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Card class: Non-HeroCategory: Payment Gateway

At a glance

The count of confirmed GoCardless bank-debit payments in the period. Highly periodic (monthly billing-day clusters for SaaS subscriptions). Each /payments row with status = confirmed is one transaction, regardless of value.
What it countsCOUNT(/payments WHERE status = confirmed). One row per payment, across all schemes.
API endpointGET /payments.
CurrencyCurrency-neutral (count).
RefundsNOT subtracted from the count.
Indemnity claimsA subsequent indemnity / chargeback removes the payment from confirmed and moves to charged_back; this changes the historical count retroactively.
Failed paymentsExcluded. Lifecycle: pending_submission, submitted, confirmed, failed, cancelled, charged_back, paid_out.
Time window30D vsP.
Alert triggerdrop >15% vsP, paired with revenue_trend.
Rolesowner, finance, operations

Calculation

Calculated automatically from your GoCardless data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading.

Worked example

30 days for Northstar Analytics (UK B2B SaaS), 03 Apr 26 to 02 May 26:
SchemeConfirmed paymentsAvg per payment
BACS Direct Debit308GBP 254.55
SEPA Core55EUR 258.18
SEPA B2B12EUR 800.00
---
Total confirmed375-
Reads:
  1. Heavy concentration on BACS billing days. SaaS subscriptions typically bill on the 1st and 15th; the 308 BACS payments are clustered on those two days plus a few smaller mid-month dates.
  2. SEPA B2B count of 12 is small but high-value. Annual prepayments for enterprise customers; once-a-year cycle.
  3. Mandate-active vs payments-confirmed gap of 380 - 375 = 5 customers. Either failed (4 BACS INSUFFICIENT_FUNDS) or still in flight (1 SEPA mandate dispute).

Sibling cards merchants should reference together

CardWhy pair
goc_total_volumeVolume / count = average.
goc_avg_transactionThe per-payment view.
goc_volume_trendDaily count is the cleanest seasonality signal for monthly billing.
goc_success_rateSuccessful / attempted ratio.
Stripe stripe_transaction_countCross-PSP comparison.

Reconciling against the vendor’s own dashboard

Where to look in the GoCardless Dashboard:
Payments → All payments (filter “Confirmed”). Count visible at the top.
Why ours may differ:
ReasonDirection
Time zoneBoundary days
Confirmation lagToday’s submissions confirm in 2, 5 days
Indemnity flipA claimed payment removed from confirmed retroactively
Cross-connector reconciliation: for SaaS merchants running both GoCardless and Stripe, the sum of payment counts should equal the active customer count × billing frequency, less churn.

Known limitations / merchant FAQs

“Why is the count clustered on certain days?” SaaS subscriptions bill on fixed days (1st, 15th, anniversary date). DD volume is highly periodic vs card volume which is more uniform across the month. “My count dropped 20%, churn?” Possible. Open the underlying mandate count: if active mandates dropped, customers churned. If active mandates held but confirmed payments dropped, mandates are failing (insufficient funds / closed accounts). “Failed payments, do they count here?” No. Only confirmed. Failed are tracked in goc_decline_rate. “Indemnity claim retroactively removes count?” Yes. A BACS indemnity claim flips the original payment to charged_back; the historical count for that period decreases by 1. “Multi-scheme, single count?” Yes; count is currency-neutral. “Mandate count vs payment count, difference?” Mandate count = active subscribers; payment count = transactions in period. A monthly biller with 300 active mandates produces ~300 payments per month. Drop in payment count without drop in mandate count = collection failures. “Multi-month annual contracts, count once or recurrently?” Annual SaaS billed annually = one payment per year per customer. Counts in the month of the annual charge.

Tracked live in Vortex IQ Nerve Centre

Total Transactions is one of hundreds of KPI pulses Vortex IQ tracks across GoCardless and 70+ other ecommerce connectors. Nerve Centre runs the detection layer; Vortex Mind investigates the cause when something moves; Ask Viq lets you interrogate any number in plain English. Start for free or book a demo to see this metric running on your own data.