> ## Documentation Index > Fetch the complete documentation index at: https://docs.vortexiq.ai/llms.txt > Use this file to discover all available pages before exploring further. # Average Transaction, Square > Average Transaction for Square stores. Tracked live in Vortex IQ Nerve Centre. How to read it, why it matters, and how to act on it. **Metrics type:** [Supporting Metrics](/nerve-centre/overview#metrics-types-explained) • **Category:** [Payment Gateway](/nerve-centre/connectors#connectors-by-type) ## At a glance > The **average value of a successful Square payment** in the period (total volume divided by transaction count). Square retail typically sits USD 25, USD 60 average ticket; Square Online sits USD 40, USD 90; Square Invoices much higher (USD 200+). Mix-shift between channels moves this number more than any single-channel pricing change. | | | | ------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **What it counts** | `SUM(amount_money.amount) / COUNT(*)` over `/v2/payments WHERE status = COMPLETED`, in each currency separately. | | **API endpoint** | [`GET /v2/payments`](https://developer.squareup.com/reference/square/payments-api/list-payments). | | **Currency** | **Per-currency.** A multi-location US+CA merchant sees USD avg + CAD avg side-by-side, no FX. | | **Refunds** | NOT subtracted (uses gross volume and gross count). | | **Cash inclusion** | Cash transactions counted in numerator and denominator. They tend to pull avg-ticket DOWN (cash is the typical impulse-purchase tender). | | **Channel mix-shift** | The dominant driver of avg-ticket change. A POS-led merchant adding Square Invoices (high avg) pulls the blended figure up; a retail-led one adding more Cash App Pay pulls it down slightly. | | **Subscription rebills** | Counted; rebills typically pull avg-ticket toward subscription-tier price. | | **Tipping** | Tipped industries see avg-ticket include tip (gross of tip). | | **Time window** | `30D vsP`. | | **Alert trigger** | `change >20% vsP` (any direction). Significant moves usually mean channel mix-shift, NOT pricing change. | | **Roles** | owner, finance, operations | ## Calculation Calculated automatically from your Square data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading. ## Worked example The Austin bookshop, 30-day window: ```text theme={null} Square total volume = USD 129,020 Square transactions = 5,649 Average transaction = 129,020 / 5,649 = USD 22.84 ``` By channel: | Channel | Avg ticket | | -------------------- | ---------- | | POS chip + tap | USD 22.92 | | Cash drawer | USD 12.03 | | Square Online | USD 34.80 | | Cash App Pay | USD 33.41 | | POS Apple/Google Pay | USD 21.67 | | Square Invoices | USD 342.86 | | Tap to Pay on iPhone | USD 22.95 | Observations: 1. **Cash drawer drags the average down hard.** USD 12.03 cash avg vs USD 22.92 card-present avg. Pure cash is the small-ticket tender (a single magazine, a paperback, a coffee). If the merchant grew online Cash App Pay (USD 33 avg) and shrank cash drawer, the blended figure would rise materially. 2. **Invoice channel matters more than its count.** 14 invoices at USD 342.86 contribute USD 4,800, which is 3.7% of total volume but pulls the blended avg up by USD 0.75. A 50% increase in invoices would lift avg-ticket by USD 0.40 even if no other channel moved. 3. **Online avg is consistently higher than retail avg.** Standard retail-vs-ecom pattern: walk-in customers buy one or two items; online customers buy multi-item baskets to qualify for free shipping. 4. **Apple/Google Pay avg lower than chip/tap.** Express tap is biased toward small-ticket impulse buys (under USD 25); larger purchases sometimes prompt the customer to use chip-and-PIN out of habit. 5. **Multi-location merchants see different averages per store.** A flagship downtown location sees higher avg-ticket than a satellite suburban store; slice by `location_id` for the per-location read. ## Sibling cards merchants should reference together | Card | Why pair with Avg Transaction | | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------- | | [`squ_total_volume`](/nerve-centre/kpi-cards/square/total-volume) | The numerator. | | [`squ_total_transactions`](/nerve-centre/kpi-cards/square/total-transactions) | The denominator. | | [`squ_top_payment_methods`](/nerve-centre/kpi-cards/square/top-payment-methods) | Tender mix is the dominant driver of avg-ticket change. | | [`squ_volume_trend`](/nerve-centre/kpi-cards/square/volume-trend) | Trend the avg over time to spot mix-shift. | | Stripe [`stripe_avg_transaction`](/nerve-centre/kpi-cards/stripe/average-transaction-value) / Viva [`viv_avg_transaction`](/nerve-centre/kpi-cards/viva-payments/average-transaction) | Cross-PSP comparison. | | Shopify / BC `aov` (average order value) | Commerce-platform AOV; should approximate the online subset of this card. | ## Reconciling against the vendor's own dashboard **Where to look in the Square Dashboard:** > **Reports → Sales → Sales Summary** → "Average sale" tile (with the same date filter). Dashboard's "Average sale" matches this card when the channel filter is "All". **Why our number may legitimately differ:** | Reason | Direction | | --------------------------- | -------------------------------------------------------------- | | Tender filter (Card vs All) | Card-only avg is HIGHER (cash drags down) | | Time zone (Austin vs UTC) | Boundary days | | Refund timing | Same-day refunds: dashboard sometimes nets, this card does not | **Cross-connector reconciliation:** avg-ticket is a useful sanity check across PSPs but legitimately diverges by channel mix. A retail-heavy Square merchant (low avg) plus a SaaS Stripe account (high avg) for the same business will show very different avg-tickets, that's expected. ## Known limitations / merchant FAQs **"Why did my avg-ticket suddenly jump 30%?"** Almost always channel mix-shift. Open [`squ_top_payment_methods`](/nerve-centre/kpi-cards/square/top-payment-methods) and check whether Cash App Pay share dropped, or whether Invoices went up. Pricing changes rarely move blended avg by 30%; mix-shift does. **"Should I exclude cash from this metric?"** Some merchants prefer to. The card defaults to all-tender. If you specifically want card-avg, the underlying field is `source_type` and you can filter `IN (CARD, WALLET, CASH_APP, EXTERNAL)` in your own analysis. **"Does this work per-location for multi-location merchants?"** Yes; the card aggregates by default but the underlying `/v2/payments` rows carry `location_id`. The location-specific breakdown is on the connector roadmap. **"My subscription business has very stable avg-ticket, is that normal?"** Yes. Subscriptions rebill at the same dollar amount every cycle; if your subscriber base is stable in tier mix, the avg-ticket flatlines. **"USD vs CAD locations, single number?"** No, currency-neutral averaging would mislead. The card returns USD avg and CAD avg separately. **"Square Online sales vs in-store, why is the gap so consistent?"** Online customers are price-aware (free-shipping thresholds, basket optimisation); in-store customers are convenience-driven. The gap exists in every retail-plus-ecom dataset and rarely closes. **"Tipping, does it inflate this metric?"** Yes. Tipped industries (restaurants, bars, salons) running Square see avg-ticket include tip. The tip flows in `tip_money` separately but the headline `amount_money` is gross of tip. **"What about refunds, do partial refunds reduce avg?"** No. Refunds are tracked separately. The original payment's full amount stays in this metric. *** ### Tracked live in Vortex IQ Nerve Centre *Average Transaction* is one of hundreds of KPI pulses Vortex IQ tracks across Square 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](https://app.vortexiq.ai/login) or [book a demo](https://www.vortexiq.ai/contact-us) to see this metric running on your own data.