The ecommerce customer retention rate measures the proportion of your customers that are loyal.
The formula is this: (E-N/S)*100, in which:
So, if there were 4,000 total customers in 2023 (E), including 3,000 new customers (N), from an original customer base of 3,000 in 2022 (S), it indicates that 1,000 of the 2023 customers were returning (E-N = 4,000 – 3,000 = 1,000). To find the retention rate: (1,000 / 3,000) * 100 = 33.33%. This means you retained 33.33% of customers year-on-year between 2022 and 2023.
Calculating customer retention rate is often more difficult in ecommerce than other industries. This is because you have to select meaningful time periods for comparison that account for seasonality and your product’s natural purchase frequency.
For example: if you sell laptops, it makes no sense to calculate retention year-on-year. Even the most loyal customer isn’t buying a laptop every year.
But if you sell books, year-on-year comparisons are too broad: you’d expect a retained customer to buy more than one book each year.
And so, to meaningfully calculate an ecommerce customer retention rate, you need detailed purchase frequency, profitability and seasonality data. Because of this additional complexity, many ecommerce owners focus their attention on other loyalty metrics, such as repeat purchase rate and average customer lifetime value (CLV).
In this guide:
As rising customer acquisition costs show no sign of slowing down any time soon, brands need to focus on maximizing the relationships they already have. Simply put, it’s more cost effective to nurture existing customer relationships than spending money to acquire new ones.
Other than potential cost-savings (and potential boosts in revenue by as much as 95%), having customer retention strategies is also critical for your overall customer relationship management (CRM). Think about it; there’s no customer relationship without the effort of retaining them.
Summed up in one equation, loyal customers = long-term sustainable growth.
Loyal customers also:
Customer retention rates vary significantly across industries. According to a report by CustomerGauge, energy and utilities had the highest, with 89%, while wholesale retailers averaged just 44%.
Other reports suggest ecommerce brands average around 30% customer retention. But again, this will naturally fluctuate.
In our experience, anything less than 25% suggests there’s a problem with your customer retention.
Loyalty marketing is a structured, strategic approach to improving customer retention. It focuses on rewarding customers for repeat business.
Combine that with a top-notch customer experience, and you could see your customer retention rate shoot up.
You can also track:
Churn rate is like a reverse retention rate: it tells you how many customers dropped out in a given time period. The formula is this:
CCR = (Lost customers ÷ total customers at the start of time period) x 100
As before, here’s an example of the formula with some numbers:
(150 ÷ 900) x 100 = 16% Churn rate
A high churn rate in your business likely means your customers aren’t happy with your product, or your services don’t meet their expectations. A low churn rate means you’re on the right track.
While having a churn rate between 10–25% is pretty typical for businesses, having it above 10% isn’t the best position to be in — you want it as low as possible.
Calculating the CLV of a customer is a little trickier than other metrics we cover in this guide only because it requires you to calculate something else first — customer value. However, knowing the CLV of your customers can help you understand your revenue source better.
On the other hand, a decreasing average CLV means you’re either attracting more low-value customers or losing customers more quickly over time.
So here’s the formula you need to use for first calculating customer value:
Customer value = (Average purchase value x average number of purchases)
For example, for an ecommerce subscription-based company, customer value could be the monthly subscription over a year, e.g. $14.99 x 12 = $179.88
From calculating a customer’s initial value, you can move on to calculating their lifetime value:
CLV = (Customer value x average customer lifespan)
If you find that your customers stay with you for an average of 3 years, the CLV of those customers would be $179.88 x 3 = $539.64.
In this example, a higher CLV can come from customers who make one-off purchases on top of their subscription, and a lower CLV would come from customers who stop subscribing earlier than average.
You can subtract customer acquisition cost (CAC) from CLV to measure the total profit made per customer.
Another interesting metric related to customer retention is revenue churn, which refers to the revenue lost from existing customers.
It’s vital to track revenue churn because this helps you understand the rate at which customers negatively affect your revenue from actions such as order cancellations or subscription downgrades. Customers with high revenue churn are likely to leave your brand behind. So here’s the formula using monthly recurring revenue (MMR):
Gross revenue churn = (Churned MRR ÷ MRR at the beginning of the month) x 100
With actual numbers, the formula looks like this:
($250k ÷ $2m) x 100 = 12.5%
This is an okay metric, but it doesn’t consider revenue expansion from existing customers from upgrades, for example. So to find this part out, you’ll need a net revenue churn formula:
Net revenue churn = (Churned MRR – expansion MRR) ÷ MRR at the beginning of the month x 100
In our example, let’s say the business gained $50k in expansion revenue, so:
($250k – $50k) ÷ $2m x 100 = 10%
With this metric, it’s possible to have a negative percentage, which tells you your revenue expansion gains outweigh your revenue losses.
NPS© is a popular metric, which you might recognize even as a customer of other brands—it measures your customer’s overall satisfaction and how likely they are to refer your business to other people. You’ll usually be able to gather the information you need for this from customer feedback surveys.
Here’s the exact formula you’ll need when you have the numbers:
NPS© = (Number of promoter scores ÷ total number of respondents) – (Number of detractor scores ÷ total number of respondents) = Answer x 100 = %
So let’s say your NPS© survey had 300 total respondents. “Promoter” scores come from positive responses, and “detractor” scores come from negative responses—dividing each by the number of responses gets you a decimal that you can turn into an overall percentage by multiplying it by 100.
For example:
(275 ÷ 300) – (25 ÷ 300) = 0.83
0.83 x 100 = 83%
This way, you can see the overall health of your customer satisfaction; if it’s a low number, you can take action to improve your customers’ experiences.
The repeat purchase rate is the formula you’ll want if you want to determine your customer loyalty. This metric helps you see the percentage of customers who return and buy more from you (which is a better formula for product-led businesses).
Tracking your repeat purchase rate is important for helping you determine if your products align with your customers’ expectations (or not, if the rate is low).
RPR = (Number of customer who purchased more than once) ÷ (total number of customers) x 100
So for numbers in this case, here’s an example:
(12,500 ÷ 50,000) x 100 = 25%
Nice and easy, right?
The name is self-explanatory, but figuring out your average time between purchases tells you how quickly your customers want to buy from you.
Here’s the formula:
TBP = (Sum of individual purchase frequency by days ÷ number of repeat customers)
Let’s say you already know your number of repeat customers from using a CRM or a customer loyalty program software, and that figure is 50.
By using each of those customers’ individual purchase frequency (using a spreadsheet would be handy if you’re doing this manually) and adding them up, you get the first part of the formula, so for example:
140 days ÷ 50 = 2.8 days (rounding it up to 3 to be conservative)
Whether or not the time between purchases is good for your business depends on the nature of your product (e.g. for FMCG goods like groceries, three days is good).
Calculating these metrics would be quite a handful if you did all of this manually — and it would become almost impossible as your business grows. Instead, you can use LoyaltyLion, which helps you record all the data from your loyal customers’ purchases.
LoyaltyLion’s customer value snapshot makes tracking metrics like the ones in this guide a total breeze.
Ready to get started? Book a demo today.