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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
›
Chapters
5
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
75%
Copyright
25%
Possible Causes
25%
Marketing Strategy
25%
Confounding Factors
25%
Market Share
25%
Mining Method
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%
Causal Variables
25%
Customer Churn Analysis
25%
High-dimensional Sparse Data
25%
Degree of Belief
25%
Deep Feedforward Neural Network
25%
Superannuation Funds
25%
Causal Bayesian Network
25%
Main Business
25%
Customer Acquisition Cost
25%
Customer Tenure
25%
Computer Science
Deep Learning
100%
Causal Analysis
100%
Future Direction
50%
Sequential Pattern Mining
50%
Feedforward Neural Network
50%
Deep Learning Model
50%
Evaluation Metric
50%
Extreme Gradient Boosting
50%
Business Marketing
50%
Bayesian Networks
50%
Social Sciences
Causal Analysis
100%
Incentive
50%
Enterprises
50%
Company
50%
Marketing Strategy
50%
Market Share
50%
Confounding factors
50%
Neural Network
50%
Engineering
Deep Learning
100%
Causal Analysis
100%
Metrics
50%
Test Data
50%
Feedforward
50%
Market Share
50%
Economics, Econometrics and Finance
Causality Analysis
100%
Customer Recovery
100%
Marketing Management
20%
Incentives
20%
Bayesian
20%
Market Share
20%
Customer Engagement
20%
Confounding Factor
20%
Customer Acquisition
20%
Customer Retention
20%
Business-to-Business Marketing
20%