Churn rate analysis in Tableau

Your churn rate—the percentage of customers who stop doing business with you within a specific period—is a critical indicator of customer behavior. Gaining a clear understanding of this metric helps you predict whether customers will stay or leave. Retaining existing customers is often less costly than acquiring new ones, making reducing your churn rate essential for sustainable growth.

With a churn analysis, you can classify customers into four categories:

• Retain: Customers who stay and are likely to continue ordering.
• Recruit: New customers doing business with you for the first time.
• Regain: Customers who return after a period of inactivity.
• Losing: Customers who are ordering less or have stopped entirely.

The data for a churn analysis is often already available in your ERP system. Sales orders and invoice data, for example, provide a wealth of information to predict when customers will reorder and how much. By adding insights such as order volume and profit contribution, you can identify which customers are most valuable.

How to analyze churn rate?

Although the necessary data is often present in your ERP system, extracting actionable insights can be challenging. This is where business intelligence tools like Tableau, come in. Tableau enables you to combine and analyze data in an intuitive way. For example, you can integrate sales orders and invoice data with a BCG-matrix,to understand the impact of each product on your churn rate. This reveals which customers need more attention—whether to encourage additional purchases or to prevent them from leaving.

You can enhance your analysis further by incorporating external data, such as economic or political factors, for even more accurate predictions.

• Customer Churn: The number of lost customers.
• Revenue Churn: The revenue lost due to churned customers.
• Margin Churn: The margin lost due to churned customers.

Tableau provides powerful visual insights. Below are examples of how Tableau can help improve your business intelligence. These insights are valuable for both the customer service and marketing teams. By integrating data from your CRM system, such as prospect conversion rates and the success of campaigns or promotions, you can further enhance your analysis.

Rolling churn

This dashboard below gives you the following insights:

• Rolling Revenue Churn:
  This graph shows the development of the churn rate over time. For instance, a churn rate of nearly 5% in March 2021 indicates significant revenue loss due to departing customers compared to earlier months.
• Overview by Customer Type:
  This graph tracks customer group development over time. Most customers fall into the Retain category, while smaller segments belong to Recruit or Regain. This suggests that growth opportunities lie in regaining old customers or acquiring new ones.

Key Features

1. Choose metrics: Customer, revenue, or margin.
2. View churn rates by sector or Sales Manager.
3. Select between percentage or monetary values for the churn rate.
4. Drill down to monthly details to see which customers churned and the associated revenue loss.
5. Analyze recovered customers from specific months.

Churn As-Of

This dashboard shows the churn rate at a selected month. This is contrary to the previous dashboard, which shows churn over time.

The bullets explained:

1. Choose one of the measures (customer, revenue, or margin).
2. Filter the data.
3. Choose between Gross and Net churn rate. Gross churn is the number of customers who dropped out. Net churn subtracts the number of newly acquired customers from this. This means that if the net churn is negative, more new customers have been acquired than customers have left.
4. As net churn is negative, more customers were gained than lost.
5. Net revenue churn is negative, which means that the amount of gained revenue by new customers is higher than the amount of lost revenue.
6. This also applies to the margin.

Customer insights

Another dashboard compares customer revenue from the current year with the previous year, highlighting customers who generate less revenue (marked in red). These customers deserve extra attention as there may be opportunities to encourage them to order more. By adding data like customer satisfaction scores, you can predict which customers are at risk of leaving and take preemptive action to strengthen relationships and reduce churn.

Conclusion

Tableau enables you to analyze and understand churn rates, providing invaluable insights for any business. Start with a simple view of churn over a specific period, then expand to predictive analyses that help improve customer retention. These insights not only optimize customer service but also refine marketing and sales strategies. With Tableau, you can better understand your customers and drive sustainable business growth.