> ## 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. # Weekend vs Weekday, BigCommerce > Weekend vs Weekday 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 > Revenue split between weekend (Sat-Sun) and weekday (Mon-Fri) over the rolling 90-day window. The card the marketing team uses to plan email send schedules, ad-spend dayparting, and promotion timing. B2C stores often see weekend AOV lifts of 10-15% with weekday volume; B2B stores see the opposite (weekday-heavy with quiet weekends). | | | | ----------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | **What it counts** | `SUM(total_inc_tax)` partitioned into weekend (Sat + Sun) and weekday (Mon-Fri) buckets over 90 days. Headline shows percentage and dollar value per bucket; secondary shows AOV and order count per bucket. | | **VAT / tax treatment** | Tax-inclusive (`total_inc_tax`). | | **Shipping** | Included. | | **Discounts** | Already deducted. | | **Refunds** | Not deducted (gross). | | **Cancelled / voided orders** | Included. | | **Currency** | Multi-currency without FX. Filter for clean comparison. | | **Channels / sources** | All channels contribute. POS retail-floor revenue often skews weekend-heavy (in-store browsing peaks Saturday); B2B portal weekday-heavy. Filter by channel for cleaner segment analysis. | | **Day-of-week boundaries** | Saturday and Sunday are weekend; Monday-Friday are weekday. UTC-based by default; toggle to local time-zone for accurate retail-day partition. | | **Bank holidays / public holidays** | Treated as weekday by default (calendar-day basis, not "trading day"). Configure a holiday calendar to exclude or reclassify. | | **B2B Edition note** | B2B portals typically show 95%+ weekday share. A B2B-heavy store with rising weekend share suggests a new self-service customer cohort or a portal accessibility shift. | | **Time window** | `90D` (rolling 90 days; longer than 30D to smooth holiday and seasonal effects) | | **Alert trigger** | None on this card directly. | | **Roles** | owner, marketing | ## Calculation Calculated automatically from your BigCommerce 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 US fashion brand on BigCommerce Pro, web only, 90-day window 14 Feb 26 to 14 May 26. | Day type | Days in period | Revenue | Share | Daily avg | Order count | AOV | | ----------------- | -------------- | --------------- | ----- | ---------------- | ----------- | ------- | | Weekday (Mon-Fri) | 64 days | \$896,000 | 60% | \$14,000/day | 14,800 | \$60.50 | | Weekend (Sat-Sun) | 26 days | \$598,000 | 40% | **\$23,000/day** | 8,600 | \$69.50 | | **Total** | 90 days | **\$1,494,000** | 100% | \$16,600/day | 23,400 | \$63.85 | What's interesting: 1. **Weekend daily average is 64% higher than weekday daily average ($23k vs $14k).** Despite weekends being only 29% of the calendar (26/90 days), they generate 40% of revenue. The per-day intensity is dramatically different. **Action: weekend ad spend should be weighted 60-70% higher than weekday baseline.** 2. **Weekend AOV at $69.50 vs weekday $60.50 is the relax-and-spend pattern.** Customers on weekends are less time-pressed, more willing to add bundles, browse longer. The 15% AOV lift on weekends is consistent with B2C fashion benchmarks. Test bundle / upsell mechanisms specifically targeted at weekend traffic. 3. **The gap between weekday and weekend implies different acquisition strategies.** Weekday traffic skews mobile-quick-purchase; weekend skews desktop / tablet / leisurely browse. Cross-reference [BC Revenue by Device](/nerve-centre/kpi-cards/bigcommerce/revenue-by-device) to confirm. 4. **A B2B-heavy comparable would invert this.** B2B fashion wholesale typically sees 90% weekday revenue, 10% weekend (and the weekend 10% is usually bored buyers casual browsing, not real intent). If you have B2B Edition, run this card filtered to retail-only for the meaningful pattern. 5. **The 60/40 split is healthy for retail B2C.