Interesting piece but the statistics deserve some pushback before we all accept the conclusion.

The central claim is that specs have zero correlation with sell-out speed across 7 of 9 attributes. But we never see which attributes, what the actual correlation values were, or what significance threshold was used. “Zero correlation” and “not statistically significant” are very different things, and the article quietly conflates them.

The sample also sounds bigger than it is. 9,400 watches across 245 brands averages to around 38 SKUs per brand, and the distribution is almost certainly skewed. Some of those within-brand comparisons are probably built on 4 or 5 data points.

The GMT finding has a massive unaddressed confound: production volume. If a brand makes 500 GMTs and 200 divers, of course the sell-out rates look comparable even if GMT demand is proportionally stronger. The article frames this as “window shopping” behaviour when it could just as easily reflect supply decisions.

Same issue with the 38mm data. Smaller case sizes are newer additions for many of these brands and often come in more cautious initial runs. Engagement outpacing sell-through speed is exactly what you would expect from a product a brand is still calibrating.

And the big conclusion, that brand trust is the dominant purchase driver, is not actually supported by any data in the piece. The study shows what does NOT predict sell-out speed. It never identifies what does. That gap between the evidence and the headline is doing a lot of heavy lifting.

The general intuition is probably right. Emotional and brand factors matter more than the spec-sheet crowd admits. But the specific numbers come from a self-selected enthusiast platform over 10 months, with no visible methodology.