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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.

Approval Rate tab allows you to evaluate the effectiveness of your routing rules and fallback strategies by tracking conversion metrics at a granular level.

Smart Splitting tab shows whether automatic split adjustment improves your approval rate and by how much, compared with distributing the same traffic evenly across the segments of a route.

Use the available filters at the top of the page to refine your analytics by Channel, Payment method group, and Configuration. Only traffic processed by routes while Smart Splitting was enabled is included.

Data on this tab is not real time. New transactions appear in Smart Splitting analytics with a delay of 3 to 5 hours.

The tab has two levels:

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.

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

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

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

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.

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

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

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

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.

Smart Splitting metrics compare what happened on a route with a what-if baseline. The baseline uses the same traffic and the same segments with the same approval rates, but splits traffic evenly across the segments.

Everything is calculated only for auth attempts processed while Smart Splitting was enabled on the route.

Orders optimized is the number of auth attempts processed by routes with Smart Splitting enabled in the selected scope and period.

Approval rate is the percentage of successful auth attempts among all auth attempts on routes with Smart Splitting enabled.

Calculation formula:

Approval rate = (successful auths on the route ÷ all auths on the route) × 100

Where:

• An attempt counts as successful if it was approved at any step of the segment it entered

Equal-distribution approval rate is the approval rate the route would have had if its traffic were split evenly across the segments that processed traffic in the period, keeping each segment’s actual approval rate. The route approval rate chart shows it as the equally distributed line.

Calculation formula:

Equal share = route auths ÷ number of segments with traffic

Baseline approvals = sum over those segments of (equal share × segment approval rate)

Equal-distribution approval rate = (baseline approvals ÷ route auths) × 100

Where:

• Only segments that processed traffic in the period are counted. A segment with zero traffic has no approval rate and is left out of the baseline
• If the route structure changed during the period, the baseline is calculated separately for each stretch with an unchanged structure and then summed

Approval rate uplift is the difference between the actual approval rate and the equal-distribution approval rate. Hub shows it in percentage points with the pp suffix.

Calculation formula:

Approval rate uplift = Approval rate − Equal-distribution approval rate

Where:

• A positive value means Smart Splitting approved more auth attempts than an even split would have approved

Gross uplift is the monetary value of the additional approvals attributed to Smart Splitting, in the selected display currency.

Calculation formula:

Gross uplift = (actual approvals − baseline approvals) × average value of an approved transaction

Average value of an approved transaction = total value of approved transactions on the route ÷ number of approved transactions

Where:

• Actual approvals are the successful auths on the route
• Baseline approvals are the approvals the equal distribution would have produced

One route, one day, two segments. Segment A processed 150 auths and approved 135, which is 90%. Segment B processed 50 auths and approved 15, which is 30%.

Orders optimized = 150 + 50 = 200.

Approval rate = (135 + 15) ÷ 200 × 100 = 75%.

Equal share is 200 ÷ 2 = 100 auths per segment, so baseline approvals are 100 × 0.90 + 100 × 0.30 = 120. Equal-distribution approval rate = 120 ÷ 200 × 100 = 60%.

Approval rate uplift = 75% − 60% = 15 percentage points, which is 30 extra approvals.

If the 150 approved transactions were worth $300,000 in total, the average approved transaction is $2,000. Gross uplift = 30 × $2,000 = $60,000.

• A bucket with no traffic is shown as zero, not as 0% approval.
• The equal-distribution line is calculated per bucket, so summing it across buckets does not necessarily equal the figure for the whole period. Both are correct and answer different questions. Plain counts such as orders, approvals, and per-segment volumes always add up.