** Stores with >70% weekend concentration may be over-reliant on weekend impulse buying; stores with >70% weekday concentration may be missing weekend audience or have weekend technical issues. Action priority order: 1. **Configure weekend ad-spend uplift** Google Ads / Meta dayparting bid modifiers, +60% on Sat-Sun. 2. **Schedule key email sends Friday afternoon and Saturday morning** to catch the weekend buying window. 3. **Weekend customer-service staffing** AOV is higher on weekends, prompt support on weekends pays off. 4. **A/B test weekend-specific promotions** "Weekend bundle: 15% off when you buy 2 items" reinforces the behavioural pattern. 5. **Quarterly: review the split**, drift toward weekend-only revenue may signal weekday-traffic problems (ad-platform changes, Monday-morning B2B prospect shift). ## Sibling cards merchants should reference together | Card | Why pair it with Weekend vs Weekday | | -------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------- | | [Revenue by Day of Week](/nerve-centre/kpi-cards/bigcommerce/revenue-by-day-of-week) | The 7-bar daily breakdown; this card is the 2-bucket aggregation. | | [BC Revenue by Hour](/nerve-centre/kpi-cards/bigcommerce/revenue-by-hour) | Hour-of-day pattern; weekend hours peak differently (broad afternoon vs weekday twin peaks). | | [BC Revenue by Device](/nerve-centre/kpi-cards/bigcommerce/revenue-by-device) | Weekend skews tablet / desktop; weekday skews mobile. | | [Total Revenue](/nerve-centre/kpi-cards/bigcommerce/total-revenue) | The denominator. | | [BC Channel Revenue Mix](/nerve-centre/kpi-cards/bigcommerce/revenue-mix-by-channel) | Channel patterns differ by day type (POS heavy weekend, B2B heavy weekday). | | [`klaviyo.kl_send_time_optimization`](/nerve-centre/klaviyo/kl_send_time_optimization) | Email send-time optimisation; weekend-heavy stores send Saturday morning. | | [`google_ads.ga_dayparting_performance`](/nerve-centre/google_ads/ga_dayparting_performance) | Ad-spend efficiency by day of week. | | [Customer Trend](/nerve-centre/kpi-cards/bigcommerce/customer-acquisition-trend) | New-customer acquisition often skews weekend; existing-customer reorders weekday. | ## Reconciling against the vendor's own dashboard **Where to look in BigCommerce Control Panel:** BC's [Analytics → Sales](https://login.bigcommerce.com/deep-links/manage/analytics) shows a daily time-series; weekend-vs-weekday partition is implicit but not directly displayed. Manually export daily revenue and pivot to compute the split. **There's no native weekend-vs-weekday view in BC**; this card is one of the highest-value adds. **Why our number may legitimately differ from BC manual export:** | Reason | Direction | | ------------------------------------------------------------------------------------------------------------ | ---------------- | | **Time-zone handling**. UTC default vs local-time toggle changes the day partition for orders near midnight. | Configurable | | **Bank-holiday handling**. Default treats holidays as their calendar day; configurable to exclude. | Configurable | | **Multi-currency**. We don't FX; manual export may. | Different totals | | **Refund netting**. We use gross; export may net. | Different totals | **Cross-connector reconciliation:** | Card | Expected relationship | What causes legitimate divergence | | ---------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------- | | [`google_analytics.ga_sessions_by_dow`](/nerve-centre/google_analytics/ga_sessions_by_dow) | Sessions by day-of-week pattern; correlates with revenue but conversion rate may shift. | Conversion typically higher on weekends; sessions and revenue shapes differ. | | [`klaviyo.kl_email_send_performance_by_dow`](/nerve-centre/klaviyo/kl_email_send_performance_by_dow) | Email send-day performance; aligning with weekend pattern improves open / click. | Klaviyo's metric is engagement, not revenue. | **The weekend-vs-weekday view is BC-aligned with similar cards on Shopify and Adobe Commerce.** ***
Same-metric documentation cross-reference (for agencies running multiple platforms) * [`shopify.weekend_weekday`](/nerve-centre/shopify/weekend_weekday) (planned) * [`adobe_commerce.weekend_weekday`](/nerve-centre/adobe_commerce/weekend_weekday) (planned)
