Learn about subscriber retention, engagement, and lifecycle metrics with clear definitions and practical examples.
Winback Rate
Upgrade/Downgrade Rate
Trial-to-Paid Conversion Rate
Retention Rate Lift
Registered to Subscribe
Reactivation Rate (Resubscribers)
Payback Period
Gross Revenue Retention (GRR)
Activation Rate
Upsell
Net Revenue Retention (NRR)
Monthly Recurring Revenue (MRR)
Customer Retention Rate
Lifetime Value (LTV)
Customer Acquisition Cost (CAC)
Cohort Retention Rate
Churn Rate
Churned MRR (Churned Monthly Recurring Revenue)
Average Revenue Per User (ARPU)
Churn Score
Annual Recurring Revenue (ARR)
Lifetime Value (LTV)
What is lifetime value (LTV)?
Lifetime value (LTV) is the total revenue a business can expect from a subscriber over the entire period they remain active. It reflects the combined impact of acquisition, engagement, retention, upselling, and cross-selling on long-term revenue. Unlike short-term metrics, LTV provides a comprehensive view of the financial contribution of each subscriber.
Why LTV matters
- Strategic planning: LTV helps determine how much you can afford to spend on acquisition while staying profitable.
- Retention impact: Longer subscriber lifecycles directly increase LTV, making retention a key driver of growth.
- Revenue optimization: High LTV accounts often respond well to premium offers, bundles, or loyalty programs.
How to calculate LTV
The simplest formula:
LTV = Average Revenue Per User (ARPU) x Average Customer Lifespan
Advanced calculations can factor in gross margin, churn probability, and cohort-based retention data for greater accuracy.
Inclusions and exclusions
- Include: All recurring subscription revenue, upsells, add-ons, and renewals.
- Exclude: One-time fees or purchases not tied to ongoing subscription value.
LTV in subscription businesses
For subscription models, LTV is a guide for balancing acquisition and retention investments. A healthy LTV-to-CAC ratio means each subscriber is not only covering their acquisition cost but generating additional profit over time. Subsets enhances LTV tracking by tying engagement behaviors, like visit breadth, session time, and payment history, to projected subscriber value, allowing teams to predict, protect, and grow revenue more effectively.

The depth and breadth of the results analysis we can generate from Subsets has been invaluable. We are aiming to turn validated experiments into 'always on' and let Subsets select subscribers for targeting and trigger the campaigns.

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