As I said in other posts, wine world is moving itself very slowly in the tech world. Use of monitoring systems is started since a few years ago, but harvest data about wine for Data Analysis activities it’s no so used as in other markets.
Cropping Wine Data
So, very few winemakers using in a smart way the powerful of Internet.
Let’s us consider use of public data, like those we all spread when we surf in the web. There are some government organizations showing some kind of data about wine: list of production by year, amount of hectoliters by variety, and so on.
But they are not upgraded, they are old. Not many countries, among wine makers ones, display their wine data, and all of those are ufficial data, from government institutions.
And what about data produced from vineries, from supply chain, from customers?
When a vinery sell its bottle, it knows only if it will go in Europe, in Asia, in USA or other. Nothing about final customer, restaurant, wine shop or individual; nothing about sentiment from social networks, and nothing about number of bottles they produce.
Yes, every vinery has these data in its website, but you have to read all those websites if you want to know the general framework.
If vineries wanted to show data, then they would need a platform where to store their data and informations and, mainly, where these data could be elaborated to take out value information.
Hot to use Open Data
But, how can we get vineries put these data in the platform? These are figures of their market, and not all want to share with others vineries.
One solution is to offer them an added value, a revenue from their own data, a gift they didn’t know to own.
Crossing sales data with number of tweets, for example, can let them know what wine lovers think of that wine and where they are tweeting from; this knowledge can help the vinery to address its social marketing strategy.
Or, we can ask to data where a specific type of wine is more drunk and check how are going our wine in that country.
We are now beginning to see tracking devices mounted over the bottle, recording data from its travel and parameters as temperature and humidity. Merging data from all vineries using these kind of devices, it could give a map of movement of bottles all around the world.
Putting together climate data and storical series of wine production, we could find out how exactly the climate change is modifying vines distribution and productivity. And so on.
What I mean, is that many companies in the world are using Data Science to find hidden information about their products, goods or services; but for Data Science, it needs … Data. And wine, hasn’t.