Payment recovery dashboard Payment recovery dashboard

Payment recovery dashboard

Tyler Yannes Tyler Yannes

Outline:


Dashboard overview

🎉 May 2024 updates  🎉

  • Daily table of subscriptions that entered payment recovery or are currently in payment recovery, and their new status
  • Upgraded error code breakdown table 
  • Distribution graphs for recoveries and cancellations by retry number
  • Recovery metrics using smart retries in the new Payment Recovery tool
  • This dashboard covers payment recovery, the recovery process a subscription enters when they have a failed payment
  • Use this dashboard to understand your risk of passive churn, defined as subscriptions that were cancelled because of failed payments and not actively by the subscriber

Things to keep in mind:

  • Dashboard filters
    • Use the calendar selector to change the date range for this dashboard
    • Adjust the comparison period with the compare to calendar selector
  • Our dashboards update every 4 hours and will likely show a lag compared to Shopify for today's values
  • Hovering over any metric name will display the metric's definition and hovering over the comparison % number will show the compare to value
  • Want a walkthrough of the dashboard? Click the "i" icon button in the upper right hand to trigger a tutorial wizard

Dunning

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Metrics

  • Total dunning amount: The total count of subscriptions that entered dunning in the date range.
  • Entered dunning: The count of all unique subscriptions that entered dunning with at least 1 failed billing attempt in the date range selected.
    • Dunning recovery %: The % of subscriptions that had a failed billing attempt in the date range selected and now has an active subscription status.
    • Dunning recovered revenue: The estimated revenue recovered from subscriptions that were recovered after failing at least 1 failed billing attempt in the date range selected. This revenue total excludes taxes, shipping, and discounts.
  • Passively cancelled: The count of subscriptions that were cancelled after reaching their max number of failed billing attempts in the date range selected.
    • Lost passively %: The % of subscriptions that entered dunning and were cancelled after reaching their max number of failed billing attempts in the date range selected.
    •  Lost revenue: The estimated revenue lost from subscriptions that were cancelled after reaching their max number of failed billing attempts in the date range selected. This revenue total excludes taxes, shipping, and discounts.
  • Actively cancelled: The count of subscriptions that entered dunning and were cancelled manually by the subscriber after at least 1 failed billing attempt in the date range selected.
    • Actively lost revenue: The estimated revenue lost from subscriptions that entered dunning and were cancelled manually by the subscriber before reaching their max number of failed billing attempts in the date range selected. This revenue total excludes taxes, shipping, and discounts.
    • Lost actively %: The % of subscriptions that entered dunning and were cancelled manually by the subscriber before reaching their max number of failed billing attempts in the date range selected.
  • In dunning: The count of all unique subscriptions that are still in the dunning process with at least 1 failed billing attempt in the date range selected and have yet to reach their max failed billing attempts.
    • Remaining %: The % of subscriptions that are still in the dunning process compared to all subscriptions that entered dunning with at least 1 failed billing attempt in the date range selected and have yet to reach their max failed billing attempts.
    • Pending revenue: The estimated revenue lost from subscriptions that are still in the dunning process with at least 1 failed billing attempt in the date range selected and have yet to reach their max failed billing attempts. This revenue total excludes taxes, shipping, and discounts.

Dunning subscriptions graph

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Dunning tab

  • Provides a visual of subscriptions that entered dunning on a specific day and the distribution of their current status of today.

Retry count tab

  • Provides a visual of total failed billing attempts and the retry count distribution to identify where in the payment recovery process.

Dunning subscriptions daily table

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Dunning tab metrics

  • Entered dunning: Count of subscriptions that entered dunning on this date.
  • In dunning: Count of subscriptions that were in dunning on this date; excludes subs that entered dunning on this date.
  • Passively cancelled: Count of subscriptions that were previously in dunning and passively cancelled by hitting the maximum number of failed billing attempts on this date.
  • Actively cancelled: Count of subscriptions that were previously in dunning and actively cancelled their subscription on this date.

Retries tab metrics

  • Successful billings: Total count of successful billing attempts on this date; includes successful billings from subs that were in dunning as well as subs that were not in dunning.
  • Failed billings: Total count of failed billing attempts on this date.
  • Recovered: Count of subscriptions that were in dunning previously and were recovered with a successful billing retry on this date.

