The average customer churn rate in eCommerce is around 70-80%, according to our real-time eCommerce benchmark report. Although churn is a natural phenomenon, you still have to keep churn rates under the radar and detect your churn risk factors.
Let’s say you have 20,000 at-risk customers that used to bring $4.6 M to your business, and you could prevent churn for at least 50% of these customers.
You could save $2.3M if you knew your company’s churn risk factors, monitored churn rate, and had a churn prevention campaign in place.
While churn occurs naturally as part of the customer lifecycle, some could be avoided if you change customers’ minds when they are about to dump you and show them that sticking with you is the best alternative.
What is churn?
Customer churn or customer attrition is what happens when customers stop buying from your store. To keep track of this phenomenon, stores regularly calculate one of the most important KPIs for their business’s health: customer churn rate, also known as customer attrition rate.
Customer churn rate is defined as the percentage of customers that stopped buying from your store during a specific period. The most common formula used to calculate churn rate is the number of customers lost during period X divided by the number of customers at the beginning of period X.
Let’s say that your store had 15,000 customers at the beginning of the year and at the middle of the year reached 13,800. For this half of the year, your store’s churn rate is 8%.
We could not say whether this is a good or an alarming churn rate as it depends on multiple factors, such as your business model or industry.
What we can say for sure is that churn prevents or delays growth, and you should always compare it to your growth rate. If your churn rate is higher, it means that you’re having difficulties growing your eCommerce business.
The importance of knowing your churn risk
The opposite of customer churn is customer retention, represented by repeat customers.
Tracking churn rates is vital for your store because it allows you to adjust your acquisition and retention efforts to maintain a healthy customer base and improve customer lifetime value.
Why do you need to track and analyze customer churn constantly?
Depending on your resources and business model, your eCommerce company should measure customer churn rates monthly, quarterly, or yearly so you can:
Identify the reasons behind the customer’s decision to stop buying from your store
Different causes ask for different approaches. Was it a poor customer experience? Was it the price increase of your subscription-based alternative? Knowing exactly what went wrong in your relationship gives you plenty of insights to improve merchandise, marketing, and customer support.
Identify communication gaps based on customer feedback
The feedback of at-risk and churning customers is gold for your optimization initiatives. Asking what made them leave or stop buying from your store helps you better understand what they need and what you can do to meet their needs and exceed their expectation. Offering excellent customer experience at every touchpoint is what leads to customer satisfaction and customer retention.
Improve acquisition and retention campaigns
Not all customers are created equal, so while some might become loyal customers with high average order values, others might only purchase once and then never turn back. Customer behavior segmentation can help you identify these types of customers and approach them differently, according to their importance to your business.
You can use the most valuable customers to create lookalike audiences for your acquisition campaigns. To understand and identify churn risk, you can study at-risk customer segments to see patterns that predict churn. Based on your learnings, you can build prevention campaigns that help you retain customers in the long run and increase their lifetime value.
Reduce CAC and increase CLV
Tracking CAC, CLV, and churn matters if you want to see better results. Acquiring new customers is indeed more expensive than keeping the existing ones. That doesn’t mean you should prioritize retention over acquisition. It means that keeping better customers starts with attracting better customers. You want to attract and retain customers with high chances of becoming loyal customers. This approach can help you improve CLV, reduce CAC and churn rates.
Predict and avoid churn
All you need to know about customer churn is in the historical data. Start with cohort analysis and use it as a foundation for in-depth customer behavior analysis. During your research, you can identify patterns and red flags, predict churn and act immediately to prevent customers from leaving your brand.
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How to predict customer churn
Identifying churn risk factors: how to look for red flags
Churn is a lagging indicator that confirms a trend from the past, but it won’t help you predict what will happen to your customers. This is why you need to look for red flags and know your churn risk factors, a.k.a. leading indicators that help with churn predictions and allow you to prevent this trend.
While no-one can predict the future, customer churn prediction becomes easier when you know what to look for.
You’re more likely to avoid churn when you’re constantly monitoring red flags and optimizing your retention campaigns. Here are some of the churn risk factors that you can easily track:
- Responses in customer satisfaction surveys show that your customers are unhappy;
- Customers have a difficult time placing a new order and abandon their carts;
- Customer support teams aren’t efficient in managing direct complaints;
- Customers leave negative reviews on your website, social media, etc.;
- Newly acquired customers haven’t placed another order within the average days between the first and the second order;
- Loyal customers haven’t placed another order within the average days between transactions;
- Product reviews show that certain products have low scores;
- Certain brands, products, or categories have a low NPS score;
- The order return rates are high for specific brands, products, or categories.
As you can see in the graph below, certain brands could be responsible for increasing churn risk. If you identify a brand with order return rates higher than others, you should start a qualitative analysis and learn the reason behind it. Along with high return rates, you could also see low NPS associated with the brand in question.
Source: REVEAL product performance reports
If you want to reduce customer churn rates, you have to look for red flags proactively.
With the right tools, you can prioritize your resources and help all departments in your store better understand customer behavior and satisfaction, and create an effective plan for preventing churn:
- Automated RFM segmentation to segment customers based on their behavior to identify at-risk customers;
- Net Promoter Score (NPS) system to monitor customer satisfaction to prevent churn, resolve complaints, and understand churn behaviors.
Identifying churn risk with automated RFM segmentation
An automated RFM segmentation tool helps your store segment customers based on their transactional behavior and identify different types of customers:
- Your best customers that deserve your maximum attention;
- Your high potential customers that you must onboard and nurture, so you increase customer loyalty;
- Your at-risk customers that you must approach before they churn and are gone forever;
- Your lost customers that help you learn from their behavior and stop making the same mistakes when you could avoid churn.
