Churn: Transactional Churn
Most transactional business, like e-commerce, use metrics like repeat purchase rate  to evaluate customer retention. This is because churn metrics require that you know when you lose a customer, which can be very hard for a transactional business. In a subscription business you know when they cancel their subscription, but what about a website where customers can come and go when they please? However, just because it’s hard doesn’t mean it’s not worth doing!
One common way of identifying when you have lost a transactional customer is using a time window for activity. Every time a customer makes a purchase you start a timer. If that same customer does not come back within a set period of time, you consider them churned. I’ve illustrated this below:
That makes sense, but what do you do if that same user comes back and makes a purchase the day after you mark them as churned?
You have a few choices on how to handle these cases:
- Treat them as a new customer. It might seem like cheating to treat a returning user as a new customer, but if your window is long enough this might be for the best. If your website and product has changed significantly over the 6 months since a customer last purchased from you, their experience will be brand new and they will be a new customer in most ways.
- Re-calculate your churn rates. Every month, you can recalculate your churn rates for the past year as you can identify customers who were thought to have churned but later returned and made a purchase after their window. This is the most accurate approach but is the hardest to use in practice because your past metrics will keep changing!
That seems pretty easy, although choosing your time window is critical. Do you use a week, a month, or a few months? If you choose a window too short, you will show an artificially high churn rate. If you choose a window too long then you won’t know when you lose customers until long after they are gone. You will need to use your knowledge of your business and typical usage patterns to make an informed choice, and revisit it if you feel the churn metrics are not reflective of real customer churn.
Tomorrow we’ll take all of this one step further by looking at churn rates over time which make it possible to identify developing problems and fix them!
Do you need help understanding your customers? Outlier is a product designed to help! Outlier looks deep into who your customers are and how they behave to highlight changes that might indicate potential causes of churn. If you’re interested in seeing a demo, schedule a time to talk to us.
 The repeat purchase rate is the percentage of customers who have returned to make another purchase. It provides you a shorthand to know how many purchases in a given time frame were from new or existing customers. Ideally, the rate increases over time as you accumulate more loyal customers.