At a glance
Daily Square payment volume across all channels, plotted over the period. The single most useful card for spotting weekend-vs-weekday seasonality, holiday pulls, or sudden cliff-drops (POS terminal outage, Square Online site issue, payment-route degradation).
| What it counts | SUM(amount_money.amount) per day, where status = COMPLETED, on /v2/payments. Plotted as a 30-day line by default. |
| Currency | Per-currency line. Multi-location US+CA merchants get two lines. |
| Channels | Unified by default; can be split POS / Online / Invoices in the drilldown. |
| Refunds / disputes | NOT subtracted from the daily volume. |
| Day boundary | UTC by default; a Texas merchant’s “Saturday” is approximately 06:00 Saturday UTC to 06:00 Sunday UTC. |
| Time window | 30D (with vsP overlay). |
| Alert trigger | cliff drop >40% day-over-day (driven by revenue_trend); also negative slope >15% week-over-week. |
| 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
30 days of the Austin bookshop, daily volumes (representative shape):| Day pattern | USD volume | Notes |
|---|---|---|
| Mondays | ~ 3,400 | Slow-day baseline |
| Tue, Wed, Thu | ~ 3,800, 4,200 | Normal weekday |
| Fridays | ~ 5,200 | Pre-weekend spike |
| Saturdays | ~ 7,800 | Peak day |
| Sundays | ~ 5,400 | Brunch-hour spike, slower afternoon |
- Day 14 cliff drop to USD 1,100. Saturday 16 Apr 26, lower-than-Sunday volume. Investigation in
squ_decline_rateshowed the chip reader had an EMV firmware fault for 4 hours mid-day; ~120 attempted card-present payments fell back to cash or were lost. - Day 22 spike to USD 12,400. Saturday 23 Apr 26, double normal Saturday. Local independent-bookshop-week event drove walk-in foot traffic. Volume held but avg-ticket dropped (more low-value impulse browsers).
- Online slope rising 8% week-over-week. Square Online’s portion of daily volume climbed steadily over the 30 days; this is structural (post-launch ramp from a recent SEO push), not a one-off.
- No Sunday-evening dropoff. A typical retail-only POS would see Sunday evening go quiet from 17:00 onward. Ravenwing stays open Sunday 12:00, 18:00 and the curve respects that.
- The trend in dollar terms hides count vs avg movement. Pair this card with
squ_total_transactionstrend to see whether growth is more transactions or higher tickets.
Sibling cards merchants should reference together
| Card | Why pair |
|---|---|
squ_total_volume | This card is its daily-resolution view. |
squ_total_transactions | Pair to read whether trend is volume-led or count-led. |
squ_decline_rate | Cliff drops here usually pair with decline-rate spikes. |
squ_avg_transaction | Slope of avg-ticket vs slope of count tells you if you’re growing baskets or footfall. |
Stripe stripe_revenue_trend | Cross-PSP daily comparison. |
Reconciling against the vendor’s own dashboard
Where to look in the Square Dashboard:Reports → Sales → Sales Summary with “Daily” granularity.The Dashboard renders the same shape; numbers should match within timezone tolerance. Common divergences:
| Reason | Direction |
|---|---|
| Time zone | Boundary-day shift (Austin vs UTC = 5h) |
| Tender filter | Cash inclusion vs Card-only |
| Refresh lag | Today’s last few minutes may be missing |
Known limitations / merchant FAQs
“Daily volume looks fine but my deposits are lumpy, why?” Square deposits are T+1 by default. Saturday’s volume hits your bank on Monday (Sunday deposits are batched on Monday in many regions). Volume trend reads transaction date; deposits read settlement date. “Why is Sunday lower than Saturday for retail?” Universal in retail: Saturday is errand day, Sunday is family / leisure day. The exception is restaurants and brunch-led businesses where Sunday brunch peaks higher than Saturday. “Should I trust the very latest day on the curve?” The freshest 5, 15 minutes may be missing due to sync lag. The latest day’s value will catch up overnight. “Cliff drops in one channel only, what to look at?” If POS dropped but Online held, the issue is hardware. If Online dropped but POS held, the issue is the website. Checksqu_decline_rate sliced by source_type.
“Promotional spike, will it be flagged as anomaly?”
The alerting is direction-aware: drops alert, spikes don’t. A 2x Saturday from a local event won’t ping.
“Can I get an hourly trend?”
Roadmap. The underlying /v2/payments carries created_at to second resolution; surfacing hourly is straightforward but not yet exposed.
“Does this include offline-mode transactions?”
Yes, once they upload. Offline-mode transactions carry the original transaction time, so they backfill the curve correctly when sync catches up.
“Multi-location stores, do I see per-location trend?”
Aggregate by default; per-location slicing via location_id is on the connector roadmap.