Building Predictive Analytics to Anticipate and Prevent Churn

Date: May 05, 2015

Author: Barry Duplantis - Hortonworks,
Francoise Tourniaire - FT Works

Hortonworks packages the open source Hadoop software into an enterprise-scaled data platform that allows organizations to collect, store, analyze, and manipulate massive quantities of data. As an open source vendor, it relies on subscription revenue, so insights into churn patterns are very important. We will share how we are using customer experience data to (1) identify the factors that matter for churn, (2) define targets for positive and negative churn, and (3) automatically score large numbers of customers and deliver alerts on actionable accounts. The unique feature of our program is that it delivers predictive analysis (that is, is a customer likely to renew, upsell, or churn?) without a traditional, intensive, one-on-one customer relationship management it is scalable. While the insights come from the open source world, they are applicable to all SaaS organizations, and beyond to on-premise vendors.

Applicable Disciplines:
Service Revenue Generation-Recurring,Support Services,Expand Selling,Customer Success

Business Outcomes, Customer Success, Customer Churn, Customer Retention, Predicting Renewals, Analytics, Predictive Analytics

Functional Areas:
Service Delivery