Nobody likes losing customers. The good news is that there’s a lot you can do to keep them, even when they’re less engaged than they once were. So how do you know a customer is about to leave? And how do you take action before it’s too late?
In this post, we’ll discuss how to measure indicators of churn, how to use that data to predict the likelihood of it happening, and how to prevent at-risk customers from churning before it’s too late.
What is customer churn?
Customer churn, also known as customer attrition, is when someone chooses to stop using your products or services. In effect, it’s when a customer ceases to be a customer.
Customer churn is measured using customer churn rate. That’s the number of people who stopped being customers during a set period of time, such as a year, a month or a financial quarter. By expressing customer churn with a metric like this, you can turn it into like-for-like data that helps you measure progress over time. You can also express your churn rate in terms of dollar value if it makes sense to do so.
When defining churn, it’s important to be clear about when you consider somebody to have churned. Some sales cycles are longer than others. For example, in some industries, such as optical eyewear or home furnishings, it’s typical for customers to go for long periods without making a purchase because of the nature of the product, not because they’re under-engaged or at risk of churn. For each product and service you provide, fit your churn definition to your typical sales cycle, otherwise you may end up making reactivation efforts with customers prematurely.
Why does customer churn matter?
Some customer churn is inevitable. It’s not realistic to think that 100% of the customers who bought from you on day 1 of your business will still be with you several years down the line. But when your customer churn rate is very high, or if it’s showing a trend of getting higher over time, you’ll want to take action.
Generally speaking, customer churn is bad news for a couple of reasons.
Firstly, a churned customer may well be an unhappy customer. Beyond the loss of their spend, you could be on the receiving end of negative word-of-mouth, bad reviews and a detriment to your overall brand value. For this reason alone, it makes sense to reach out to customers in danger of churning to try and repair the relationship.
Secondly, it’s often said that keeping an existing customer costs less and delivers more value than acquiring a new one. Stats and figures on this vary, and some take the view that customer lifetime value matters more than a single cost dimension like acquisition or retention, but whichever perspective you look from, it generally makes more sense to maintain an existing relationship rather than writing it off and starting again from scratch.
How to measure customer churn
With each customer who churns, there are usually early indicators that could have been uncovered with churn analysis.
Looking at both operational insights (e.g. declining repeat purchases, reduced purchase amounts) as well as experience insights along the customer journey is foundational to predicting churn. For example, a customer who has declined in recent visits and gives a Net Promoter Score of 7 after their latest shopping experience, could have an increased probability of churning.
To start understanding the customer’s journey and the experiences they have, begin with setting up relational feedback requests that help you assess and diagnose key drivers of customer satisfaction.
Once you’ve done this, you can move into measuring transactional experiences, such as purchase or post-support follow-up, so you can get a better sense of where you have detractors and build out a plan to follow up with them.
Finally, you can map out the full customer journey and measure the key experiences across the journeys, from the moment there is a need (e.g. to purchase an item, to get help, to file a claim) to the moment it is fulfilled. The Qualtrics Customer Experience platform can help you not only measure these critical experience touchpoints, but analyze and surface key insights, such as likelihood to churn, so you can take action and drive outcomes for your business.
How to predict customer churn
Once you’ve built out a holistic view of your customer’s experience history with your brand, you need to combine it with operational data, such as repeat visits or credit card usage, to identify key drivers of churn and begin making predictions. Using deep learning and neural networks, Qualtrics Predict iQ combines experience data and operational data to help you predict individual customer behaviour, and take action before it is too late.
Predict iQ helps you accomplish four key elements of churn prediction and prevention:
- Understand the drivers of customer churn
- Automatically identify at-risk customers
- Define thresholds for taking action based on the likelihood of churn
- Easily create tickets and take immediate action for closed-loop follow-up
It all starts with building a model. You can select your outcome variable, such as churn, and then Predict iQ looks at patterns in operational data, like return visits and credit card usage, and combines those with experience data, like satisfaction or likelihood to recommend. It automatically builds out a model that will predict the probability of churn for each individual customer.
Now you can skip the days or weeks of complex analysis and creating prediction models. Predict iQ does the number crunching for you, so you get insights and results more quickly.
How to prevent customer churn
Reducing customer churn isn’t just about saving at-risk customer relationships from the point of no return, although that’s an important part of the picture. Reducing the conditions for churn is something you can do at every stage of the customer lifecycle, through initiatives like:
- Improving CX
A great customer experience is one of the best investments you can make in customer acquisition as well as retention. Great CX makes customers feel good about doing business with you, whether they’re brand new or returning for the 50th time.
- Educating your customer
Part of providing good service is giving customers the information and support they need to get the most out of your products and services. That might mean offering how-to guides and explainers on your website, giving prompt answers through a live agent or chatbot feature, or being active on social media when customers share opinions and ask questions.
- Rewarding loyalty
Loyalty programs and discounts give your customers an incentive to keep coming back to you again and again. They also help give you and edge of your competitors
- Recognizing your best customers
Dollar for dollar, some customers offer more than others across the lifetime of the business relationship. Recognizing and appreciating your MVPs (most valuable players) will help you make sure that they’re not the ones who end up churning.
Closing the loop
Once you’ve predicted whether a customer is at risk of churning, closing the loop with those at-risk customers is the critical next step. Predict iQ can help you create alerts and tickets for customers in various states of unhappiness with your products or services.
For example, you can set a target which requires all tickets for customers with an 80% likelihood to churn to be resolved within 24 hours. If you get a low score on an experience survey and the churn threshold is triggered for a specific customer, Qualtrics automatically generates a ticket requiring specific attention and immediate resolution.
With Qualtrics and the action-planning module, you can go beyond continuously reacting to customer pain, taking insights from the closed-loop process to drive system-wide improvements that avoid customer issues altogether. Employees can collaborate with others, tag owners, set deadlines, and even supply step-by-step guidance.
Drive more value from your CX program with automated prediction
Reducing customer churn directly impacts your company’s bottom line, with increased revenue and reduced acquisition costs. Qualtrics Predict iQ leverages deep learning neural networks to identify customers and accounts likely to churn, and provides the visibility to know what is driving that behavior. You get the insights you need while avoiding days or weeks of tedious analysis.
Want to learn more about how to increase customer loyalty and boost customer retention? Dig deeper with our guides.