Day-of-week patterns are the most useful statistical signal in retail. Most owners feel them intuitively but never quantify them. The insight tags do the quantification — and surface the patterns as actionable signals.
01 Day-of-week patterns are real
Almost every brick-and-mortar shop has a pattern: peak days that bring 1.5–2× your weekly average, weak days that bring 0.5–0.7×. The pattern is remarkably stable across months — Saturdays don't randomly become Mondays.
02 How the tag fires
Once you have at least 14 days of data, the Insights panel can identify your peak and weak days statistically. The tag shows up when:
- Peak day: the highest-revenue weekday is consistently 50%+ above your average.
- Weak day: the lowest-revenue weekday is consistently 30%+ below your average.
Both calculations use median + coefficient of variation to filter outliers — one busy Tuesday doesn't flip Tuesday into your peak day.
03 What owners do about it
- Peak day: staff up, prep more, raise the price floor a touch if you can.
- Weak day: reduce staff, consider a half-day, run a focused promotion.
- Both: reset your supply orders to match the rhythm — don't order Sunday quantities for Tuesday.
04 Why patterns are stable
Day-of-week patterns are driven by customer behaviour — when people grocery shop, when they get lunch, when they socialise. Those behaviours don't change quickly. A shop's peak day might gradually shift over years (commute patterns change, office workdays change) but week-to-week it's stable.
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