With RFM Segmentation, your customers are grouped according to their score for three variables: recency, frequency, and monetary value.
An automated tool uses the existing customer data from your eCommerce platform to group and constantly update segments according to customer behavior.
In REVEAL, the at-risk customer segment is named “About To Dump You.” They are customers that used to buy from your store but haven’t done so for a while. Something went wrong in their customer journey and less frequent purchases occur: drop in purchases are strong churn indicators.
Knowing who these customers are is fundamental in understating why they deviated from their typical behavior and what you can do to prevent customer churn.
Source: CVO Academy
In the image above, you can see the About To Dump You segment of an eCommerce shop. This at-risk group has low customer engagement and hasn’t purchased anything lately. These 17k+ customers used to generate total revenue of $3.9M.
If these were your numbers, you would want to dig deeper for the reasons why they stopped buying from you, knowing how hard it was to get them to buy from your store in the first place. Decreasing the number of customers that reach this segment means that your company makes progress in its efforts to reduce churn.
> Learn everything you need about who to approach the “About To Dump You” segment
Using the NPS system as a predictive churn force
Measuring and monitoring the Net Promoter Score helps you predict future customer behavior. The lower the NPS, the lower the chances your customers will purchase again from your store or recommend your brand as being trustworthy. Lowers scores are usually indicators of churn.
Depending on the scores and answers received from your customers, you can identify three types of customers:
- Detractors: NPS score is 0-6
- Passives: NPS score is 7-8
- Promoters: NPS score is 9-10.
Detractors are most likely to leave your company because they had a poor experience with your store. If you want to prevent churn, you must carefully approach them to fix their problems and minimize the effects of their low customer experience. Briefly, you must show that you care about them.
There’s no better way to show customers you care than treating objections in real-time. To enable this, you should integrate your NPS system with the customer support and email marketing platforms.
When it’s best to act? What’s the best approach for detractors?
We want to help you prioritize your actions, so we invite you to download the full resolution of our blueprint for monitoring and using the Net Promoter Score.
Source: CVO Academy
One aspect that you should keep in mind is measuring and monitoring NPS both pre and post-delivery. Why? It is easier for you to understand if there’s a gap between the two phases of the customer experience. Then, you will know if you’re dealing with problems generated by the marketing around your products or the experiences with your products.
> Read The Ultimate NPS Guide and see how you can use NPS as a predictive force
Using RFM and NPS tools to manage customer attrition will allow you to build better strategies for all types of customers: from improving customer onboarding campaigns for newly acquired customers to avoiding losing your most valuable customers through prevention campaigns.
How to eliminate churn risk
So, you’ve seen the multiple ways in which you can identify customers at the risk of churning. However, prevention is the best treatment.
After you conduct your customer churn analysis and identify customers at risk, you can take a few steps to lower churn: both voluntary and involuntary churn.
Firstly, you need to include quality educational or support materials, that help customers better understand how to succeed with your products.
Failure to visualise success with your products is one of the most common customer churn risk factors, so educating and helping customers without asking for anything in return increases retention.
Of course, you should identify customers at the risk of churning and begin your prevention campaigns starting from the power customers and making your way down the RFM segments.
There’s no point in struggling to meet the needs of bargain hunters or Don Juans, when you have valuable customers that need your immediate attention.
What should you do about customers at risk of churn?
If you used the methods described in this article, you probably identified customers who are about to leave you.
While some natural churn does occur, your safest bet for churn reduction is being proactive – engage your customers before they need you. Prove to them you’re really interested in their well-being and invest time in helping them.
bunch of features I hadn’t explored yet:
> Learn more about customer churn prevention campaigns
Wrap up
As in health care, prevention is better than curing chronic disease. It’s vital to distinguish natural churn from churn that could be avoided and identify the business’s churn risk factors.
Ignoring customer churn rates cost eCommerce businesses a lot of money, and some will go bankrupt when nothing they try can’t stop the leaking bucket.
Luckily, there are tools to help you spot and prevent churn trends, allowing you to design an effective plan for your store.
Discover more REVEAL reports that help you keep track of customer churn risk:
- Revenue vs. Margin by Customer Type;
- Revenue vs. Margin by RFM Group;
- Average Retention Rate;
- Chances to Place Next Order;
- NPS Score;
- Customer Distribution;
- Retention Curve;
- Cohort Analysis;
- Buyer Habits.
Frequently asked questions about customer churn
The most common formula used to calculate churn rate is the number of customers lost during period X divided by the number of customers at the beginning of period X.
In sales, churn can refer to the revenue lost after customers left. It can also provide valuable insights about the delivery gap between the sales pitch and the reality of the products.
Customer churn measures how many customers a business lost over a certain period of time. Customer attrition, on the other hand, measures both how many customers a business lost and how many it has gained over that time period.
Customer churn refers to the phenomenon that occurs when customers stop buying from your store because of reasons like low product quality compared to the promised value or lack of response to their complaint from your customer success team.
You can calculate your store’s customer churn rate by dividing the number of customers lost during the analyzed period by the number of customers you had at the beginning of the analyzed period.
Churn risk prediction helps you identify the customers most likely to stop buying from your store and detect low customer satisfaction signals that lead to customer churn. Based on the conclusions of your churn analysis, you can set and trigger churn prevention campaigns.
