It seems like the following article about wine consumption in the NBA is getting a lot of attention: http://www.espn.com/espn/feature/story/_/id/22358028/the-nba-obsession-wine. I found three aspects of the article particularly interesting:
First, the sheer popularity of wine in the NBA. Some of the players are even taking team-sponsored vineyard visits:
Second, the article's introduction focused on a group of Cavs players visiting the Mayacama winery. I hadn't heard of Mayacama before, but it seems that the winery is a Napa Valley staple. They only offer three wines on their website: a 2013 cabernet sauvignon, a 2013 merlot, and a 2003 cabernet sauvignon. I think the ability to purchase older wine directly from the vineyard is intriguing, and given the price ($250 vs. $150 for the 2013 cab) I'd also like to note that the vineyard is earning a 5.25% annual return just for cellaring the wine. Of course, this assumes that the 2003 cabernet sauvignon would retail for $150 years ago, which is a big assumption. Even so, the return strikes me as reasonable if you have the room to cellar the wine.
Third, various winemakers were impressed by the detailed and sophisticated nature of the NBA players' questions. These clearly aren't mere dilettantes. Carissa Mondavi offers the following analogy: "NBA players are the product of so many unseen hours spent perfecting so many hidden details, all leading to the moment when the ball is tossed in the air. So too is wine crafted against countless variables -- the weather, soil, harvest, tanks, the barrels and blends, the delicate alchemy of it all -- until, one day, the cork is pulled. For both to shine, it takes so much work no one will ever see." The precision needed for winemaking has a corollary in the intense focus that drives elite athletic performances!
Tuesday, February 20, 2018
Monday, February 19, 2018
Machine Learning in Wine Marketing?
We talked a lot in class / in blogs about the wine shopping experience: consumers are often overwhelmed by the plethora of brands and have a difficult time making a choice. There are just too many options. Even if a consumer knows roughly what she is looking for (e.g., California Cabernet Sauvignon or Burgundy Chardonnay), chances are that she will still have to decide from a dozen or dozens of brands in her preferred price range.
However, at the end of the day the consumer has to make a purchase decision. So how does she actually selects a bottle of wine amidst uncertainty and lack of information? The possible approaches are:
a) Pick randomly ("I'll just try this bottle for no reason")
b) Consult someone at the store / online ("Let me ask the wine specialist / Vivino")
c) Go with her "gut" ("This bottle looks interesting")
I'd like to dive a bit deeper into approach c). What is the "gut feeling" of a customer, and based on what is the gut feeling formed? More specifically, if a consumer looks at 10 bottles of wines from the same region / grapes at the same price, what would influence her gut feeling?
The most straightforward hypothesis is that label design, when all else are equal, heavily influence consumers' purchase decision. I think it would be very interesting to use regression analysis / machine learning to understand the specific factors that drive consumer adoption. Several factors / regressors to consider in this analysis, for example:
Brand name:
- Length
- Binary variables for category (e.g., has name of location, has animal, has family name, has number...)
- Language (English, French, German, not a real word, etc.)
Label design:
- Brand name font and font size
- Color scheme (number of colors, background color, dominant color(s), etc.)
- Center image category (estate, nature, grape, animal, human, coat of arms, signature, no image, etc.)
- Center image style (watercolor, oil painting, sketches, modern art, wood-carved, etc.)
Label information:
- Grape varietal shown
- Vintage shown / vintage year
- Appellation / AVA / geography shown
There are other nuanced but important decisions to make for this experiment. For example:
- Do we want to include price as a regressor, or run experiment on wines at the same price?
- How do we separate brand name impact from pure label design impact? Should we run experiment of lesser-known brands only?
- How do we categorize the "emotion" invoked by label design?
It would be interesting to see if any data scientist or startup company can dig into the science of wine label design and reveal the obscure trends in consumer preference.
However, at the end of the day the consumer has to make a purchase decision. So how does she actually selects a bottle of wine amidst uncertainty and lack of information? The possible approaches are:
a) Pick randomly ("I'll just try this bottle for no reason")
b) Consult someone at the store / online ("Let me ask the wine specialist / Vivino")
c) Go with her "gut" ("This bottle looks interesting")
I'd like to dive a bit deeper into approach c). What is the "gut feeling" of a customer, and based on what is the gut feeling formed? More specifically, if a consumer looks at 10 bottles of wines from the same region / grapes at the same price, what would influence her gut feeling?
