Getting SKAN 4.0 Right: A Practical Guide for Marketers

Introduction

Have you ever had the experience of staring at your iOS marketing dashboard and asking yourself where your analytics went? If this has happened to you, you’re not alone.

Apple first announced its App Tracking Transparency Initiative in 2021, letting it be known that mobile marketers must now incorporate privacy into their marketing systems. With SKAdNetwork coming into play, we had to let go of many aspects of user data. To make things simple, SKAdNetwork tries to play the role of business attribution by being a “privacy-first” platform.

The fact that marketers are facing issues such as lack of data, delayed reporting, and ineffective conversion values since the introduction of the platform is known too well.

On the other hand, there is also some good news. The launch of SKAN 4.0 has caused a revolution in the industry. No matter if you spend a fortune on ads every day or just a few hundreds on a campaign, it is still important to know about innovations on the platform.

Apptrove is here to help you understand how to navigate through SKAN 4.0 easily. Cut through the technical nonsense and give you a clear path forward with SKAN 4.0. No buzzwords, no consultant-speak, just practical knowledge you can actually use. This guide is your first step to stop being frustrated and start getting results again.

What is SKAdNetwork? 

Let’s go back a few steps. Up until 2021, everything in iOS marketing was a piece of cake. We could base our marketing efforts on IDFA (identifier for advertisers), which was an ID of the device and allowed you to see who clicked on a particular ad, who downloaded a particular app, and what happened after that. This made it easy to track results and optimize campaigns. It was a period of golden successes.

But then Apple made a big splash with the introduction of its new App Tracking Transparency policy, meaning that users would have to actively agree to be monitored. And, of course, the majority of users disagreed. As a result, only around 25% of users around the globe agree to be monitored (Statista), and our holy grail of user-level data vanished. Your ad kind of worked; here’s some general information, but we’re not providing any details of who installed.”

At the end of the day, this is what you really gain:

• You find out your campaign led to an install, but you don’t know what impact it had on any one user.
• You are given some conversion data – very cryptic data for activities after install.
• You had experienced delays, and in previous times, you only got one postback for each install (before SKAN 4.0).

While you can imagine that Apple was trying to mess with marketers with SKAdNetwork, that’s not the case. But, in practice, it’s trying to balance between fulfilment and privacy while eliminating the mammoth data breaches that are getting plastered across the news.

The SKAdNetwork guide explains in detail and shares tips on how you can work with rather than against the system that’s here to stay.

The thing is that SKAdNetwork is Apple’s new iOS attribution tool. As new updates come (for instance, SKAN 4.0), its use is becoming less complicated and painful. But why should you give a flip about it? No longer an option – learning how this system works is the only way to measure the efficiency and profitability of iOS campaigns.

What’s New in SKAN 4.0?

SKAN 4.0 is Apple’s attempt at striking a balance between user privacy and effectiveness in performance marketing. The update no longer just cements the flow of data — it provides sufficient data for marketers to ensure user privacy.

It’s like having a less foggy view of the world – it could still be “foggy,” but it is good enough to make a decision.

It’s evident that the world is paying attention, and the following numbers show that 30% of the ad traffic on iOS is already supported by SKAN 4.0.

Let’s take a look at the changes that SKAN 4.0 has brought about:

Multiple Postbacks (Instead of Just One)

Previously, with SKAN 4.0, only one postback was available per install, and there was a delay associated with the time of arrival of the postback (which could be anytime between 24 to 48 hours), comprising a single conversion value and hence had to squeeze the performance into a small, narrow 6-bit signal.

It has three parts to its postback that would take some time to arrive – with the rollout of SKAN 4.0.

– Postback 1 received between 0-2 days after install.

– Postback 2 which would arrive 3-7 days after the first postback.

– Postback 3, which would arrive in 8-35 days’ time.

The postbacks allow these marketers to get information about the user’s action during this period so they can perform some predictive modelling, taking into account Day 1 engagement, Day 7 retention, etc.

4-Digit Source Identifier 

The original 2-digit campaign ID has been given a makeover with SKAN 4.0, changing it to a 4-digit source identifier. That means you can track geo, platform, ad set and creative individually without having to track them all separately.

