Churn analysis doesn’t have to be complicated.
One of the most important metrics for growing your business, churn can be a difficult metric to monitor and reduce. Every company should perform churn analysis to mitigate the effect churn has on profitability. Using churn analytics you can stay on top of your customer retention rates and understand at what rate customers are leaving your service and why.
With churn being crucial for growing your business you are probably wondering how do you analyze churn? And how can I predict and prepare for future churn?
Here we will cover the basics, starting with what churn is and it can be measured in your business.
Simply put, churn or customer attrition is an term used to measure the rate at which customers are canceling their subscriptions or stop using your service over a specific amount of time. Examining churn can help SaaS, eCommerce, and other types of companies understand the possible indicators of customer dissatisfaction, competition and effectiveness of marketing and advertising programs.
Churn is a crucial metric to monitor and reduce, as a high churn rate means lower customer retention and a loss of recurring revenue.
Churn analysis is the data-driven process of examining the customer lifecycle and addressing the issues causing customers to discontinue using your service. Many businesses prioritize new customer acquisition over retention. While this can be beneficial for growing your new startup, if you are not retaining customers, you are likely losing more money than you earn. Chun analytics doesn't only look at the rate at which your customers are leaving but helps you understand the causes and find solutions to those problems.
With robust churn analytics, you can
There are two basic kinds of churn, customer and revenue. Both are important to understand to help grow your business.
Starting with customer churn or customer attrition. This is the rate at which customers are canceling their subscriptions or discontinuing the use of your service. Customer churn can be broken down into a few subcategories to help better understand the bigger picture of churn.
Contractual churn is one subcategory, where customers do not renew expired contracts which thus increases churn or cancel their current contract, which is most common for SaaS companies.
There is also voluntary churn, where customers discontinue the use of existing services. Voluntary churn is more applicable to telecommunications companies and streaming service providers.
Next, we have non-contractual churn which can be applied to retail businesses and eCommerce sites, where customers leave before completing a purchase or in other words, abandon their shopping carts.
Lastly, there is involuntary churn. Involuntary churn happens when customers can no longer afford or their payment method is declined to lead to the cancelation of their service.
Common reasons customers churn can include, poor service or better prices but, in reality, there is no one reason why customers churn. Using churn analytics can help your company identify instances of churn and dig deeper into the root causes that may be affecting your profitability.
Revenue churn or MRR churn can be defined as the rate at which monthly recurring revenue (MRR) is lost, caused by customer churn -OR- customer downgrades in service.
With churn metrics it may seem as if you can pick one and use it to determine the health of your business, but only measuring customer churn or revenue churn will not provide enough information for understanding the bigger picture.
For example, let's say over the course of one month you have one churned customer, you may think something bad is happening and it's causing customers to leave. However, in that same month, you upsell 3 existing customers into better pricing packages, you would have increased MRR, making up for that lost customer you may not notice that a customer has been churned.
There is no perfect metric for monitoring your business so being diligent and diving deeper into your data will greatly benefit your business goals.
When it comes to churn analytics, customer churn will help you understand your customer retention rates, while revenue churn helps you understand your revenue retention and cross-selling and up-selling rates.
Churn analysis is a powerful tool to help businesses grow and stay on top of their industry. Since churn analysis can be segmented into revenue churn or customer churn, even companies with few high-value clients are using churn analysis to grow their business.
These are a few examples of how churn analysis is used:
Analyzing churn can seem like a daunting task, especially for an early stage business. With the proper tools and attention to detail, you can help grow your startup, improve your customer experience and increase your customer lifetime value.
Here a few ways to get started in the process of churn analytics:
The churn rate is the percent of customers who stop using your services in a given time period. For your business to grow your existing customers and new customers need to be greater than the number of customers lost over the specified time. To calculate your simple churn rate, start with the number of churned customers in one month. Then divide that number by the daily user – users who remain active on a day-to-day basis and new users in the same month. This will give you a simple understanding of your monthly churn.
To start measuring churn, you can use Apteo’s new churn analytics.
Putting an end to churn is nearly impossible, and reducing it can be excruciatingly difficult but to start, identify the drop-off points. You will need to start using funnel analysis to monitor where your customers are getting stuck in the conversion funnel and eventually dropping off. Your customer funnel shows customer behavior, how they navigate your service, and what leads them to churn. With this method, you will be able to see where customers are lost after onboarding and the events that occur prior to churning.
Using customer data you will be better equipped to analyze customer behavior, help you make churn predictions and improve customer experience, leading to greater customer retention and lower acquisition costs.
Hotjar and Google Analytics are great tools to find drop-off points.
Here comes the hard part. You will need to analyze and analyze your customer data beyond the drop-off points. Here you will be looking for the reasons customers churn. Ask yourself, are the price points comparable to industry competition or standards? Are customers satisfied with the service provided? What is our customer success rate? These questions will help guide you in making a hypothesis to which you can start making actionable change.
With your hypothesis in mind, you will begin testing your solutions. Using A/B testing or your preferred method test your hypothesis and solution before implementing semi-permanent change.
The bright side is that customers may not be churned forever. As you continue to grow your business, develop new software and improve the customer experience you may regain those customers and acquire additional customers.
It’s a fact that retaining existing customers is much less expensive than acquiring new ones. With Apteo, you can begin to understand which customers are likely to churn based on their behaviors and character traits. If you are looking to increase your recurring revenue and reduce churn, schedule a demo to learn more.