Case study

Survival Analysis for Customer Lifetime Value

Survival analysis

Client

An American media conglomerate with primary interests in cinema and cable television.

Business Situation

  • Minimize churn rate of customers on the app.
  • Identify pain points in the funnel conversion analysis.
  • Consider customer behavior attributes and video engagement metrics.
  • Automate data capture to minimize manual efforts.
  • The app had grown to acquire ~2m subscribers.
  • Release the right content at the right time in a personalized manner to reduce churn and ensure subscription renewal.

Solution

  • SGA built a model for identifying the drivers of survival of customers on the app and survival analysis models to understand the impact of various on survival and to predict customer lifetime.
  • SGA calculated the hazard probabilities and survival curves for segments of the customer base and how they can be used to extract valuable key performance indicators and to fine-tune the timing of campaigns.
  • SGA conducted machine learning analysis of user engagement for the first seven days post-install and accurately predicted the likelihood of users to churn (abandon the app) within the next 30 days.
  • SGA segmented the users with high and mediumhigh churn-likelihood scores into a dynamic audience and targeted them with a special offer via a push message campaign.
  • The marketing team composed several different message segments and used automated A/B/n testing to prioritize the highest performing segments.

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