Reduce Churn via Predictive Analytics on your Kentico EMS Site
Wednesday, September 21, 2016 10:00 AM
About the Presentation:
Many marketers assume that the number of users with last login date older than 30 days predicts the amount of people who are about to leave your site. Often times this metric is referred to as churn. What if we could predict churn, and do something about it before those users abandon the product or service your site is selling? view the recording to see how you can view Kentico EMS activity and behavior data to predict and stop churn.
About Brian McKeiver:
Brian has been working with the web for over 15 years doing both web development and general programming. He is extremely excited about software platforms and technologies that can help solve real world problems. Brian is a Solution Architect / Co-Owner of BizStream, located in Michigan. Brian has been working with the Kentico CMS since version 3.1A almost 7 years ago, and back in early 2012 was honored as a Kentico MVP.