At a glance
GMV Over Time is a Revenue & Sales metric tracked from Alibaba data. It plots gross merchandise value across the trailing period so you can see the shape of demand: steady growth, seasonal swings, or a stall. As an area trend rather than a point reading, it is the backdrop against which order counts, average order value, and fees make sense. The card pairs with Total Revenue and Average Order Value to separate volume effects from price effects. Cross-reference the related cards below for context.
| What it counts | Gross merchandise value over the trailing period as exposed by the Alibaba integration. The metric is computed from the latest available data and refreshed on the standard data refresh. |
| Sample type | Backend API data from Alibaba, refreshed on the standard data refresh. |
| Why it matters | The metric appears in the Revenue & Sales category and complements the sibling cards listed below. The trend shape reveals momentum and seasonality that a single-period number hides. |
| Reading the value | Read the curve, not just the latest point. Compare the recent slope to earlier in the window to judge direction, and cross-reference siblings to explain it. |
| Currency | currency |
| Time window | 90D |
| Alert trigger | - |
| Sentiment key | ali_revenue_trend |
| Roles | owner, finance |
Calculation
Calculated automatically from your Alibaba data by summing the gross merchandise value of orders across each interval in the trailing window and plotting the series. Inputs are the order values the Alibaba integration exposes over the period. The card is an area trend over 90 days rather than a single live value. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading.Worked example
A representative reading of GMV Over Time for a typical Alibaba supplier. Suppose the 90-day curve sits flat near 120,000 USD per month through January and February, then climbs steadily from early March, reaching roughly 165,000 USD by 12 Mar 26. Reading the shape, the lift lines up with a new wholesale tier launch and a run of RFQs converting to repeat orders. The next question is whether the gain came from more orders or larger ones, which is exactly where Total Transactions and Average Order Value come in. For deeper investigation, use Vortex Mind to attribute the slope change to specific listings or buyer countries; for natural-language exploration, ask Ask Viq what drove the March uptick.Sibling cards merchants should reference together
| Card | Why merchants reach for it |
|---|---|
total-revenue | Revenue & Sales sibling: the period total behind the trend. |
average-order-value | Revenue & Sales sibling: separates price effects from volume. |
total-transactions | Revenue & Sales sibling: order volume driving the curve. |
net-revenue-after-fees-refunds | Revenue & Sales sibling: what the GMV trend nets down to. |
orders-by-buyer-country | Revenue & Sales sibling: which markets shape the trend. |
Reconciling against Alibaba Seller dashboard
Where to look in Alibaba’s own dashboard: Open My Alibaba > Data Insights / Business Analysis and view the sales or transaction trend over a comparable date range. Confirm period boundaries and filter settings match the Vortex IQ profile to reconcile cleanly. Why the Vortex IQ value may legitimately differ:| Reason | Direction | What to do |
|---|---|---|
| Period boundary. Vortex IQ uses a 90-day rolling window by default; Alibaba’s analytics may use calendar months or a different range. | Variable | Match the period range. |
| Time zone. Alibaba uses account time zone; Vortex IQ aligns to your merchant reporting time zone, which can shift orders across interval boundaries. | Marginal | Confirm time zone match. |
| Filter scope. Profile-level filters (storefront, category, test orders) may narrow the Vortex IQ view. | Variable | Match filter settings. |