Case study

How a file-sharing subscription service cut its involuntary churn rate in half.

$22M
Incremental revenue annually
38%
Decrease in churn
2.75x
Increase in payment cure

The situation

The company is a file-sharing subscription service with over 10M paying subscribers and 500M users spread across its consumer and enterprise offerings. The company suffered from high rates of involuntary churn—subscriber drop-off caused by a failure to collect payment on time.

Three main problems:
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    Reduce the number of users failing payments,
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    Appropriately handle users in a delinquent payment state
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    Increase the likelihood that a lapsed user would successfully update their payment information.

In the course of a single year, more than 750,000 paying users and 65,000 paying enterprise accounts failed at least one payment.

The Challenge

Involuntary Churn Due to Failed Payment Collection (involuntary churn comprised 65% of the mix of the company’s overall churn).

The company needed a solution to address the leaky bucket of silently churning users. For every 100 previously paid users, only 35 had explicitly asked to cancel their subscriptions. The company was bleeding users who had not opted in to stop using their product—causing pain both for the company, and for its customers who were unaware that their access to the service was imminently at risk.

The Solution

The company proactively prevented payment lapse by identifying at-risk users and updating payment information prior to scheduled billing dates.

An ML-based approach to scheduling payment collection attempts was implemented—including:

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    Dynamic decline handling based on error codes provided by issuing banks
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    Optimal time of day billing for charge attempts, and
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    Personalized Dunning schedules sorted by card scheme, funding source, and other high-value parameters

The Results

Targeted interventions led to a massive decline in involuntary churn at the company—from 65% of overall churn to just 25% for its enterprise product. The company realized massive improvements in the rate of payment updating for lapsed users—from 10.9% to 33.5% on Day 0 and from 15.7% to 43.4% on Day 24. As a result of these cumulative changes, the company realized a massive benefit in revenue saved that accounted for $22M in top-line annualized recurring revenue—$14M on the enterprise side and $8M on the consumer side of the business.

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    Involuntary churn fell from 65 to 25% of overall volume
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    Payment cure rose from 15.7 to 43.4%
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    Incremental revenue totalled $22M annually

The company is now enabled to better serve recurring customers and spare users the inconvenience of being involuntarily kicked off a service they rely upon for every day productivity.