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Metrics type: Supporting Metrics • Category: Ecommerce Platform

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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).

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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.

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Worked example

A US fashion brand on BigCommerce Pro, web only, 90-day window 14 Feb 26 to 14 May 26. What’s interesting:
  1. Weekend daily average is 64% higher than weekday daily average (23kvs23k 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 69.50vsweekday69.50 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 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).

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Sibling cards merchants should reference together

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Reconciling against the vendor’s own dashboard

Where to look in BigCommerce Control Panel: BC’s Analytics → Sales 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: Cross-connector reconciliation: The weekend-vs-weekday view is BC-aligned with similar cards on Shopify and Adobe Commerce.

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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 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.

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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 or book a demo to see this metric running on your own data.