When Apple dropped iOS 14.5, it felt like the sky was falling. Marketers scrambled, platforms crashed, and everyone predicted the end of mobile advertising as we knew it. Three years later, we're still here—battle-scarred but wiser.
Now iOS 17 brings another wave of privacy changes. But this time, we're prepared. Here's your comprehensive guide to what's changing, what it means, and how to adapt.
Key Deadline Alert
Privacy Manifests are required for all App Store submissions as of Spring 2024. Apps using certain APIs without proper declarations will be rejected. Review your SDKs now.
The iOS 17 Privacy Timeline
September 2023: iOS 17 Release
Link Tracking Protection enabled in Safari, Mail, and Messages by default.
Fall 2023: SKAN 5 Preview
Apple announces SKAdNetwork 5.0 with reengagement attribution and improved conversion windows.
Spring 2024: Privacy Manifest Requirement
All apps must declare tracking domains and API usage reasons.
2024-2025: SKAN 5 Adoption
Ad networks gradually adopt SKAN 5 features for improved attribution.
Link Tracking Protection (LTP)
This is the change most marketers are worried about, and for good reason. LTP automatically strips tracking parameters from URLs in Safari, Mail, and Messages.
What Gets Stripped?
- Click IDs: gclid (Google), fbclid (Meta), msclkid (Microsoft)
- UTM Parameters: Sometimes stripped, sometimes preserved (inconsistent)
- Custom Parameters: Any parameter Apple's algorithm identifies as tracking
What This Means for Attribution
Click-based attribution becomes less reliable for Safari users (60%+ of mobile web in US). This primarily affects:
- Web-to-app flows
- Email marketing attribution
- SMS marketing campaigns
- Influencer link tracking
Workaround: First-Party Redirects
Tracking parameters sent through your own domain (e.g., yourapp.com/go?campaign=xyz) are less likely to be stripped than third-party parameters. Consider building a first-party redirect system.
Privacy Manifests: The Technical Deep Dive
Privacy Manifests are Apple's new disclosure system. Every app (and SDK) must declare what data it collects and why.
What You Must Declare
- Privacy Nutrition Labels: Categories of data collected
- Tracking Domains: All domains used for cross-app tracking
- Required Reason APIs: Justify use of sensitive APIs
Required Reason APIs
These APIs now require explicit justification in your Privacy Manifest:
- UserDefaults: Must explain why you're storing data
- File Timestamp APIs: Used to fingerprint devices
- System Boot Time: Another fingerprinting vector
- Disk Space APIs: Can create device fingerprints
- Active Keyboard APIs: Keyboard layout fingerprinting
Action Items for Marketers
- Audit all SDKs in your app for Privacy Manifest compliance
- Request updated SDKs from vendors (many are still catching up)
- Work with engineering to declare legitimate API uses
- Test submission with new requirements before deadline
SDK Vendor Checklist
Contact these vendors to confirm Privacy Manifest compliance: your MMP (AppsFlyer, Adjust, etc.), ad networks (Meta, Google, TikTok), analytics (Firebase, Amplitude), crash reporting (Crashlytics), and any third-party SDKs.
SKAdNetwork 5.0: Better Attribution at Last?
SKAN 5 represents Apple's most significant improvements to their attribution framework since launch.
Key Improvements
- Reengagement Attribution: Finally, SKAN can attribute re-engaged users, not just new installs
- Multiple Conversion Windows: Configure different windows for different conversion values
- Source Identifier Improvements: More bits for campaign identification
- Finer Crowd Anonymity: Better conversion value resolution at lower volumes
Reengagement: The Game Changer
Before SKAN 5, you couldn't attribute users who reinstalled or re-engaged after lapsing. This made retargeting attribution nearly impossible on iOS. SKAN 5 introduces a redownload flag and separate attribution for returning users.
Implementation Considerations
SKAN 5 requires updates from:
- Your MMP (measurement partner)
- Ad networks running your campaigns
- Your app's SKAN implementation
All three must support SKAN 5 for the new features to work. Adoption is gradual—expect full ecosystem support by mid-2025.
Practical Strategies for iOS 17 Success
1. Embrace Probabilistic + Deterministic
Use SKAN for deterministic iOS attribution, but complement with probabilistic modeling for a fuller picture. MMPs like AppsFlyer and Adjust offer probabilistic modeling that, while less precise, helps fill attribution gaps.
2. Invest in First-Party Data
Every piece of first-party data becomes more valuable as third-party tracking erodes:
- Encourage account creation early in user journey
- Collect email/phone with clear value exchange
- Build customer data platform capabilities
- Use owned channels (email, push) for attribution-friendly engagement
3. Master SKAN Conversion Values
Your conversion value strategy determines what you can learn from SKAN. Prioritize:
- Revenue events over engagement events
- Early signals that predict LTV
- Conversion values that inform bidding
4. Build for Privacy-First Creative Testing
With less user-level data, creative iteration becomes critical. Test more, faster:
- Launch 3-5x more creative variants
- Use platform-side A/B testing (Meta DCO, Google App Campaigns)
- Trust aggregate creative performance data
The Bigger Picture
iOS 17 is not an endpoint—it's another step in Apple's privacy journey. The trend is clear: less tracking, more privacy, increasing reliance on aggregate data and first-party relationships.
The marketers who thrive won't be those fighting these changes, but those who adapt fastest. Every privacy restriction is also an opportunity to differentiate through better creative, stronger brands, and genuine user value.
iOS 14.5 survivors already know this. We rebuilt our attribution models, redesigned our campaign structures, and learned to live with uncertainty. iOS 17 is just the next chapter in that story.
Stay Ahead of Privacy Changes
ClicksFlyer continuously updates our attribution models and SKAN integration to reflect the latest iOS capabilities. Our platform helps you make sense of fragmented data across SKAN, MMPs, and first-party sources.