Customer Churn Analysis: What is Customer Churn and How to analyze it?
Understanding why customers buy more goods or services — or don't — is critical to a company's success. The first step in gaining this data is to determine how many customers are leaving your company. Then you may dive further to establish trends among existing customers, identify areas for improvement, and avoid losing more customers.
Customer Churn Analysis is the technique of determining how quickly people abandon a product, website, or service. It allows teams to take action by answering the questions they are doubtful about.
In this blog post, we’ll tell you about customer churn, customer churn analysis, the importance of customer churn analysis and ways to do churn analysis. Are you ready? Let’s begin.
What is Customer Churn?
In simple words, customer churn happens when a customer decides to not be a customer. When a customer stops purchasing goods or services from a company, that is known as customer churn.
The rate at which customers exit from doing business with a company is known as the customer churn rate.
Churn is unavoidable. It happens in every business and every industry. You can only work towards reducing the churn rate by identifying the reason behind it.
What is Customer Churn Analysis?
Customer Churn Analysis is a way to measure customer churn rate, the rate at which customers are stopping to purchase from a company. Churn analysis informs you what percentage of your customers don't return compared to the percentage that does.
You might be able to spot trends that will help you avoid failure or take an existing successful product or service to the next level by diving deeper into these numbers. Calculating this KPI over various timeframes and trending the results is one method of measuring customer churn.
To assess customer churn rate and use it to bring results, it's critical to track customer sales and retention KPIs. These data can either be calculated manually (in small businesses) or via complex tools (in large businesses).
Irrespective of the method you use, you'll need data on current and previous customers to develop churn models and uncover reasons why some customers stick around while others leave.
The process of reducing churn does not end with analysis: Once you've identified trends and gathered insights, it's essential to put together an action plan to reduce churn and improve every new customer's value.
Working on Customer Churn Analysis
For customer churn prediction or analysis, the prerequisite is having a customer database and a program like a spreadsheet to analyze the data.
To reduce time and enhance accuracy, you should export statistics such as customer churn rate, customer renewal rates, etc. from company data software.
Next, you should break the collected data by product, region, customer group, etc. to acquire meaningful insights. This will provide your team with information about where and why you're losing customers.
Method to calculate Customer Churn
To calculate customer churn, 2 information is needed:
- Number of customers at the period's beginning
- Number of customers at the period's end
The delta (or change) is the number of customers that are churned (or have stopped the purchase).
Churn Rate = Number of Churned Customers (delta) ➗ Number of customers at the period's end
For instance, suppose a company has 200,000 customers at the beginning of the year, 220,000 at the year end, and lost 80,000 customers in that year.
Then, the customer churn rate will be 80,000 (lost customers) ➗ 220,000 (customers at the end) = 36%
The company's year-end results would be even better if it could cut its churn rate in half.
Advantages of Customer Churn Analysis
Why spend time on customer churn analysis when you could be working on various other projects? Here's a quick rundown of the advantages of customer churn analysis.
1. Boost in profits
The key purpose of a company is to earn money by selling its goods or services. As a result, the true objective of a customer churn analysis is to boost earnings by reducing customer churn.
If more customers stay for a longer period, you'll see a rise in sales and profits. Customer churn prediction can help you with this by telling you the reasons your customers don't stay longer.
2. Enhanced customer experience
One of the most common reasons for losing a customer is an easily avoidable error, such as sending the incorrect item. Understanding why customers leave can help you understand their priorities, spot your flaws, and improve the customer experience (CX).
Customer experience also refers to the customer's perception of your company or brand which is formed throughout the buyer's journey.
Performing customer churn analysis can help you in identifying whether customer experience is the issue. Then you can take actions to enhance customer experience.
3. Better product and service optimization
You now have an opportunity to improve if customers are leaving due to particular issues with your products, services, or delivery methods.
Acting on these insights will not only reduce customer churn but will also result in an improved product or service, which will bring you greater future growth.
4. Increase in customer retention
Customer retention is the polar opposite of customer churn: a company's ability to keep customers and generate income from them.
Customer retention is important because it helps a company to increase the profitability of existing customers and optimize their lifetime value (LTV). Churn analysis will help you in increasing customer retention.
Customer churn prediction or analysis is crucial for businesses as most of the revenue is contributed by recurring customers.
So, retaining customers is more important than customer acquisition. With this, you know how to calculate customer churn analysis.
Now, you can further reduce the churn rate by working on the reasons that forced your customers to back out. It can either be your product, service, customer experience, or anything. Just find that out from customer churn analysis and take action accordingly.