You launched a fitness app three months ago. Your CFO asks a straightforward question: "Which marketing channels are actually driving profitable subscribers?"

Your current answer: "We're getting 15,000 trial starts monthly from Meta and Google campaigns. Trial-to-paid conversion is 18%."

Your CFO's follow-up: "But what's our CAC by channel? What's the LTV of subscribers from each source? Which campaigns drive subscribers who actually renew versus subscribers who churn after one month?"

You realise you can answer install attribution and trial start attribution, but you cannot connect acquisition spend to subscription renewals, churn timing, or lifetime value by channel.

This is the subscription attribution problem. Standard attribution tracks installs and first conversions, but subscription apps need to track the entire lifecycle: trial start, trial-to-paid conversion, first renewal, second renewal, churn event, and total LTV by acquisition source.

This guide provides a complete framework for subscription attribution covering trial tracking, conversion measurement, renewal attribution, and churn analysis with practical implementation steps.

Why Standard Attribution Breaks for Subscription Apps (The Revenue Delay Problem)

Most mobile attribution focuses on point-in-time conversions. An eCommerce app attributes a purchase to the campaign that drove the install. A gaming app attributes an in-app purchase to the originating channel. These are immediate, single-event conversions.

Subscription apps work differently. Revenue isn't a single event, it's a stream of recurring payments over time:

Month 1: User installs via Meta campaign, starts 7-day free trial, converts to monthly subscription

Month 2: Subscription renews automatically, generating second payment

Month 3: Subscription renews again, generating third payment

Month 4: User cancels subscription

Total revenue generated from that single install: ₹600 (₹150 × 4 months). But standard attribution only captures Month 1 (₹150), missing 75% of the actual value.

The financial impact compounds at scale. A subscription app spending ₹8 lakh monthly on user acquisition with 3-month average subscription length generates ₹24 lakh in total subscription revenue. If you're measuring ROAS based only on first-month revenue, you're seeing 1.0× ROAS when true ROAS is 3.0×.

Without subscription-aware attribution, you'll underinvest in channels that drive loyal subscribers and overinvest in channels that drive one-month churners.

The Subscription Attribution Challenge: Tracking Value Beyond Install

Subscription attribution requires tracking five distinct conversion moments:

1. Trial Start: When did the user begin their free trial or freemium experience?

2. Trial-to-Paid Conversion: When did the trial convert to a paying subscription?

3. First Renewal: Did the subscriber renew after their first billing period?

4. Subsequent Renewals: How many billing cycles did the subscription last?

5. Churn Event: When did the subscription cancel, and can we attribute churn to campaign quality?

Each event needs attribution back to the original acquisition source to calculate true CAC and LTV by channel.

Event #1: Trial Started (Attribution Window Begins)

What It Measures

Trial Started tracks when a user initiates a free trial or begins using premium features under a freemium model. This is your first monetisation signal.

Why It Matters

Install-to-trial conversion rate reveals campaign quality. Users who install but never start trials typically lack intent. Users who start trials within 24 hours show 4-6× higher trial-to-paid conversion compared to users who start trials after 3+ days.

This metric also exposes onboarding friction. If 60% of users from organic sources start trials but only 25% from paid campaigns start trials, either your paid creative overpromises or your onboarding fails to communicate value to paid users.

Implementation Details

Event Name: trial_started

When to Fire: When user initiates free trial or unlocks premium features in freemium model

Parameters to Track:

• hours_since_install: Time from install to trial start

• trial_duration_days: Length of trial period (7-day, 14-day, 30-day)

• trial_type: Type of trial (free trial, paid trial with refund, freemium unlock)

• subscription_tier: Which premium tier was selected (basic, pro, premium)

Channel-Level Benchmarking

Healthy subscription apps typically see:

• 40-60% of installs start trials within 7 days

• Median time-to-trial-start: 4-12 hours

• High-intent channels (search, referrals): 60-75% trial start rates

• Discovery channels (social, display): 35-50% trial start rates

If a campaign drives 10,000 installs but only 2,500 trial starts (25%), investigate creative messaging and landing experience.

Event #2: First Core Action Completed (Activation Signal)

What It Measures

First Core Action Completed tracks when a trial user completes your app's primary value-delivering behaviour. For a fitness app, this is completing a workout. For a meditation app, this is finishing a session. For a productivity app, this is creating a project.

Why It Matters

Trial start alone doesn't predict conversion. Users who start trials but never use the product churn at 80-90% rates. Users who complete core actions within 48 hours of trial start show 3-5× higher trial-to-paid conversion.

