Meta reactivates Advanced Mobile Measurement: what does it mean for your UA campaigns?

On June 17, 2025, Meta announced the reactivation of its Advanced Mobile Measurement (AMM) program, once again giving advertisers access to device-level (non-aggregated) data through major MMPs (AppsFlyer, Singular, Adjust…). This marks a key shift in mobile measurement after several years of restrictions tied to privacy regulations.

While the announcement may sound significant, its real impact depends on your ability to make use of that data. Addict Mobile breaks down what AMM enables today and what it truly changes in your acquisition strategy.

What Advanced Mobile Measurement enables

To activate Advanced Mobile Measurement, the app administrator simply needs to accept the program’s terms in Meta Business Suite, for each relevant app. Once this is done, data starts flowing automatically through the MMP.

The reactivated AMM offers more granular visibility into Meta attributions across both iOS and Android. Specifically:

• You gain access to device-level attribution data.
• This includes: campaign, ad set, creative, device ID, click timestamp, impression timestamp, install timestamp… The data is no longer aggregated and is available as user-level logs.
• It’s accessible via your MMP, through raw data exports, APIs, or custom dashboards.
• Usage is strictly limited to measurement: no targeting, no retargeting, no custom audience creation.

Note: This is not a new attribution method. Advanced Mobile Measurement simply provides more detailed access to the attributions Meta already calculates through its own systems.

What it changes (or doesn’t) in campaign management

Advanced Mobile Measurement doesn’t alter how your campaigns run or how you manage them in Ads Manager. However, it can significantly enhance your analysis, provided you have the right tools in place.

What you can get out of it:

• A clearer view of performance by OS, geo, device type, or creative.
• Faster creative and targeting optimization thanks to more granular cohort analysis.
• A solid foundation for more accurate LTV modeling based on complete user journeys.
• Richer datasets to feed your internal models (ROAS, retention, etc.).
• A more consistent view across SANs, especially if you already use device-level data on platforms like Google Ads.

What it doesn’t change:

• Campaign optimization is still driven by Meta’s internal signals.
• No new signals are fed into the bidding or learning algorithms.
• Activating AMM won’t “automatically” improve your performance.

In short, AMM strengthens the strategic and analytical side of mobile measurement but doesn’t directly impact your short-term UA operations.

Meta, SKAN, and SANs: a strategic repositioning

The return of AMM comes in the broader context of ongoing tension between proprietary frameworks (Meta, Google) and imposed standards like SKAdNetwork and AdAttributionKit (AAK). By re-enabling device-level data, Meta is sending a clear message: it intends to maintain, and even reinforce, independence from Apple’s attribution ecosystem.

For many, this move could further slow down AAK adoption. If Meta isn’t fully committed, other platforms are unlikely to follow. This reinforces the position of Self-Attributing Networks (SANs), where each major player defines its own rules for attribution and reporting.

Bottom line: we’re moving further away from a unified ecosystem, and multi-channel analysis now relies more than ever on strong MMP integration and a solid understanding of each platform’s specific logic.

Our perspective at Addict Mobile

At Addict Mobile, we already activate Advanced Mobile Measurement where relevant to enrich our analysis, particularly for high-value verticals like gaming, subscription-based apps, or e-commerce apps.

That said, we remain realistic: AMM is a strategic lever, not a magic switch. It requires analytical maturity and sufficient volume to generate meaningful insights. Its potential is real, but only if you have the right tools to process the signals, cross them with other data sources, and turn them into actionable decisions.

Key takeaways

• The return of AMM gives access to more detailed attribution data from Meta.
• It’s not a real-time optimization tool, but an analytical lever for performance and strategy teams.
• Meta is clearly moving away from Apple standards like SKAN or AAK, reinforcing its own measurement ecosystem.
• To fully benefit from AMM, you need structure: BI tools, analytical capabilities, and a data-driven mindset.

For advertisers ready to go further, Advanced Mobile Measurement is a real opportunity: it enables deeper performance analysis, more informed iteration, and stronger long-term measurement. For others, it remains a useful, but secondary, layer of insight.