Navigating the Marketing Impact of iOS 26 Release

When New OS Updates Say Jump...

It’s an accepted fate among digital media buyers that ways of buying media are subject to change based on what device and operating system-owners, notably Google, Amazon, and Apple, deem necessary. Their internal standards and protocols effectively become the de facto regulations for the entire industry when changes occur in hardware, software, or services. The sheer scale of their market penetration requires digital advertisers to adapt to meet new industry standards when updates roll out.

In the case of consumer privacy, Apple has taken an unwavering stance on protecting consumer data. With rapid adaptation to AI advancements, iOS 26 is increasing its sophistication and bringing unparalleled transparency to data management. The new iOS can be considered a significant factor in accelerating consumer awareness of data privacy, unveiling what companies are tracking your data. Ahead of the landmark iOS release, it’s important to test new targeting strategies with consumer privacy regulations incorporated and rely less on traditional targeting methods.

Why Privacy Actually Matters in 2025

When considering the current state of consumer perceptions, it’s clear why privacy is prioritized. For example, a 2023 Deloitte survey highlighted that nearly six in ten consumers worry about their devices being vulnerable to security breaches and are concerned about being tracked. Reinforcing Deloitte’s results, Research from the ANA and Think with Google underscores this trend, revealing that a positive privacy experience can be a significant competitive advantage. A striking finding from their joint study is that a significant percentage of consumers would switch from their first-choice brand to a competitor that offers a better privacy experience.

iOS Privacy Milestones

September 2018: iOS 12 Intelligent Tracking Prevention 2.0 (ITP 2.0)

The privacy initiative began first on Apple’s web browser, Safari. ITP 2.0’s security protocol blocked cookies for domains identified as having tracking capabilities, unless the user directly consented. Social media "Share" and "Like" buttons, along other embedded content, also required user consent. This was a significant first step that impacted digital advertising, reducing the scale of trackable inventory and increasing competition in-auction for tracked inventory.

 

Source: Apple

April 2021: iOS 14.5 App Tracking Transparency (ATT)

Extending ITP 2.0 to the app ecosystem, App Tracking Transparency (ATT) began requesting user consent for cross-app tracking via their Identifier for Advertisers (IDFA). This led to a significant drop in IDFA’s shared by users, negatively impacting mobile players like Meta and notably causing a public feud between the two tech giants.

Source: Apple

September 2021: iOS 15 Mail Privacy Protection (MPP)

Along with ATT, iOS 15 added Mail Privacy Protection (MPP), which obscured email opens and IPs, making established KPIs like open rates obsolete. Naturally, newsletter campaigns began shifting their focus toward click and conversion performance, as more meaningful engagement or “signs of life”. Subsequent updates, including iOS 17's Link Tracking Protection and iOS 18's granular data controls and on-device AI emphasis further limited cross-site tracking and ensured local data usage.

Source: Apple WWDC

September 2025: iOS 26 Link Tracking Protection, Advanced Fingerprinting Protections, AdAttributionKit (AAK), and more

iOS 26 continues Apple’s leadership on privacy by embedding it deeper into the OS and leveraging on-device AI for intelligent features without compromising user data, once again aligning with global privacy regulations like GDPR (EU), CCPA (California), DSA (EU), and DMA (EU). Additionally, with Apple continuing to build out its own "walled garden" advertising ecosystem, these changes level the playing field against more established competitors. Developer Betas of iOS 26 have already been released for testing, with a public beta expected this month. Below is a summarized table of the expected updates and impacts to a brand’s potential advertising strategies.

Upstream Biddable Advertising Measures

Speaking from a programmatic lens, I believe these changes signal further depreciation of traditional attribution models, increased CPMs due to a shrinking pool of targetable users, and an urgent need to re-evaluate data collection and measurement strategies. To mitigate any drastic changes to performance, Adapting data signals to privacy-compliant methods will mitigate any drastic changes to performance ahead of iOS 26.

Prioritize First-Party Data Collection and Activation

Begin collecting and activating first-party data through owned properties (ex. Customer Lists, Pixel Data). It is privacy-compliant, accurate, relevant, and resistant to platform changes.

Return to Contextual Advertising and Enhance Creative Optimization

With behavioral signals disappearing, brands should invest in AI-driven sentiment targeting for prospecting and dynamic creative optimization (DCO) for additional optimization levers.

Replace IDFA with IDFV Where Possible

IDFV (Identifier for Vendors) is an ID applied to a single device across all of a single developer’s apps. Developers track users across their owned apps, and do not require the same levels of user consent as IDFA. Approach Developers/Publishers to use this data for targeting within their ecosystems.

Implement IDFA-less Targeting

For any broad-targeted strategies, consider approaching monetization SDK partners (ex. Unity, DTX) to send avails where users have opted out of tracking. These users will not be bid on by those with traditional data layered, opening the door for CPM efficient reach.

Incorporate Session Duration Metrics

Similar to the above, approach monetization SDK partners to send deal avails either early in session duration (high attention/recall) or late in session duration (lower CPMs).

Use Privacy-Enhancing Technologies (PETs)

Utilize tools that allow for detailed analysis while minimizing exposure of Personally Identifiable Information (PII). Key examples include:

Server-Side Tracking

Fill gaps in data by sending events directly from the brand's server to the various ad platforms. Can also integrate offline conversions like phone orders and in-store purchases. Google Tag Manager is an easy and effective tool for tag management. Server to Server (S2S) can include Meta CAPI, TikTok Events API, or MMPs like Singular and Kochava.

AdAttributionKit (AAK) for App-Driving Campaigns

Next generation of Apple’s SKAdNetwork (SKAN), gives insight into app marketing performance and allows for re-engagement without compromising user privacy.

Federated Learning and Differential Privacy

Federated Learning trains algorithms on decentralized systems, keeping raw data on separate platforms while sharing insights learned from each to the central model. Incorporate differential privacy to this by adding calculated noise to the data sets to ensure anonymity while maintaining statistical trends.

Data Clean Rooms

Data Clean Rooms are secure, privacy-compliant databases can ingest various data sources to combine and analyze user data. Examples include Google’s Ads Data Hub (ADH) and Amazon’s Marketing Cloud (AMC).

Tokenization

Replaces personal or device information with non-sensitive tokens, allowing for data processing without sensitive information.

Aggregate Measurement and Attribution Models

Current attribution models are going the way of the dinosaur, shifting to shorter windows (ex. 7-day click-only) and statistical solutions such as Mixed Media Modeling (MMM). Analytics will increasingly rely on aggregated data, and brands must revisit customer journey mapping on their site to prioritize key touchpoints for insight.

Foster Trust and Transparency

Building consumer trust through clear communication of ethical data practices, while respecting user choices, is paramount.

Source: dandad.org

Make Moves Upstream, Future-Proof Digital Strategy

iOS 26 is a significant, and arguably predictable, next step in Apple's user privacy evolution. It further erodes legacy 3rd Party data targeting strategies, as well as existing measurement and attribution frameworks. Despite the challenges it will present, the release creates significant opportunities for innovation through first party data usage, emergence of alternative targeting solutions, and adoption of new attribution methodologies among others. With consumers demanding more and more control over the usage of their data, I believe that brands seeking a leg up on their competition must adapt and integrate these tactics into every aspect of their marketing strategy.