### Analyzing Customer Churn Using Tableau: A Comprehensive Guide
Customer churn, the rate at which customers stop doing business with a company, is a critical metric that can significantly impact the bottom line of any business. Analyzing churn helps companies identify why customers are leaving and develop strategies to improve retention. This guide explores how to use Tableau, a powerful data visualization tool, to analyze customer churn effectively.
#### Step 1: Data Preparation
Before diving into Tableau, it’s essential to prepare your data. Ensure your dataset includes customer IDs, transaction dates, amounts, and any other relevant information like customer demographics or service usage data. Data quality is paramount; thus, clean your data to remove duplicates or incorrect entries to ensure accuracy in your analysis.
#### Step 2: Setting Up Tableau
Once your data is ready, import it into Tableau. Create a connection to your data source, and Tableau will display the fields available for analysis. Utilize the drag-and-drop interface to start exploring your data. For churn analysis, you'll typically look at data over time, so ensure your date fields are correctly recognized by Tableau as date data types.
#### Step 3: Calculating Churn Rate
To analyze churn, you first need to define what constitutes churn in your context—whether it's not purchasing within a certain period or canceling a subscription. Using calculated fields, create a churn flag: a binary indicator (0 for active, 1 for churned) based on your criteria.
For example, if a customer has not made a purchase in the last 90 days, they could be considered churned. Create this calculated field by comparing the date of last purchase against the current date and setting conditions that match your churn definition.
#### Step 4: Visualizing Churn
With your churn flag in place, start visualizing the data. A simple but effective visualization is a line graph or a bar chart showing the number of active vs. churned customers over time. This visualization helps quickly spot trends or issues in customer retention.
Advanced visualizations can include cohort analyses, where customers are grouped based on their acquisition date, and churn rates are tracked across these cohorts. This analysis can be particularly insightful to see if changes in your product, service, or customer experience have impacted customer retention over time.
#### Step 5: Dive Deeper with Segmentation
Segment your data to gain deeper insights into which customer groups are churning the most. Use Tableau’s ability to segment and filter data to look at churn by demographics like age, gender, or region, or by behavioral segments such as usage tiers or product types.
Visualize these segments using stacked bar charts or tree maps. These visualizations can highlight which segments have higher churn rates and deserve more focused retention strategies.
2. Objective
The goal of this project is to leverage advanced
analytics with Tableau to provide NACOM, a
fictional Telecom company, with a comprehensive
understanding of their customer churn dynamics.
By doing so, the project aims to equip NACOM
with the necessary insights to formulate robust
retention strategies, thus directly contributing to
the reduction of customer churn and bolstering
overall customer satisfaction and loyalty.
Ultimately, the intention is to foster a more stable
and profitable customer base for the company.
5. The Data Key Characteristics
NACOM, a
fictitious
Telecom
Provider
One big table
containing 29
columns
One row per
customer
Snapshot of
the database
at a specific
moment in
time.
6. The Data
Dimensions
Column Name Description
Customer_id The unique ID that identifies a
customer
Churn Label Contains ‘Yes’ or ‘No’ to indicate if a
customer churned.
Demographic
fields
Age, Gender, State, ….
Premium Plans Unlimited Data, International Plans,….
… ….
7. The Data
Measures
Column Name Description
Total charges Sum of all monthly charges
Monthly charge The average of all monthly
charges billed to the customer
Extra data charges Extra charges for data
downloads above the specified
customer plan
Extra international charges Extra charges for international
calls for customers not on an
international plan
Customer service calls Number of calls made to
customer service
… …
8. The very first analysis
The Demographic Investigation
Analysis revealed that senior clients have a greater
tendency to stop using services, with a churn rate of
38.22%, compared to 24.30% for non-senior clients.
Although fewer in number, senior clients are leaving at a
higher rate, indicating a possible issue with service
satisfaction that may require specific attention to improve
retention among the elderly.
14. Conclusion
Advice to NACOM:
Prioritize retention strategies for senior customers, as they have higher churn rates,
particularly in California which shows the highest churn rate. Address issues with
monthly contract customers who churn more frequently. Promote group plans with
more than two members to reduce churn. Counteract competition with better devices
and offers. Monitor and adjust international calling plans for non-active users. Ensure
offered data plans are above 10 GB for greater customer satisfaction.