Error code reasons table

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Metrics

  • Error code: The error message received from your payment processor for a failed billing attempt
  • Entered dunning: The count of subscriptions that entered dunning with this error message in the date range; if a subscription entered dunning in a prior period but was in dunning in this date range it will be counted towards this total
  • In dunning: Count of subscriptions that were in dunning on this date; includes subs that entered dunning on this date and subs that entered dunning before the start of the date range.
  • Passively cancelled: Count of subscriptions that were previously in dunning and passively cancelled by hitting the maximum number of failed billing attempts on this date.
  • Failed billings: Total count of failed billing attempts on this date.
  • Recovered: Count of subscriptions that were in dunning previously and were recovered with a successful billing retry on this date.
  • Retries: The count of total failed attempts for the entire date range with this error message

Recovered subscriptions

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Metrics

  • Recovered subscription %: The % of all subs that were in dunning in the date range that were recovered in the date range; subscriptions in dunning have a failed status and recovered subscriptions have an Active status
  • Recovered subs by retry #: The distribution of subscriptions in dunning in the date range that were recovered on a certain retry attempt number in the date range

Cancelled subscriptions

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Metrics

  • Cancelled subscription %: The % of all subs that were in dunning in the date range that were cancelled in the date range; subscriptions in dunning have a failed status and cancelled subscriptions have a cancelled status and will include both passively and actively cancelled statuses
  • Cancelled subs by retry #: The distribution of subscriptions in dunning in the date range that were cancelled after a certain retry attempt number in the date range

Billing attempts

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Metrics

  • Successful attempts: The total number of successful billing attempts for recurring orders in the date range selected. This total does not include checkout billing attempts.
    • Successful % of total: The percentage of this scorecard's metric out of total metric.
    • Successful avg per day: The total number metric divided by the number of days in the date range filter.
  • Failed attempts: The count of failed billing attempts for recurring orders in the date range selected compared to all billing attempts. This total does not include checkout billing attempts.
    • Failed % of total: The percentage of this scorecard's metric out of total metric.
    • Failed avg per day: The total number metric divided by the number of days in the date range filter.
  • First failed attempt count: Count of subscriptions that had their first failed attempt in the date range
    • First failed % of total failed: The % of the count of subscriptions that had their failed attempt divided by the total subscriptions in dunning in the date range
    • First failed avg per day: Total subs with first attempt divided by the date range; excludes first failed attempts
  • Failed 2nd+ retry count: Count of subscriptions that had a 2nd (or greater) failed retry in the date range
    • Failed 2nd+ % of total failed: The % of the count of subscriptions that had a 2nd (or greater) attempt divided by the total subscriptions in dunning in the date range
    • Failed 2nd+ retry avg per day: Total subs with a 2nd (or greater) attempt divided by the date range; excludes first failed attempts
  • Recovered subs with smart adjustments: Count of subscriptions recovered in the date range from a smart adjusted, successful retry
    • % of total recoveries w/ smart adjustments: The % of all subscriptions recovered in the date from a successful, smart adjusted retry
    • Avg recoveries per day from smart adjusted retries: Count of subscriptions recovered in the date range from a smart adjusted, successful retry divided by the date range
  • Recovered subs without smart adjustments: Count of subscriptions recovered in the date range from a successful retry that did not have smart adjusted override applied
    • % of total recoveries w/o smart adjustments: % of all subscriptions recovered in the date from a successful, retry that did not have smart adjusted override applied
    • Avg subs recovered w/o SA per day: Count of subscriptions recovered in the date range from a successful, retry that did not have smart adjusted override applied divided by the date range


Successful vs failed charge attempts graph

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Graph description

  • This graph provides daily metrics on total successful vs failed billing attempts.
  • Hovering over a daily column provides the value for that day.

 

FAQs

Why is there a discrepancy between the count of subscriptions with a Failed status and the count of subscriptions that entered dunning?

  • The main metrics at the top of the dashboard are calculated for subscriptions that entered dunning in the date range and breaks up those subscriptions by the status on the day you view the dashboard.
  • Without a date range dimension to filter subscriptions by when they had their first failed payment, it's not possible to show the change in their status from failed to active or cancelled.
  • The daily tables "in dunning" metric displays all subscriptions with a failed status which can be used to identify the count of subscriptions in payment recovery per day.

A lot of my subscribers are passively cancelled. Is there any way to lower that number?

  • Yes! You can update your payment recovery campaign to improve subscriber recovery.
  • Subscriptions are passively cancelled once they have gone through all retry phases configured in your payment recovery campaign i.e. reached the maximum number of billing retry attempts in each phase. 
  • There are a few changes you can make to your Payment Recovery campaign to try to improve results: 
    • Enabling smart retries is one of the most effective ways to boost campaign success. Smart retries allow skio to optimize the time when billing retries are attempted for better results. 
    • Adding additional retry phases or increasing the number of billing retry attempts in your existing phases are both ways to boost recovery by creating more opportunities for successful billing attempts. 
    • Add discount codes to your campaign phases. These discount codes automatically apply to billing retries and can lead to more successful retries because the amount being charged is lower.
  • To learn more about configuring and optimizing your Payment Recovery campaign. Take a look at our recommendations & best practices. 

What is smart adjustment?

  • Subscriptions that had their retry date changed via our Smart Retries feature powered by our advanced data model count towards the Smart Adjustment metric.
  • In our Payment Recovery feature, we have a setting called Smart Retries which leverages our data model to choose when a subscription should be retried to achieve the highest recovery rate.

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