Meta Dayparting by Spend and Orders
Meta Dayparting compares imported delivery with the times realized shop orders and net revenue land. Weekday-hour, hour-of-day and normalized day-of-month views reveal timing patterns without pretending exposure and purchase happen at the same moment.
Weekday and Hour Performance Cells
The heatmap can shade by spend, realized orders, cost per realized order or realized-revenue ROAS. It combines Meta campaign-hour delivery with the shop’s hourly order mart by weekday and clock hour, preserving cells that exist on either side.
- Cost per realized order — summed Meta spend divided by summed realized orders for the cell.
- ROAS — realized net revenue divided by Meta spend when both the spend and order basis exist.
- Orders per thousand impressions — realized orders divided by Meta impressions, scaled by 1,000.
- Campaign filter — narrows delivery using campaign-hour observations and keeps the reporting dates explicit.
Hourly Spend and Order Share Comparison
For hour 00 through 23, the report sums Meta spend, impressions and clicks, then places them beside realized orders and net revenue. Spend share minus order share creates a signed gap: positive means spend takes a larger share than orders; negative means orders take the larger share.
- No realized orders — order share and dependent efficiency measures carry an explicit unavailable reason.
- No Meta observation — the row remains visible when the shop has activity, but Meta metrics are not manufactured.
- Comparison — current and previous hours are paired by clock-hour key, retaining newly observed and no-longer-running rows.
- Scheduling caveat — conversion lag, time zone, other channels and always-on campaigns can separate exposure time from purchase time.
Normalized Month-End Performance Patterns
Raw totals make the 29th, 30th and 31st look weak simply because they occur less often. Dayparting divides spend, delivery, orders and revenue by each calendar-day number’s occurrence count before calculating shares and efficiency. A day number the window never reached is absent, not zero.
Use this view around payday, subscription renewal, promotion or month-end cycles. Paid-media owners can test delivery schedules, domain owners can see when demand reaches the checkout, and SEO teams gain timing context for landing-page traffic. Compare day-of-month windows only when their lengths and occurrence counts match.
weekday-hour map, plus hour and month-day views
Every ratio is built from summed components, with missing denominators explained instead of silently zeroed.
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