attacking customer churn with text and web analytics

Write a four- to five-page paper in which you:

Evaluate the importance of unstructured data in the churn analysis.
List other structured and unstructured data other than the memo and Web blogs that you need to use in your churn analysis.
Propose a series of steps for deriving a predictive model using text and Web analytics. Provide at least one example of how the process can be integrated in the modeling process using structured data.
Identify at least two technologies that you can use to construct the predictive model and highlight their pros and cons.
Explain why “voice of the customer” carries much more insight into churn analysis and prevention.
Suggest at least one churn prevention method that you can use to reduce your churn rate based on your model.
Use at least three quality resources in this assignment. Note: Wikipedia and similar Websites do not qualify as quality resources.

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