Churn rate analysis in Tableau

Your churn rate is a crucial metric. The churn rate provides insight into your customers behavior. With insight in your churn rate, you can estimate whether your customers will continue to do business with you or if they will leave.

Churn rate – the percentage of customers who stopped doing business with you in a specific period.

In general, it is less expensive to retain existing customers than to recruit new ones. Companies therefore try to keep their churn rate as low as possible. A churn analysis is very valuable because it gives you a great insight into your customers behavior. When we analyze churn, we can distinguish four different types of customers:

• Retaining: Customers who have done business with you and are still doing so and are likely to continue to do so.
• Recruiting: Customers who have started doing business with you but have not done so in the past.
• Regaining: Customers who have started doing business with you again after a certain period.
• Losing: Customers who have done business with you but do less and less or even stop.

Your ERP software contains all the data you need for a churn analysis. We can make predictions based on your sales order and invoice data. Predictions such as when a customer will order again and how much they will order. Often even with a certainty percentage. By categorizing customers according to order volume, revenue, and margin, we can distinguish customers who contribute a lot or little.

How to analyze churn rate?

Even though all the data you need is available in your ERP software, it can be hard to gain the right insights. This is where business intelligence come into play. Using BI tools, such as Tableau, enables you to combine data in a way that makes it easy to interpret. Using Tableau, we can even combine our sales order and invoice data with a BCG-matrix, which also gives us direct insight into the share of each product in your churn rate. With these analyses you will find out which customers you should give more attention, because you can sell more to these customers or because they may otherwise stop doing business with you.

Make your analyses even more advanced by adding external data. Add, for example, geological, political, and economic influences and developments. This will make your new insights even more accurate.

With our Tableau analyses, we can calculate churn using three different measurements:

• Customer churn: the amount of lost customers
• Revenue churn: the amount of lost revenue due to lost customers
• Margin churn: the amount of lost margin due to lost customers

Tableau gives you powerful, visualized insights. Below we give you several examples. With this real business intelligence, you can manage your customer department even better. And the marketing department benefits greatly from this as well. Especially if we combine this with the data from the CRM system, which shows the conversion rate of prospects and the success of certain campaigns or promotions.

We will give you three examples of Tableau analyses that provide meaningful insights:

• Rolling churn
• Churn as-of
• Customer insights

Rolling churn

This dashboard below gives you the following insights:

• The top graph Rolling Revenue Churn shows the development of the churn rate. In this example, the churn rate is close to 5% in March 2021. That is a high percentage compared to the previous months. This means that a relatively large amount of revenue is lost due to customers who have dropped out.
• The bottom graph Overview by Customer Type shows the different types of customers (as explained above) over time. In this graph we see that most customers can be classified as Retain. The number of customers we retain has been fairly stable over time. However, we see only a small part of the customers as Recruit or Regain. From this we can conclude that to achieve growth, attention must be paid to regaining old customers or acquiring new customers.

The interactivity on this dashboard is explained using the bullets:

1. Choose one of the measures (customer, revenue, or margin).
2. View the churn rate for a particular industry or Sales Manager.
3. Choose whether you want to see the churn rate as a percentage or as an amount.
4. Zoom in on the details of a month. All customers who left in the selected month are then shown on the right-hand side. In this example, customer AG left in May 2020, resulting in a loss of € 782.400 in sales.
5. Zoom in on the details by selecting a month. These are shown on the right (Regain Customers – March 2020).
6. This is where the drill-down details are shown after a month is selected on the left side.

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

In this dashboard you can see which customers generate more, less or the same revenue in the current year compared to last year. For the red customers, the revenue in the current year is lower than last year. This is very interesting information for a sales manager, as there is a potential to sell more to these customers. By adding more data to these analyses, such as a customer satisfaction score, this analysis could give insight in which customers are likely to stop doing business with us. A sales manager or account manager can use this information to improve the relationship with these customers so that this can be prevented.

Conclusion

Tableau helps you to analyze your customer churn rate. Analyzing churn rates is valuable for any kind of business. You can start simple, by visualizing the churn rate over time and doing cross-sectional analysis of churn at the current month. Later, you can also start predicting churn which can help you in retaining customers.