Monitor payment routing analytics with connector-level success rates, decline breakdowns, and performance trends for data-driven tuning
Orchestration analytics in the Orchestration section of the
Solidgate
Hub gives you a clear, actionable view of how your routing strategy performs in production.
Use analytics to monitor routing and segment efficiency, compare connector and connector account distribution, and quickly identify where approval rate or volume can be improved.
Analytics overview
Key benefits of orchestration analytics include:
Track and monitor routing and segment efficiency Understand how each route and cascade step performs to identify weak links before they impact conversion.
Control traffic distribution across connectors and connector accounts Compare load and outcomes across connectors to align routing with business and risk goals.
Compare split testing efficiency directly in Hub Evaluate configurations side by side and quickly see which routing logic delivers stronger approval.
Gross volume tab gives you visibility into how your successful payment traffic is distributed across different connectors and payment methods.
Use the available filters at the top of the page to refine your analytics by Channel, Connector, Payment method group, Connector account, Configuration, Configuration version, Analytics Route ID, and Route.
Charts
GV by connector
Compare traffic by connector to spot concentration and underperforming routes.
GV by payment method group
See which methods drive volume and how routing impacts channel mix.
GV by connector account
Track performance at the account level for operational and reconciliation needs.
Approval rate tab allows you to evaluate the effectiveness of your routing rules and fallback strategies by tracking conversion metrics at a granular level.
Use the available filters at the top of the page to refine your analytics by Channel, Connector, Payment method group, Connector account, Configuration, Configuration version, Analytics Route ID, and Route.
Charts
AR by payment method group
Validate routing impacts on approval quality across methods.
AR by configuration routes
Compare route effectiveness to refine rules and priorities.
Route AR breakdown by configuration route segments
Measure cascade efficiency and identify weak fallback steps.
For deeper analysis:
select custom date ranges for granular or broad views
group metrics by daily, weekly, or monthly intervals
filter data by channel, connector or connector account, and any routing entity
select the display currency, the currency selector adjusts all amounts to the chosen currency
You can also combine multiple filters to isolate high-impact routing patterns and quickly validate optimization hypotheses.
For fast navigation, from insight to action, click any entity in the dashboard to jump straight to its
details:
Click a connector account > opens Connector account details in a new tab
Click a routing entity > opens Routing configurations page and highlights essential parameters for faster investigation
Metrics explained
Gross volume is the total monetary value of successfully processed payments, normalized to USD.
It answers how much money moved through routing in a final success state, not how well attempts convert or how customers behave.
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GV by connector charts gross volume for each connector in each date bucket (daily, weekly, or monthly). Share is how much of the bucket total that connector represents. Share is computed separately for each bucket and for this grouping by connector. It is not mixed with other breakdowns.
Calculation formula:
Gross volume = sum of amount_usd for successful transactions in scope.
Share for one connector = (connector volume ÷ total volume of all connectors in the same date bucket) × 100
Where:
amount_usd – transaction amount in USD
Only transactions in a successful final state count toward volume
In scope – successful flows the analytics include, such as card, recurring, wallet payments, MOTO, and related sale actions
Failed, voided, and refunded amounts are excluded from the volume
Date bucket – the grouped interval you selected for the chart
Example
Choose a range from 15 September to 16 September with daily grouping. You get two date buckets, 15 September and 16 September.
Connector A (gross volume per bucket):
15 September: $200
16 September: $900
All connectors combined in the same buckets:
15 September: $500
16 September: $1,200
Share for Connector A is calculated per bucket, not across the whole range at once:
15 September: $200 ÷ $500 × 100 = 40%
16 September: $900 ÷ $1,200 × 100 = 75%
GV by payment method group uses the gross volume and share rules from GV by connector, but groups and compares payment methods, for example Card, Apple Pay, and Google Pay, within each date bucket.
Calculation formula:
Same as GV by connector, with volume and share calculated per payment method group.
Where:
Entity – the payment method group you are viewing
Bucket total – sum of successful amount_usd for all payment method groups in that date bucket
Example
Choose a range from 15 September to 16 September with daily grouping. You get two date buckets, 15 September and 16 September.
Card (gross volume per bucket):
15 September: $200
16 September: $900
All payment method groups combined in the same buckets:
15 September: $500
16 September: $900
Share for Card is calculated per bucket:
15 September: $200 ÷ $500 × 100 = 40%
16 September: $900 ÷ $900 × 100 = 100%, since Card is the only method with volume in that bucket
GV by connector account uses the gross volume and share rules from GV by connector, but groups and compares connector accounts. Row and column totals follow the same bucket rules as the other gross volume views.
Calculation formula:
Same as GV by connector, with volume and share calculated per connector account.
Where:
Entity – the connector account you are viewing
Bucket total – depends on whether you read a cell total for one interval or the overall range, consistent with the table tooltips
Example
Choose a range from 15 September to 16 September with daily grouping. You get two date buckets, 15 September and 16 September.
