Mastering Metrics: How AI Improves Marketing Analytics

When it comes to reporting metrics and proving ROI, marketers know it’s a constant struggle. 

As long as data is being measured, there’s always room for improvement.

A new Wunderkind report highlights just how difficult it is for marketers in 2025, with 39% of those surveyed saying their biggest challenge in presenting marketing data is struggling to make it easy to understand and 27% pointing to how difficult it is to prove the revenue contribution from email and text.

That difficulty with performance data, according to the report, suggests “teams may present raw engagement metrics (open rates, click-throughs) rather than tying results to revenue. Without clear storytelling, leadership may undervalue these channels compared to paid media, where spend-to-revenue tracking is more direct.”

(Source: Wunderkind)

In suggesting analytic solutions, the report found the AI features most marketers want include recommendations for optimizing spend (53%), cross-channel segmentation (40%), revenue forecasting (35%), and “automated anomaly detection and alerts” (27%).

“To maximize AI in marketing analytics, brands need solutions that move beyond static reporting into predictive intelligence and automation,” the report says. “By integrating AI-driven recommendations into analytics, marketing teams can reduce manual effort, improve targeting accuracy, and make smarter, data-backed decisions that drive real revenue growth.”

For more information about how to improve your email deliverability, download A Beginner’s Guide to Email Marketing by Mirabel’s Marketing Manager: