Lifetime value (LTV)

What is Lifetime value (LTV)?

Lifetime value (LTV) is a metric that predicts the total net revenue a user generates over the entire duration of their engagement with an app or service. Also known as CLV or CLTV (Customer Lifetime Value), LTV helps mobile marketers evaluate whether the cost of acquiring and retaining a user is justified by the revenue that user produces. It is one of the most fundamental metrics for assessing the long-term health and profitability of a mobile app business.

How it works

LTV is calculated by combining revenue and cost data to estimate the net value a user delivers over their active lifetime. Two common formulas are used in mobile marketing contexts.

LTV Using Customer Acquisition Cost (CAC)

The most direct formula subtracts acquisition costs from projected lifetime revenue:

LTV = (ARPU × Average User Lifetime) - CAC

ARPU (Average Revenue Per User) is calculated by dividing total revenue by total users over a given period. Average User Lifetime represents how long a typical user remains active before churning. CAC (Customer Acquisition Cost) covers all expenses associated with acquiring a single user, including media spend, agency fees, and sales costs. The result is the net value a user contributes after accounting for what it cost to bring them in.

LTV Using Churn Rate

An alternative formula replaces average user lifetime with a churn-derived estimate:

LTV = ARPU × (1 / Churn Rate)

The expression 1 / Churn Rate calculates the implied average user lifetime based on the rate at which users stop engaging. If 10% of users churn per month, the implied average lifetime is 10 months. This approach is particularly useful when direct lifetime data is unavailable but churn is tracked consistently.

Predictive vs. Historical LTV

Historical LTV measures the actual revenue a user has generated to date. Predictive LTV (pLTV) uses statistical modeling and early behavioral signals to forecast future value before a user completes their lifecycle. Predictive approaches allow marketers to make acquisition and bidding decisions earlier, based on projected rather than realized value.

Why it matters

LTV is a foundational metric for sustainable mobile growth because it defines the ceiling on what a business can profitably spend to acquire a user. When LTV exceeds CAC by a meaningful margin, a business has room to invest in growth. When the ratio narrows, acquisition efficiency must improve or retention must strengthen.

For user acquisition teams, LTV informs bid strategies and channel prioritization. Channels that deliver users with high LTV justify higher CPIs, while channels producing low-LTV users may appear efficient on surface metrics but erode profitability over time.

For product and retention teams, LTV highlights which user segments, cohorts, or behaviors correlate with higher long-term value. This enables targeted engagement campaigns, personalized onboarding, and lifecycle communications designed to extend active user lifetime and increase in-app revenue.

For finance and leadership, LTV provides a basis for forecasting revenue from current user cohorts and modeling the return on incremental acquisition investment. It also informs decisions about monetization model adjustments, such as pricing changes, subscription tiers, or in-app purchase strategies.

MMPs like Airbridge connect attribution data with in-app event tracking, enabling marketers to calculate LTV by cohort, channel, campaign, and creative. This granularity allows teams to move beyond blended averages and optimize acquisition toward the specific sources that consistently deliver high-value users.

How to measure Lifetime Value (LTV)

Measuring LTV accurately requires integrating revenue data, engagement data, and acquisition cost data into a unified view.

1. Define your revenue signals. Identify all revenue events relevant to your app, including in-app purchases, subscriptions, ad impressions served, and microtransactions. Ensure these events are tracked consistently via your analytics or MMP SDK.

2. Calculate ARPU by cohort. Segment users by acquisition date, channel, or campaign. Calculate ARPU for each cohort over a defined window (for example, 7-day, 30-day, or 90-day ARPU) to understand how revenue accrues over time.

3. Estimate average user lifetime. Use retention curves or churn rate data to determine how long users in each cohort remain active. Retention reports from your MMP or analytics platform provide the data needed to build these curves.

4. Apply the LTV formula. Use LTV = (ARPU × Average User Lifetime) - CAC for a net value view, or LTV = ARPU × (1 / Churn Rate) when working from churn data. Apply consistently across cohorts for comparability.

5. Build toward predictive LTV. Once enough historical data exists, use early behavioral signals (such as session depth, first purchase timing, or feature adoption) to model predicted LTV for new users. Predictive LTV allows real-time bidding and campaign optimization before full lifecycle data is available.

6. Monitor LTV by acquisition source. Break LTV down by channel, campaign, ad network, and creative. This reveals which sources deliver users with the highest long-term value, enabling smarter budget allocation beyond last-touch cost metrics.

7. Revisit and recalibrate regularly. LTV is not a static number. Changes in monetization, product features, or user behavior shift the underlying inputs. Recalculate LTV on a regular cadence and update acquisition benchmarks accordingly.

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