Cohort analytics
We’ve upgraded our Cohort analytics dashboard to help you unlock deeper retention and behavior insights across your subscriber base. This gives you long-term visibility into how customers behave after their first order, when they churn, and which cohorts are worth doubling down on.
With these updates, you can now:
- Track cohort retention and churn across up to 36 months.
- Analyze customer behavior at both monthly and order-level precision.
- Compare multiple metrics side-by-side for any cohort.
- Identify which acquisition windows or campaigns led to better subscriber outcomes.
- Fine-tune onboarding, upsell, and win-back flows using granular cohort trends.
In this article
Key highlights
Features | What it enables |
|---|---|
10+ cohort metrics | Go beyond retention: analyze churn, AOV, upsells, conversion, and more. |
Extended cohort timeframe | Evaluate subscriber performance across a full 36-month view. |
Order-level cohort breakdown | Zoom into behavioral patterns by order milestone, not just monthly buckets. |
Key features
Track 10+ subscriber cohort metrics
Get a complete picture of how subscriber cohorts evolve over time - whether by month or by order count milestone.
- Go beyond basic retention: Analyze churn, AOV, revenue, order count, upsells, and more.
- Filter cohorts by acquisition month or order milestone.
- View retention curves by order number (e.g., after first, second, third order), not just by month.
- Spot if subscribers drop off after a specific order, and design win-back flows accordingly.
- Segment based on products, plans, and customer actions.
Where to find it: Cohort analytics → Metrics overview.
Analyze cohorts over extended timeframes
See how your customers behave well beyond the first few months.
- Track cohort performance over 36 months.
- Identify long-term value contributors vs early churners.
- Inform retention and LTV forecasting with historical data.
Where to find it: Cohort analytics → Time range filter.
Visualize behavior by order milestone
Not all drop-offs happen month by month - now see exactly when they occur.
- Break down cohort data by order number (1st, 2nd, 3rd, etc.).
- Spot churn moments tied to specific order experiences.
- Tailor post-order flows to reduce fall-off.
Where to find it: Cohort Analytics → Order-level View.
Key metrics
Subscriber Retention
Tracks the percentage of subscribers who remain active over time, segmented by acquisition month or order milestone. This metric helps merchants understand retention patterns across cohorts, identify churn triggers, optimize lifecycle strategies, and evaluate the performance of different plans and campaigns.
Benefits
- Plan & frequency insights: Understand which selling plans and delivery cadences retain subscribers most effectively, and identify underperforming combinations that may need adjustment or targeted interventions.
- Onboarding & early churn: Detect drop-offs in the first few months or orders to refine onboarding flows, trigger timely win-back campaigns, and reduce early-stage churn.
- Campaign evaluation: Evaluate how specific acquisition campaigns, promotions, or channels impact cohort retention and identify low-LTV subscribers for better targeting.
- Plan changes impact: Analyze the effect of changes in delivery frequency, subscription length, or discount structures on subscriber behavior to make informed updates.
- Order milestone analysis: Track churn patterns at specific order milestones to tailor post-order communications, upsells, or check-ins to reinforce engagement.
- Operational planning: Forecast subscriber retention trends to guide inventory planning, revenue projections, and customer support resources more accurately.
Where to find it: Analytics → Cohorts → Metric: Subscriber retention
Subscriber orders placed
Tracks the total number of orders placed by subscribers over time, indexed to the month they first started a subscription. You can view this either as raw order count or order placement rate (% of subscribers who placed an order in that month), helping you monitor purchasing momentum and engagement across the subscriber lifecycle.
Benefits
- Engagement tracking: Measure how actively subscribers are placing orders over time, distinguishing between passive subscribers and highly engaged ones.
- Plan & frequency insights: Compare ordering behavior across different selling plans and delivery intervals to see which cadences generate the most consistent activity.
- Drop-off detection: Identify months or order milestones where order activity slows or stagnates, enabling targeted retention efforts or upsell campaigns.
- Operational planning: Align fulfillment, inventory, and revenue forecasts based on actual subscriber order patterns.
- Prioritize upsells: Recognize cohorts with higher order frequency to target with upsell offers or premium products for maximum impact.
Where to find it: Analytics → Cohorts → Metric: Subscriber orders placed
Average cumulative orders per subscriber
Tracks the average number of total orders placed by subscribers in each cohort over time. This metric accumulates month by month and shows how frequently subscribers continue to purchase after their first subscription.
Benefits
- Purchase frequency insights: Understand how often subscribers are placing orders, and identify cohorts building consistent buying habits versus those that remain passive.
- Plan & frequency analysis: Compare how different selling plans and delivery intervals influence cumulative order growth, highlighting which combinations lead to long-term engagement.
- Forecast future orders: Use historical cohort trends to predict future order volume, aiding revenue modeling and operational planning.
- Lifetime value correlation: Combine with average order value (AOV) to estimate revenue potential from repeat purchases and identify high-value cohorts.