This leads to:

• More detailed information on the A/B test results.
• Better creative-level insights
• Cleaner cohort mapping

You’ll have to adhere to Apple’s privacy requirements to get all the data, of course, but for marketers who fly by the seat of their pants, it’s a great improvement.

Crowd Anonymity Tiers

Now it’s time for the philosophical discussion at Apple. The new “crowd anonymity” tiers in SKAN 4.0. Simply put: the more traffic you generate, the more data you can obtain back. Fewer installs? Less insight.

There are four levels:

• Not enough installs = Tier 0 – No Data
• Tier 1 – Some installs = basic postback (coarse data)
• Tier 2 – Moderate installs = medium detail
• Tier 3 – High volume = full postback, source ID and detailed conversions

The takeaway? Scale thoughtfully. Apple pays attention to volume.

The Lock Window

Prior to this update, it was necessary to wait for Apple’s timer before receiving a postback. SKAN 4.0 adds a new tool: the lock window.

If you know that a user would buy your product 6 hours after installing your app, you will not have to wait 48 hours to get it. Locking in the conversion value early and receiving a postback sooner.

This will help your learning cycles along, particularly useful if your app generates a lot of activity during Day 0.

How SKAdNetwork Attribution Works Now

Whereas SKAdNetwork 3.0 was a bit of a wild goose chase, SKAN 4.0 provides some structure to attribution. Remain privacy-oriented, but not as cumbersome as it used to be once you know the new rules. Let’s dissect the way that attribution works in SKAN 4.0, from ad impression to postbacks. 

Ad Click or Impression is Logged

When a mobile advertiser clicks (or views) an ad, such as on Safari or an app, or in Apple News, the ad network records the event and records a Source Identifier (your 4 digit campaign code).

This code is handed over to Apple as part of SKAdNetwork registration.

App is Installed and Opened

If the user installs the app but doesn’t open it within 30 days, Apple assumes it’s a conversion.If the person installs the app within 30 days and opens the app, it is assumed to be a valid conversion.

Once SKAN opens the conversion window, it allows the app to change the conversion value, depending on user behavior.

Conversion Values are Updated (or Locked)

This is where you set what to measure: In-app purchases, onboarding events, ad views, whatever is important for your growth loop.

• In SKAN 4.0 you have 6 bits (up to 63 values) to encode this in the fine-grained system.
• Alternatively, 3 coarse values (low/medium/high) if your campaign falls into a lower crowd anonymity level.
• If a valuable action occurs quickly, you can now use a lock window to finalize this action early.

Postback(s) Sent by Apple

Instead of one generic postback, SKAN 4.0 offers up to three, spaced out over time:

• Postback 1 (0–2 days): Includes conversion value (if crowd anonymity tier is high enough).
• Postback 2 (3–7 days): Includes coarse or no value, depending on volume.
• Postback 3 (8–35 days): Often delayed and anonymized, but helpful for long-term LTV signals.

Postback(s) Sent by Apple

Unlike one generic postback, SKAN 4.0 provides up to three different postbacks over time:

• Postback 1 (0-2 days): Contains conversion value (when the crowd anonymity tier is sufficiently high).
• Postback 2 (3–7 days): Includes coarse or no value, depending on volume.
• Postback 3 (8-35 days): Delays but anonymous and useful for LTV signals in the longer term.

Each postback includes:

• Not the actual time but a time stamp bucket.
• The source identifier (only in tier 3).
• If your campaign is successful in meeting privacy requirements, conversion value.

Yes, there is still some obfuscation and some randomisation, but it’s much more organised than it was.

Why This Matters

• New models are available to build to compare Day 0 against Day 7 behavior.
• Multi-day funnels such as subscriptions or trials can be tracked.
• It is okay to optimize for high-volume campaigns and not necessarily short-term ROAS.

SKAN 4.0 doesn’t have to be Apple’s rules, Apple’s game, anymore, but it’s finally a scoreboard.

How to Strategize Campaigns for SKAN 4.0 

In this session, participants will learn how to strategize campaigns for SKAN 4.0. SKAN 4.0 is not merely a software update, it’s a strategic change. The old playbooks, which are based on IDFA, are no longer valid. SKAN attribution is not something to work around; it’s something to work with. 

So let’s explore what you should do, not do and what you should try when creating campaigns under Apple’s new privacy regulations. 

