Case Study: Analyzing Customer Churn in Power BI
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Description
Are you ready to apply your Power BI skills to a real-world dataset? For subscription-based businesses, reducing customer churn is a top priority. In this Power BI 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 measures and calculated columns, while simultaneously creating eye-catching report pages. Read more.
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The techniques and tools covered in Case Study: Analyzing Customer Churn in Power BI are most similar to the requirements found in Business Analyst job advertisements.
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This hands-on case study focused on the fictitious telecom company, Databel, and provided invaluable insights into understanding and addressing customer churn. Here’s a glimpse of what I accomplished:
DAX Functions
Utilized basic DAX functions like SWITCH and IF statements to analyze data.
Visualizations
Created an array of visuals including line charts, scatterplots, cards, maps, and various bar and column charts. In total, I developed around 17 visuals spread over 5 pages.
Key Findings
- Churn Rate : Discovered that the churn rate for Databel was approximately 26.86%.
- Top Reasons for Churn : Identified that customers churned primarily due to better offers and devices from competitors, and dissatisfaction with customer support.
- Regional Insights : Found that California had the highest churn rate, but with only 68 customers, its impact might be minimal.
- Contract Types : Noted that customers with month-to-month contracts had the highest churn rate at 46%.
- Age Factor : Observed that churn rate increased with age, indicating older customers were more likely to leave.
- Customer Service Calls : Determined that higher customer service interactions correlated with increased churn likelihood.
Though Databel is a fictitious company, the dataset reflected real-world scenarios, making this an incredibly engaging and educational experience.
COMMENTS
In this Power BI case study, I'll investigate a dataset from an example telecom company called Databel and analyze their churn rates. This case study helps to understand why customers are churning at the rate they are, and how to reduce churn.
In this Power BI case study, you'll investigate a dataset from an example telecom company called Databel and analyze their churn rates. Understand why customers churn 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.
In this Power BI case study, we'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.
In this Power BI 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.
In this Power BI case study, you'll investigate a dataset from an example telecom company called Databel and analyze their churn rates. ... The techniques and tools covered in Case Study: Analyzing Customer Churn in Power BI are most similar to the requirements found in Business Analyst job advertisements. Similarity Scores (Out of 100) Fast Facts
Case Study: Analyzing Customer Churn in Power BI Defining churn The churn rate , also known as the rate of attrition or customer churn, is the rate at which customers stop doing business with an entity
This webinar delves into analyzing customer churn in the telecommunications sector using Power BI, offering guidance on utilizing Power BI for efficient chur...
Churn Rate: Discovered that the churn rate for Databel was approximately 26.86%.; Top Reasons for Churn: Identified that customers churned primarily due to better offers and devices from competitors, and dissatisfaction with customer support.; Regional Insights: Found that California had the highest churn rate, but with only 68 customers, its impact might be minimal.
Presentation Title to be adjusted on the 1st master page June 30, 2020 Case Study: Analyzing Customer Churn in Power BI Download Power BI Desktop
Here is an example of Analyzing customer churn in Power BI: . ... Case Study: Analyzing Customer Churn in Power BI. Project Outline. 1. Exploratory Analysis Free. 0%. In this first chapter, you'll start exploring the new dataset and revisit creating measures in Power BI to get a better understanding of why customers are churning. View Chapter ...