This metric separates valuable trials (engaged users) from wasted trials (curious browsers who never activate).

Implementation Details

Event Name: core_action_completed

When to Fire: When user completes your app's primary value action during trial period

Parameters to Track:

• hours_since_trial_start: Time from trial start to first core action

• action_type: Specific action completed (workout finished, project created, document exported)

• action_count: Number of core actions completed during trial

Activation Thresholds

Successful subscription apps typically see:

• 60-75% of trial starts complete at least one core action

• 40-55% complete 3+ core actions during trial

• Users who complete 5+ core actions during trial convert at 50-70% rates

• Users who complete 1-2 core actions convert at 15-25% rates

• Users who complete zero core actions convert at 2-5% rates

Without tracking core action completion by acquisition source, you can't distinguish channels that drive engaged trial users from channels that drive tire-kickers.

Event #3: Trial-to-Paid Conversion (Primary Revenue Event)

What It Measures

Trial-to-Paid Conversion tracks when a free trial converts to a paying subscription or when a freemium user upgrades to premium.

Why It Matters

This is your primary monetisation event. Install-to-paid-subscriber conversion reveals true campaign efficiency. A campaign driving 5,000 installs with 12% paid conversion generates 600 subscribers. A campaign driving 3,000 installs with 20% paid conversion generates 600 subscribers at 40% lower cost.

Without trial-to-paid attribution, both campaigns look equally valuable at the install level.

Implementation Details

Event Name: trial_converted or subscription_started

When to Fire: When user's first subscription payment processes successfully

Parameters to Track:

• days_since_install: Time from install to paid conversion

• days_since_trial_start: Time from trial start to conversion

• subscription_tier: Which plan was purchased (monthly, annual)

• subscription_value: Revenue amount

• core_actions_before_convert: Number of core actions completed before converting

• conversion_trigger: What prompted conversion (trial expiring, feature limit, proactive upgrade)

Conversion Windows by Vertical

Typical trial-to-paid timing varies by vertical:

Fast-converting verticals (3-7 day trials):

• Fitness apps: 60-75% convert in final 24 hours of trial

• Meditation apps: 55-70% convert in final 48 hours

• Content apps: 50-65% convert in final 72 hours

Considered-purchase verticals (14-30 day trials):

• Productivity tools: 40-55% convert mid-trial (days 7-14)

• Creative software: 35-50% convert late-trial (days 10-20)

• B2B SaaS: 30-45% convert after trial ends (grace period)

Your attribution window should match your trial length plus 3-7 days for grace period conversions.

Event #4: Subscription Renewed (Retention Confirmation)

What It Measures

Subscription Renewed tracks when a paying subscriber's subscription automatically renews for another billing period.

Why It Matters

First renewal is your strongest retention signal. Subscribers who renew once typically renew 2-4 more times. Subscribers who churn immediately after first billing period indicate low-quality acquisition or poor product-market fit.

Renewal attribution reveals channel quality differences invisible at install or trial level. A channel driving subscribers who renew 6+ times has substantially higher lifetime value than a channel driving subscribers who cancel after one month.

Implementation Details

Event Name: subscription_renewed

When to Fire: When subscription payment processes successfully for renewal (not initial purchase)

Parameters to Track:

• renewal_number: Which renewal this is (1st, 2nd, 3rd, etc.)

• days_subscribed: Total days as paying subscriber

• subscription_tier: Current plan (track if users upgrade/downgrade)

• renewal_value: Revenue amount for this billing period

• cumulative_value: Total revenue from this subscriber to date

Attribution Connection

Connect renewal events back to original acquisition source. Your MMP should show:

This reveals:

• Organic subscribers show strongest retention (4.1 month average vs 2.5-2.8 months paid)

• Meta drives better retention than Google despite similar CAC

• Month-over-month retention curves show organic declining slower than paid

Without renewal attribution, all three sources appear equally valuable after initial conversion.

Event #5: Churn Event (Attribution to Last Campaign Touch)

What It Measures

Churn Event tracks when a subscription cancels, either through user-initiated cancellation or failed payment.

Why It Matters

Churn timing and churn rate by acquisition channel reveal quality problems. Channels that drive subscribers who churn after one month indicate targeting issues or expectation mismatches. Channels that drive subscribers who stay 6+ months indicate high-quality user acquisition.

Churn attribution also reveals whether acquisition quality degrades over time. If your Meta campaigns drove 4-month average subscription length in Q1 but 2-month average in Q3, creative fatigue or targeting drift has eroded quality.

