Next generation measurement for every marketer | Adjust

Summary

The article outlines the transformation of mobile measurement from traditional attribution to next-generation analytics powered by AI and machine learning. Three core methodologies are highlighted: predictive analytics, which uses ML to forecast user value (e.g., day 14 revenue) within 24 hours, enabling early targeting and improved ROI; incrementality analysis, which isolates the causal impact of marketing actions to avoid wasted spend and optimize mid-term planning; and marketing mix modeling (MMM), a statistical technique for long-term budget allocation by analyzing online/offline channels, seasonality, and external factors. Key data points include a quote from Natalia Chirkova (Axlebolt) noting improved iOS purchase volume via early revenue prediction, and testimonials from Otto and Sleep Cycle emphasizing reduced reliance on data science teams and efficient handling of iOS data challenges post-iOS 14.5.

Actionable takeaways: marketers should adopt predictive analytics for real-time user valuation, use incrementality to validate campaign effectiveness, and apply MMM for holistic spend optimization. The article stresses that these tools are accessible to all marketers, enabling faster, independent, data-based decisions in a privacy-constrained landscape.