> ## 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. # Total Orders, BigCommerce > Total Orders for BigCommerce stores. Tracked live in Vortex IQ Nerve Centre. **Metrics type:** [Key Metrics](/nerve-centre/overview#metrics-types-explained) • **Category:** [Ecommerce Platform](/nerve-centre/connectors#connectors-by-type) ## At a glance > **Number of orders placed in the period.** The headline volume metric, paired with `total_revenue` and `aov` to triangulate the three legs of commercial performance. **Orders × AOV = revenue**: when revenue moves, this card and the AOV card together explain whether the move came from volume or basket size. The card is the operational pulse for fulfilment teams (how many packages do we ship today?) and the marketing pulse for acquisition teams (how many customers did we convert this period?). | | | | ---------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **What it counts** | The absolute count of orders with successful payment status (`paid`, `captured`, or `completed`) placed within the current period (default 30 days). Excludes cancelled, refunded (count remains since the order was placed), declined, and incomplete orders that never captured payment. | | **Sample type** | Backend API data from BigCommerce orders, refreshed on the standard data refresh. | | **Why total orders matters** | It is the volume leg of revenue. **Falling orders + rising AOV** means the merchant is losing breadth (fewer customers, possibly higher-value cohort remaining). **Rising orders + falling AOV** means the merchant is winning breadth, often through price-driven acquisition or new-customer surges. **Falling both** is the bad case; **rising both** is the rare healthy growth pattern. The card sits at the centre of the morning operational review for owner, finance, and operations roles. | | **Reading the value** | (1) Compare absolute count to prior period (vsP delta surfaces in `order_count_trend`). (2) Compare against the seasonal baseline (year-over-year for high-seasonality categories). (3) Decompose by channel (`bc_orders_by_channel_id`), country (`bc_orders_by_state`), and device (`bc_orders_by_device`). (4) Cross-reference traffic and conversion to identify which leg of the funnel is moving. | | **Currency** | absolute count. | | **Time window** | `30D vsP`. | | **Alert trigger** | `order_count_trend < -10%` (referenced via the trend card; this card is the absolute view). | | **Sentiment key** | `order_count_trend` (TREND\_BASED; this card displays the absolute, the trend card carries the alert-threshold logic). | | **Roles** | owner, finance, operations | ## Calculation ``` total_orders = COUNT(orders WHERE payment_status IN ('paid', 'captured', 'completed') AND date_created >= period_start AND date_created < period_end) ``` Cancelled, refunded (where the original payment did not actually capture), and incomplete orders are excluded. Refunded orders that did capture payment originally are included in the count (the order was placed; it was later refunded as a separate event tracked by `refund_rate`). ## Worked example A UK-based BigCommerce home-and-garden store, total orders reading on Wednesday 15 May 26. | Metric | Current (15 Apr - 15 May) | Previous (16 Mar - 15 Apr) | YoY (May 25) | | ---------------- | ------------------------: | -------------------------: | -----------: | | **Total orders** | **2,103** | 2,408 | 1,950 | | Sessions (GA4) | 108,142 | 116,540 | 95,200 | | Conversion rate | 1.94% | 2.07% | 2.05% | | AOV | £261.09 | £243.27 | £232.40 | | Total revenue | £549,142 | £585,795 | £453,180 | What the headline reading is telling us: 1. **Total orders: 2,103, down 12.7% vs the prior period, up 7.8% year-over-year.** The store is contracting period-over-period but growing year-over-year. The two readings together suggest the prior period was unusually strong (likely a discount campaign), not that the store is in genuine decline. 2. **Decompose into traffic × conversion:** * Sessions: -7.2% (some traffic loss; check ad spend or organic erosion) * Conversion rate: -6.3% (some conversion drop; check site speed, checkout flow) * Combined effect roughly matches the -12.7% order drop 3. **AOV is rising while orders fall.** This pattern shows in the data: -12.7% orders × +7.3% AOV ≈ -6.3% revenue. **The discount-cycle artefact** is the most likely explanation: prior period had heavy discounts pulling in deal-driven shoppers; current period has none, so only higher-AOV core shoppers are converting. 4. **Year-over-year comparison softens the picture.** 7.8% YoY growth means the underlying business trajectory is healthy. The period-over-period decline is largely a comparison-base effect. 5. **Operational implications:** * **Fulfilment**: 2,103 orders / 30 days = 70 orders/day average shipping load. Confirm fulfilment capacity matches. * **Cash flow**: at AOV £261, total revenue £549K for the period. Compare against payment-processor settlements. * **Customer service**: anticipate ticket volume proportional to order count. 