The Decline Recovery Dashboard answers one question: how much revenue are you getting back through retries, and how much are you still leaving on the table?
When an authorization is declined, most merchants retry it. This dashboard separates what was approved on the first attempt from what was recovered afterwards, so you can see the value your retry strategy is actually adding rather than just your headline approval rate.
Read this before the numbers. This dashboard counts at two different levels. Some metrics count authorization attempts; others count unique orders. One order can carry several attempts, so the two will never reconcile and are not meant to. The section below explains which is which.
Understanding the four levels
Every metric here belongs to one of four groups. Knowing which group a number came from is the difference between a useful read and a misleading one.
|
Level |
Counts |
What it answers |
|---|---|---|
|
Overall |
Authorization attempts, not deduplicated |
How did our authorization traffic perform in raw terms? This is the level that matches the Authorizations dashboard |
|
Orders |
Unique orders |
What share of customers ultimately got through, regardless of how many tries it took? This is the number closest to realised revenue |
|
Initial |
First attempts only |
How well does our authorization perform without any retry help? |
|
Retry |
Unique orders that needed more than one attempt |
How much did retries recover that would otherwise have been lost? |
The relationship between the last three is what the dashboard exists to show. Initial is your floor, Orders is your ceiling, and Retry is the gap between them. If Initial and Orders are close together, retries are adding little.
KPI Section
KPIs are based on the last complete month of data and are not affected by any date range control on the page. Each tile carries an info tooltip, a month-over-month comparison with a coloured arrow, and a sparkline.
The tiles sit behind three tabs. A metric you expect is almost certainly on another tab rather than absent.
Orders tab
Order-level outcomes, deduplicated. Start here for the headline.
|
KPI |
Description |
|---|---|
|
Orders |
Total unique orders in the period |
|
Order Approval Count |
Unique orders that were approved |
|
Order Approval Amount |
Total dollar value of approved orders |
|
Order Approval Rate |
Order Approval Count ÷ Orders. The share of customers who eventually got through |
Initial tab
First-attempt performance, before retries do any work.
|
KPI |
Description |
|---|---|
|
Initial Attempts |
Count of first authorization attempts |
|
Initial Approval Count |
Transactions approved on the first attempt |
|
Initial Approval Amount |
Dollar value captured immediately on the first try |
|
Initial Approval Rate |
Initial Approval Count ÷ Orders. Note the denominator is total orders, not initial attempts, so this is directly comparable with Order Approval Rate |
Retry tab
What the retries recovered. This tab carries five tiles, one more than the others.
|
KPI |
Description |
|---|---|
|
Retry Attempts |
Unique orders that were retried at least once. Not a count of retry authorizations |
|
Retry Approval Count |
Unique orders approved after the first attempt, excluding those already approved on the first try |
|
Retry Approval Amount |
Dollar value recovered through subsequent attempts |
|
Retry Approval Rate |
Retry Approval Count ÷ Retry Attempts. Of the orders that needed a retry, how many were rescued |
|
Retry Uplift Rate |
Order Approval Rate − Initial Approval Rate. This is the single number that quantifies what retries are worth. A positive value is the percentage points of approval your retry strategy added |
Retry Approval Rate and Retry Uplift Rate answer different questions and can move in opposite directions. A high Retry Approval Rate on a small number of retried orders produces very little uplift. Read them together.
Charts Tab
Eight charts, each with its own controls. The Date Range for Charts defaults to the last 6 months including the current month and, as the on-screen note says, does not apply to the KPIs above.
They fall into three groups: how approval is trending, how recovery builds up attempt by attempt, and where recovery is happening across your business.
How approval is trending
1. Approval Rate by Month
A line per approval rate, with all three plotted by default: Order Approval Rate, Initial Approval Rate, and Retry Approval Rate. The Type control lets you drop any of them.
The gap between the Order and Initial lines is your retry uplift drawn out over time. If that gap is narrowing, retries are losing effectiveness even when the headline approval rate looks stable.
2. Orders Approved by Month
Approved order volume over time, stacked by which attempt approved the order. The 0 segment is orders approved first time; 1 is orders rescued by the first retry, and so on, with the smallest contributors collected into Others.
This is the clearest picture of where your approvals actually come from. A thick 0 segment with thin bars above it means retries are rescuing very little. Controls: a Count Vs Amount toggle defaulting to Amount, and Top N defaulting to 15.
3. Retry Uplift
A full-width combination chart: Retry Approval Amount as bars against Retry Uplift Rate as a line. Use it to check whether recovered value and recovery effectiveness are moving together. Falling bars with a steady line means less volume needing rescue; falling bars with a falling line means retries are genuinely working less well.
