SKAN Attribution Guide: How SKAdNetwork Works in 2026

Key Takeaways

• SKAdNetwork (SKAN) is Apple's privacy-preserving attribution API that provides campaign-level conversion data for iOS without requiring user-level identifiers.
• SKAN is the Layer 3 fallback in iOS attribution — used when neither IDFA nor Google ICM signals are available.
• SKAN data is aggregated, delayed (24–72 hours), and capped at campaign-level granularity — no creative, ad group, or user-level data.
• Conversion values (0–63) must be pre-configured to map to meaningful in-app events — misconfiguration means losing measurement of your most important KPIs.
• SolarEngine's iOS attribution integrates all three layers — IDFA, Google ICM, and SKAN — to maximize iOS attribution coverage for every campaign.

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Table of Contents

1. What Is SKAdNetwork (SKAN)?
2. Why SKAN Exists: The ATT Context
3. How SKAN Attribution Works
4. SKAN Conversion Values: The Critical Configuration
5. SKAN Limitations Every UA Team Must Know
6. SKAN vs Probabilistic Attribution
7. The Three-Layer iOS Attribution Stack
8. FAQ

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What Is SKAdNetwork (SKAN)? {#what-is}

SKAdNetwork (SKAN) is Apple's official attribution API for iOS. It provides mobile measurement data — specifically, which ad campaigns drove app installs — without sharing any user-level or device-level information with ad networks or measurement partners.

Apple designed SKAN to enable campaign-level attribution in a privacy-safe way. Instead of reporting "User X installed your app after clicking Ad Y," SKAN reports "Campaign Z received N attributed installs in this time window, with aggregated conversion value V."

SKAN is not optional for iOS attribution in 2026. For the segment of iOS users who decline ATT (the majority), SKAN is the only Apple-approved method for receiving any attribution signal at all.

One-sentence definition: SKAdNetwork (SKAN) is Apple's privacy-preserving attribution API that provides aggregated, delayed, campaign-level install data for iOS apps — without user identifiers.

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Why SKAN Exists: The ATT Context {#context}

Apple's App Tracking Transparency (ATT) framework, introduced with iOS 14.5, required apps to explicitly request permission before accessing the IDFA (Identifier for Advertisers). Most users decline this request.

The result: the standard deterministic attribution path — click on ad → IDFA collected → IDFA matched to install — became unavailable for the majority of iOS users.

SKAN was Apple's solution. Rather than abandoning attribution entirely, SKAN creates a privacy-preserving channel where:

• No individual user is identified
• No cross-app tracking occurs
• Apple controls the timing and aggregation of the data
• Ad networks and MMPs receive only what Apple's framework allows

Understanding ATT is essential for understanding why SKAN is structured the way it is — its constraints are not technical limitations but privacy design decisions.

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How SKAN Attribution Works {#how-it-works}

SKAN attribution follows a fundamentally different flow from standard MMP attribution:

Step 1: Ad Network Registers Campaign
The ad network registers its campaign with Apple's SKAN framework, receiving a campaign ID (limited to 100 campaign IDs per ad network in SKAN 4).

Step 2: User Clicks Ad and Installs
When a user clicks a SKAN-registered ad and installs the app, Apple's framework — not the MMP SDK — initiates the attribution process on-device.

Step 3: Conversion Value Updated
After install, the app has a configurable window to update a conversion value (a number from 0–63) that maps to meaningful in-app events. The MMP SDK provides the logic for updating this value based on events that occur in the app.

Step 4: Apple Sends Postback (Delayed)
After a privacy threshold is met and a timer expires (24–72 hours minimum, potentially days longer), Apple sends a postback to the ad network containing:

• Campaign ID
• Conversion value (the final value registered before the timer expired)
• Aggregate install count (with crowd anonymity threshold requirements)

Step 5: MMP Receives and Decodes Data
The ad network forwards the postback to the MMP. The MMP decodes the conversion value back into the in-app events it represents and includes the data in campaign reports.

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SKAN Conversion Values: The Critical Configuration {#conversion-values}

SKAN provides a 6-bit conversion value (0–63) — 64 possible states — to represent everything meaningful that happens in your app post-install. How you map these 64 values to actual events is one of the most consequential configuration decisions in iOS measurement.

What conversion values can represent:

• Revenue tiers (e.g., 0 = no purchase, 1 = <1, 2 = 1–5, etc.)
• Funnel stages (e.g., tutorial completed, first level passed, subscription started)
• Engagement thresholds (e.g., 3+ sessions, D1 retention)
• Hybrid maps combining revenue and engagement signals

Common misconfiguration mistakes:

• Mapping values only to installs (no post-install signal)
• Using too many granular tiers that rarely trigger (data never reaches Apple's threshold)
• Not updating conversion values within the activity window (the value locks before meaningful events occur)

Best practice: Map conversion values to the 2–3 events that most closely predict LTV for your app category. For casual games: D1 retention + first ad view + first purchase. Prioritize events that occur within the first 24 hours — values that update later may not be captured before Apple's timer expires.

