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.
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.
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.
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.
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.