The most straightforward hypothesis is that label design, when all else are equal, heavily influence consumers' purchase decision. I think it would be very interesting to use regression analysis / machine learning to understand the specific factors that drive consumer adoption. Several factors / regressors to consider in this analysis, for example:
Brand name:
- Length
- Binary variables for category (e.g., has name of location, has animal, has family name, has number...)
- Language (English, French, German, not a real word, etc.)
Label design:
- Brand name font and font size
- Color scheme (number of colors, background color, dominant color(s), etc.)
- Center image category (estate, nature, grape, animal, human, coat of arms, signature, no image, etc.)
- Center image style (watercolor, oil painting, sketches, modern art, wood-carved, etc.)
Label information:
- Grape varietal shown
- Vintage shown / vintage year
- Appellation / AVA / geography shown
There are other nuanced but important decisions to make for this experiment. For example:
- Do we want to include price as a regressor, or run experiment on wines at the same price?
- How do we separate brand name impact from pure label design impact? Should we run experiment of lesser-known brands only?
- How do we categorize the "emotion" invoked by label design?
It would be interesting to see if any data scientist or startup company can dig into the science of wine label design and reveal the obscure trends in consumer preference.
Relating a Wine’s Label with its Seal: The Movement toward Screw Tops
Listening to both Yoav Gilat and Terry Wheatley’s comments
regarding their wine labels and the level of detailed consideration that goes
into the labeling, I began to wonder about how much weight is placed on the decision
of sealing the wine with a cork versus a screw cap.
There are many important considerations when making this
decision beyond just branding and marketing. According to James Foster, senior
winemaker at Cupcake Vineyards, the decision is largely dependent on the type
of wine (not necessarily meaning the quality of the wine). (1) For example,
Foster uses screw caps for sauvignon blanc and pinot grigio because it more
effectively seals the bottle of wine, preventing oxygen from entering the
bottle and better preserving the wine. (1) He chooses cork or synthetic cork,
however, for chardonnay and red wines, which improve with the small amount of
oxygen that cork allows to enter the bottle. (1) In addition winemakers are
starting to abandon cork because of issues of cork taint, which causes the wine
to develop a moldy and musky taste. (2) Some studies say that cork taint
effects as many as one in ten bottle of wine. (2) Frustrated by frequency of
this issue, some wineries have even moved to 100% screw caps to eliminate the
problem all together. (2) While there are numerous scientific reasons for
opting for screw caps over cork, consumer perceptions could still be
controlling the winemakers’ decisions. (1)
Screw caps are a more economical option for winemakers and
were first adopted by winemakers producing cheaper wines. That plus the
diversion from the traditional cork created a perception among consumers that
screw top wines were cheaper and of a lesser quality than corked wines. Still,
winemakers have increasingly been choosing screw tops over cork. In the 1990s,
95% of wine was sealed with cork but that number dropped as low as 62% in 2009.
(2) The broad adoption of the screw top combined with its ease of use has been
gradually changing its perception.
Considering the thought and resources involved in creating a
wine label, I wonder how wineries choose to make labeling decisions and sealing
decisions together as opposed to independently. Does the type of seal change a
labeling strategy? Or are most wineries that choose to target customer segments
with modernized labels relatively unconcerned with the consumer’s hesitation to
select a screw top bottle?
Sources:
Sunday, February 18, 2018
What’s the Deal with the Names of Large Format Wine Bottles?
Many of the names of large format champagne and wine bottles have biblical names (primarily named after kings). They are names that have been used throughout history (actually, mostly originating in Scotland), but are now largely out of use. According to wineworld.com, it is now illegal to put these names of these bottles, and are not just a fun thing to know in quizzes. However, there’s one exception – the magnum.
It’s one of the oldest of all the terms – first appearing in a poem by Robert Burns in 1788. It is an abbreviation of magnum bonum, which means “a large good thing.” In Scotland it first came to be used for wine bottles, but now has been used to refer to many varieties of things (e.g., potatoes, cooking plums, guns, and apparently a large-barreled steel pen).
