Developing data-driven user engagement metrics for contents(functions) in Updatable home appliances

Developing a new metric for measuring customer satisfaction based on user activity data

2023.06 – 2024.05
LG ElectronicsSystem Monitoring & Anomaly Detection
Customer RetentionUser SatisfactionSurvival AnalysisData-Driven Metrics

Motivation

In non-contractual settings, it is difficult to measure customer satisfaction as real churn is not directly observable. Furthermore, many existing metrics fail to accurately capture true user satisfaction.

Methodology

Utilizing survival analysis techniques (e.g., the Kaplan-Meier estimator) to measure customer retention.

Contribution

Developed a novel metric that accurately measures customer retention in a non-contractual environment.

Applying clustering methods for customer segmentation and using the developed metric to obtain different insights into retention probability.