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Causal analysis of customer churn using deep learning
David Hason RUDD
, Huan HUO
,
Guandong XU
Offices of the President (P)
Research output
:
Chapter in Book/Report/Conference proceeding
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Chapters
8
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Citations (Scopus)
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Dive into the research topics of 'Causal analysis of customer churn using deep learning'. Together they form a unique fingerprint.
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Keyphrases
Deep Learning
100%
Causal Analysis
100%
Customer Churn
100%
Churn
50%
Copyright
25%
Possible Causes
25%
Marketing Strategy
25%
Confounding Factors
25%
Market Share
25%
Sequential Pattern Mining
25%
Business Marketing
25%
Deep Learning Model
25%
Evaluation Metrics
25%
XGBoost
25%
Customer Retention
25%
Customer Engagement
25%
Churn Model
25%
Customer Churn Analysis
25%
High-dimensional Sparse Data
25%
Degree of Belief
25%
Deep Feedforward Neural Network
25%
Superannuation Funds
25%
Main Business
25%
Customer Acquisition Cost
25%
Customer Tenure
25%
Mining Operations
25%
Churn Risk
25%
Causal Variable
25%
Existing Customers
25%
Causal Bayesian Networks
25%
Economics, Econometrics and Finance
Causality Analysis
100%
Customer Recovery
100%
Deep Learning Method
100%
Customer
80%
Marketing Management
20%
Bayesian
20%
Market Share
20%
Customer Engagement
20%
Confounding Factor
20%
Customer Acquisition
20%
Customer Retention
20%
Business-to-Business Marketing
20%
Xgboost
20%
Social Sciences
Causal Analysis
100%
Deep Learning Method
100%
Customer
100%
Marketing Strategy
9%
Market Share
9%
Confounding factors
9%
Neural Network
9%
Probability Theory
9%
Xgboost
9%
Bayesian
9%
Business Marketing
9%
Customer Engagement
9%