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Sales by hour, across the week
When the store is busy and when it is quiet, by day, from the tills rather than from memory.
Most trading hours are set by habit, not evidence, and the quiet hour at open or close still carries a full wage bill. This workflow puts your sales next to your hours, so you can see which parts of the day are paying their way.
Opening and closing times tend to carry forward year after year, set long ago and rarely questioned. The first hour and the last hour still cost a full complement of wages, whether or not the customers are there to justify it.
The sales data that would settle the question is already in the POS, hour by hour. What is usually missing is a simple way to see it, and to line it up against when the store is actually staffed.
Retail+ reads that hourly detail live. When the day earns its keep, and when it does not, stops being a hunch and becomes something you can look at.
When the store is busy and when it is quiet, by day, from the tills rather than from memory.
The parts of the day that trade low week after week, not just on a slow afternoon, so you know which pattern is real.
The hours where more cover would meet demand rather than stand idle.
Open Retail+ and look at sales by hour and by day of week, live from the tills, so the shape of the trading day is in front of you.
In Real-time Analytics, compare this period to the last to confirm whether a quiet hour is a pattern or a one-off, and set the hourly picture against when you actually roster staff.
Put the hourly questions to Hank in plain English and the answer comes straight back, drawn from your own POS.
Illustrative of what you can ask once your data is connected.
Where the numbers back it, adjust trading hours or move staff from a quiet period to a busy one, and raise the change as a task with an owner and a due time.
Re-run the same hourly view after the change to confirm the store is busier when it is open and better staffed when it is full.
For any store and any period, in the same shape each time.
Which hours trade low as a pattern rather than by chance.
Cover lined up against demand across the day.
Trading-hour and rostering changes with owners and completion tracking.
Trading hours run on convention, and staff are spread evenly across the day whether the customers are there or not. Nobody can say for certain whether the first or last hour covers its cost.
The hourly picture is live and self-serve. Trading-hour and staffing calls are made against the numbers, and every hour the store is open has a reason to be.
The tapestry® Economic Impact Report models a conservative A$27.5k of net value per store per year, a central estimate of A$85.7k, and up to A$181.4k at the top of the modelled range, on a A$30m store. Modelled scenario only. Individual results may vary.
Run the 4-week free trial on your own POS data and see, hour by hour, where the trading day earns its keep. No setup fees.