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 |
- Weekend daily average is 64% higher than weekday daily average (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.
- Weekend AOV at 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.
- 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.
- 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.
- 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.
- Configure weekend ad-spend uplift Google Ads / Meta dayparting bid modifiers, +60% on Sat-Sun.
- Schedule key email sends Friday afternoon and Saturday morning to catch the weekend buying window.
- Weekend customer-service staffing AOV is higher on weekends, prompt support on weekends pays off.
- A/B test weekend-specific promotions “Weekend bundle: 15% off when you buy 2 items” reinforces the behavioural pattern.
- 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 | The 7-bar daily breakdown; this card is the 2-bucket aggregation. |
| BC Revenue by Hour | Hour-of-day pattern; weekend hours peak differently (broad afternoon vs weekday twin peaks). |
| BC Revenue by Device | Weekend skews tablet / desktop; weekday skews mobile. |
| Total Revenue | The denominator. |
| BC Channel Revenue Mix | Channel patterns differ by day type (POS heavy weekend, B2B heavy weekday). |
klaviyo.kl_send_time_optimization | Email send-time optimisation; weekend-heavy stores send Saturday morning. |
google_ads.ga_dayparting_performance | Ad-spend efficiency by day of week. |
| Customer 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 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 |
| Card | Expected relationship | What causes legitimate divergence |
|---|---|---|
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 | Email send-day performance; aligning with weekend pattern improves open / click. | Klaviyo’s metric is engagement, not revenue. |