To grow new subscribers using predictive analytics to improve conversion rates and lower costs per new start.
Mather completed a predictive model analyzing conversion probability for registered non-paid users. Those customers that were estimated to have a high propensity to subscribe were sent targeted offers via email.
Our modeling was found to identify users who are more likely to pay for content, and it discovered factors that lead to conversion. We found that an acceleration in a user consumption of page views and unique days on site are leading indicators to conversion. The model’s data-driven approach helped grow conversions 3X more than a mass-marketing campaign via the email channel. We are now working to expand the model to apply to anonymous visitors on site through the paywall.