How to Model 30/60/90-Day Payback Periods for Apps

Most app marketers optimize for lifetime value, a metric that requires 18-24 months of data and makes assumptions about retention curves that rarely hold.

The result: acquisition decisions based on projections instead of performance.

Payback period shifts the focus to a more practical question: "How quickly do we recover what we spent to acquire this user?"

For mobile apps, modeling payback at 30, 60, and 90-day intervals provides actionable insight into unit economics without waiting years for data to mature.

Here's how to build and optimize payback models that inform real decisions.

Why Payback Period Matters More Than LTV

LTV has a fundamental problem: it's a backward-looking prediction that relies on assumptions about future behavior.

You're estimating what users will spend over 12, 24, or 36 months based on early cohort data. Any shift in retention, monetization, or competitive dynamics invalidates your model.

Payback period is different. It measures actual cash recovery in defined time windows.

Key advantages:

• Faster feedback: You know if a channel works in 30-90 days, not 12+ months
• Cash flow clarity: Shows when you recover capital to reinvest in growth
• Less assumption risk: Based on observed revenue, not projected retention curves
• Actionable insights: Informs bidding strategies and budget allocation in near-real-time

For mobile apps where monetization often front-loads (subscriptions, IAP, early conversions), payback periods provide the clearest view of unit economics.

The Core Payback Formula

The standard payback calculation is:

Payback Period (months) = CAC ÷ (Monthly ARPU × Gross Margin)

Where:

• CAC = Customer Acquisition Cost (total spend ÷ paying customers)
• ARPU = Average Revenue Per User (monthly)
• Gross Margin = Revenue after COGS, platform fees, payment processing

Example:

• CAC: $110
• Monthly ARPU: $26.78
• Gross margin: 92%
• Payback period: $110 ÷ ($26.78 × 0.92) = 4.4 months

This tells you that you recover your acquisition investment in 4.4 months on average.

Modeling 30/60/90-Day Payback

The traditional formula works for steady subscription revenue, but mobile apps often have variable monetization patterns.

A more granular approach tracks cumulative revenue recovery at specific intervals.

Step 1: Calculate True CAC

Most teams calculate CPI (cost per install), but payback requires CAC (cost per paying customer).

CAC calculation:

CAC = Total UA Spend ÷ Paying Customers Acquired

Example:

• Monthly UA spend: $50,000
• Installs acquired: 20,000
• Install-to-paid conversion: 5%
• Paying customers: 1,000
• CAC: $50 per paying customer

This is the number you need to recover.

Step 2: Track Cohort Revenue by Day

Build a cohort table that tracks cumulative revenue per paying customer over time.

Example cohort revenue table:

Days Since Install	Cumulative ARPU	% of CAC Recovered
Day 1	$2.50	5%
Day 7	$8.75	17.5%
Day 14	$15.00	30%
Day 30	$25.00	50%
Day 60	$42.50	85%
Day 90	$55.00	110%

Key milestones:

• Day 30: 50% payback (halfway to recovery)
• Day 60: 85% payback (near break-even)
• Day 90: 110% payback (profitable, beginning to generate ROI)

Step 3: Calculate Payback Percentage

For each time interval, calculate what percentage of CAC you've recovered:

Payback % = (Cumulative Revenue at Day X ÷ CAC) × 100

Using the example above:

• 30-day payback: ($25.00 ÷ $50.00) × 100 = 50%
• 60-day payback: ($42.50 ÷ $50.00) × 100 = 85%
• 90-day payback: ($55.00 ÷ $50.00) × 100 = 110%

This shows you cross break-even between Day 60 and Day 90.

Step 4: Identify Break-Even Point

Your break-even point is when cumulative revenue equals CAC.

In the example above, if revenue continues to accumulate linearly between Day 60 and Day 90, you'd estimate:

• Revenue needed to break even: $50.00
• Revenue at Day 60: $42.50
• Revenue at Day 90: $55.00
• Gap to close: $7.50 in 30 days
• Daily revenue rate: $0.42/day
• Days to close gap: $7.50 ÷ $0.42 = 18 days

Estimated payback: Day 78 (or 2.6 months)

Benchmarks for Mobile Apps

Payback expectations vary by app category and monetization model.

General benchmarks:

• Elite performers: 5-7 month payback
• Strong performance: 8-10 months
• Acceptable: Under 12 months
• Concerning: 12-18 months
• Unsustainable: 18+ months

By app category:

Category	Target Payback	Notes
Gaming (casual)	30-90 days	Front-loaded IAP monetization
Gaming (mid-core)	60-180 days	Longer engagement, recurring spend
Subscription (entertainment)	4-8 months	Recurring revenue, moderate churn
Subscription (productivity)	6-12 months	Higher LTV, annual plans common
E-commerce	2-6 months	Transaction-based, repeat purchases
Finance/Banking	8-15 months	High LTV justifies longer payback

Gaming apps can afford shorter payback windows because they monetize quickly through IAP. Subscription apps with annual billing may achieve payback in a single transaction.

Using Payback Milestones for Bidding

The most practical application of payback modeling is informing acquisition bidding strategies.

Milestone-based bidding framework:

Set ROAS (Return on Ad Spend) targets at each payback interval and adjust bids based on performance.

Example ROAS targets:

• Day 15: 20% ROAS (early signal of monetization)
• Day 30: 40-50% ROAS (halfway to payback)
• Day 60: 80-90% ROAS (near break-even)
• Day 90: 110-120% ROAS (profitable)

If a channel or campaign consistently underperforms at Day 30 (e.g., only 25% ROAS instead of target 40%), you can:

• Reduce bids to lower CAC
• Pause and reallocate budget to better performers
• Optimize creative, targeting, or landing experience

This approach lets you make data-driven decisions within weeks instead of waiting months for LTV curves to mature.

