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Customer Service Value in Marketing Analytics

Learn how to use customer service value in marketing analytics as well as customer churn from this free online course.

Publisher: NPTEL
Customer Service Value in Marketing Analytics is a free online course that offers an in-depth understanding of customer service value as well as the importance of the customer churn approach in marketing analytics. You will learn about the various nuances that can be used to predict customer churning behaviour and also study the use of text mining in digital marketing.
Customer Service Value in Marketing Analytics
  • Duration

    4-5 Hours
  • Students

    499
  • Accreditation

    CPD

Description

Modules

Outcome

Certification

View course modules

Description

Customer Service Value in Marketing Analytics is a free online course that offers a comprehensive guide to understanding the importance of the customer churn approach in marketing. This course will teach you how various techniques can be used to predict customer-churning behaviour in marketing analytics. It begins with an analysis of customer service control, and how it can be used to solve real-life problems.

Next, you will learn about text mining, as well as the impact of Internet availability on the analytics process. You will also study the features and application of natural language processing in analytics, as well as the roles of information and digital technologies. Then you will discuss the features of tokenization, as well as how to use the mining natural language processing approach in marketing. Analyze the customer lifetime value approach, as well as studying how to maintain a relationship with customers. Finally, you will grapple with customer relationship management, as well as the other features of the economics of CRM in marketing analytics.

This free online course provides practical knowledge and numerous applications like spam detection in text mining and sentiment analytics, as well as how to use the naive Bayes classifier algorithm for the spam detection process. This course will be of significant interest to business organizations, programmers and anyone interested in using marketing analytics for private or professional e-commerce.

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