Which machine learning technique revolutionized retail churn prediction by reducing false positives by over 30% when first widely adopted around 2015?

Retail businesses lose billions annually due to customer churn. Modern predictive analytics has transformed how companies identify at-risk customers before they leave. This poll tests your knowledge about a pivotal moment in retail churn prediction technology that changed how businesses approach customer retention. Can you identify the breakthrough that revolutionized how retailers predict which customers might leave their service?

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Random Forest algorithms that could process multiple decision trees simultaneously
Gradient Boosting Machines (GBM) that sequentially improved prediction accuracy
Neural networks with specialized retail-focused architecture
Support Vector Machines optimized for categorical retail data