Missing out on revenue due to declined credit card payments can be a frustrating experience. You've done the hard work of acquiring a customer who wants the product, yet passive churn can still happen for reasons outside of your control.
Common reasons for declined payments include insufficient funds, potential fraud flagged by the bank, and incorrect card details. While declined payments are an unavoidable part of any business, Ordergroove makes it easy to recuperate revenue using Recovery Optimizer, accessible in Ordergroove under Settings, Payments.
Auto-optimize (Recommended)
💡 Recent Updates
Recovery Optimizer is currently being upgraded for Shopify merchants, and we’re scoping improvements for non-Shopify stores. You may notice better recovery rates as we continue refining the retry cadence. This feature is actively being tested and improved.
The Auto-optimize mode uses intelligent payment recovery strategies tailored to your specific transaction patterns. Our system adjusts retry timing and frequency based on factors like payment method type, error type, and other signals to maximize recovered revenue.
What to expect:
- Retry schedules are optimized automatically and may change over time as we refine our approach
- The system may run experiments to improve recovery rates
- Different strategies may be applied based on the specific payment failure reason
- You don't need to manage or configure anything - the system works on your behalf
This dynamic approach leverages payment best practices and analysis of merchant data to increase the chances of successful recovery, such as retrying after typical pay cycles when cardholders are more likely to have sufficient funds.
Note: We recommend sticking with Auto-optimize. The system is designed to balance maximizing recoveries while minimizing drawbacks like card authorization fees, fraud flagging, and customer complaints.
The Auto-optimize mode pairs payment best practices with analysis of merchant data to maximize recovered revenue. With this schedule, your payments will be retried 5 times over a span of at least 15 days, increasing the chances of retrying after a pay cycle when the cardholder has sufficient funds. This schedule also has custom targeting for hours and days of the week that are more likely to yield a successful recovery.
The default cadence provided by Recovery Optimizer weighs the benefits of increasing the retry attempts with the drawbacks of retrying an order too many times. Some drawbacks of retrying an order in excess include card authorization fees, fraud flagging, and customer complaints.
Note: We recommend sticking with the default settings. The default cadence provided by Recovery Optimizer weighs the benefits of increasing the retry attempts with the drawbacks of retrying an order too many times. Some drawbacks of retrying an order in excess include card authorization fees and customer complaints.
Enhanced auto-optimize features with dynamic retry strategies are coming soon to all platforms.
Manual-optimize: Customizing your payment retry schedule
If you choose not to use the auto-optimized schedule, you can still customize these settings and analyze how different schedules impact the payment recovery rate.
The above chart outlines the typical range of orders that are recovered on each retry attempt. It provides a helpful starting point for new merchants when establishing a retry strategy. Each attempt recovers a positive percentage of orders. Additionally, as the number of attempts increases the likelihood of recovering a payment decreases.
To manually optimize, you can adjust any of the following retry settings and then perform pre/post analyses to monitor the impact on your revenue recovery rate.
For example, let's say you have a current retry schedule of 2 retry attempts every 2 days and want to explore how much the recovery rate improves if you increase rejected orders to retry 3 times every 3 days.
- First, update the retry schedule through the Payment Settings page.
- Next, wait for a full retry window to pass for results to mature before analyzing. A retry window is the length of time that passes until the last retry attempt triggers and the retry flow for a single order completes (i.e. it is the total attempts multiplied by the days interval).
- Finally, dig into the recovery results in the Order Analytics tab.
The recovery rate chart above shows trends over time, so you can compare recovery rates before and after the retry schedule was updated.
The chart above shows the percentage of orders recovered on each retry attempt, so you can see the additional gains of each retry.
Pro tip: When viewing recovery data, filter to only include dates in the past when the recovery window is complete.
Advanced Retry Customizations (Early Access)
Coming soon: Advanced Retry Customizations. This feature will let you build your own retry playbook with full control over error reasons, timing, and retry frequency—helping you recover more revenue with a strategy that fits your business.
🛠️ Early Access
Advanced Retry Customizations currently in a closed Alpha for Shopify merchants. If you're interested in being in the alpha, please reach out to your CSM.
Additional Information
For more information about understanding declined payments and increasing recovered revenue, take a look at Handling Rejected Payments. If you have any questions or want a second opinion on your settings, please reach out to support and we'll be happy to help.