## Known limitations / merchant FAQs **Why is my weekend share so low (under 25%)?** Likely B2B-heavy or weekday-pattern customer base. Run the card filtered to retail customers only; if still under 25%, your customer cohort genuinely buys during work hours. This is fine if margins support weekday-only marketing; concerning if you're missing weekend audience that competitors are reaching. **Should I send my biggest email blast on Saturday morning?** For B2C stores with weekend-heavy patterns, **yes**. Saturday 8-10 AM local time captures the weekend browsing window before retail competitors send. For B2B / weekday-heavy stores, send Tuesday morning. **Match send-day to revenue pattern, not to industry default.** **My share keeps shifting between weeks, why?** Holiday weeks distort the pattern. Bank holidays move work into "weekend" mode (people order from home rather than office). The 90-day window smooths but a heavy-holiday quarter still shifts the headline. Cross-reference [Revenue Over Time](/nerve-centre/kpi-cards/bigcommerce/revenue-over-time) for daily detail. **Why does my POS revenue look so weekend-heavy?** Retail-floor footfall peaks weekends. POS terminals capture in-store walk-ins, which concentrate Sat-Sun. POS-only stores often see 60-70% weekend share; this is healthy operational pattern. **Should I run weekend-specific promotions?** Test it. "Weekend bundle" or "Sat-Sun 15% off" promotions can lift weekend AOV further if your audience responds; some stores find it cannibalises full-price sales. A/B test for 4 weeks before committing. **My weekday share is rising, what changed?** Common causes: (1) B2B portal new account activity (weekday-heavy by definition); (2) shifted email send strategy to weekday; (3) new ad campaign targeting work-hours audiences (Google Ads B2B campaigns); (4) competitor weekend promotions pulling weekend customers away. Diagnose by cross-referencing the channel mix. **Why is my weekend AOV higher than weekday?** Time-on-site is higher on weekends; customers browse more, add more bundles, less rushed checkouts. Weekend AOV lift of 10-20% is consistent across most B2C BC stores; if your weekend AOV equals weekday, you may be missing a bundling opportunity. **Can I see weekend vs weekday by channel?** Yes, configure the card to filter by channel, then compare two filtered views. POS will show 60-70% weekend; Amazon \~50/50; B2B portal 90%+ weekday; web-DTC typically 40-45% weekend. Each channel has its own pattern. **Should I increase weekend customer service staffing?** For weekend-heavy B2C stores, yes. AOV is higher, customers expect prompt response, 1-2 live chat agents Saturday 10-18 covers the typical weekend support load. Weekend customer service ROI is usually positive given the AOV uplift it protects. **My multi-currency store, do weekend patterns vary by currency?** Often yes. US (USD) shoppers buy more on weekends than UK (GBP) due to time-zone offset. Filter by currency for region-specific patterns. Stores serving multiple regions should plan ad-spend dayparting per currency / region, not store-wide. **Why should I use 90-day window instead of 30-day?** Weekend / weekday counts vary slightly across months (some months have 9 weekends, some 8). The 90-day window normalises this and includes \~26 weekend days vs \~64 weekday days, statistically robust. 30-day is noisier; 180-day starts to mix seasonal effects. **My e-commerce store has POS; how do I separate retail-floor from web?** Filter by channel: web-only filter shows the digital pattern (typically weekend-heavy for B2C); POS-only shows the retail-floor pattern (very weekend-heavy). Don't aggregate them for digital-marketing decisions; the POS pattern can mask weekend gaps in the digital experience. **Bank holidays: are they treated as weekend or weekday?** Default: weekday by calendar day. Configure a holiday calendar (Vortex Mind setting) to reclassify or exclude holidays. For "trading day" analysis, exclude holidays entirely; for "calendar day" analysis, the default is correct. *** ### Tracked live in Vortex IQ Nerve Centre *Weekend vs Weekday* 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.