Some online businesses, like SaaS companies, spend a lot of time thinking about their churn rate. (This is typically the percentage of customers who unsubscribe from their service in a given month.) For subscription businesses, a low churn rate can be the difference between life and death.

Companies with non-subscription business models, however, typically don’t think about customer behavior in terms of churn. E-commerce players, for example, think about long-term customer relationships in terms of conversion rates and repeat purchase rates. There is rarely a clear distinction between a “current customer” and a “churned customer” in these analyses.

That is, until recently. Every month we’re seeing more and more e-commerce leaders adding “churn rate” into their RJMetrics dashboards.

How can an e-commerce business measure churn if customers never “unsubscribe?” There are a number of approaches that make sense, and typically they depend on how your company plans to act on the data.

One of the most popular methods is to set a cutoff date after which, if a customer has not made a purchase, they are considered to have “churned.” The choice of this date can be arbitrary, or it can be influenced by things like time between orders, repeat purchase rate, and cohort analysis of historical data.

Once you have defined populations of “active” and “churned” customers, you can pursue a number of new analyses and strategies. Here are some tactics we’ve seen:

  • Segment things like referral sources and product categories by percentage of customers churned. This can tell you more about where your most loyal customers come from and what they tend to buy, which can inform marketing and merchandising decisions. This is probably most valuable as part of a cohort analysis.
  • Identify populations of customers who are “about to churn” and send them special promotions or offers to encourage a purchase. While these groupings are definitionally as arbitrary as your churn threshold, instituting this practice on a regular basis will ensure that you are consistently reaching out to new populations of at-risk customers (since customers from previous batches who did not purchase will have churned and those who did purchase will no longer be at-risk).
  • Monitor the health of your business by tracking churn rate over time. Changes in the percentage of customers who move from “active” to “churned” in a given month can be an directional indicator of changes in customer loyalty or behavior.

Giving lapsed customers a definitive “churn” event changes the slow, unpredictable fade-away of an e-commerce customer into a sharp step function that can be monitored, quantified, and acted against. It can simplify goals and clarify vision.

For more on churn rate. check out www.churn-rate.com. To give this a try on your own data, you can try RJMetrics free for 30 days.

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  • http://digimantic.blogspot.com Tauqueer Ali

    I believe direct marketing companies have been using this metric for a while; they call it customer-defection rate. Defection/churn is actually a process and customers go through a number of stages before they finally defect. If you want an actionable framework to put these stages in perspective and design a set actions to catch people as they fall through these stages – check out LifeCycle Grid by Jim Novo.

    http://blog.jimnovo.com/2010/01/21/acting-on-buyer-engagement/
    http://www.jimnovo.com/newsletter-8-2006.htm

  • Leonardo Teixeira

    Hi Robert, would you be able o point out what are customary churn rates for stable/consolidated e-commerces?

    • http://rjmetrics.com/ Tristan Handy

      Hi Leonardo! Thanks for the comment.

      Benchmarking churn across all ecommerce businesses isn’t really useful. Imagine one company that sells pool supplies and another one that sells pool tables. Their customers will behave incredibly differently–one will be extremely seasonal and potentially make multiple small purchases, whereas the other will probably only make a single purchase ever.

      Because businesses skew all over the place like this, the best thing to do is to identify your best (highest CLV) customers and look at their repeat purchase rates over the course of some reasonable time period. Then, find customers who are below 50% of that repeat purchase rate. Those are the folks you should worry about.

      Let me know if that makes sense…

      • Leonardo Teixeira

        Thanks it does.