At a glance
The shape of your Amazon sales over the period, plotted as an area chart. Where Total Revenue gives you one number, this gives you the trajectory: the ramp into a promotion, the cliff after a stockout, the weekly rhythm, the slow decay of a fading hero ASIN. It is the card you scan first to know whether the business is accelerating, flat, or sliding, and where on the timeline something changed.
| What it plots | Ordered product sales over time across the selected window, drawn as an area chart so the trend and the cumulative shape are both visible at a glance. |
| Revenue basis | Ordered product sales (gross of Amazon fees and refunds), the same population as Total Revenue, just resolved over time instead of summed to a single figure. |
| Granularity | Daily points across the 90D window by default, so weekly seasonality (weekend lift, midweek dip) and one-off spikes are both legible. |
| What it reveals that a single number cannot | The when and shape of change: a sharp drop on a specific day (suppression or stockout), a step change (price or listing edit), a gentle slope (rank erosion), or a promo spike and its post-promo trough. |
| Fulfilment scope | FBA and FBM ordered product sales combined, matching the headline revenue population. |
| Fees / refunds | Gross. This is the demand line, not the banked line. For post-fee and post-refund trajectory use Net Revenue (after fees + refunds). |
| Anomaly partner | The trend is the human-readable view; Sales Volume Anomalies is the automated detector that flags statistically unusual points on this same series. |
| Time window | 90D (the selected period) |
| Alert trigger | Configurable on trend movement |
| Roles | owner, finance |
Calculation
Calculated automatically from your Amazon Seller Central 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 supplements seller reading the 90D area chart on 01 May 26 (window 01 Feb 26 to 01 May 26). Figures are illustrative.| Phase on the chart | Dates | Daily revenue (approx) | What the shape shows |
|---|---|---|---|
| Steady baseline | 01 Feb to 28 Feb | $3,800/day | Healthy weekly rhythm, weekend lift |
| Promo spike (Prime-style deal) | 01 Mar to 03 Mar | $9,500/day peak | Sharp area spike, then a post-promo trough |
| Post-promo trough | 04 Mar to 10 Mar | $2,900/day | Pull-forward demand dip, recovers within a week |
| Stockout cliff | 22 Mar to 02 Apr | $700/day | Near-vertical drop, the hero ASIN ran out |
| Recovery | 03 Apr onward | $3,600/day | Climbs back as stock and rank rebuild |
- The stockout cliff is the headline. A near-vertical drop on 22 Mar that holds low for ten days is the signature of a stockout, not soft demand. The chart dates it precisely, which is what you need to tie it back to inventory and to estimate the cost. Cross-check with ASINs Stocking Out <7 Days.
- Promo spikes borrow from next week. The 01 Mar deal peaked at $9,500/day but was followed by a trough as demand was pulled forward. Reading the spike without the trough overstates the promo’s true incremental lift.
- Recovery is slower than the fall. The drop was instant; the climb back took weeks. Going out of stock does not just cost the out-of-stock days, it costs rank that has to be rebuilt afterward. That second cost is only visible on the trend, not in a single revenue number.
- This is gross demand, not banked cash. The area shows ordered product sales before fees and refunds. To see what actually lands, overlay Net Revenue (after fees + refunds); the two diverge most during high-return promo periods.
Sibling cards merchants should reference together
The trend tells you when something changed. These tell you what and how much:| Card | Why pair it with Revenue Over Time |
|---|---|
| Total Revenue | The single-number summary of this exact series. The trend is the same data resolved over time. |
| Sales Volume Anomalies | The automated flagger for the unusual points you spot by eye on this chart. |
| Orders | The volume side. A revenue dip with steady orders means AOV fell; a dip with falling orders means demand fell. |
| Net Revenue (after fees + refunds) | The banked-cash version of this trend. Overlay to see fee and refund drag over time. |
| ASINs Stocking Out <7 Days | Explains the cliffs. Most vertical drops on this chart trace to a stockout. |
| Organic vs Ad Sales Share | Decomposes the trend into paid and organic so you know whether growth is bought or earned. |
Reconciling against Amazon Seller Central
Where to look in Seller Central: The closest Amazon-native views are:Reports → Business Reports → Sales and Traffic (the by-date view shows ordered product sales per day), and the Sales Dashboard on the Seller Central home, which plots a comparable sales-over-time chart.The Business Reports by-date export is the cleanest reconciliation source: set the same date range and the daily ordered-product-sales series should track this card’s shape closely. Timing, settlement, and reporting-lag table:
| Topic | Detail |
|---|---|
| Timezone | Amazon’s Business Reports use the marketplace’s local time. Vortex IQ uses UTC for day boundaries, so individual daily points can shift slightly across midnight, the overall shape is unaffected. |
| Ordered vs shipped | This card plots ordered product sales (by order date). Some Amazon views default to shipped or settled date, which shifts the curve by the fulfilment lag, most visible right at the trailing edge. |
| Today is incomplete | The most recent point is a partial day and will rise as orders land. Read the trend, not the final partial bar. |
| Multi-marketplace | If you sell across marketplaces, read per marketplace; the card does not FX-normalise multiple currencies into one trend line. |
| Reason | Direction | Why |
|---|---|---|
| Ordered vs shipped/settled date | Curve shifts at the edge | If the Amazon view you compare uses shipped or settled date, its curve lags this card’s ordered-date curve by the fulfilment window. |
| Timezone boundaries | Daily points shift | UTC vs marketplace-local day boundaries move a handful of orders across adjacent days. The shape holds; individual bars wobble. |
| Partial latest day | Latest point lower | The newest point is incomplete until the day closes and webhooks fully settle. |
| Currency aggregation | Shape mismatch multi-market | Summing multiple currencies into one trend is not meaningful; read per marketplace. |
| Card | Expected relationship | What causes legitimate divergence |
|---|---|---|
amazon.total_revenue | Same data, two views. The area under this curve over the window equals Total Revenue for the same window. | Edge effects (partial latest day, timezone) cause tiny differences; the totals reconcile over a closed window. |
shopify.total_revenue trend | Cross-channel demand shape. For sellers on both, overlaying the two trends shows whether a promo on one cannibalised the other or grew the total. | Independent populations; a shared promotion may move both, but the channels are otherwise separate. |