limit.
How can I use cohort retention data to improve my business?
Actionable insights from cohort analysis:
• Identify retention drops: Target specific months where customers typically churn
• Compare acquisition periods: Find which marketing efforts bring stickier customers
• Measure improvements: Track retention changes after product updates
• Set realistic goals: Use stabilization points to forecast long-term retention
• Segment analysis: Focus retention efforts on your most valuable customer types
Need help making sense of your cohort patterns or building stronger retention strategies? Our team is here to help you turn these insights into action.