An MMP, or mobile measurement partner, is a company that helps app marketers measure campaign performance across channels, media sources, and ad networks. It collects and analyzes app data to deliver consistent metrics, and acts as an impartial referee in attributing conversions to the correct media source.

How does an MMP work?

An MMP matches campaign engagements with app installs and post-install in-app actions. It combines device IDs, aggregated data, and probabilistic modeling, using an SDK to associate ad engagements with specific user activities within an app.

What are the benefits of working with an MMP?

Working with an MMP can improve app performance, return on ad spend (ROAS), and lifetime value (LTV) through accurate data, which is consolidated in a single dashboard. It also enables you to allocate budgets effectively, scale marketing efforts across ad networks, and save time and resources.

Any marketer with an app needs an MMP to accurately assess campaign performance across the data-rich mobile marketing channel. This is crucial if you want to optimize LTV and ROAS, without the need for manual analysis across multiple dashboards and spreadsheets.

What challenges do SDKs present in mobile attribution?

SDKs, while essential for mobile attribution, can pose challenges such as delays, costs, and the manual effort involved in integrating new ad networks. MMPs address these challenges by offering a universal SDK that connects to thousands of ad networks efficiently.

How do you choose an MMP?

When selecting an MMP, consider security and privacy, fraud prevention, data accuracy, comprehensive features, and experience. Ensure the MMP is unbiased, has a robust and fraud-free ecosystem, offers granular data and multi-touch attribution, and has a proven track record.

How have recent privacy-driven developments affected MMPs?

Privacy changes, especially on iOS with the App Tracking Transparency (ATT) framework, have made attribution more challenging and forced MMPs to innovate. They’ve adapted with methods like incrementality measurement solutions, predictive modeling, and web-to-app flows, ensuring accurate but privacy-safe measurement.