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Recurly Launches Machine Learning-Powered Revenue Optimization Engine

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Recurly has unveiled a machine learning-based Revenue Optimization Engine, designed to repair transaction declines and help businesses boost their monthly revenue.

The Revenue Optimization Engine provides businesses with the ability to:

  • Repair failed transactions: Using machine learning to craft an optimal retry schedule tailored to each individual declined transaction, resolving credit and debit card payment issues more quickly.
  • Minimize involuntary churn: When not managed appropriately, declined transactions can lead to involuntary subscriber churn, which can cause otherwise-satisfied subscribers to be lost. The engine can help subscription businesses minimize involuntary churn by resolving a greater number of declined transactions in a shorter amount of time.
  • Streamline the customer experience: The Revenue Optimization Engine reduces the number of emails, texts or alerts asking subscribers to update billing info or resolve a problem with their payment.  This allows subscription businesses to focus on subscriber satisfaction efforts rather than payment questions. 

Because subscription businesses rely on recurring revenue, improvements made during each billing cycle have a compounding effect over time on subscriber retention and total recurring revenue.

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