Fighting Churn with Data

Churn is a major issue for subscription businesses, but this hands-on guide provides data-driven techniques to maximize customer retention and minimize actions that cause them to stop engaging or unsubscribe. It covers identifying processes suited to machine learning, using machine learning to automate back office processes, and seven everyday business process projects.

Format: Paperback / softback
Length: 504 pages
Publication date: 01 February 2021
Publisher: Manning Publications

Churn is a significant challenge for subscription businesses, including content subscriptions, software as a service, and ad-supported freemium apps. To enhance customer retention, businesses can implement product changes and targeted engagement campaigns based on data-driven interventions. This comprehensive guide offers practical techniques for converting raw data into measurable metrics, testing hypotheses, and presenting findings to non-technical decision-makers. By preventing customers from leaving subscription services and losing their money, Fighting Churn with Data provides valuable insights for maximizing customer retention and minimizing churn.

The guide covers various topics, including identifying processes suitable for machine learning, utilizing machine learning to automate back-office processes, implementing seven everyday business process projects using open-source and cloud-based tools, and presenting case studies for machine learning decision-making. It is designed for readers with basic data analysis skills, including Python and SQL.

By leveraging data-driven techniques, subscription businesses can gain a competitive advantage and improve their overall customer satisfaction and retention rates.

Weight: 914g
Dimension: 187 x 235 x 34 (mm)
ISBN-13: 9781617296529