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Scala Machine Learning Projects

You're reading from  Scala Machine Learning Projects

Product type Book
Published in Jan 2018
Publisher Packt
ISBN-13 9781788479042
Pages 470 pages
Edition 1st Edition
Languages

Table of Contents (17) Chapters

Title Page
Packt Upsell
Contributors
Preface
1. Analyzing Insurance Severity Claims 2. Analyzing and Predicting Telecommunication Churn 3. High Frequency Bitcoin Price Prediction from Historical and Live Data 4. Population-Scale Clustering and Ethnicity Prediction 5. Topic Modeling - A Better Insight into Large-Scale Texts 6. Developing Model-based Movie Recommendation Engines 7. Options Trading Using Q-learning and Scala Play Framework 8. Clients Subscription Assessment for Bank Telemarketing using Deep Neural Networks 9. Fraud Analytics Using Autoencoders and Anomaly Detection 10. Human Activity Recognition using Recurrent Neural Networks 11. Image Classification using Convolutional Neural Networks 1. Other Books You May Enjoy Index

Why do we perform churn analysis, and how do we do it?


Customer churn is the loss of clients or customers (also known as customer attrition, customer turnover, or customer defection). This concept was initially used within the telecommunications industry when many subscribers switched to other service providers. However, it has become a very important issue in other areas of business, such as banks, internet service providers, insurance companies, and so on. Well, two of the primary reasons for churn are customer dissatisfaction and cheaper and/or better offers from the competition.

As you can see in Figure 1, there are four possible contracts with the customer in a business industry: contractual, non-contractual, voluntary, and involuntary. The full cost of customer churn includes both the lost revenue and the (tele-) marketing costs involved with replacing those customers with new ones. However, this type of loss can cause a huge loss to a business. Think back to a decade ago, when Nokia...

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