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Metrics type: Supporting Metrics • Category: Ecommerce Platform

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At a glance

Revenue split by day-of-week, averaged across the window. The card that turns “we did £232k this month” into “Tuesday accounts for 11% of weekly revenue and Saturday accounts for 19%”. Day-of-week patterns matter for staffing (CS coverage, fulfilment scheduling), marketing (when to send email, when to launch campaigns), and operations (when to deploy code, when to run inventory updates). Most BC stores have surprisingly consistent DoW patterns that are stable across months and seasons.

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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 apparel brand on BigCommerce, 90-day window, all currency converted to USD for the example. What’s interesting:
  1. Friday is the peak day (+19% vs Sunday). Classic apparel pattern: Friday-evening payday-spend, weekend-prep purchases, and the start of weekend leisure browsing. Saturday is also strong; the weekend block (Fri+Sat+Sun) is 46.2% of the week’s revenue.
  2. Tuesday is the trough (-8% vs Sunday). Most BC stores show this; mid-week is the lowest commerce activity. Use Tuesday for code deploys, inventory updates, and operational changes because the impact of any outage is smallest.
  3. The pattern is remarkably stable. Across 90 days the DoW distribution rarely shifts more than 1-2 percentage points week to week (assuming no promotional events). Once you know the pattern, you can detect anomalies easily: a Friday at 11% instead of 17% is a major red flag.
  4. The 4.6:1 weekend-to-Tuesday revenue ratio sets staffing. CS team should be heaviest Friday-Saturday; fulfilment scheduling should target Saturday-Monday volume; ad spend should peak Thursday-Friday for weekend conversion windows.
  5. Email send timing. Most categories see best email-driven conversion when sent Thursday morning (preparing for the Friday peak) and Saturday morning (capturing the in-progress weekend audience). Tuesday and Wednesday sends typically convert poorly; aspirational content (browse, save) works better than promotional content (buy now).
Action playbook this card surfaces:
  1. Schedule code deploys for Tuesday or Wednesday. Lowest impact if something breaks.
  2. Schedule promotional email campaigns for Thursday or Saturday. Capture peak-day conversion.
  3. Stage CS team coverage to match revenue distribution. 30-40% capacity Friday-Saturday-Sunday combined.
  4. Use BC Revenue by Hour for sharper time-of-day signals within the days. The DoW * hour combination shows when each day’s buying happens.
  5. Compare DoW pattern by channel. POS will skew weekend; B2B will skew weekday-business-hours. Use channel filter to see each channel’s distinct pattern.
Categories with different patterns:
  • Subscription / replenishment: more even distribution (subscriptions fire on cadence regardless of DoW).
  • B2B: heavily Tuesday-Thursday concentrated; weekends near-zero.
  • Wedding / events: Saturday peak much stronger.
  • Flash sales / drops: distorts DoW for the days the drop happens, then reverts.

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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’s own dashboard: BC Insights doesn’t natively expose a day-of-week revenue breakdown. The closest equivalent is the Sales Over Time chart with daily granularity; export to CSV and pivot by WEEKDAY() in spreadsheet for the same view. For Plus and Enterprise tiers with custom Insights queries, the merchant can build a DoW report manually. Standard tier merchants typically rely on this card for the analysis. Why our number may legitimately differ from the vendor’s: Cross-connector reconciliation (when both connectors are connected for this merchant):

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Known limitations / merchant FAQs

My DoW pattern shifted dramatically last month, what changed? Three usual causes, in order: (1) channel mix change (a new marketplace integration with different DoW pattern, or a B2B channel growth shifting the weekday lean), (2) promotional event distortion (a Tuesday flash sale will show as a Tuesday peak), (3) customer-base shift (acquiring new customers via different channels changes the underlying DoW behaviour). Pull BC Channel Revenue Mix and Discount Over Time for the same period. Why is my Tuesday so high? It should be the trough. You’re a B2B-skewed store, or you do regular Tuesday email sends, or you have a B2B Edition portal that processes wholesale orders Tuesday-Thursday. B2B stores look like the inverse of DTC: weekday peak, weekend trough. Should I send my newsletter on the peak day? Counter-intuitive answer: usually no. Send the day before the peak, so customers receive it during high-intent browsing time. If Friday is the peak, send Thursday morning. If Saturday is the peak, send Friday afternoon or Saturday morning. My weekend pattern is 50/50 Saturday-Sunday but my friend’s store is 70/30, why? Category and customer-base differences. Apparel and lifestyle skew Saturday (active shopping); home and beauty skew Sunday (relaxed browsing). Family-target categories skew Sunday; impulse / fashion skew Saturday. The split is informative; copy the analysis approach, not the specific numbers. Why is Monday slower than Sunday on my store? Two reasons: (1) customers who would shop Sunday evening for Monday delivery often place the order Sunday and Sunday gets the credit, (2) Monday is the start of the work week and shopping attention drops. Most stores show Monday at 92-98% of Sunday baseline. Does this card respect channel filters? Yes via Ask Viq: “revenue by day of week for channel_id 1 only over last 90 days”. Per-channel DoW patterns differ significantly; web is variable, POS is heavily weekend, B2B is heavily weekday. Why does my flash-sale Wednesday show 28% of weekly revenue? Promotional-day distortion. The 90-day average is contaminated by the flash-sale day. Either exclude promotional days from the analysis (set an exclusion window in card settings) or use a longer window (180D) to dilute the effect. Can I see day-of-month patterns? Not directly on this card, but yes via Ask Viq: “revenue by day of month for last 90 days”. Useful for stores with monthly subscription cycles or payday spike patterns (e.g., 1st of month for US-based payday). My DoW pattern is identical to last year, is that suspicious? No, it’s normal. DoW patterns are extremely stable; the shape rarely shifts year-over-year for the same store. The magnitude changes (revenue grows or shrinks), but the % share by day stays within 1-2pp. Should I read this card weekly or quarterly? Quarterly for trend changes; ad hoc when staffing or campaign-timing decisions arise. The pattern is stable enough that monthly review is overkill unless you’re actively running channel-mix experiments. Why is Sunday the baseline? Arbitrary convention; most BC stores have their lowest variance on Sunday so it’s a stable reference point. Toggle the baseline to any day in chart settings; the relative percentages don’t change. My subscription store has a flat DoW pattern, is that fine? Yes. Subscriptions fire on cadence regardless of DoW; if 60% of revenue is subscription-driven, the pattern flattens. Look at the non-subscription slice separately for organic DoW signal.

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Tracked live in Vortex IQ Nerve Centre

Revenue by Day of Week 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.