SKAN 4.0 Implementation with Coarse Value and LockWindow

TRUETECH is engaged in the development, support and maintenance of iOS, Android, PWA mobile applications. We have extensive experience and expertise in publishing mobile applications in popular markets like Google Play, App Store, Amazon, AppGallery and others.

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These are just some of the types of mobile applications we work with, and each of them may have its own specific features and functionality, tailored to the specific needs and goals of the client.

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SKAN 4.0 Implementation with Coarse Value and LockWindow
Complex
~3-5 days
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Many developers face unexpected behavior: after switching to SKAdNetwork 4.0 (SKAN 4.0), the fine conversion value only arrives in the first postback, and coarse value is a non-obvious parameter. Let's figure out how to configure this mechanism and avoid losing attribution data. Our team has experience implementing SKAN 4.0 for apps with monthly ad budgets starting from $10,000. Get a consultation on implementation — it will take no more than an hour.

What Changed in SKAN 4.0

Three Postbacks Instead of One

In SKAN 2.x/3.x, the ad network received one postback after the timer expired. SKAN 4.0 introduces three time windows:

Postback Time Window Contains
First 0–2 days after install fine value (0–63) + coarse value + source identifier
Second 3–7 days coarse value (low/medium/high)
Third 8–35 days coarse value

The second and third postbacks are sent only if the user was active in the corresponding window. This allows seeing if the user remained active on day 7 and day 35 — impossible without the first postback.

Fine Value and Coarse Value

Fine conversion value — the previous 6 bits (0–63). It appears only in the first postback and only with high crowd anonymity (Apple does not disclose the exact threshold, roughly several thousand installs from a single campaign).

Coarse value — a new field with three values: low, medium, high. It is sent in all three postbacks even with low traffic volumes. Less informative but stable.

Source Identifier

A new 2–4 digit field replacing campaign ID. The first two digits are always included in the postback; the third and fourth only with sufficient crowd anonymity. Allows encoding not only campaign but also ad set or individual ad.

How to Set Up SKAN 4.0 in Three Steps?

The process consists of three steps:

  1. Update the updatePostbackConversionValue call with fineValue, coarseValue, and lockWindow parameters.
  2. Ensure backward compatibility with iOS 14.x by keeping the updateConversionValue call for older versions.
  3. Configure MMP (AppsFlyer, Adjust) to receive three postbacks and map coarse value.

Updating updateConversionValue

In SKAN 4.0, the method takes three parameters:

import StoreKit

// iOS 16.1+
if #available(iOS 16.1, *) {
    SKAdNetwork.updatePostbackConversionValue(
        fineValue: 15,          // 0–63, only for first window
        coarseValue: .medium,   // .low, .medium, .high
        lockWindow: false,      // true = immediately close window, don't wait for timer
        completionHandler: { error in
            if let error = error {
                print("SKAN update failed: \(error)")
            }
        }
    )
}

The lockWindow: true parameter is new in SKAN 4.0. If called with true, Apple immediately triggers postback sending without waiting for the timer. Useful when you know the user performed a key action and further updates are unnecessary. According to Apple documentation, lockWindow allows immediately closing the window.

Backward Compatibility

The app must support SKAN 3.x for iOS 14.x and SKAN 4.0 for later versions. Both APIs need to be called in parallel:

func trackPurchase(revenue: Double) {
    let fineValue = encodeFineValue(revenue: revenue)
    let coarseValue: SKAdNetwork.CoarseConversionValue = revenue > 20 ? .high : .medium

    if #available(iOS 16.1, *) {
        SKAdNetwork.updatePostbackConversionValue(
            fineValue,
            coarseValue: coarseValue,
            lockWindow: false
        ) { _ in }
    } else if #available(iOS 14.0, *) {
        SKAdNetwork.updateConversionValue(fineValue)
    }
}

Configuring MMP

AppsFlyer and Adjust already support SKAN 4.0, but you need to explicitly activate three postbacks in the app settings within the dashboard. By default, MMP continues to operate in SKAN 3.x mode. In AppsFlyer, under iOS App Settings → SKAdNetwork: select SKAN 4.0 mode, set coarse value mapping for the second and third windows.

What is lockWindow and How to Use It?

LockWindow is a new tool for precise timer control. When you call updatePostbackConversionValue with lockWindow: true, Apple immediately captures the current values and sends the postback without waiting for the natural window expiration. This is critical for events after which further updates are meaningless (e.g., a one-time purchase).

