Note
The Dunning Dashboard gives you accurate insights into failed Payment Recovery and dunning performance. Use it to understand your true Recovery Rate, identify where payment retries succeed or fail, and take targeted action to reduce churn and protect revenue.
Before you start
Check your dashboard version: This guide covers the latest version (V3) of the Dunning Dashboard. If you're using an older version, some features and metrics may appear differently. You can identify V3 by the "Completed their dunning cycle in the period" vs "Entered their dunning cycle in the period" selector at the top.
Permissions required: You need admin access or access to analytics to view the Dunning Dashboard. Learn more about permissions.
Data refresh frequency: The dashboards update every four hours. Data for the current day may lag slightly compared to real-time Shopify reporting.
What you should know: The V3 dashboard uses historical precision to track Subscription Status changes over time. Unlike older versions where data could change retroactively (for example, if a recovered subscription was later cancelled), V3 locks in historical outcomes so your metrics stay accurate and reliable for trend analysis.
Exporting data: You can export the aggregated data as it appears in the tables on the dashboard. Raw, session-level data Exports are planned for a future update.
What is the Dunning Dashboard?
The Dunning Dashboard is your tool for managing failed payments and optimizing revenue recovery. It answers critical questions like:
What's my actual recovery rate for subscriptions that completed their dunning cycle?
How many subscriptions are currently in dunning?
Which retry attempts in my dunning sequence are most effective?
What error codes cause the most payment failures?
How much revenue am I saving through successful payment recovery?
The dashboard helps you identify exactly where to focus your efforts—whether that's adjusting your retry schedule, targeting specific error types with customized messaging, or offering discounts at strategic points in the dunning cycle.
Filters and KPI cards
At the top of the dashboard, you'll find controls for customizing your view:
Date Range: Select the time period you want to analyze
Compared to: Choose to compare your selected period to the previous period or no comparison
Net / Gross: Toggle between revenue after discounts (net) or before discounts (gross)
Daily / Weekly / Monthly: Select the time granularity for viewing data trends
Entered Dunning / Completed Dunning: Choose which cohort to analyze:
Completed their dunning cycle in the period: Shows subscriptions that exited a failed status during your date range, revealing true final outcomes (recovered, actively cancelled, or passively cancelled). Best for analyzing historical dunning performance and calculating accurate recovery rates.
Entered their dunning cycle in the period: Shows subscriptions that entered a failed status during your date range, with their status as of the last day. Best for monitoring recent dunning activity and identifying payment failure spikes.
Recovery Rate: Percentage of subscriptions that successfully recovered (moved from failed to active) after exiting dunning in the last 30 days
Subscriptions Recovered: Real-time count of subscriptions currently in a failed state
Currently in Dunning: Total count of subscriptions recovered in the last 30 days
Recovered Revenue: Total revenue from successfully recovered subscriptions in the last 30 days
Dunning Performance
A time-series graph tracking the daily breakdown of dunning outcomes for your selected cohort and date range. The chart shows the count of subscriptions for each outcome:
Recovered: Subscriptions that successfully moved from failed to active status
Passively cancelled: Subscriptions automatically cancelled after the final billing attempt failed
Actively cancelled: Subscriptions cancelled by the customer during the dunning cycle, before all retry attempts were completed
Still in dunning: Subscriptions currently in a failed state (only appears when viewing the "Entered Dunning" cohort)
Hover over any point on the chart to see the specific breakdown for that day (5). The summary counts on the right show totals for the entire period, with percentage changes compared to your previous period. Use this visualization to spot trends, identify unusual spikes in failures or recoveries, and monitor the overall health of your dunning performance over time.
Retry Progress Funnel
A stacked bar chart and table showing how subscriptions progress through each retry attempt in your dunning sequence. This visualization reveals where recoveries occur and where subscribers drop off.
Total Recovered: Count of subscriptions that entered dunning in the period and successfully recovered.
Total Lost: Count of subscriptions that were cancelled (both passively and actively), with Churn Rate percentage
Revenue Saved: Total revenue generated from recovered subscriptions
Retry: The retry attempt number
Recovered: Count of subscriptions that recovered at this retry stage
Passively cancelled: Count automatically cancelled after this retry
Actively cancelled: Count cancelled by customers at this retry stage
Remaining: Subscriptions still in the dunning process at this stage
Total: Total subscriptions that reached this retry attempt
You can hover any point in the graph (10) to show many subscriptions entered each retry attempt (Retry 2, Retry 3, Retry 4, 5+) and the outcome breakdown at each stage: Recovered (green), Passively cancelled (light purple), Actively cancelled (dark grey), or Total in dunning process (light pink).
Use this graph to identify where major drop-offs occur in your dunning cycle and find opportunities for intervention. For example, if you see a steep drop-off after the third retry, consider targeting the fourth retry with a discount or personalized outreach to improve recovery rates.
Top Error Causes
A table organizing payment error codes by their impact on recovery. For each error code, you'll see:
Percentage distribution compared to all other errors
Count of subscriptions recovered
Count of subscriptions passively cancelled
Count of subscriptions actively cancelled
Count of subscriptions still in dunning
Total subscriptions with that error
This helps you identify which payment failures lead to the lowest recovery rates so you can optimize your strategy, whether that's updating dunning email messaging, adjusting retry timing, or reaching out to customers proactively. Hover over any point in the graph to see a breakdown of what reasons contributed to the total count that day.
Details Breakdown
A detailed table showing the daily breakdown of all dunning metrics for your selected period. For each date, you'll see:
Date: The specific day
Recovered: Count of subscriptions that moved from failed to active status
Passively cancelled: Count of subscriptions automatically cancelled after final retry
Actively cancelled: Count of subscriptions cancelled by customers during dunning
Still in dunning: Count of subscriptions remaining in a failed state
Total: Total subscriptions with dunning activity on that day
Recovered revenue: Revenue generated from recovered subscriptions
This table provides granular, day-by-day data for tracking dunning performance trends and can be exported for custom analysis outside the dashboard. Use it to identify specific dates with unusual activity or to analyze patterns over time.
All Dunning Window Data
A customer-level table showing detailed information for all subscriptions that entered or exited dunning within your selected period. For each subscription, you'll see:
Email: The customer's email address
Error message: The specific payment error that initiated the dunning cycle
Billing attempt date: When the failed payment attempt occurred
Next billing date: When the next retry or billing will occur
Exited status: The current or final status (Still in dunning, Active/Recovered, Cancelled, etc.)
Subscription: Link to view the full subscription details
This table provides subscription-level detail for investigating specific customer cases and understanding individual dunning scenarios. Use it to identify patterns in error types, follow up with specific customers, or export the data for deeper analysis outside the dashboard.