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Enthusiasm in Retrograde?

Watches and Wonders, the annual industry trade show in Geneva, is now squarely in the rearview mirror.
AI Generated image.
As is so often the case in the modern era, though, it leaves behind a lot of digital "breadcrumbs," such as Google Local Guide Benjamin Spiegel's relatively glowing review of the convention space. One particular trail of Watches and Wonders breadcrumbs serves as a barometer of enthusiasm for watches and watch collecting. That's what this post is all about.

Through its Trends service, Google provides a window into search activity on its platform. I've used Google Trends data as applied to the watch industry for a few articles in the past (on this blog and for a piece in Time and Tide, for example). Out of curiosity, I pulled the data on "Watches and Wonders - Topic" from Google Trends and I think there are some interesting patterns in the data.

Let's begin with the raw data. The first Watches and Wonders took place in 2021, when Covid was still very much an active consideration when it came to travel and in-person gatherings. Perhaps unsurpisingly, then, interest in the event, as measured by Google Trends, was lowest in that year. In 2022, interest in Watches and Wonders almost doubled followed by an additional 48% increase in interest in 2023. The highest level of interest in the event took place in 2024.

Here is where the story begins to change: in 2025, the Google Trends data went down for the first time, a decrease of 3%. While this may seem to be a somewhat modest decrease, we also have to keep in mind that this reversal represents both a loss of positive momentum and a sign change of that momentum into the negative. In other words, we lack a benchmark "counterfactual" to compare this year's Google Trends results with what would have happened if the positive momentum from past years could have been maintained. So let's use some statistical methods to estimate that benchmark.

I'll provide some details about my statistical methodology as an endnote to this post, but I ran the Google Trends numbers through a model which allows me to project how much attention Watches and Wonders would receive if the momentum from prior years continued unabatted. The model characterizes 2023 and 2024 as years in which the trade show "overperformed." In 2023, the model predicted a Google Trends index value of 72 (see the orange dot in the figure) whereas the actual level of interest reached 80, roughly 11% higher. Similarly, in 2024, the model predicted a Google Trends value of 91 while the measured value of attention reached 100, a 9.8% overperformance of interest.

The ebbing of interest in 2025 comes in focus when we have the model's prediction in hand. If the upward trajectory of attention to Watches and Wonders had continued into 2025, we would have seen a Google Trends index value of 108 (well, it would have been 100 and all the others would have been 8 lower but that's kind of down in the weeds). However, the Google Trends index reached only 97, an underperformance of 11%. From this result we can conclude that interest in Watches and Wonders has cooled off in the most recent year by just as much as interest overperformed in 2023.

In summary, the Google Trends data related to Watches and Wonders is another indicator of a retrenchement, of sorts, in interest when it comes to the watch industry. In all honesty, though, the ebbing of attention to Watches and Wonders is not, by any means, tragic or drastic. In fact, much of the overperformance in 2023 and 2024 may be reasonably ascribed to the novelty of the trade show itself. It is hard to determine if 2025's Google Trends data was driven by the overall slowdown in watch buying, higher familiarity with Watches and Wonders, or both. Regardless of the cause, it is probably worth considering 2025's departure from prior years when it comes to strategizing for upcoming shows. With a little creativity and innovation, my guess is that is entirely possible to reverse 2025's momentum.

Methodological Notes

The result presented above were obtained from OLS estimation of the parameters in the following specification:

GTt= β0+β1 WWt+β2 WWt·t+ et

Where GT is the Google Trends data, WW is a dummy variable equal to 1 during the week of Watches and Wonders (zero otherwise) and t is a time trend. The parameter β1 represents the typical increase in Google searches for Watches and Wonders during the week of the trade show. The parameter β2 captures the extent to which the Google Trends response to Watches and Wonders changes over time (ie if it is positive, then searches respond more to Watches and Wonders over time but if it is negative, the opposite takes place). All the parameters are statistically significant (point estimates are 3.2, 14.8 and .35). I obtain an R2 of .82, a very good fit for a fairly parsimonious model.
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