Customer Lifetime Value App Survival Analysis

Client

A US-based media conglomerate with interests primarily in cinema and cable television.

Opportunity

The client had a pressing need to minimize the churn rate of customers on the app and identify pain points in the funnel conversion analysis. It aimed at releasing the right content at the right time, while considering customer behavior attributes and video engagement metrics. The client was also facing issues with manual intervention in the data capture process.

Solution

Using its experience and deep understanding, SGA implemented a three-step approach for the above problem:

• The SGA team collected clickstream data to understand user behavior and performed basic EDAs to gauge the app’s performance.
• The SGA team employed the Kaplan–Meier estimator to provide descriptive statistics and study the effect of different attributes on the survival of the customers. The key predictors used included behavioral attributes such as visits, return frequencies, etc. used in a semi-parametric Cox model in R.
• SGA’s model helped identify how the effect of different predictors combined together affects the survival of different customers. Based on the effect of these predictors, the SGA team was able to predict the lifespan of anew/existing active customers.