At a glance
Daily booked revenue over the last 90 days, plotted as an area chart. The shape of the curve answers “are we accelerating or decelerating?” without needing a calculator.
| What it counts | SUM(Transaction.Amount) for revenue-class GL accounts, posted, daily-bucketed across the last 90 days. Same definition as Revenue Booked into GL but as a time series rather than a single headline. |
| Tax treatment | Net of tax. |
| Shipping | Included if mapped to revenue accounts. |
| Refunds / Credit Memos | Deducted on posting day (not original Invoice day). This is correct for trend reading; refunds are a current-period economic event. |
| Cancelled / voided orders | Excluded by definition. |
| Currency | OneWorld: reporting currency at transaction-date FX. Single-subsidiary: native currency. |
| Subsidiary scope | Respects dashboard filter. |
| Granularity | Daily by default. Switchable to weekly or monthly via dashboard control. |
| Time window | 90D rolling |
| Alert trigger | None at headline (the Revenue Booked into GL card carries the alert) |
| Roles | owner, finance |
Calculation
Calculated automatically from your NetSuite data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading.Worked example
A UK omnichannel apparel brand on NetSuite OneWorld. The 90-day window covers 12 Jan 26 to 12 Apr 26.| Month | Revenue booked (GBP) | Pattern |
|---|---|---|
| 12 Jan 26 to 11 Feb 26 | £4,720,000 | January sales surge; weekly Mondays at 2x baseline |
| 12 Feb 26 to 13 Mar 26 | £4,180,000 | Post-sale dip; trough days at 0.5x baseline |
| 14 Mar 26 to 12 Apr 26 | £5,187,000 | Spring season ramp; week-on-week up 4-7% |
- The chart shape tells the story. A flat line is steady-state; an upward sloping line is momentum; a downward sloping line is the warning. The Controller can read it in 5 seconds.
- Weekly cyclicality is dominant. Mondays are the biggest GL-booking day because Friday’s commerce orders flow through the SO-to-Invoice pipeline over the weekend. Sundays are the smallest. The chart smooths this with a 7-day rolling average overlay.
- The post-Christmas dip in mid-Feb is the seasonal trough. Apparel businesses always see this; the trend chart helps the Controller distinguish “expected dip” from “structural decline”.
- Spring ramp from 14 Mar onward shows the business recovering on schedule. WoW growth of 4-7% for three consecutive weeks is healthy; if the slope flattened in week 3, that would warrant investigation.
- Credit Memo deductions create occasional notches. When a large customer return posts (e.g. a £40K wholesale return from a department store), the day shows lower than the rest of the week. The card lets the user hover for the per-day breakdown.
Sibling cards merchants should reference together
| Card | Why pair it with Revenue Trend |
|---|---|
| Revenue Booked into GL | The point-in-time headline. Trend is the shape; headline is the magnitude. |
| Invoiced Revenue | Invoice-only slice of the same trend. Useful for AR-side analysis. |
| Cash Collected | Receipts trend. Lagged by 30-60 days from Revenue Trend. |
| Revenue by Subsidiary | The subsidiary cut. Tells you which sub is driving the trend. |
| Revenue by Class | The Class cut. Most actionable on consolidated trends. |
| Open SO Value | Forward indicator. Open queue today predicts trend tomorrow. |
| shopify.total_revenue / bigcommerce.total_revenue | Commerce-side trend. Compare slopes to detect pipeline drift. |
Reconciling against the vendor’s own dashboard
Where to look in NetSuite:Reports → Financial → Income Statement with period view set to “Last 90 Days” by Day Reports → Sales → Sales by Date for transaction-level daily totalsThe native Income Statement at daily granularity should match this card across the trend line. NetSuite’s chart tools are limited; this card is the rendered view that the Controller would otherwise have to export and chart manually. Why our number may legitimately differ from NetSuite’s reports:
| Reason | Direction | Why |
|---|---|---|
| FX rate cadence | Small | Card uses transaction-date rates per posted line. Some Income Statement renders use period-average. Difference is < 1% unless rates moved sharply. |
| Daily boundary | Small | Card uses subsidiary base time zone for daily buckets; user time zone may shift 1-day for late-evening transactions. |
| Subsidiary scope | Either | Card defaults to all subsidiaries; native report typically per-subsidiary. |
| Credit Memo posting day | Either | Card uses the Credit Memo’s posting date, not the original Invoice date. NetSuite reports follow the same convention. |
| Period close lock | None | Closed periods are immutable; trend can be replayed identically. |
| Card | Relationship | Why |
|---|---|---|
| shopify.total_revenue | Same trend with offset | Shopify shows commerce gross. NetSuite trend lags by ship-to-bill cycle. The slopes should be parallel; persistent divergence is a signal. |
| bigcommerce.total_revenue | Larger lag | B2B BC orders take longer to bill, so the trend lag is wider. |
| adobe_commerce.total_revenue | Similar to BC | Wholesale orders queue similarly. |
| stripe.stripe_total_revenue | Stripe-routed slice | Comparing slopes detects payment-mix shifts. |