ARPU and LTV Relationship: Structural Correlations Between Revenue Metrics
ARPU and LTV Are Not Just Revenue Metrics – They’re Structures
ARPU (Average Revenue Per User) and LTV (Lifetime Value) are two of the most frequently cited metrics in mobile game marketing. However, many marketers mistakenly treat them as independent revenue metrics. In reality, ARPU is a core component that creates LTV, and LTV is the time-accumulated result of ARPU. In other words, the two metrics are in a cause–and–effect relationship and at the same time function as paired indicators that can predict one another.
To increase LTV, you ultimately need higher ARPU, and any strategy that raises ARPU fundamentally steepens the slope of the LTV curve. In this sense, ARPU and LTV are two sides of the same monetization structure.
ARPU represents the current quality of your users.
LTV represents the future value of your users.
When designing UA strategy, if LTV forecasting is difficult, analyzing short-term ARPU changes is the fastest and most practical alternative.
ARPU → LTV: Three Structural Principles That Explain How ARPU Drives LTV
LTV can essentially be broken down into the following formula:
LTV = ARPU × Retention × Time
This means ARPU is the starting point of LTV, and the higher your ARPU, the larger the base value on which LTV is built. The relationship between ARPU and LTV can be explained through three main structural perspectives.
The Higher the ARPU, the Steeper the Initial LTV Slope
For LTV, the slope of the curve during the first 7–14 days is extremely important.
If ARPU is high in this early window, the LTV curve will quickly converge toward a higher overall ceiling.
For example:
Games with high Day 1 ARPU are highly likely to show strong Day 30 LTV.
Conversely, even if retention is good, games with low early ARPU struggle to generate steep LTV growth.
In other words, early ARPU has strong predictive power for final LTV.
Day 3 and Day 7 ARPU are some of the most important signals for LTV forecasting.
In IAP-heavy genres, early ARPU almost directly translates into the shape and height of the LTV curve.
ARPU Combined with Retention Dramatically Changes the LTV Curve
ARPU represents average revenue per user, while retention represents how long users stay in the game.
When these two values are combined, you can get completely different LTV outcomes even with the same ARPU.
Example structures:
High ARPU × Low Retention → Limited LTV
Low ARPU × High Retention → Slowly rising LTV
High ARPU × High Retention → Explosive LTV growth
In this sense:
ARPU defines the unit value per user,
Retention defines how long the value accumulates.
Focusing only on retention improvements for LTV is a half-finished strategy.
In many cases, raising ARPU can lead to faster and more meaningful LTV improvements than retention optimization alone.
The “Type” of ARPU Changes the “Shape” of LTV
ARPU is generally composed of two main sources:
Ad-based ARPU (IAA)
Purchase-based ARPU (IAP)
Each structure generates a completely different LTV curve pattern.
For ad-based ARPU:
Session length and the number of ad impressions primarily determine ARPU.
LTV tends to grow quickly at first but has a relatively low ceiling.
For IAP-based ARPU:
The timing and frequency of purchase events heavily pull up LTV.
LTV rises more slowly at first but can reach a much higher overall level.
As a result, the way you choose to increase ARPU fundamentally changes the shape of your LTV curve.
LTV → ARPU: How LTV Feeds Back into ARPU Improvement Strategy
If ARPU is what builds LTV, then LTV in turn dictates how you should improve ARPU.
In other words, ARPU ↔ LTV form a mutually interactive structure.
In High-LTV Games, ARPU Improvement Strategies Naturally Move in These Directions
Increasing user session depth
Strengthening repeat visits
Advancing IAP design (tiered package structures, higher-value bundles)
Targeting high-intent users
Allocating budgets by country based on purchasing power
In markets where LTV is too low to justify CPI, there’s no point in aggressively applying ARPU-boosting strategies.
Ultimately, LTV becomes the baseline for deciding where to allocate resources to improve ARPU.
In low-LTV markets, reducing CPI is more important than optimizing ARPU.
In high-LTV markets, even a 1% increase in ARPU can have a disproportionately large impact on profitability.
Why the ARPU–LTV Relationship Has a Decisive Impact on UA Strategy
In a global UA strategy, the riskiest approach is to choose countries based mainly on CPI.
Even if CPI is low, if LTV is low, ROAS will never work.
Conversely, even if CPI is high, markets with strong ARPU–LTV structures can become the most profitable over the long term.
In conclusion, UA strategy should be built in the following order:
Understand genre-level ARPU structures
Predict LTV by country based on purchasing power
Choose media channels optimized for high-intent user acquisition
Apply session-based ARPU expansion strategies
This flow is exactly how the ARPU–LTV relationship should be applied to UA strategy.
The Intersection of Playtime-Based Reward UA and the ARPU–LTV Relationship
There are not many methods in the industry that can simultaneously lift both ARPU and LTV. Playtime-based reward structures are one of the rare UA models that directly and structurally impact both of these metrics.
Session Growth → Simultaneous Boost to Ad ARPU and IAP Triggers
For ad-based ARPU, more session time naturally leads to more impressions.
For IAP-based ARPU, faster progression pulls purchase events forward in time.
Retention Improvement → Higher LTV
In a playtime-based reward model, users must actually open and actively use the app to receive rewards.
This structural requirement acts as a powerful driver of both revisit rate and total usage time, naturally and very effectively strengthening retention, which in turn directly increases LTV.
User-Quality Filtering Effect
One of the most common problems in reward-based acquisition is users who collect the reward and immediately churn.
The core goal, therefore, is to block this behavior and retain only users who genuinely intend to play and contribute to the service over time—building a loyal, high-value user base.
Playtime-based reward structures accomplish this by requiring meaningful gameplay before a reward is granted, naturally filtering out low-intent users.
Strategic Summary: ARPU and LTV Relationship
ARPU is the foundation of LTV, and LTV is the cumulative result of ARPU.
Higher ARPU steepens the initial LTV slope, and when combined with strong retention, LTV can grow dramatically.
Ad-based ARPU and IAP-based ARPU create fundamentally different LTV shapes.
UA performance is determined more by the ARPU–LTV structure than by CPI alone.
Playtime-based reward platforms are uniquely positioned to strengthen both ARPU and LTV at the same time.
If you need support with ARPU-driven performance improvement, LTV modeling, or global UA strategy, contact [email protected].
Want more insights like this? Download our latest Global Game Advertising Trends Report.
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