Reducing passive churn, identifying readers at risk of churning, and modeling propensity to churn are the focuses of this module featuring case studies from Telegraph Media Group, Business Insider, and Deep.BI. The module looks at predicting churn before readers even think of leaving, fixing passive churn so you never lose a reader by accident, and handling breakups gracefully but smartly.
YOU MUST BE A MEMBER TO ACCESS THIS CONTENT
INMA members have unparalleled access to ideas and peer connections that make a difference in the success of their companies and their careers.
Click Here to Become a Member NowAlready a Member? Log In
Total access to all INMA reports on just-in-time topics, trends, and case studies
The most powerful tool in media: global peer connections at the leading companies
Daily news industry headlines personally curated by INMA, inclusive of archives
Thousands of best practices and case studies to grow audience, revenue, and brand
Learn what fellow INMA members are prioritising: most-read, social shares, searches
Thousands of INMA conference presentations for ideation and benchmarking
Bring INMA to your computer or phone with exclusive case study-based Webinars
Subscribe to 20+ newsletters by latest content, topic, or world region
Members enjoy up to 50% registration discounts on INMA conferences worldwide