Coarse Value as a Fallback Signal

Coarse value is a "fallback" signal for situations where fine value is hidden due to crowd anonymity. Even with a small number of installs (less than 1000–2000 from a single campaign), you will still get coarse: low, medium, or high. This allows estimating retention and conversions without linking to an exact amount.

Designing Conversion Value Schema for Three Windows

For SKAN 4.0, you need to design three independent schemas — one for each postback window:

First window (0–2 days): detailed information about initial actions. Fine value encodes, for example:

  • 0–15: registration without purchase, engagement level
  • 16–31: added to cart, product category
  • 32–63: made a purchase, revenue bucket

Second window (3–7 days): coarse value reflects retention status:

  • low — did not return
  • medium — opened app but no key event
  • high — repeat purchase or high engagement

Third window (8–35 days): similar to the second, but for the second month of lifecycle.

Why SKAN 4.0 is More Effective Than SKAN 3.x?

Characteristic SKAN 3.x SKAN 4.0
Number of postbacks 1 up to 3
Fine conversion value yes (0–63) only in first
Coarse value no yes (low/medium/high)
LockWindow no yes
Source identifier campaign ID 2–4 digit identifier
Crowd anonymity protection only fine fine + source identifier

SKAN 4.0 is three times more informative, providing data about user behavior on day 7 and day 35.

Limitations and Reality

Crowd anonymity means that for small apps (less than 1000–2000 installs from a specific campaign), Apple replaces fine value in the first postback with null. Coarse value always arrives. This must be accounted for in analysis: absence of fine value is not an integration error but a privacy protection. By our estimates, incorrect SKAN 4.0 configuration leads to losing up to 15% of advertising budget. Correct integration can significantly reduce these losses.

What's Included in the Work

  • Audit of current SKAN integration and SKAdNetwork version in Info.plist
  • Design of a three-level conversion value schema
  • Implementation of updatePostbackConversionValue with iOS 14+ support
  • Configuration of SKAN 4.0 in AppsFlyer / Adjust
  • Verification of postbacks via test traffic
  • Savings on test traffic amount to up to 40% due to precise analysis.

Timeline

3–5 days. Most of the time is spent on schema design and alignment with the ad team, not the code itself. Pricing is individual.

Contact us to help you set up SKAN 4.0 for your needs. Get a specialist consultation.

Mobile App Analytics: Firebase, Amplitude, AppsFlyer and Attribution

Our team regularly encounters projects where analytics is already "set up" but yields no real insights. A typical example is a startup with 50k DAU: tracking dozens of events without a single answer to the question "why don't users reach payment?". In two weeks we built a basic funnel and found that 70% of users drop off at the phone number verification screen. After fixing the bug, retention increased by 12%. The takeaway: analytics should start with specific questions, not tracking everything indiscriminately.

Why Event Taxonomy is the Foundation of Mobile App Analytics?

Firebase Analytics, Amplitude, Mixpanel — technically similar. The difference lies in what you put into them. A common mistake: events like screen_view, button_tap_1, button_tap_2 without context. A month later, no one remembers what button_tap_2 means.

Proper taxonomy: object + action + context. product_viewed, checkout_started, payment_completed with parameters product_id, category, price, source. This allows building funnels, cohort analysis, and retention without additional tracking.

We document the naming convention in a tracking plan — a document (Google Sheet or Amplitude Data Catalog) describing every event, its parameters, and triggering conditions. The tracking plan is synced with the analytics team before development begins, not after. This approach ensures that data remains interpretable months later and doesn't become a dump. Experience from 50+ projects confirms: without a tracking plan, analytics maintenance costs increase 2-3 times due to rework.

What Should You Choose for Mobile App Analytics: Firebase, Amplitude, or Mixpanel?

The table below highlights key differences between the three popular platforms. Choice depends on budget, traffic, and tasks.

Criteria Firebase Analytics Amplitude Mixpanel
Free limit Unlimited (Spark plan) Up to 10M events/month Up to 1K MTU/month (Special)
Data latency Up to 24 hours (standard) Minutes (real-time) Minutes (real-time)
Funnels and cohorts Basic funnels, limited count Deep funnels, Journeys, cohorts Funnels, Retention, Insights
BigQuery export Yes (free, raw data) Yes (subscription) Yes (Enterprise)
Session Replay No Yes (iOS/Android SDK) No
Ad integration Google Ads (native) Via Universal Links Via partners

Firebase Analytics — free, deep integration with Google Ads, BigQuery export for raw data. Limitations: data latency up to 24 hours, limited funnels. For startups with Google Ads traffic, it's the first choice.

