Case Study: Global improves song performance insights with Peak

Global - Customer Case Study

Global, Europe’s largest radio company, wanted a clearer understanding of how songs and advertisements affected listener behavior across its major commercial stations. The company needed to predict when certain tracks would cause listener drop-off and use that insight to improve personalization, station retention, and the overall listener experience. Global worked with Peak and its AI platform to connect creativity from DJs and programmers with data-driven analysis.

Peak used its Customer Intelligence applications and machine learning models to analyze song performance, including when listeners were switching off and how time of day or day of week affected those trends. The solution helped Global map song performance over time, identify optimal play counts on a song-by-song basis, and rank songs by predictive bounce and disconnect performance, giving the team new metrics to inform programming decisions and improve the listening experience.

Global

Mark Crawford

Head of Brand and Audience Insight