6. **Recommended response (this is the volume reading; trend reading drives the alert threshold):** * Cross-reference `order_count_trend` for alert-threshold-driven alerts. * Decompose by channel via `bc_orders_by_channel_id` to see whether storefront, B2B, or marketplace is moving. * Decompose by country via `bc_orders_by_state` to see whether geographic concentration changed. * If trend is alert-state (below -10%), follow the diagnostic flow on `order_count_trend`. The diagnostic flow: 1. **Read the absolute count.** Compare to expected (90-day baseline + seasonality). 2. **Decompose by channel, country, device.** 3. **Cross-reference traffic + conversion** for upstream causes. 4. **If the trend variant flags red, investigate via the diagnostic flow on `order_count_trend`.** Rapid-response playbook: | Time horizon | Action | | ------------ | ------------------------------------------------------------ | | First 1 hour | Read absolute. Compare to expected baseline. | | First day | Decompose by channel, country, device. | | First week | If trend is red, follow `order_count_trend` diagnostic flow. | ## Sibling cards merchants should reference together | Card | Why merchants reach for it | | ---------------------------------------------------------------------------------------- | --------------------------------- | | [`total_revenue`](/nerve-centre/kpi-cards/bigcommerce/total-revenue) | Revenue companion (orders × AOV). | | [`aov`](/nerve-centre/kpi-cards/bigcommerce/average-order-value) | AOV companion. | | [`bc_orders_by_channel_id`](/nerve-centre/kpi-cards/bigcommerce/bc-orders-by-channel-id) | Per-channel decomposition. | | [`bc_orders_by_state`](/nerve-centre/kpi-cards/bigcommerce/orders-by-state-region) | Per-country/state decomposition. | | [`bc_orders_by_device`](/nerve-centre/kpi-cards/bigcommerce/orders-by-device) | Per-device decomposition. | | [`unfulfilled_count`](/nerve-centre/kpi-cards/bigcommerce/unfulfilled-count) | Open orders awaiting fulfilment. | ## Reconciling against the vendor's own dashboard **Where to look in BC:** Analytics → Orders; Orders list with date filter. **Why our number may differ:** | Reason | Direction | What to do | | ----------------------------------------------------------------------------------------------- | --------- | --------------------------------------- | | **Cancelled order inclusion.** BC may show all orders by default; Vortex IQ excludes cancelled. | BC higher | Apply "exclude cancelled" filter in BC. | | **Test order inclusion.** BC may include test; Vortex IQ excludes. | BC higher | Apply `is_test = 0` filter. | | **Period boundary.** BC defaults to calendar; Vortex IQ uses 30-day rolling. | Variable | Match periods. | | **Channel filter.** Profile-level filtering. | Variable | Match channel filter. | **Cross-connector:** `shopify.total_orders`, `adobe_commerce.total_orders`, `ga.purchase_count`. The GA-recorded purchase count should be within ±3% of BC orders; larger gaps indicate tracking issues. **Quick rule:** check cancelled, test, period, channel, in that order. ## Known limitations / merchant FAQs **Q: We see 2,103 here but our BC dashboard shows 2,150. Why?** The 47-order gap is almost always cancelled, declined, or test orders that BC includes in the all-orders view by default. Apply the `is_test = 0` and "exclude cancelled" filters in BC and the numbers should reconcile within ±0.5%. **Q: Refunded orders, are they counted?** Yes, if the original payment captured. The order was placed; it was later refunded as a separate event. Refund-rate is tracked separately on `refund_rate`. The volume reading should not be discounted by refunds, they're a distinct signal. **Q: Pre-orders and back-orders, do they count?** Configurable per profile. Default: pre-orders count when payment captures (typical). Back-orders count when payment captures and order is placed, even if fulfilment is delayed. **Q: B2B orders, are they included?** By default yes, treated identically to D2C orders. For B2B-heavy stores where B2B distorts the volume picture, configure profile-level filtering to view storefront-only or B2B-only. **Q: How does this card differ from `order_count_trend`?** This card is the absolute count for the period. `order_count_trend` is the percentage change vs the prior period. Use this card for "how many orders did we receive?"; use the trend card for "is volume growing or shrinking?" **Q: We launched a new sales channel this period. Will the count include it?** Yes, channel filtering is applied at profile level. New channels show up automatically once the integration is connected. To see the channel-specific contribution, use `bc_orders_by_channel_id`. **Q: Why does the volume number not have an alert threshold?** Because absolute count comparability across stores is meaningless. A 100-order period is healthy for one store and concerning for another. Alert-threshold logic lives on the trend card (`order_count_trend`), which reads the percentage change. Trend % is comparable across stores; absolute count is not. **Q: Manual orders (placed by staff via the BC admin panel), do they count?** Yes by default. Manual orders represent legitimate revenue (phone, B2B, pop-up, custom) and should appear in the operational and financial view. To exclude, configure profile-level filtering. *** ### Tracked live in Vortex IQ Nerve Centre *Total Orders* is one of hundreds of KPI pulses Vortex IQ tracks across BigCommerce 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.