Weekly Sales Pattern Report for Shopify
Your true day-of-week rhythm — which days and hours actually sell — so you staff, schedule ads, and send emails when buyers are buying.
5 from 1,800+ merchants
2,000+ data fields
Trusted by 40,000+ Shopify stores
Updated June 2026
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Why this report matters
Most stores have a weekly rhythm they’ve never measured. Sunday evenings convert; Tuesday mornings crawl. Run on assumption and you staff the wrong shifts and send your best email at the worst time.
Shopify’s Sales over time report shows a continuous line, not a clean day-of-week pattern, and it can’t be scheduled. The cyclical signal — the part you can actually plan around — stays buried in the trend.
Aggregating orders and revenue by weekday (and hour) surfaces the recurring pattern. That’s the input for staffing the real peak, timing ad budget to high-intent windows, and scheduling email and SMS for when your audience actually buys.
What’s included
Pattern
Day of week
Sales aggregated into Monday through Sunday across the whole range.
Heads up: Aggregation uses your store time zone; a global audience can smear the pattern, so segment by region if you sell worldwide.
Hour of day (optional)
A finer cut — weekday × hour — for intraday timing.
Volume & value
Orders per weekday
Average or total orders on each day, the demand signal.
Net sales per weekday
Revenue by day, before vs after discounts and returns.
Formula: Net sales = Gross − Discounts − Returns
% of weekly sales
Each day’s share of the week — the staffing and budget weighting.
Formula: Day share = Day net sales ÷ Week net sales × 100
Example: Saturday 22% vs Tuesday 9% of the week — staff and spend accordingly.
Average order value by day
Whether some days bring bigger baskets, not just more of them.
Formula: AOV = Day net sales ÷ Day orders
Who uses this report
Retail / ops manager
Performance marketer
Email / SMS marketer
Owner
How to read the report
- Use a long enough range. A single week is noise; aggregate a quarter or more so the recurring pattern separates from one-off spikes.
- Read share, then AOV. A day can have fewer orders but bigger baskets; weight decisions on revenue share, not order count alone.
- Watch the time zone. A global audience smears the curve; segment by region if your buyers span continents.
- Separate pattern from events. Strip out big sale days before reading the baseline rhythm, or they’ll distort every weekday average.
How to build the report in Report Pundit
- Open Report Pundit in your Shopify admin and choose Create Report (or the pre-built “Weekly Sales Pattern” template).
- Set the data source to Sales / Orders.
- Group by Day of week (and optionally Hour of day) of the order timestamp.
- Add columns: Orders, Units, Net sales.
- Add a calculated Day-share column and an AOV column.
- Set a date range long enough to be representative (a quarter or more).
- Optionally exclude known big sale days to read the baseline.
- Run, eyeball the weekday curve, and Save.
- Schedule a periodic refresh, or export to Google Sheets to chart the pattern.
Customization & filters
- Toggle between day-of-week and weekday×hour granularity.
- Filter by channel, location, or product type.
- Exclude promo days to isolate the baseline rhythm.
- Segment by region for global audiences.
- Export to Google Sheets for a heat-map of week × hour.
Automate & export
- Schedules — hourly, daily, weekly, monthly, or custom cron
- Delivery formats — Excel, CSV, PDF, or push to Google Sheets in real time
- Group by month or week — trends instead of a static snapshot
- Destinations — email (multiple recipients), Google Sheets, Google Drive, FTP/SFTP, Looker Studio, BigQuery
- Conditional alerts — get notified only if a channel's net sales drop more than X% week-over-week
Report Pundit vs Shopify's native Sales by Channel report
Frequently Asked Questions
Sales Over Time shows a continuous trend; this aggregates every Monday, Tuesday, and so on into a recurring weekly pattern. One is the trajectory, the other is the rhythm you plan staffing and sends around.
A quarter or more. A single week is too noisy to reveal a stable pattern, and big one-off sale days should usually be excluded so they don’t distort the weekday averages.
Yes. Add an hour-of-day cut for a weekday × hour view — ideal for intraday staffing and choosing email or ad send times.
Benefits
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Granular Product-Level Insights
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Discount Analysis
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Order Tracking
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