Implementation Details

Event Name: subscription_cancelled or subscription_churned

When to Fire: When subscription ends (user cancels or payment fails after retry attempts)

Parameters to Track:

• days_subscribed: Total length of subscription

• renewal_count: How many times subscription renewed before churning

• churn_reason: Why subscription ended (user cancelled, payment failed, downgrade to free)

• cumulative_revenue: Total revenue generated from this subscriber

• churn_type: Voluntary cancellation vs involuntary (payment failure)

Churn Analysis by Channel

Connect churn events back to acquisition source to identify problem channels:

Healthy churn patterns:

• 20-30% churn after month 1 (natural trial-error filtering)

• 10-15% churn month 2-3 (continued product fit evaluation)

• 5-10% churn month 4+ (stabilised user base)

Problem churn patterns:

• 45%+ churn after month 1: Poor targeting, creative overpromise, or weak onboarding

• Accelerating churn month-over-month: Product quality issues or missing features

• Involuntary churn (failed payments) exceeding 15%: Poor payment UX or insufficient retry logic

If a campaign shows 60% month-1 churn compared to 25% platform average, pause that campaign and investigate targeting.

Freemium vs Paid Trial: Different Attribution Models for Different Monetisation Strategies

Freemium Attribution Model

Freemium apps offer free core functionality permanently, monetising through premium upgrades. Examples: Spotify, Notion, Duolingo.

Attribution challenge: Users might install, use the free product for months, then upgrade. Standard attribution windows (7-30 days) miss these late conversions.

Solution: Use extended attribution windows (60-90 days) for freemium apps, or implement re-attribution for users who upgrade after initial window closes.

Key metrics:

• Install to free user activation rate

• Free user engagement depth (DAU/MAU, feature usage)

• Free-to-paid conversion rate by acquisition source

• Time-to-upgrade by channel (how long free users stay free before converting)

Example freemium attribution:

• Meta campaign drives 10,000 installs in January

• 6,500 become engaged free users (65% activation)

• By end of March (90 days), 650 have upgraded to paid (10% free-to-paid conversion)

• Average time-to-upgrade: 45 days

• CAC: ₹400, LTV at 90 days: ₹3,250 per upgraded user

Without extended attribution windows, you'd only capture upgrades in the first 30 days (maybe 200 of the 650), dramatically understating channel value.

Paid Trial Attribution Model

Paid trial apps require users to start a free trial upfront, with automatic conversion to paid subscription at trial end unless cancelled. Examples: most fitness apps, streaming services, productivity tools.

Attribution challenge: Trial starts don't equal revenue. Some users cancel before first payment.

Solution: Track trial starts separately from paid conversions, measure trial-to-paid rates by source.

Key metrics:

• Install to trial start rate

• Trial-to-paid conversion rate by acquisition source

• First renewal rate (indicates trial quality)

• Average lifetime by acquisition channel

Example paid trial attribution:

• Google campaign drives 8,000 installs in January

• 4,800 start 7-day free trials (60% trial start rate)

• 1,200 convert to paid after trial (25% trial-to-paid)

• 840 renew after first month (70% renewal rate)

• CAC: ₹667 per paid subscriber, not ₹250 per install

Without trial-to-paid tracking, you'd celebrate 4,800 "conversions" (trial starts) instead of the true 1,200 paying subscribers.

Attribution Windows for Subscription Apps: Why 30-90 Days Matters

Subscription apps need longer attribution windows than transactional apps because value realisation happens over weeks or months, not hours or days.

Recommended Windows by Subscription Model

7-day free trial apps:

• Minimum attribution window: 14 days

• Optimal window: 21 days

• Rationale: Captures trial starts (days 1-7) + trial-to-paid (days 7-10) + first renewal signal (day 14-21)

14-day free trial apps:

• Minimum attribution window: 21 days

• Optimal window: 30 days

• Rationale: Captures full trial period + conversion lag + early renewal indicators

30-day free trial apps:

• Minimum attribution window: 45 days

• Optimal window: 60 days

• Rationale: Captures trial completion + conversion window + first renewal

Freemium apps:

• Minimum attribution window: 60 days

• Optimal window: 90 days

• Rationale: Users often explore free tier for 30-60 days before upgrading

Annual subscription apps:

• Minimum attribution window: 45 days

• Optimal window: 90 days

• Rationale: Annual purchase decisions take longer, users research alternatives

Why Longer Windows Matter

Example: A meditation app with 7-day trials uses a 7-day attribution window.

