How much do recent US wine imports differ between years?

In a previous post I looked at the volume of wine-brand imports into the USA in 2012 (Yellow Tail — wine imports into the USA do fit a "power law"). It might be of interest to now look at some more recent data, to see how the different brands fare through time.

In the following graph I compare the lists of the top-25 imported wine brands in terms of volume sales in the USA, for 2012 (horizontally; the data come from my previous post) and 2016 (vertically; the data come from the AAWE Facebook page). Note that both axes of the graph are logarithmic.

There are only 17 wine brands that appear in both top-25 lists (represented by blue diamonds in the graph) — that is, one-third of the wine brands (one-third) were replaced in the top-25 imported volume sellers across the 4 years.

Five of the top six wine brands were at the top in both years, as labeled in the graph. These brands have retained consistent sales volumes across the 4 years. Both Yellow Tail and Lindemans come from Australia, while Cavit and Riunite are imported from Italy, and Concha y Toro is from Chile.

The big difference in the top grouping is that Principato drops off the list, from 3rd place in 2012 (the pink diamonds represent wine brands that appear in only one of the two lists). This Italian wine brand seems to have greatly decreased its portfolio recently, now down to just three distinct wines.

The sales of the remaining 12 wine brands were much less consistent in wine sales, even though they appeared on both lists — that is, the sales volume in 2016 did not necessarily reflect the sales volume in 2012. There were also another seven wine brands that have been replaced from the 2012 list.

So, the answer to the title question is: reasonably consistent at the top, but not very consistent elsewhere on the top-25 list. There seems to be a lot of room for maneuvering the volume of brand sales among most of the imported wines.

Finally, it is worth looking at the topic covered in my previous post, which is the fit of a Power Law to the data, specifically Zipf's Law, which refers to the "size" of each event relative to it's rank order of size. In the previous post, I noted that data for the volume of imported wine do fit a Power Law very well. That is, when you plot a graph of the logarithm of sales volume (vertically) and the rank order of the wine brands (horizontally), it forms a straight line.

This next graph compares the 2012 data (in blue) with the 2016 data (in pink).

This graph shows that the Power Law for 2012 was not a fluke, but was repeated in 2016. Indeed, the fit of the data to a Power Law is actually slightly better in 2016 (99% vs. 97%).

I think that it is remarkable that so often in our world, complex economic data, like wine sales volumes, which are presumably subject to all sorts of market forces, actually fit very simple mathematical models. This implies that all of the different forces cancel each other out, leaving a simple pattern for us to see and interpret. In this case, for example, we should not expect Yellow Tail wines to sell any better than they already do.