Case Study: a large U.S. publisher improves subscriber targeting with Mather Economics

Large U.S Publisher - Customer Case Study

Mather Economics worked with a large U.S. publisher that wanted a better understanding of its subscriber base in order to develop more effective marketing strategies. The publisher needed a way to segment subscribers based on their behaviors and interests, including factors like tenure and digital engagement.

Mather Economics built data transfer protocols to access and combine subscriber data, then used hierarchical clustering, iterative k-means clustering, and principal components analysis to create actionable audience segments. Mather Economics helped implement these segments directly into the publisher’s marketing databases, enabling more targeted campaigns, lower communication costs, and better tailoring of offers such as upsells or retirement-related content.