Focus on Volume to Unlock Better Insights

According to SKAdNetwork 4.0 the attribution data that you may receive depends on Apple’s crowd anonymity parameters. These parameters define the precision of your conversion metrics and source identification in your postbacks.

What’s the difference between campaigns with high and low volumes?

• Higher installation rates: Campaigns with high volume of conversions usually meet higher crowd anonymity requirements for accurate attribution information.
• Better information quality: Depending on the anonymity level of your campaign, your postbacks may provide either detailed or vague conversion and source data.
• Limited possibility to collect accurate knowledge of low-volume campaigns: If a campaign has a low total number of conversions, the information that you get may not be precise enough (some of the metrics may be unknown).

Do: Combine campaigns when appropriate in order to get enough conversions.

Don’t: Create too many small ad units without a clear purpose of testing your ad campaign.

The objective is to find a middle ground between effective experimentation and a sufficient level of conversions.

Rethink Conversion Value Mapping

SKAN 4.0 provides a limited but useful framework for measuring post-install activity. Fine conversion values offer 64 possible values (0–63), while coarse conversion values provide three categories: low, medium, and high. The challenge is to make every available signal count.

Best practices for conversion value mapping:

• Build a conversion ladder: Map meaningful user actions, such as registration, product exploration, and first purchase, to your conversion value strategy.
• Prioritize valuable early signals: Focus on actions that indicate user intent and help distinguish promising users from less engaged ones.
• Plan for privacy thresholds: Design your mapping strategy to account for situations where only coarse conversion values are available.
• Use the lock window strategically: If your measurement goals are met early, consider locking a postback window to receive the relevant information sooner. Balance this against the possibility of capturing additional activity later.

Pro tip: Prioritize early-funnel events for Postback 1, which measures activity within the first two days after installation. This helps you capture early engagement signals without overlooking the value of longer-term measurement.

Map Your Funnel to the 3-Postback Timeline

One of the key advantages of SKAN 4.0 is its support for up to three postbacks per eligible installation. These postbacks provide opportunities to measure user activity across different stages of the post-install journey.

Here’s how to align your measurement strategy with the available windows:

• Postback 1 (Days 0–2): Measure onboarding, registration, and early engagement.
• Postback 2 (Days 3–7): Evaluate deeper engagement, product exploration, and trial initiation.
• Postback 3 (Days 8–35): Capture later-stage signals, such as purchases or subscription activity, where supported by your conversion value design.

The later postbacks use coarse conversion values, and their availability and reporting detail depend on Apple’s privacy requirements.

Do: Design conversion value mappings around the different stages of your user journey.

Don’t: Rely exclusively on first-day activity to evaluate campaign quality or predict long-term performance.

A well-planned postback strategy gives you a broader view of user behavior while working within SKAN’s privacy constraints.

Use Source Identifiers Wisely

The launch of SKAN 4.0 brings hierarchical source identifiers to the table. Based on privacy requirements and postback type, these identifiers may consist of two, three, or four digits, which provides advertisers with valuable campaign-level insights.

Best practices for effective construction of source identifiers include:

• Using a proper encoding framework: Assign digits to valuable dimensions, like campaign groups, creative variations, and geographic locations, to create an identifier logically.
• Mapping aggregation: Build your identifiers only around relevant dimensions so meaning will remain the same in every campaign.
• Keeping consistency: Include instructions on how to decipher the identifier to avoid unnecessary transformations while campaigning.
• Maintaining granularity: Make sure you can still use your identifiers for analytics if you will have fewer digits in the identifier.

Utilizing identifiers as elements of your measurement strategy rather than simply labels for campaigns.

Work Within SKAN’s Measurement Limitations

SKAN aims to approach attribution in a manner that does not violate privacy of users, which means marketers should expect that they will receive aggregated results, fewer conversion indicators, and less accurate statistics about consumer behavior. However, constraints imposed by SKAN do not limit the ability to conduct performance measurement.

Here are some approaches to follow in this case:

• Conduct experiments: Conduct geographical or temporal testing in order to verify impact of marketing campaigns using aggregated information from SKAN.
• Analyze conversion flows: Analyze the distribution of conversion data in order to discover general trends in consumers’ behavior across multiple campaigns.
• Use data models with caution: Before building predictive models in your analysis, you should already have some conversion data, so you can combine that data to predict future results (including LTV).