- Plateau detection: Spot when order growth flattens to trigger loyalty campaigns, upsells, or engagement interventions.
Where to find it: Analytics → Cohorts → Metric: Average cumulative orders per subscriber
Subscriber Revenue Realized
Tracks the revenue generated each month from subscriber cohorts, starting from acquisition. Available as both absolute revenue and percentage of total potential revenue, this metric helps evaluate monetization effectiveness and consistency over the lifecycle.
Benefits
- Revenue performance monitoring: See how much each cohort contributes financially over time and whether revenue is front-loaded or sustained.
- Plan & frequency comparison: Filter by selling plan and delivery interval to evaluate which combinations generate higher revenue or maintain long-term value.
- Drop-off identification: Detect points where revenue contribution declines, helping pinpoint if churn or lower order frequency is the cause.
- Campaign evaluation: Assess the monetization impact of acquisition campaigns, promotions, or product launches.
- Forecasting support: Historical revenue data enables better revenue projections, inventory planning, and growth strategy alignment.
Where to find it: Analytics → Cohorts → Metric: Subscriber revenue realized
Average subscriber LTV
Tracks the average cumulative revenue per subscriber in each cohort since acquisition, allowing assessment of long-term value and ROI of subscriber acquisition strategies.
Benefits
- Cohort value assessment: Identify which cohorts generate the highest lifetime value and spot patterns tied to pricing, product, or campaigns.
- Plan & frequency insights: Compare LTV across selling plans and delivery intervals to find the most profitable structures.
- ROI measurement: Evaluate acquisition campaign effectiveness and determine break-even points for marketing spend.
- Retention & AOV context: Pair with retention and order value metrics to understand what drives high LTV.
- Future planning: Forecast subscriber value for budgeting, growth, and strategic planning.
Where to find it: Analytics → Cohorts → Metric: Average Subscriber LTV
Subscription retention
Tracks the retention of active subscriptions month-over-month, grouped by their initial activation date. Available in both count and percentage views to help identify plan-specific drop-offs.
Benefits
- High-churn identification: Determine which plans or delivery frequencies see early drop-offs and which maintain longer engagement.
- Lifecycle visibility: Track how long subscriptions stay active and when retention begins to flatten.
- Granular comparison: Use count and percentage views to assess absolute volumes and normalized retention trends.
- Incentive effectiveness: Measure the impact of trials, discounts, or bundles on subscription longevity.
- Revenue & operations forecasting: Inform MRR projections, inventory planning, and operational decisions based on subscription longevity.
Where to find it: Analytics → Cohorts → Metric: Subscription retention
Subscription orders placed
Measures total orders placed per subscription over time, either by month or order milestone, available in both count and rate views.
Benefits
- Engagement tracking: Monitor how actively subscriptions generate orders over time.
- Drop-off detection: Identify specific months or orders where activity declines and tailor interventions.
- Plan & frequency analysis: Compare order behavior across plans and delivery intervals.
- Count vs rate view: Absolute order volume vs normalized engagement for a complete picture.
- Operational planning: Align fulfillment, inventory, and staffing with subscription order patterns.
Where to find it: Analytics → Cohorts → Metric: Subscription orders placed
Average cumulative orders per subscription
Tracks the average total orders per subscription over time, segmented by subscription start month.
Benefits
- Subscription engagement: See how actively subscriptions continue to order over time.
- Plan & frequency comparison: Determine which plan structures sustain long-term ordering.
- Future order forecasting: Estimate total orders per subscription for operations and revenue modeling.
- Drop-off detection: Identify when subscriptions stop ordering and proactively engage.
- LTV correlation: Combine with AOV to estimate revenue potential per subscription.
Where to find it: Analytics → Cohorts → Metric: Average cumulative orders per subscription
Subscription revenue realized
Tracks total revenue generated by subscriptions over time, by month or order milestone, in both absolute and percentage terms.
Benefits
- Revenue monitoring: Track how subscriptions contribute financially over their lifecycle.
- Plan & frequency insights: Compare which plan types or intervals generate sustained revenue.
- Drop-off analysis: Identify revenue declines due to churn or lower order frequency.
- Campaign evaluation: Measure monetization impact of promotions or product launches.
- Forecasting: Historical revenue trends inform future planning and operational decisions.
Where to find it: Analytics → Cohorts → Metric: Subscription revenue realized
Average subscription LTV
Tracks the average cumulative revenue per subscription cohort over time.
Benefits
- Subscription value assessment: Determine which subscriptions generate the most revenue over time.
- Plan & frequency comparison: Evaluate which combinations maximize long-term LTV.
- Monetization validation: Test the impact of upsells, bundles, or pricing changes.
- Retention & AOV context: See whether high LTV comes from higher frequency, larger orders, or both.
- Forecasting: Predict subscription revenue and support strategic growth planning.
Where to find it: Analytics → Cohorts → Metric: Average subscription LTV
Head to Loop Subscription app → Analytics → Cohorts to get started today!
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Loop Subscriptions Team 🙂
Updated on: 18/08/2025
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