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Premiumization Part 1: How to take an up-close look before you leap into the race

The race for the top end of the wine business is all the rage and presented as something kin to the next gold rush for wine. There are, indeed, opportunities, but also some barriers including market sizes, demographics and more.


Good data is vital for making sound business decisions and getting a grasp on the metrics that describe reality. But vast tables of numbers are hard to grasp. That’s why charts can be so helpful. Or not, if they are oversimplified to make a point.


Charts are at their most useful when accompanied by the underlying data. We’ll see why lower down in this first part of two articles.


Charts versus data tables


The following is a table of data from Nielsen for all table wine going back roughly two years. I is important to note that Nielsen data captures about 75 percent of all wine sold off premise. However, it is vital to keep in mind that the higher-end segment ($20+) is not as completely captured by the Nielsen data as the lower segments are.


Short of Rain Man-level savant capabilities, it’s hard to get an immediate grasp of what is going on.


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Here is a chart of that same table (below), along with a trend line automatically created by Excel. It offers an immediate picture of what the data are saying. And the trend line could leave you saying OMG!


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But that OMG! moment only offers a view of a mountain from 10,000 feet and isn’t much help in figuring out what’s causing the trend. The first step is to find data that offers a look at the rock formations and then the actual minerals there. This is increasing granularity.


The table below (excerpted from the huge table in this article on wine premiumization) gives us a closer look at the deceleration of overall wine dollar gains…


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… can be charted in ways that do a better job of illuminating opportunities and potential hazards. As we will see in the next installment of this series of articles, this but one step step and is not the ultimate in useful granularity.


For example, the chart below illustrates two sides of the premiumization issue. The purple line shows that two of the lowest-priced segments declined in dollar volume even as they reduced the average per-bottle selling price.


Given that expensive wines are not as well represented in Nielsen numbers as the lower segments, this price drop could represent a grocery-store and mass-market outlet phenomenon. Significantly, those markets are dominated by large distributors and brands.


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The second lowest price segment, $3-5.99, also got cheaper, but showed a slight increase in dollar volume. Checking the table, you can see that the increase was just 0.6%.


However, the chart, below, shows you that the $3-$5.99 segment has the largest overall dollar volume of any of the segments, more than $4 billion.


The $9-$11.99 segment is the second largest segment at over $3 billion. Together they represent $7.37 billion which is 53% of wine’s total off-premise, the Nielsen data dollar volume of $13.9 billion.


That means the behavior of these two segments play an out-sized role in affecting the decline of overall market price gains/losses in the first chart.


It’s also vital to keep in mind that Nielsen captures about 75% of off-premise sales. Getting reliable data about the remaining 25% is possible but expensive. However, experts we have spoken with suggests that  the remaining 25% is weighted toward the high end of the market.


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Dollar gains with lower prices


For now, if we take a close look at the right end of the chart, below,  we see that the two most expensive price segments managed low double-digit dollar volume increases achieved by lowering prices.


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Also, by looking at the charts and referencing the table, we find that the two middle segments — $9-$11.99 and $12-$14.99  are the only two price segments to show growth in every metric — no red anywhere in their table rows. And together, they represent $5.16 billion in an overall market size of $13.86 billion.


And remember, one of these segments — $9-$11.99 — is the second largest of all Nielsen segments measured.


The value of having the data behind the chart


This closer look shows why,  in order to interpret it accurately, it is helpful to have the data behind a chart.


While desirable, sometimes the data is simply not available. Plus, some sources have combined multiple data sets into a single chart in proprietary ways whose interpretation is not transparent.


Decisions: It’s Complicated


What does all that mean for the overall deceleration of price gains and a company’s look at where to make profits.


Clearly the biggest market of all … the second smallest price segment, is growing very slowly and dominated by big players like Gallo and The Wine Group and Constellation, who have the scale of production and distribution to make many pennies off large volume.


But even at this level of granularity, there are significant details that are not readily apparent. The next installment will offer a finer-grained look at the details of the low end and segments and the surprising trend driving it.


Middle or Top?

The big players see that the middle two segments together are the largest market of all and offer better profit margins. That’s getting crowded, but currently showing no signs of slowing.


So, one decision might be to go after the $20+ segment which is the smallest market, growing fastest, but requires the expensive ability to make wines that deserve 90+ points. However, because off-premise consumer purchases at this high-end level are not well captured by Nielsen data, the purchase of additional data would be wise before making a decision to jump in.


On the other hand, looking at the middle market — whose data is well represented bu Nielsen numbers — could be a solid option because it is very large, growing at a healthy pace, and can be produced less expensively than the top end.


Clearly, as far as data goes, one size does not fit all. There can be opportunity in more than one market segment and success will depend on unique plans and great execution. However, all of those decisions should be founded on solid data.


In the next article, we will explore a few more complications for the decision process.