Here’s a list of some other bottle names and sizes for your next bar trivia night:
|
Name
|
Volume in bottles
|
|
Magnum*
|
2
|
|
Jeroboam
|
4
|
|
Rehoboam
|
6
|
|
Methuselah
|
8
|
|
Salmanazar
|
12
|
|
Balthazar
|
16
|
|
Nebuchadnezzar
|
20
|
|
Melchior
|
24
|
|
Solomon
|
28
|
|
Soverign
|
33.3
|
|
Primat
|
36
|
National Day Day
National Walk Around Things Day. National Dirty Dishes Day. National Pizza With the Works Without Anchovies Day. (source)
If you follow any brand on Instagram, it's likely that you know just how truly bizarre the "national day of" celebrations can get.
This came to mind today when, lo and behold, I scrolled through social media and saw that it was yet another holiday: National Drink Wine Day. Now what's so special about February 18th for National Drink Wine Day? How about:
If you follow any brand on Instagram, it's likely that you know just how truly bizarre the "national day of" celebrations can get.
This came to mind today when, lo and behold, I scrolled through social media and saw that it was yet another holiday: National Drink Wine Day. Now what's so special about February 18th for National Drink Wine Day? How about:
- March 3rd, National Mulled Wine Day
- April 17th, International Malbec Day
- April 24th, Sauvignon Blanc Day
- May 9th, National Moscato Day
- May 21st, National Chardonnay Day
- May 25th, National Wine Day
- June 11th, Rosé Day
- July 25th, National Wine and Cheese Day
- August 1st, National Albariño Day
- August 18th, National Pinot Noir Day
- September 3rd, International Cabernet Day
- September 18th, International Granache Day
- November 7th, International Merlot Day
- November 12th, International Tempranillo Day
- November 19th, National Zinfandel Day
- December 31st, National Champagne Day (source 1, 2)
The list goes on.
We know that these kinds of holidays are so-called marketing ploys, often used to boost sales during off-season, "Hallmark-certified" holiday times. But do they actually lead to an increase in sales?
While there's very little published resource about lift attributed to national days, I did stumble across this article that somewhat recently (2015) studies cross-industry peak times in revenue. No surprise -- traditional holidays still make up upwards of 30% of companies' annual revenues. What's interesting, though, is how new e-commerce retailers are making changes in traditional consumers' shopping behaviors:
"But today’s most innovative online retailers—companies like Mizzen & Main, Harry’s, Plated, and more—build relationships with their customers throughout the year. They use subscription models to create regular purchase habits, build high-quality brands to nurture affinity, and use effective (but not always discount-based) retention marketing. Because of this, they’re less reliant on holiday shopping than traditional retailers."
I wonder: can some of the more recent wine club startups (ex: Vinebox) contribute to more regular, repeat purchases?
Saturday, February 17, 2018
Conjoint & Wine
Before the GSB I worked for two year in economic consulting, and about 80% of my time was doing conjoint analysis. Conjoint analysis is a really common tool in surveying and marketing to determine how much a consumer is willing to pay for a feature of a product. For example, are you willing to pay more for a jacket that is red or blue? Wool or polyester? And how much? The way that it is (generally) done is by showing consumers a few different options of a product, and seeing which one they select. So the study might show you three items:
(1) A red jacket, made of wool, produced in America, priced at $100
(2) A blue jacket, made of wool, produced in Bangladesh, priced at $120
(3) A red jacket, made of polyester, produced in America, priced at $80
After showing a variety of different selections to thousands of people, researchers can parse out your willingness to pay for each attribute of the item (e.g., I am willing to pay $10 more for a red jacket than a blue one).
In academia, some very classical studies have been done on wine. There are multiple articles written by two professors in Spain (Mercedes Sánchez and José Maria Gil) that evaluate consumers’ preferences on wine from two different Spanish regions – Aragon and Navarre. One that I find particularly interesting evaluates the difference in consumer preferences by the outlet where they purchase (wine shops, supermarkets and directly from the producer). Here, instead of evaluating exactly willingness to pay, they used a slightly different model and evaluate the attribute that has the biggest impact on a consumer’s decision. They find that price is the most important aspect for wine shop consumers, origin is the most important attribute for supermarket buyers and vintage is the most important for those who buy wine directly from the produce.
What do you think are some potential reasons for this?
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