Are MMPs Evolving into MMMs?

The mobile app industry has long relied on Mobile Measurement Partners (MMPs) to track and attribute user acquisition efforts. These platforms provide deterministic attribution, helping advertisers understand which campaigns drive installs and revenue. However, with increasing privacy regulations, signal loss, and the rise of AI-driven analytics, a new measurement approach is gaining traction: Marketing Mix Modeling (MMM).

As deterministic tracking becomes more challenging, will MMPs evolve into MMM platforms? Let’s explore the future of mobile measurement and the shift from event-level attribution to probabilistic modeling.

The Challenges Facing MMPs

MMPs have traditionally been the source of truth for app marketers, but their dominance is now being challenged by:

1. Privacy-First Changes

• iOS 14.5+ (App Tracking Transparency – ATT): Apple’s privacy framework has drastically reduced the effectiveness of IDFA-based tracking, limiting MMPs’ ability to attribute users accurately.

• Google’s Privacy Sandbox: Google plans to phase out third-party cookies and introduce privacy-friendly attribution methods for Android.

These changes mean that deterministic tracking is no longer reliable, forcing MMPs to adapt.

2. Signal Loss & Data Gaps

With restricted access to user-level data, MMPs now rely on aggregated and modeled data for attribution. The days of tracking every user event with 100% accuracy are gone, and this shift is pushing marketers toward probabilistic measurement.

3. The Shift to Multi-Touch & Incrementality

MMPs have historically focused on last-touch attribution, but as multi-touch and incrementality measurement gain importance, marketers are looking for holistic and channel-agnostic solutions – something that traditional MMPs struggle to provide.

Why MMM is Making a Comeback

Marketing Mix Modeling (MMM) is not a new concept – it has been around for decades, primarily used by large brands with offline marketing channels. However, with the decline of deterministic tracking, MMM is making a comeback in digital marketing, especially for mobile apps.

How MMM Works

MMM uses statistical modeling to analyze historical data and determine the impact of different marketing channels. Unlike MMPs, which rely on user-level tracking, MMM operates at an aggregate level, making it privacy-friendly and adaptable to changing regulations.

Benefits of MMM for Mobile Growth

✅ Privacy-First: Doesn’t rely on user-level data or device identifiers.

✅ Cross-Channel Analysis: Measures the impact of paid, organic, and offline channels together.

✅ Incrementality Testing: Helps marketers understand the true causal impact of each marketing effort.

✅ Long-Term Strategy: Provides a broader view of brand vs. performance marketing impact.

Are MMPs Becoming MMMs?

Leading MMPs like Adjust, AppsFlyer, and Singular have already started integrating MMM capabilities into their platforms. While they were originally built for deterministic attribution, they now offer:

• Predictive modeling & data science solutions

• Privacy-centric attribution using aggregated data

• Multi-touch and incrementality measurement tools

This shift suggests that MMPs are not disappearing but evolving into MMM-first platforms.

The Future of Measurement: Hybrid Approaches

The most effective approach for mobile marketers will likely be a hybrid measurement model that combines:

• MMM for high-level budget allocation and trend analysis

• MMP-based probabilistic attribution for campaign performance insights

• Incrementality testing for measuring real impact

Companies that embrace AI-driven MMM while leveraging MMPs for tactical decision-making will gain a competitive edge in the new era of mobile marketing.

Conclusion

The mobile measurement landscape is undergoing a fundamental transformation. As privacy regulations limit traditional attribution, MMPs are evolving into MMM-powered platforms to stay relevant. Marketers who adopt hybrid measurement strategies will be best positioned for long-term success.