What attribution captures:

• Installs: 10,000

• Trial starts within 7 days: 6,000

• Paid conversions within 7 days: 800 (most trials haven't ended yet)

• Calculated CAC: ₹625 per paid subscriber

• Calculated ROAS: 0.8×

What actually happened (measured at day 21):

• Trial starts: 6,500 (some users started trials on days 8-14)

• Paid conversions: 1,625 (25% of trial starts)

• Actual CAC: ₹308 per paid subscriber

• Actual ROAS: 1.6×

The 7-day window made campaigns look 2× worse than reality, causing underinvestment in working channels.

Measuring True LTV: Connecting Acquisition Spend to Lifetime Subscription Value

LTV Calculation Framework

Lifetime value (LTV) for subscription apps = Average subscription duration × Monthly revenue

Example:

• Average subscription length: 5.2 months

• Monthly subscription price: ₹299

• LTV = 5.2 × ₹299 = ₹1,555

But this is blended LTV across all channels. Channel-specific LTV reveals massive differences:

With ₹400 target CAC, this reveals:

• Organic: ₹2,332 LTV / ₹150 CAC = 15.5× return (incredible)

• Referral: ₹1,854 LTV / ₹280 CAC = 6.6× return (excellent)

• Meta: ₹1,346 LTV / ₹420 CAC = 3.2× return (profitable)

• Google: ₹1,136 LTV / ₹450 CAC = 2.5× return (marginally profitable)

• Display: ₹628 LTV / ₹520 CAC = 1.2× return (barely breaking even)

Without channel-level LTV measurement, you'd treat all channels equally despite 12× difference in true profitability.

Leading vs Lagging LTV

Lagging LTV (observed): Actual measured lifetime of churned subscribers

• Accurate but requires waiting 6-12 months for full cohort maturity

• Only tells you what happened in the past

Leading LTV (predicted): Estimated based on early retention signals

• Available within 30-60 days

• Enables faster optimization decisions

Calculate leading LTV using:

• Day 7 retention rate

• Day 30 retention rate

• First renewal rate

• Historical churn curves

Example leading LTV calculation:

• Day 7 retention: 65%

• Day 30 retention: 48%

• First renewal rate: 72%

• Historical data: Apps with this profile average 5.1 month lifetime

• Predicted LTV = 5.1 months × ₹299 = ₹1,525

Use leading LTV for week-to-week optimisation decisions. Use lagging LTV for channel-level investment decisions.

Channel Quality Analysis: Which Acquisition Sources Drive Longest Subscriptions?

Not all acquisition channels produce equal subscriber quality. Build a quality scorecard showing:

Metric #1: Trial-to-Paid Conversion Rate

What percentage of trial starts become paying subscribers?

Good benchmarks:

• Top-quartile channels: 30-40% conversion

• Average channels: 20-30% conversion

• Weak channels: <15% conversion

Low trial-to-paid rates indicate targeting problems or creative overpromise.

Metric #2: First Renewal Rate

What percentage of paid subscribers renew after first billing period?

Good benchmarks:

• Top-quartile channels: 75-85% renewal

• Average channels: 60-75% renewal

• Weak channels: <50% renewal

Low first renewal rates indicate expectation mismatches or poor targeting.

Metric #3: Average Subscription Length

How many billing cycles do subscribers stay active?

Good benchmarks by vertical:

• Fitness/wellness apps: 4-6 months

• Productivity tools: 6-12 months

• Entertainment/streaming: 8-18 months

• B2B SaaS: 12-36 months

Shorter subscription lengths indicate weak retention or competition.

Metric #4: Cumulative LTV at 90 Days

How much revenue has each subscriber generated within first 90 days?

Example scorecard:

This scorecard reveals:

• Organic drives 3.5× better 90-day LTV than TikTok

• Meta and Google show similar quality despite different conversion rates

• TikTok drives subscribers who churn fast (2.2 month average)

Without quality scoring, you'd allocate budget based on install volume or CPI instead of subscriber lifetime value.

Churn Attribution: Identifying Which Campaigns Drive High-Risk Subscribers

Churn isn't random. Specific acquisition sources drive subscribers more likely to cancel early.

