Running the Numbers
I developed all of the management software for the Las Vegas gallery. In the process, I came up with two very interesting algorithms to keep us efficient.
The first was that we recorded the exact time of day for each sale, so we knew the day of the week and the time. After three months, I analyzed the data to see whether any days or times were particularly strong. Tom and I were very surprised to see that Wednesdays between 3.30 pm and 5.30 pm were dominant. The shift change was at 4.30 pm. Moving forward, on Wednesdays, I had the late shift come in an hour earlier, and the early shift stay an hour later, and we gave everybody an extra $20 for the inconvenience. The bases were loaded. Did we make more sales? Yes, we did. Not every week, but more than enough to cover the extra payroll. Did Wednesdays between 3.30 pm and 5.30 pm remain dominant? Yes, it did. Did we ever figure out why? No, we did not.
The second was even more interesting. We had 5,500 square feet of space, which cost us $27,000 a month: our base rent. We calculated exactly how much each artist cost us to display, and we tracked those costs against sales. If an artist wasn't generating three times their cost in revenue within 90 days, their work was returned, and a new artist was brought in. It didn't matter how much any of us liked the art; it was gone. Business was business, and emotion was irrelevant.
#artsales
This is a brilliant use of data, and the Wednesday afternoon discovery is the kind of insight most businesses never bother to look for.
The two algorithms you're describing hit on something that applies well beyond a gallery floor:
- Tracking sale timing (day + hour) and staffing to match demand is exactly what direct-to-collector artists should be doing with their email sends and social posts. If your sales cluster on Tuesday evenings, that's when your next drop announcement goes out.
- The overlap staffing move (bringing the late shift in early on peak windows) is the brick-and-mortar version of what online sellers do when they stack their best content and highest-intent offers during proven engagement windows instead of spreading everything evenly across the week.
- Three months of data was enough to surface a real pattern. Most artists selling online have months of email open-time data and website traffic data sitting in their dashboard right now and have never once filtered by day-of-week or hour. That's the first move.
The core principle here, let the data tell you when your buyers are active and then show up heavier in those windows, is one of the highest-leverage habits in any selling environment. Thanks for sharing this one.
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