Popular article Social network analysis examples for customer churn prediction

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Predictive Analytics World Conference London - Full
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Predictive Analytics World Conference London - Full

Date Mar 4, 2018

he single most important business application of social network analysis and mining. Predictive modeling can be used for targeted marketing and advertising (see Provost et al. [2009]), churn prediction, and several others. . Advanced Network Analysis for Detecting Groups of Fraud The Belgian Social Security Institution is a federal agency that registers and monitors every active company in Belgium, and is responsible for the collection of employer and …

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Churn Prediction - KNIME
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Churn Prediction - KNIME

Date Mar 2, 2018

€˘Churn is the term used to describe customer attrition or loss • Churn rate is the number of participants who discontinue their use of a service divided by the average number of total participants during a period. lassification and regression analysis. Given a set of training examples, each marked as belonging to one or the other of neural network on the telecommunication dataset of customer segmentation and misclassification cost for churn prediction. Customer segmentation is a way to distinct the

Social Network Analytics for Churn Prediction in Telco
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Social Network Analytics for Churn Prediction in Telco

Date Mar 5, 2018

We propose a strategy to protect customers’ privacy for churn prediction. The customer’s data are preprocessed using data distortion algorithms, and then churn prediction methods are 2006), social network analysis (Dasgupta, Singh, …. We have implemented a recurrent neural network for customer churn prediction and found it to make significantly better predictions then a logistic regression baseline. It is built on a flexible event emitter/aggregator framework that allows a wide variety of features to be included in the model and added over time.

US8843431B2 - Social network analysis for churn prediction
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US8843431B2 - Social network analysis for churn prediction

Date Mar 4, 2018

This study examines the use of social network information for customer churn prediction. An alternative modeling approach using relational learning algorithms is developed to incorporate social network effects within a customer churn prediction setting, in order to handle large scale networks, a time dependent class label, and a skewed class …. Churn rate (sometimes called attrition rate), in its broadest sense, is a measure of the number of individuals or items moving out of a collective group over a specific period. It is one of two primary factors that determine the steady-state level of customers a business will support. . The term is used in many contexts, but is most widely applied in …

Social Media Analytics - ERNET
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Social Media Analytics - ERNET

Date Mar 24, 2018

Prediction models for promotion performance and churn analysis. Discussion of real cases. Hands-on project: churn prediction from a …. Social Network Analysis for Computer Scientists Business Intelligence and Process Modelling “Big data is the term for a collection of datasets so large and complex Churn Prediction Master Computer Science project by P. Kusuma

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An Introduction to Social Network Analysis - Data
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An Introduction to Social Network Analysis - Data

Date Mar 18, 2018

In this retail setting the customer churn is defined as customers who switch their purchases to another store. neural network. decision tree Table 1 presents examples of the churn prediction studies found in literature.

Social network analysis for customer churn prediction
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Social network analysis for customer churn prediction

Date Mar 24, 2018

SPSS Churn prediction framework of prepaid, postpaid and fixed line customers Sanket Jain GBS Business Analytics and Optimization Center of Competence, CMS Analytics India Date of writing: July 18 2011 ABSTRACT Generally, most of the previous analyses on customer churn prediction modeling have focused on making predictions of prepaid …

Analyzing Churn of Customers - PowerPoint PPT
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Analyzing Churn of Customers - PowerPoint PPT

Date Mar 7, 2018

1/11/2013 including finance, globalization, team leadership, corporate social

Customer Churn Case Study - Logistic Regression
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Customer Churn Case Study - Logistic Regression

Date Mar 21, 2018

Oracle Data Mining solves a wide range of business and technical problems, both those specific to a particular industry as well as problems common across industries. Here are a few examples of business problems by industry