Optimizing Payback Performance

Once you've modeled your baseline payback, focus on these levers to accelerate recovery:

1. Improve Monetization Timing

Front-load value delivery to encourage earlier conversions.

Tactics:

• Offer trial-to-paid incentives in first 7 days
• Introduce limited-time upgrade offers post-onboarding
• Gate high-value features to encourage earlier subscription

A shift from 30-day to 14-day average time-to-conversion can cut payback period in half.

2. Reduce CAC Through Channel Optimization

Lower acquisition costs directly improve payback timelines.

Tactics:

• Shift budget toward lower-CPI channels with comparable LTV
• Optimize creative to improve CTR and CVR (lower effective CPI)
• Improve App Store conversion to reduce cost per install

A 20% reduction in CAC (e.g., $50 to $40) improves payback from 78 days to 62 days in our earlier example.

3. Increase Early ARPU

Higher revenue per user in the first 30-60 days accelerates payback.

Tactics:

• Introduce one-time onboarding offers or bundles
• Test higher-priced annual plans vs. monthly subscriptions
• Add complementary IAP or upsell opportunities

If you increase Day 30 ARPU from $25 to $30 (20% improvement), your payback % improves from 50% to 60% at the 30-day mark.

4. Improve Early Retention

Users who churn before monetizing extend payback indefinitely.

Tactics:

• Optimize onboarding to reach "aha moment" faster
• Implement Day 1, Day 3, Day 7 re-engagement campaigns
• Reduce friction in conversion flows

Improving Day 30 retention from 30% to 40% increases the pool of users who reach monetization, improving overall cohort ARPU.

Tracking Payback Across Channels

Not all acquisition channels deliver the same payback performance.

Build channel-specific payback models to inform budget allocation.

Example multi-channel payback:

Channel	CAC	Day 30 ARPU	Day 30 Payback %	Day 90 Payback %
Apple Search Ads	$35	$28	80%	140%
Facebook Ads	$52	$22	42%	95%
TikTok Ads	$48	$18	37.5%	85%
Google App Campaigns	$40	$25	62.5%	125%

Insights from this data:

• Apple Search Ads delivers fastest payback due to high intent and lower CAC
• Facebook has higher CAC but eventual payback is acceptable by Day 90
• TikTok shows weakest payback, requiring investigation or budget reallocation

You might shift more budget to Apple Search Ads and Google, reduce TikTok spend, and optimize Facebook creative to improve early monetization.

Common Payback Modeling Mistakes

Using LTV instead of actual revenue: Payback should be based on realized revenue, not projected LTV. If you haven't collected the cash, it doesn't count toward payback.

Forgetting gross margin: Revenue isn't profit. Subtract platform fees (Apple/Google 15-30%), payment processing (2-3%), and COGS to get true margin.

Ignoring cohort decay: Early cohorts may perform differently than later ones due to market saturation, creative fatigue, or user quality changes. Update models monthly.

Not segmenting by channel: Blended payback hides channel-specific inefficiencies. Model each major channel separately.

Optimizing only for speed: Fastest payback isn't always best. A channel with 6-month payback and $500 LTV may be better than 3-month payback and $100 LTV.

Payback Period and Capital Efficiency

Payback period directly impacts how much growth you can fund with available capital.

Capital recycling example:

• Starting capital: $100,000
• CAC: $50
• Payback period: 90 days
• Users acquired in Month 1: 2,000

After 90 days, you recover $100K and can reinvest it. If payback were 180 days, you'd wait twice as long to recycle capital.

Growth impact:

Faster payback → faster capital recycling → more reinvestment → accelerated growth

This is why elite mobile apps obsess over shortening payback windows. It's not just unit economics—it's growth leverage.

Final Considerations

Payback period modeling is most useful when it's:

• Cohort-based: Track each acquisition cohort separately to identify trends
• Channel-specific: Different channels have different economics
• Updated regularly: Monthly model updates reflect changing market conditions
• Action-oriented: Use insights to adjust bids, budgets, and strategies

The goal isn't perfect prediction. It's building a framework that shows when users become profitable and how to accelerate that timeline.

Start by calculating your current payback at 30, 60, and 90 days. Compare to category benchmarks. Identify the biggest opportunity (reduce CAC, increase early ARPU, improve retention) and optimize.

The best payback model is the one you can act on.

FAQs

What's a good payback period for mobile apps?

Strong performing apps achieve 5-7 month payback periods, with targets under 12 months being common industry-wide. Gaming apps often target 30-90 day payback due to front-loaded monetization, while subscription apps may accept 6-12 month payback given higher lifetime value.

Why use payback period instead of LTV?

Payback period is more practical for mobile apps because it requires shorter observation windows and provides actionable cash flow insights. LTV calculations require 12-24+ months of data and make assumptions about future retention that may not materialize.

How do I calculate CAC payback period?

Payback Period (months) = CAC ÷ (Monthly ARPU × Gross Margin). For example, with $110 CAC, $26.78 ARPU, and 92% margin: Payback = $110 ÷ ($26.78 × 0.92) = 4.4 months.

Should I calculate payback per install or per paying customer?

Always calculate based on paying customers (CAC), not installs (CPI). Payback measures when you recover acquisition investment, which only happens through monetized users. Free users who never pay have infinite payback.

How often should I update payback models?

Review cohort payback monthly to identify trends and update assumptions. Quarterly deep-dives help validate whether your optimization efforts are improving payback timelines or if market dynamics are degrading performance.

---

Payback period modeling transforms unit economics from abstract projections into concrete cash flow timelines. Build models that track 30, 60, and 90-day recovery, compare across channels, and optimize for faster capital recycling.