Overview
Analytics queries return pre-aggregated statistics for a single store. Every analytics query takes:- A store identifier —
storeIdorstoreSlug(top-level argument, at least one required). - A required
filterof typeAnalyticsFilterInput!.
granularity and currency. The time-bucket granularity uses the TimePeriodGranularity enum: DAY, WEEK, MONTH, QUARTER, YEAR, ALL_TIME.
Each analytics query returns a structured object, not scalar totals. Amount fields are returned as display strings. Select the nested fields you need — the examples below show the available shape.
Order Statistics
Order counts, dual-source revenue, and buyer metrics.revenueByCurrency / revenueByPeriod are dual-source: pspTotalAmount is the PSP actual amount, snapshotTotalAmount is the snapshot expected amount, and mismatchCount counts payments where the two disagree.Payment Statistics
Success rate, failure reasons, refunds, method distribution, and tax summary.successRate is an object ({ totalAttempts, succeeded, failed, pending, successRate }), not a scalar.Product Statistics
Product counts, top sellers, and revenue contribution.Trend Analysis
Period-over-period growth, cumulative revenue, and moving averages.Distribution Analysis
Order amount percentiles, average-order-value trend, and amount buckets.Customer Analysis
Cohort retention, LTV distribution, purchase frequency, and top customers.Tax Analysis
Tax amounts by category, rate group, and country, plus B2B/B2C comparison.Subscription Analysis
Billing period distribution, cancellation stats, trial conversion, and churn.Refund Ticket Analysis
Reason distribution, review efficiency, and approval rate.Settlement Analysis
Actual settled amounts sourced from settlement files (post-fee, post-refund). This is the ground truth for reconciliation, distinct frompaymentStatistics.settlementRevenueByCurrency (a PSP projection at payment time).
settlementAnalysis time range is based on the settlement date, not created_at. Additional analytics queries are available depending on your role, including deliveryAnalysis (webhook/email delivery) and payoutAnalysis (payout tickets, scoped to the merchant). Use schema introspection to discover their full field sets.