Case Study: The New York Post triples campaign conversions with mParticle's Cortex ML

Key results

The challenge

The New York Post reaches a large anonymous and known digital audience and wanted to better predict which readers would subscribe to its Sports+ premium membership. Rule-based, metered segmentation limited the accuracy of its targeting.

The solution

The Post deployed mParticle's Cortex machine-learning engine to score subscription likelihood from real-time behavioral signals rather than static rules, powering the Sports+ premium membership flyout campaign.

The results, in context

The machine-learning approach delivered a 3x increase in campaign conversions versus the metered approach, and using real-time data instead of batch data drove a 40% increase in Sports+ campaign conversions. The Post also reported a 7% increase in accuracy and a 46% increase in audience size.

Products used