Amplitude — product analytics focused on cohorts and user journeys. Journeys (formerly Pathfinder) shows actual paths between events — not assumed funnels but real routes. Session Replay records sessions for UX analysis. The free tier up to 10M events/month is enough for most products at launch.

Mixpanel — close to Amplitude, stronger in real-time segmentation. Insights, Funnels, Retention cover 90% of product analysts' tasks.

How to Solve Multi-Channel Attribution with AppsFlyer?

Knowing where a user came from is a separate task. Firebase Attribution works only within the Google ecosystem. For multi-channel attribution (Facebook Ads, TikTok, Apple Search Ads, programmatic), an MMP (Mobile Measurement Partner) is needed.

AppsFlyer is the market leader. OneLink — universal deep link working on iOS and Android, correctly attributing installs from any channel. Protect360 — built-in fraud protection (fake installs, click injection on Android). Adjust and Branch are competitors with similar features. Branch excels in deep linking; Adjust is popular in gaming.

According to Apple, with iOS 14.5, apps must obtain user permission via ATT before collecting IDFA for tracking. AppsFlyer uses probabilistic matching (IP + user agent + timing) for these users — accuracy is lower but better than nothing. SKAdNetwork and Privacy Preserving Attribution provide aggregated data from Apple with a 24-72 hour delay.

How to Set Up Crash Analytics to Not Miss Bugs?

Firebase Crashlytics is the standard for crash reporting. It automatically groups crashes by stack trace, shows affected users %, and sends velocity alerts when crash rate increases by more than 10% per hour.

Important: symbolication. On iOS, .dSYM files must be automatically uploaded with each build — via Fastlane upload_symbols_to_crashlytics or Xcode Cloud built-in. Without symbols, crashes in Crashlytics appear as memory addresses. This happens more often than expected when switching to a new CI — in one project with 500k users, we found that 40% of crashes remained unsymbolicated due to a missing CI/CD step. After automation, bug response time dropped from 3 hours to 15 minutes.

For React Native and Flutter, @sentry/react-native and sentry_flutter provide additional context: breadcrumbs, network requests before the crash, Redux/Provider state.

Below is a comparison of popular crash analytics tools to choose according to your needs.

Criteria Firebase Crashlytics Sentry Instabug
Free limit Unlimited (Spark) 5k events/month 250 MAU
Grouping By stack trace + parameters By fingerprint By stack trace + metadata
Symbolication Automatic (via file) Automatic (via CLI) Automatic
Velocity alerts Yes (by % change) Yes (by count) Yes (by threshold)
Extra context Logs, Keys, Custom Keys Breadcrumbs, User, Tags User steps, network requests
Price Free (in Firebase) Paid plans available Paid plans available

Environment Setup

Three environments with separate Firebase projects: dev, staging, production. Mixing analytics from test sessions and production is a common mistake that skews all metrics. On iOS via GoogleService-Info.plist per scheme, on Android via google-services.json in each flavor folder.

Timelines: basic analytics with Firebase + Crashlytics — 3-5 days. Full tracking plan + Amplitude/Mixpanel with funnels and cohorts — 2-3 weeks. Attribution via AppsFlyer with deep linking and fraud protection — 1-2 weeks. Cost is calculated individually based on integration complexity.

What Is Included in Our Work

As part of analytics implementation, we provide:

  • Development and approval of a tracking plan with product and marketing teams.
  • SDK integration (Firebase, Amplitude, Mixpanel, AppsFlyer) considering your stack (Swift/Kotlin/Flutter/React Native).
  • Setup of funnels, cohorts, dashboards, and alerts.
  • Automation of symbolication and .dSYM upload via Fastlane.
  • Documentation of events and parameters.
  • Team training on the analytics platform.
  • Two weeks of post-release support and tracking adjustments.

Our experience: 7 years of analytics implementation and over 80 successful projects in mobile development. We guarantee data correctness and transparency at every stage.

Contact us for a consultation on setting up analytics for your app. Request an audit of your current analytics — and we will show you which metrics you are losing.