Connector account A (gross volume):
15 September: $200
16 September: $900
Total for 15–16 September: $1,100
All connector accounts combined:
15 September: $500
16 September: $1,200
Total for 15–16 September: $1,700
Share for Connector account A by bucket:
15 September: $200 ÷ $500 × 100 = 40%
16 September: $900 ÷ $1,200 × 100 = 75%
Overall share for Connector account A across the full 15–16 September range:
$1,100 ÷ $1,700 × 100 = 64.7%
Approval rate is the percentage of successful payment attempts among auth attempts initiated on the merchant side.
It reflects checkout experience, integration quality, and overall payment flow efficiency, not only routing rules.
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AR by payment method group shows approval rate (merchant-side conversion on auth attempts) as the percentage of successful auth attempts out of all auth attempts in each bucket. Settle, void, and refund are excluded from both the numerator and denominator. Each attempt is counted separately, even when several attempts relate to the same order.
The view can also include a decline breakdown for failed auths. Each line shows a reason, Solidgate decline code, count, and percentage share of all declines in that bucket and method.
Calculation formula:
Approval rate = (successful auth attempts ÷ all auth attempts in the bucket) × 100
Decline share for one reason = (declines with that reason ÷ all declined auths in the bucket) × 100
Where:
Counts include only auth type transactions for the selected payment method group and interval
Decline breakdown uses only declined auths when computing each reason’s share
Example
There were 301 auth attempts for Card in a bucket, and 244 were approved. Approval rate is 244 ÷ 301 × 100 ≈ 81.06%.
There were 57 declines in that bucket, and 15 of them used one decline code. Share for that code is 15 ÷ 57 × 100 ≈ 26.32%.
AR by configuration routes lists each configuration and route for the selected period with the number of auth attempts (Orders), Route AR, %, and Route share, % (that route’s share of all auths handled by the configuration). Route share appears as a horizontal bar. The tooltip shows the configuration name, route name, and share percentage. Only auth attempts count. Settle, void, and refund are excluded.
Calculation formula:
Route AR = (successful auths on the route ÷ all auths on the route) × 100
Route share = (auths on the route ÷ all auths for the configuration) × 100
Where:
Both formulas use the same selected date range
Orders in this view = auth attempts in the selected period
Configuration total – all auth attempts processed by that configuration in the period
Example
A configuration processed 1,385 auth transactions in total. One route handled 325 of them with Route AR = 98.46%. Route share is 325 ÷ 1,385 × 100 ≈ 23.47%.
Route AR breakdown by configuration route segments breaks down performance by configuration, route, segment, and cascade step. Step approval rate reflects connector-side technical success for attempts that reached that step, isolated from merchant behavior and cascade design. Certain internal system errors are excluded from the step total. segment AR breakdown, % and Segment approval rate, % describe merchant-side outcomes for traffic that entered the segment. Comparing segment AR breakdown and segment approval rate shows which steps contribute most to final approvals.
Calculation formula:
Step approval rate = (successful connector attempts at the step ÷ adjusted attempts at the step) × 100
segment AR breakdown for a step = (approvals produced at the step ÷ merchant attempts that entered the segment) × 100
Segment approval rate = (merchant attempts that succeeded in the segment ÷ merchant attempts that entered the segment) × 100
Where:
Adjusted attempts – connector attempts at the step, excluding specific internal system errors from the total. This keeps the rate focused on typical connector outcomes. Excluded codes: 7.02 Google payment error, 7.03 Smart cascade decline, 7.07 SCA engine error.
Entered the segment – each merchant attempt is counted once, regardless of retries or steps visited
Succeeded in the segment – eventual success anywhere inside the segment
segment AR breakdown, % – technical declines are not removed from the merchant-side denominator, unlike step approval rate, so the two metrics can differ when many transactions fail before reaching a step
A step can show a high step approval rate but low segment AR breakdown, % if only a small share of segment traffic reaches it
Segment approval rate, % – is at least as high as any single step’s segment AR breakdown, %, because several steps can contribute approvals toward the same segment outcome
Settle, void, and refund are excluded, consistent with other auth-based approval views
Example
200 merchant attempts to enter a segment. At step 1, 160 are approved (segment AR breakdown for step 1 = 160 ÷ 200 = 80%). 40 continue. At step 2, 20 more are approved (segment AR breakdown for step 2 = 20 ÷ 200 = 10%). In total 180 succeed, so Segment approval rate = 180 ÷ 200 × 100 = 90%.
In this same scenario, step approval rate is calculated on traffic that reached each step:
step 1: 160 ÷ 200 × 100 = 80%
step 2: 20 ÷ 40 × 100 = 50%
If some connector attempts at a step fail only due to excluded system errors, step approval rate uses an adjusted attempt total at that step. The failed system-error attempts are not counted in the denominator.
