Customer Churn

Customer churn, the loss of customers to a business, is a significant problem across various industries, motivating research into accurate prediction and effective retention strategies. Current research focuses on developing sophisticated predictive models, employing techniques like ensemble learning, deep neural networks (including recurrent and feedforward architectures), and causal inference methods to analyze churn drivers and improve prediction accuracy. These advancements aim to optimize resource allocation for customer retention efforts, ultimately impacting profitability and business sustainability. The integration of causal analysis is a growing trend, enabling a deeper understanding of the underlying factors contributing to churn and informing more targeted interventions.

Papers

October 21, 2024

Explainability of Highly Associated Fuzzy Churn Patterns in Binary Classification
D.Y.C. Wang, Lars Arne Jordanger, Jerry Chun-Wei Lin
Machine Learning Model Classification Code High Explainability Binary Code Churn Prediction Bug Pattern Customer Churn

September 7, 2024

Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn
Hongyao Tang, Glen Berseth
Reinforcement Learning Proximal Policy Optimization Learning Dynamic Net Present Value Policy Iteration Churn Prediction Customer Churn

August 29, 2024

Enhancing Customer Churn Prediction in Telecommunications: An Adaptive Ensemble Learning Approach
Mohammed Affan Shaikhsurab, Pramod Magadum
Churn Prediction Telecom Domain Adaptive Ensemble Customer Churn

May 18, 2024

Causal Customer Churn Analysis with Low-rank Tensor Block Hazard Model
Chenyin Gao, Zhiming Zhang, Shu Yang
Causal Model Causal Approach Block Model Churn Prediction Customer Churn

September 25, 2023

Early Churn Prediction from Large Scale User-Product Interaction Time Series
Shamik Bhattacharjee, Utkarsh Thukral, Nilesh Patil
Churn Prediction Customer Churn

August 24, 2023

A Greedy Approach for Offering to Telecom Subscribers
Piyush Kanti Bhunre, Tanmay Sen, Arijit Sarkar
Timely Communication Greedy Approach Churn Prediction Heterogeneous User Telecom Domain Customer Retention Customer Churn

April 23, 2023

Improved Churn Causal Analysis Through Restrained High-Dimensional Feature Space Effects in Financial Institutions
David Hason Rudd, Huan Huo, Guandong Xu
Causal Analysis High Dimensional Feature Churn Prediction Customer Churn

April 20, 2023

Causal Analysis of Customer Churn Using Deep Learning
David Hason Rudd, Huan Huo, Guandong Xu
Deep Learning Causal Analysis Churn Prediction Customer Retention Customer Churn

April 2, 2023

Modelling customer churn for the retail industry in a deep learning based sequential framework
Juan Pablo Equihua, Henrik Nordmark, Maged Ali, Berthold Lausen
Deep Learning Recurrent Neural Network Sequential Model Deep Survival Model Retail Store Customer Behavior Customer Churn

March 2, 2023

Customer Churn Prediction Model using Explainable Machine Learning
Jitendra Maan, Harsh Maan
Explainable Machine Learning XGBoost Model Churn Prediction Customer Churn

January 30, 2023

Prediction of Customer Churn in Banking Industry
Sina Esmaeilpour Charandabi
Human Prediction Random Forest Customer Retention Neural Network Structure Supervised Learning Method Customer Churn

September 6, 2022

Combining Sequential and Aggregated Data for Churn Prediction in Casual Freemium Games
Jeppe Theiss Kristensen, Paolo Burelli
Neural Network Architecture Sequential Information Aggregated Data Churn Prediction Customer Churn

June 1, 2022

The Phenomenon of Policy Churn
Tom Schaul, André Barreto, John Quan, Georg Ostrovski
Rare Event Greedy SLIM Value Based Reinforcement Learning Customer Churn Greedy Policy Implicit Exploration