> ## 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. # Orders Over Time, BigCommerce > Orders Over Time for BigCommerce stores. Tracked live in Vortex IQ Nerve Centre. How to read it, why it matters, and how to act on it. **Metrics type:** [Supporting Metrics](/nerve-centre/overview#metrics-types-explained) • **Category:** [Ecommerce Platform](/nerve-centre/connectors#connectors-by-type) ## At a glance > Daily order count plotted as an area chart over 90 days. The trend version of [Total Orders](/nerve-centre/kpi-cards/bigcommerce/total-orders). Where Total Orders gives you point-in-time numbers, this card shows the daily shape, peaks, troughs, weekly seasonality, and the long-term direction. | | | | ----------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **What it counts** | `DATE_HISTOGRAM COUNT(_id)` per day across every order in the 90-day window. | | **VAT / tax treatment** | n/a, count metric. | | **Shipping** | n/a. | | **Discounts** | n/a. | | **Refunds** | Not deducted (refunded orders count on placement date). | | **Cancelled / voided orders** | Included (the order existed; cancellation is a downstream state). | | **Currency** | n/a. | | **Channels / sources** | All channels contribute. **Channel-shape patterns**: web orders cluster around lunch / evening peaks; POS clusters around store-open hours; marketplace orders distribute more evenly across the day. Multi-channel stores see a smoother trend than single-channel. | | **Day-of-week effects** | Most BC stores see weekend dips on weekday-categories (B2B, office supplies) and weekend peaks on weekend-categories (homewares, fashion). The 7-day rolling average smooths these effects; the daily bars expose them. | | **`Incomplete` orders** | Included by default. They represent customer-intent events; for "successful orders only" trend, exclude `status = Incomplete`. | | **Multi-currency** | The trend is the same regardless of currency mix; count is currency-insensitive. | | **B2B Edition** | B2B order placement clusters around month-end (procurement cycles); single-month windows can hide this rhythm. The 90-day view typically shows the pattern. | | **Time window** | `90D` (rolling 90 days, daily granularity) | | **Alert trigger** | None at this card; sentiment key `order_count_trend` is monitored at the [Total Orders](/nerve-centre/kpi-cards/bigcommerce/total-orders) and [BC Alert Revenue Drop](/nerve-centre/kpi-cards/bigcommerce/revenue-drop-alert) levels. | | **Roles** | owner, marketing, operations | ## Calculation ``` DATE_HISTOGRAM COUNT(_id) WHERE date BETWEEN [period_start, period_end] ``` ## Worked example A US homewares brand on BigCommerce Pro, 90-day window from 13 Jan 26 to 12 Apr 26. | Period | Avg orders/day | Notable peaks | Trend direction | | ---------------------- | -------------- | -------------------------------------- | ----------------------------- | | 13 Jan 26 to 26 Jan 26 | 198 | 320 on 22 Jan (clearance flash sale) | Declining (post-holiday tail) | | 27 Jan 26 to 9 Feb 26 | 224 | 280 on 8 Feb (Spring catalogue launch) | Rising | | 10 Feb 26 to 23 Feb 26 | 235 | 410 on 14 Feb (Valentine's) | Stable+ | | 24 Feb 26 to 9 Mar 26 | 248 | 290 on 5 Mar (mid-week spike) | Stable | | 10 Mar 26 to 23 Mar 26 | 232 | nothing notable | Slight decline | | 24 Mar 26 to 6 Apr 26 | 218 | 380 on 28 Mar (Spring launch promo) | Concerning | | 7 Apr 26 to 12 Apr 26 | 210 | 320 on 11 Apr (bank-holiday weekend) | Continued decline | What's interesting: 1. **The 90-day shape: peak around mid-Feb, gradual decline since.** The store's typical-day order count fell from 248 (peak) to 210 (recent), a 15% decline in 6 weeks. **Concerning trend even though no individual day looks alarming.** The 90-day shape is what catches slow declines that single-period summaries miss. 2. **Campaign spikes are clearly visible.** Valentine's, Spring launch, and the 11 Apr bank holiday all show as 1.5-2x baseline days. Healthy responsiveness to promotions; problematic if the underlying baseline is falling between promotions. 