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DataCamp

Case Study: Analyzing Customer Churn in Tableau

via DataCamp

Overview

You will investigate a dataset from a fictitious company called Databel in Tableau, and need to figure out why customers are churning.

Are you ready to apply your Tableau skills to a real-world dataset?

For subscription-based businesses, reducing customer churn is a top priority. In this Tableau case study, you'll investigate a dataset from an example telecom company called Databel and analyze their churn rates. Analyzing churn doesn’t just mean knowing what the churn rate is: it’s also about figuring out why customers are churning at the rate they are, and how to reduce churn. You'll answer these questions by creating calculated fields and various visualizations in Tableau, such as dual-axis graphs and scatter plots. You'll make your graphs dynamic by using filters and parameters, and combine everything into a story to share your insights.

Syllabus

  • Exploratory analysis
    • In this first chapter, you'll start exploring the new dataset and revisit creating calculated fields in Tableau to get a better understanding of why customers are churning.
  • Investigating churn patterns
    • You'll continue by leveraging the Tableau knowledge you gained from the prerequisite courses to further investigate why customers are leaving Databel.
  • Visualizing your analysis
    • In the last chapter, you'll create Tableau interactive dashboards and arrange them into stories, so that you can share your results with stakeholders.

Taught by

Carl Rosseel

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4.6 rating at DataCamp based on 24 ratings

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