Using Adjust Growth Copilot for smart, fast data insights | Adjust

Summary

Adjust Growth Copilot is an AI-powered partner for app marketers, built on Adjust's measurement infrastructure. It addresses the challenge of growing data volumes by providing instant, contextual answers to performance questions via natural language queries. Key capabilities include: (1) assessing campaign performance in seconds with summaries of top campaigns by ROAS and retention, plus alerts for anomalies; (2) identifying unusual data patterns like CPI spikes or conversion drops before they escalate; (3) optimizing channel efficiency by ranking channels by CPI, ROAS, and conversion metrics, with recommendations for budget reallocation; (4) discovering top-performing creatives by region and channel, highlighting effective formats and audience patterns; (5) forecasting ad spend to avoid over- or underspending; and (6) uncovering full-funnel trends with explanations of anomalies and next-step recommendations.

The tool transforms data into confident decisions, allowing marketers to focus on growth rather than manual reporting.

Analyst Note

What's notable here is how Adjust is positioning Growth Copilot not as a standalone AI assistant, but as a direct extension of its measurement infrastructure. This is a clear competitive move: while other MMPs offer AI-powered alerts or automated reporting, Adjust is betting on natural-language querying to lower the barrier for data-driven decisions. For UA teams, the practical impact is reduced dependency on data-science or BI teams for routine analysis—queries like 'which channels had the lowest CPI this week?' become self-service.

The timing aligns with the ongoing privacy-driven complexity in mobile attribution (SKAN, consent frameworks), which has made performance data harder to interpret. An AI layer that contextualizes anomalies or surfaces correlations across the funnel fills a gap left by fragmented, post-IDFA measurement. What's underappreciated is the feedback loop: each query trains the model on a marketer's specific data landscape, potentially creating switching costs.

For ad ops professionals, the broader signal is the commoditization of dashboard exploration. The competitive moat will shift from measurement accuracy alone to how seamlessly AI can translate raw data into actionable narratives—and Adjust is explicitly targeting that shift.