How recovery builds up, attempt by attempt
4. Cumulative Approvals
A waterfall running from the first attempt through each successive retry to a Total. Each step shows how many additional approvals that attempt number contributed.
This is where you decide how many retries are worth making. Once the steps flatten out, further attempts are adding almost nothing. Controls: Top N defaulting to 15, and a Count Vs Amount toggle defaulting to Count.
5. Recovered at Each Retry
For each attempt number, the split of outcomes into Approved, Declined, and Unknown. Where Cumulative Approvals shows what you gained, this shows the success rate at each stage, so you can see how quickly the odds fall away with each retry. Controls: Top N defaulting to 5, and a Count Vs Amount toggle defaulting to Count.
Where recovery is happening
6. Order Approval Rate by Acquirer
One line per acquirer, so you can see whether a dip is across the board or confined to a single processor. Controls: Type, Group, Top N defaulting to 10, and Date Granularity.
7. Order Approval by Count & Acquirer
Approved order volume by month, stacked by acquirer. Read it alongside the chart above: the rate chart tells you who is performing badly, this one tells you whether they carry enough volume for it to matter. Controls: Type, Measure, Group, Top N defaulting to 10, and Date Granularity.
8. Order Approval Count by MID and Card Funding Source
A horizontal bar chart with two grouping levels, showing approved orders per MID split by card funding source (credit, debit, prepaid, and so on). Use it to find whether a recovery problem is concentrated in one merchant account or one card type. Controls: Type, Measure, Group 1, Group 2, and Top N defaulting to 10.
Time Trends Tab
A focused trend view with a single Type selector, so you can follow one level at a time rather than comparing all three at once. It has its own Date Range for Time Trends control, independent of the Charts tab.
This tab measures dates differently from the rest of the dashboard. An order retried across a month boundary can therefore land in a different month here than it does elsewhere on the page. This is expected behaviour, not a data error.
Retry Data Tab
Two tables, with a shared Date Range for Retry Data control.
The first table breaks retry performance down by your chosen dimensions, with Group 1, Group 2, and a Top N defaulting to 15. Use this when the Retry KPIs have told you recovery is weak and you need to know where. Grouping by acquirer, issuer, or decline reason is what turns "our retry uplift dropped" into something a routing or retry-logic change can act on.
The second table shows the five retry measures as rows against periods as columns, with Groups set to None by default and Top N defaulting to 10. This is the quickest way to read Retry Attempts, Retry Approval Count, Retry Approval Amount, Retry Approval Rate, and Retry Uplift Rate side by side over time.
Top N on this tab ranks by Retry Attempts regardless of what you are grouping by, and the two tables do not target the same grouping level: one applies Top N to Group 2, the other to Group 1. Set your grouping before applying Top N, and see Top N Filter for the per-table breakdown.
Order Data Tab
Two order-level tables with a shared Date Range for Order Data control. Use them to work from the order records behind the Orders KPIs, or to export for analysis outside Harmonize.
Top N here ranks by Orders and targets Group 1.
Filtering Tips
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Four independent date controls. Charts, Time Trends, Retry Data, and Order Data each have their own, all defaulting to the last 6 months including the current month. Changing one does not change the others, so check the control on the tab you are actually reading.
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The KPIs ignore all of them. KPI tiles always show the last complete month. If a KPI and a chart disagree, this is the first thing to check.
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Top N defaults vary across the page, and so does what it ranks by. Orders Approved by Month and Cumulative Approvals default to 15; Recovered at Each Retry defaults to 5; the acquirer and MID charts default to 10. The Orders Approved chart follows your Count Vs Amount toggle, the Retry Data tables rank by Retry Attempts, and the Order Data tables rank by Orders. Top N Filter has the full table, including a Decline Recovery section.
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Date Granularity defaults to Month, switchable to Yearly, Quarterly, Weekly, or Daily. The most recent period is usually partial, so the final point often sits below trend simply because the month is incomplete.
Use Case Example
"Our approval rate looks flat, but is our retry strategy still earning its keep?"
Open the Retry KPI tab and read Retry Uplift Rate. This is the percentage points of approval that retries added last month
Compare it against Retry Approval Rate. A healthy retry rate with low uplift means few orders are reaching retry at all, which is a different problem from retries failing
On the Charts tab, watch the gap between the Order and Initial approval rate lines over six months. A narrowing gap means retries are recovering less than they used to
Use Cumulative Approvals to see how many attempts are still worth making. If the steps flatten after the second retry, attempts beyond that are costing you more than they return
Move to Retry Data and group by acquirer or decline reason to find where recovery is falling off, then take that to your retry logic or routing owner