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SKAN Limitations Every UA Team Must Know {#limitations}

SKAN attribution is structurally different from standard attribution. These are not bugs — they are by-design constraints:

Limitation	Impact
No user-level data	Cannot analyze individual user journeys; cohort analysis unavailable
No creative-level attribution	SKAN reports at campaign level only — no ad group or creative breakdown
Delayed reporting	Data arrives 24–72+ hours after install, making real-time optimization impossible
Privacy thresholds	Low-volume campaigns may receive null or randomized postbacks to prevent re-identification
100 campaign ID limit	Limited campaign segmentation per ad network per app
Conversion value lock	Once Apple's timer expires, no further updates — events after the window are invisible

The practical implication: SKAN data is useful for understanding campaign-level trends but cannot replace user-level MMP reporting for creative optimization, cohort analysis, or LTV modeling. It is a complement to — not a replacement for — deterministic attribution.

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SKAN vs Probabilistic Attribution {#vs-probabilistic}

Both SKAN and probabilistic attribution are used when IDFA is unavailable, but they work very differently:

	SKAN	Probabilistic
Source	Apple's on-device framework	MMP inference from contextual signals
Granularity	Campaign level only	Can reach ad group / creative level
User data	None (fully aggregated)	IP, device model, OS, timing
Delay	24–72+ hours	Near real-time
Accuracy	Guaranteed for consented attribution	Estimated — accuracy varies
Privacy	Apple-enforced	MMP-policy dependent

Which to use: SKAN and probabilistic attribution address different gaps. SKAN is the Apple-sanctioned method for iOS attribution; probabilistic fills coverage gaps across both iOS and Android scenarios where device IDs are unavailable. A complete iOS measurement strategy uses all three layers — IDFA, probabilistic/ICM, and SKAN — not one or the other.

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The Three-Layer iOS Attribution Stack {#three-layer}

SKAN is Layer 3 in the complete iOS attribution framework:

Layer	Signal	Users Covered
Layer 1 — IDFA	Device identifier	ATT-consented iOS users
Layer 2 — Google ICM	Google's Install Conversion Measurement	Non-consented users, Google Ads traffic
Layer 3 — SKAN	Apple's SKAdNetwork	All remaining iOS users

SolarEngine's iOS attribution implements all three layers. SKAN is configured through SolarEngine's SDK, which handles conversion value updates, postback receipt, and decoding — so clients receive SKAN data in the same unified report as IDFA and ICM data, without managing Apple's framework separately.

For the complete picture of iOS attribution and how all three layers work together, see
Mobile App Attribution: Complete Guide [2026]

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FAQ

Q: What is SKAdNetwork (SKAN)?
SKAdNetwork (SKAN) is Apple's privacy-preserving attribution API for iOS. It provides aggregated, campaign-level install data without user identifiers. SKAN is the Apple-approved attribution method for iOS users who have declined ATT permission, delivering delayed postbacks with conversion values instead of user-level data.

Q: Why is SKAN data delayed?
SKAN data is delayed by design. Apple's framework requires a timer to expire (minimum 24–72 hours) before sending the attribution postback, ensuring that no individual user can be identified from the timing of the data. Low-volume campaigns may experience longer delays due to crowd anonymity thresholds.

Q: What is a SKAN conversion value?
A SKAN conversion value is a number from 0 to 63 (6 bits) that your app updates after install to represent in-app events. The final value recorded before Apple's timer expires is included in the attribution postback. Conversion values must be pre-configured to map to meaningful events — the mapping strategy directly determines what post-install insights you receive from SKAN campaigns.

Q: Does SKAN replace my MMP?
No. SKAN provides Apple-approved attribution signals for non-consented iOS users, but it only delivers campaign-level, delayed, aggregated data. Your MMP receives, decodes, and integrates SKAN data alongside IDFA-based deterministic attribution and other signals — giving you a unified view. SKAN is one input into your MMP's iOS reporting, not a standalone solution.

Q: What is the difference between SKAN 3 and SKAN 4?
SKAN 4 (introduced with iOS 16.1) added support for multiple postbacks per install (up to 3, with decreasing fidelity), increased campaign ID limits to 100, and introduced crowd anonymity tiers. SKAN 4 provides more post-install data than SKAN 3 but still operates under the same fundamental constraints: aggregated, delayed, no user-level attribution.

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Conclusion

SKAN attribution is not optional for iOS measurement in 2026 — it's the only Apple-approved method for attributing the majority of iOS users who decline ATT. But SKAN is a complement to, not a replacement for, full-stack iOS attribution.

The teams that get the most from iOS measurement are those that implement all three layers — IDFA, Google ICM, and SKAN — and configure conversion values strategically to capture the signals that matter most for their app category.

Set up SKAN attribution with SolarEngine → — three-layer iOS coverage configured and ready, with dedicated support for conversion value strategy from day one.