3. **The 28 Mar Spring launch peak (380 orders)** was a single-day surge but the days after it didn't sustain. Compare against the 14 Feb Valentine's peak which was followed by a multi-day elevated baseline; the Spring launch retained less. **That's a customer-quality signal**: the launch acquired campaign-driven first-time buyers who didn't return. 4. **The mid-week 5 Mar spike (290)** with no apparent campaign driver is suspicious. Almost always one of three causes: (a) a viral social post / influencer mention, (b) a competitor outage that pushed traffic to you, (c) a leaked discount code being aggregated. Investigate via [BC Top Coupons](/nerve-centre/kpi-cards/bigcommerce/top-coupons) and social listening. 5. **Day-of-week pattern visible underneath the trend.** Most homewares stores see Saturday and Sunday as peak ordering days; weekends in this trend cluster 30-50% above weekdays. Healthy seasonality, not a problem. The diagnostic playbook when the trend declines: 1. **Compare 30-day rolling avg to 30-day rolling avg from prior period**, smooths out daily noise. A 5%+ rolling-avg decline is real; under 5% is noise. 2. **Cross-reference [Customer Acquisition Trend](/nerve-centre/kpi-cards/bigcommerce/customer-acquisition-trend).** Order trend declines driven by new-customer drops are top-of-funnel; driven by repeat-customer drops are retention. 3. **Pair with [BC Channel Revenue Mix](/nerve-centre/kpi-cards/bigcommerce/revenue-mix-by-channel).** Drops usually concentrate in 1-2 channels. 4. **Audit campaign cadence.** If campaigns were running steadily and have stopped, the baseline reflects the no-campaign reality, the question becomes whether your campaign cadence is sustainable as the always-on state. 5. **Check the BC Incomplete Rate trend.** Rising incomplete with falling orders = checkout friction is the cause. ## Sibling cards merchants should reference together | Card | Why pair it with Orders Over Time | | -------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------- | | [Total Orders](/nerve-centre/kpi-cards/bigcommerce/total-orders) | The point-in-time summary. This card shows the daily shape; that one shows current vs prior. | | [Revenue Over Time](/nerve-centre/kpi-cards/bigcommerce/revenue-over-time) | Same shape, different axis. Together they show whether order growth = revenue growth or AOV-shift. | | [Total Revenue](/nerve-centre/kpi-cards/bigcommerce/total-revenue) | Revenue context. Order trend up + revenue trend up at same rate = volume growth; rates diverging = AOV moved. | | [Customer Acquisition Trend](/nerve-centre/kpi-cards/bigcommerce/customer-acquisition-trend) | New-customer trend. Pairing with order trend shows whether growth is driven by new or returning. | | [BC Channel Revenue Mix](/nerve-centre/kpi-cards/bigcommerce/revenue-mix-by-channel) | Channel decomposition. | | [BC Revenue by Hour](/nerve-centre/kpi-cards/bigcommerce/revenue-by-hour) | Intra-day shape. Daily trend + hourly view = full temporal picture. | | [BC Weekend Weekday](/nerve-centre/kpi-cards/bigcommerce/weekend-vs-weekday) | Day-of-week aggregation. Strong weekend / weekday patterns visible here. | | [BC Alert Revenue Drop](/nerve-centre/kpi-cards/bigcommerce/revenue-drop-alert) | Real-time alarm when this trend dips abruptly. | ## Reconciling against the vendor's own dashboard **Where to look in BigCommerce Control Panel:** [Analytics → Sales](https://login.bigcommerce.com/deep-links/manage/analytics/in-store-conversion) → "Orders over time" chart shows the daily order trend. The granularity is daily by default; switch to hourly for intra-day view (Plus / Pro). Standard plan stores need to compute manually from the order export. **Why our number may legitimately differ from BC Analytics:** | Reason | Direction | | -------------------------------------------------------------------------------------- | --------------------------------- | | **`Incomplete` order treatment.** We include them; BC Analytics typically excludes. | Vortex IQ HIGHER bars | | **Cancelled / Declined orders.** Included here, may be excluded in BC Analytics. | Vortex IQ HIGHER bars | | **Time zone.** UTC vs store TZ; daily bars at the boundary shift. | Boundary effects | | **Sync lag.** Recent days are preliminary until end-of-day. | Vortex IQ slightly LAGS for today | | **Channel coverage.