Churn Risk Indicators

High churn risk signals:

• Acquired from awareness campaigns (not intent-driven)

• Never completed core actions during trial

• Upgraded only due to trial expiring (not proactive)

• Low session frequency during first 30 days

• Came from broad targeting (not niche audiences)

Low churn risk signals:

• Acquired from search or referrals (high intent)

• Completed 5+ core actions during trial

• Proactively upgraded mid-trial

• High engagement first 30 days (4+ sessions/week)

• Came from specific interest targeting

Churn Attribution Methodology

Connect churn events back to acquisition source:

1. Identify churned cohorts by month and channel

2. Calculate churn rates at 30, 60, 90 days by source

3. Compare to benchmarks to identify outlier channels

4. Investigate high-churn sources for targeting or creative issues

5. Pause or fix channels with persistent high churn

Example churn analysis:

This reveals:

• Brand awareness campaigns drive 2× higher churn than conversion campaigns

• Google Search and Referrals drive lowest churn

• By day 90, brand campaigns retain only 32% vs 68% from referrals

Reallocate budget from high-churn sources to low-churn sources for better LTV:CAC ratios.

Implementation Playbook: Setting Up Subscription Attribution in Week One

Step 1: Define Your Subscription Events (Day 1-2)

Map your subscription journey and identify tracking points:

Required events:

• trial_started: When user begins free trial or unlocks premium

• subscription_started: When first payment processes

• subscription_renewed: When recurring payment processes

• subscription_cancelled: When subscription ends

Optional but recommended:

• core_action_completed: Key value-delivering actions during trial

• subscription_upgraded: User moves to higher tier

• subscription_downgraded: User moves to lower tier

• payment_failed: Subscription payment declined (involuntary churn risk)

Step 2: Implement Event Tracking (Day 3-5)

Integrate your MMP SDK and payment processor webhooks:

For trial events:

Use your MMP SDK to fire events when users start trials or complete core actions.

For subscription events:

Configure webhooks from your payment processor (Stripe, RevenueCat, App Store, Google Play) to your MMP. This ensures subscription renewals and cancellations get attributed correctly.

Step 3: Configure Attribution Windows (Day 5-6)

Set attribution windows matching your subscription model:

• 7-day trial apps: Use 21-day windows minimum

• 14-day trial apps: Use 30-day windows

• Freemium apps: Use 60-90 day windows

Step 4: Validate Event Flow (Day 6-7)

Test the complete subscription flow:

1. Install app via test campaign link

2. Start trial and complete core actions

3. Convert to paid subscription

4. Verify all events appear attributed to test campaign

5. Wait for renewal window and verify renewal events attribute correctly

Step 5: Build Reporting Dashboards (Ongoing)

Create reports showing:

• Trial starts by channel

• Trial-to-paid conversion by source

• Renewal rates by cohort and channel

• Churn rates and timing by source

• LTV projections by acquisition channel

How Linkrunner Simplifies Subscription Attribution

Platforms like Linkrunner provide subscription apps with unified attribution across the full subscriber lifecycle. Instead of stitching together data from your MMP, payment processor, and analytics tools, Linkrunner connects acquisition spend to trial starts, paid conversions, renewals, and churn in a single dashboard.

For subscription apps specifically, Linkrunner provides:

• Extended attribution windows (up to 90 days) capturing late conversions in freemium models

• Renewal attribution showing which channels drive subscribers who stay 3, 6, 12+ months

• Churn analysis identifying campaigns that drive high-risk subscribers who cancel after one month

• LTV projections by channel using early retention signals

• Automated postback configuration sending subscription events to Meta, Google, TikTok for value-based bidding

• Cohort reporting comparing retention curves across acquisition sources

Starting at ₹0.80 per attributed install, subscription apps get complete lifecycle attribution without the ₹2-8 lakh monthly costs of legacy MMPs or the complexity of custom data warehouse implementations.

Key Takeaways

Subscription attribution requires tracking five critical events:

1. Trial Started: Activation signal separating engaged users from browsers

2. Core Action Completed: Strongest predictor of trial-to-paid conversion

3. Subscription Started: First revenue event, primary optimization target

4. Subscription Renewed: Retention confirmation revealing channel quality

5. Subscription Cancelled: Churn attribution identifying problem campaigns

Use extended attribution windows (21-90 days depending on trial length) to capture complete subscription lifecycle.

Measure channel-specific LTV by connecting acquisition spend to subscription duration and renewal rates, not just first-month revenue.

Optimise toward channels that drive subscribers who stay 4+ months, not channels that drive trial starts or one-month subscribers who immediately churn.

For subscription apps ready to implement lifecycle attribution, request a demo from Linkrunner to see how unified trial, conversion, renewal, and churn tracking can reveal which campaigns actually drive profitable subscribers.