Why media mix modeling is becoming essential for predictive ROAS measurement

Gary Danks, GM, AIM by Kochava

For years, app marketers have leaned heavily on last-touch attribution as the foundation of their measurement strategy. It’s fast, familiar and baked into most performance workflows. But as privacy regulations expand, identifiers disappear and user journeys grow more nonlinear, last-touch attribution’s blind spots are becoming impossible to ignore.

The challenge isn’t that last-touch attribution is wrong; it’s that it’s incomplete. And incomplete measurement inevitably leads to incomplete investment decisions. That doesn’t mean that today’s most effective marketers are abandoning last-touch attribution; they’re pairing it with next-generation media mix modeling to create a more comprehensive, privacy-safe and predictive approach for measuring return on ad spend. MMM doesn’t replace the tactical value of last-touch attribution. It fills in the gaps by capturing the full-funnel impact that the latter routinely overlooks. As mobile marketing accelerates into a privacy-centric future, this combined approach is quickly becoming the new baseline for comprehensively measuring media effectiveness.

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