** Both views aggregate every channel; differences are sync timing. | Same direction | **Cross-connector reconciliation:** | Card | Expected relationship | What causes legitimate divergence | | ------------------------------------------------------------------------------------------------- | ------------------------------------------- | --------------------------------------------------------------------------------- | | [`google_analytics.ga_purchases_trend`](/nerve-centre/kpi-cards/google-analytics/purchases-trend) | GA4 purchase event trend should track shape | GA4 misses 10-25% of orders; absolute level differs but shape aligns. | | [`stripe.stripe_charges_trend`](/nerve-centre/stripe/stripe_charges_trend) | Stripe-side charge count trend | Stripe sees only successful captures; this card includes Incomplete and Declined. | **Same-metric documentation cross-reference:** * [`shopify.orders_over_time`](/nerve-centre/kpi-cards/shopify/orders-over-time) (planned) * [`adobe_commerce.orders_over_time`](/nerve-centre/kpi-cards/adobe-commerce/orders-over-time) (planned) ## Known limitations / merchant FAQs **My trend has a clear weekly seasonality, what's the right way to read it?** Use 7-day rolling average instead of raw daily bars. The weekly pattern is real (weekend peaks, mid-week troughs in homewares; opposite in B2B) and obscures the underlying trend. Most stores enable rolling averages as the default chart view. **The trend dropped 10% over 60 days but no single day looks alarming, is that a problem?** Yes, this is exactly what slow-decline patterns look like. No single day fires an alert (the alert threshold is 20% per period); the cumulative effect is materially negative. **Monitoring slow declines is what 90-day trend charts are for.** Investigate via the diagnostic playbook in the Worked Example. **My today bar is unusually low, did the integration break?** Check the time. Today's bar is partial until end of day. If it's mid-afternoon and the bar reads zero, check Settings → Sources status. Most stores see today's bar at 30-70% of normal until \~6pm local time, then it climbs to baseline. **My Black Friday week dwarfs the rest of the year, can I exclude it?** Yes via filtering. The rolling-90-day view will show the spike for \~3 months after; for a smoother long-term view, run 365-day or year-over-year comparisons. **Why does my B2B store look so flat compared to D2C peers?** B2B order volume is more even because procurement schedules drive ordering rhythm. D2C is campaign-driven and seasonal; B2B is contract-driven and steady. Both are healthy patterns. **Can I overlay revenue on this chart?** Not from this card directly. Pair with [Revenue Over Time](/nerve-centre/kpi-cards/bigcommerce/revenue-over-time), the two charts together show whether order count and revenue track or diverge. Diverging trends signal AOV mix shifts. **My 5 Mar spike has no apparent cause, how do I find it?** Almost always one of: (a) a viral social post, (b) a competitor outage, (c) a leaked discount code. Check social platforms for spike-day mentions of your brand; check [BC Top Coupons](/nerve-centre/kpi-cards/bigcommerce/top-coupons) for unusual code activity that day; check status pages for major competitors. **Why does my POS terminal look like it has a "ghost orders" pattern, occasional clusters of 30+ on one day, then 0 the next?** Almost certainly a sync-batching issue. The terminal uploads in batches; one day's batch lands the next day in BC. Real-time sync would smooth this out. Configure your POS to sync continuously (not in batches). **Can I export this chart to share with the team?** Yes, all Vortex IQ charts support PNG/CSV export from the chart menu. For embed in slides, use the PNG; for further analysis, use the CSV. **Should I worry about the most recent 3 days being lower than baseline?** Most recent 3 days are partially-mature. Today and yesterday will rise as orders trickle in (especially POS and Channel Manager which sync slower). Wait 48 hours before drawing trend conclusions from any 24-72 hour cliff. *** ### Tracked live in Vortex IQ Nerve Centre *Orders Over Time* 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.