Take uncertainty into account: You should remember that predictions need to be verified.

Your SKAN 4.0 Strategy Checklist

A practical SKAN 4.0 strategy requires more than configuring conversion values. Campaign structure, event prioritization, source identifiers, and ongoing testing all influence the insights you can derive.

Use this checklist to evaluate whether your measurement setup is ready.

Do: Consolidate Campaigns Strategically

• Group campaigns where appropriate to support meaningful conversion volume.
• Prioritize high-performing sources while preserving room for controlled testing.
• Reduce unnecessary fragmentation across campaigns and ad sets.

Don’t: Fragment Your Budget Without a Clear Objective

• Avoid creating numerous low-volume ad sets without a defined testing hypothesis.
• Don’t assume every campaign will receive the same level of attribution detail.
• Evaluate whether small experiments justify the potential trade-off in reporting granularity.

Do: Plan Around the Three-Postback Timeline

Map conversion events to the relevant measurement windows:

• Days 0–2: Onboarding, registration, and early engagement.
• Days 3–7: Deeper engagement, product exploration, and trials.
• Days 8–35: Later-stage conversion signals, such as purchases and subscriptions.

Account for the differences in conversion value granularity and privacy conditions across postbacks.

Do: Design Conversion Values With Intent

• Employ conversion values to accurately assess the importance of behaviors for which detailed values exist.
• Categorize behaviors into low, medium, and high-value conversion categories as a backup assessment system.
• Rank behaviors in order of importance regarding campaign performance.
• Evaluate lock window settings based on the trade-off between prior reports and additional behavior data.

Don’t: Engage in Set and Forget Conversion Mapping

• Reassess your conversion value approach continuously as campaign goals and user behavior change over time.
• Analyze new strategies and compare outcomes against previous approaches.
• Track postback results and reporting degrees of detail.
• Take notes of new approaches so the comparison of results is meaningful.

Do: Ensure A Consistent Source Identifier Framework

• Create an unambiguous system of encoding of groupings and other relevant facets of reporting.
• Ensure that the encoding system is adaptable across campaigns and according to the lengths of the identifiers.
• Keep records so that different specialists can interpret identifiers uniformly.

Future-Proof Your Mobile Measurement Strategy With SKAN 4.0

Adapting SKAN 4.0 is not a one-off technical job. It necessitates a measurement strategy developed in the light of privacy considerations, changing campaign goals, and the signals available at every step of the user journey.

While SKAN 4.0 provides only block-level performance data rather than user-level data, SKAN still lays the groundwork for valuable insights on install attribution as well as post-install behavior. The key is to have realistic expectations, focus on significant conversion signals, and conduct the correct data interpretation.

Use SKAN as a Performance Measurement Approach

Do not stop at just compliance. Spend effort on conversion value planning, experimentation with campaigns, and continuous performance measurement. With a systematic approach, it is easier to understand which signals have significance for you and where your measurement strategy should be enhanced.

Be Ready for Continuous Learning and Improvement

There is no ready-to-use SKAN recipe to follow. The results depend on several factors, including the application category, the amount of campaign activity, the conversion flow, and the measurements. Start with a solid framework and gradually build on top of it through testing and improvement.

Choose a Mobile Measurement Partner That Fits Your Needs

Mobile measurement platforms will assist your organization in deciphering attribution statistics, identifying even the slightest conversion signals, and analyzing campaigns through the lens of Apple’s privacy rules. 

Apptrove is in the business of mobile measurement and attribution processes, which enable marketers to start making better choices based on statistical data. When assessing MMPs and their benefits in the context of SKAN 4.0, investigate their capabilities to set conversions in an individual manner, provide reports on postbacks, and comprehend the peculiarities related to SKAN in comparison to your needs.

Ready to Build a Smarter SKAN 4.0 Strategy?

At Apptrove, we enable mobile marketers to understand the meaning of attribution and transform their findings into smart actions when carrying out their campaigns.

Whether you’re planning your conversion value mapping or evaluating how to measure post-install performance, the right measurement strategy can help you work more effectively within Apple’s privacy framework.

Want to explore how Apptrove can support your mobile measurement needs?

Let’s talk—reach out today.