Many teams think of passive churn as purely a payments, or card-level problem, and as a result, they consider "smart" retries to be the ultimate solution.
We've found it's much more balanced in practice. 50% of our recovery comes from retries, and 50% comes from customers updating their payment method.
Why is this?
If you've read about the 4 outcomes, you know there are only 4 outcomes that can follow a failed payment. And if you think about it, 3 of the 4 tend to involve an active customer decision.
So if customer decision making is part of 3 of the 4 outcomes, we're bound to see the same things that affect active churn, having an impact on passive churn as well:
- Sample Size: With a limited number of subscribers experiencing a billing issue, even large companies may notice unpredictable fluctuations in their Recovery Rate.
- Seasonality: Events such as annual holidays, temporary promotions, and surges in new subscribers can affect the Recovery Rate in future months.
- Billing Cycles: Annual or quarterly subscribers renew less often than monthly—and their cards are more likely to get declined. They're also less likely to remain subscribed.
- Customer Acquisition: Customers who subscribe at a large discount or subscribe unintentionally have a higher tendency to churn.
- Service Quality: By improving your product quality, support services, and onboarding experience, you can lower churn rates and increase Recovery Rate.
- Price Points: Customers who subscribe at a lower price can be more likely to churn.
And with retention, your customer segments are all mixed up. Each time period includes a diverse bunch of customers, and those who churn come from different cohorts. Some are on their second monthly order, others are coming up on their annual renewal from that promotion you ran a year ago. This is exactly why you'll see passive churn performance going up and down, even without changes to your recovery efforts.
High-Churn vs Low-Churn Companies
It's why we often see 2 similar companies (ie coffee subscriptions) using an identical recovery process, with drastically different recovery rates: 20% vs 80%.
The 80% Recovery Rate Company:
Customers opt-in to a subscription, and get a limited 10% discount for doing so. Product quality is high, and customers genuinely want to remain subscribed.
The 20% Recovery Rate Company:
Customers don't know they're signing up for a subscription, or they're subscribing to unlock a 40%+ discount while setting a reminder to cancel the subscription before it renews, or even using an invalid card that will surely get declined on the 2nd attempt. Product quality is low, and customers don't tend to stick around. This company thinks they have a payments/declines problem, but they really have a customer loyalty/general churn problem that surfaces as a payments issue. Performance is so much lower than the 80% company, because for 3 of the 4 outcomes, customers are choosing to churn:
- Card Updates: Customers choose not to take action to remain subscribed
- Cancellations: Customers actively click the cancel button
- Passive Churn: Customers choose to ignore their emails
Understanding where your company sits compared to benchmarks is key, and understanding natural variance is really helpful in conducting analysis.
Next Up: Understanding Natural Variance
Once your data is formatted in daily cohorts, with the 4 outcomes broken out, and you've learned about active/passive churn, you're ready to learn more about natural variance.
Without clarity on your natural variance, you're bound to attribute natural ups/downs in performance, to the strategies or tools you're using, when they would have happened anyway.
Learn more about natural variance.
