The global wine industry is expected to generate almost $292 billion in 2014, reports MarketLine. At that point market volume should exceed 22.1 billion liters, representing a near 3.5% increase in five years. Still wine represents the leading market segment, accounting for almost 81% of the global wine market.
The world wine market is characterized by intense fragmentation. The wine market can lose ground to alternatives such as beer and spirits, especially as consumptions trends change. The market is characterized by a moderate degree of competition.
Wineries are involved in the manufacture of wine from the fermented juice of grapes. Most wines have an alcohol content of between 10% and 15%. Wineries may also grow grapes, manufacture brandies and blend wines.
In India, the wine industry is now an emerging market. The manufacturing of wine and its consumption in India is insignificant in comparison to any other countries. Generally the wine production in India has arisen since the 1980s. Production of wine in India peaked in 2010 at about 130,000 hl, according to a report. The prospects of growth for wine in India are quite high.
States like Maharashtra, Karnataka and Himachal Pradesh have taken steps to encourage the wine industry and given preferential treatments by liberalizing their excise regime and reducing excise duties. Eighty percent consumption of wine in India is confined to major cities such as Mumbai, Delhi, Bangalore and the Goa.
One of the most interesting cases of real time usage of big data is chronicled by Chris Taylor in his blog that tells of the journey to create VinSpin, a mobile application to provide personalized wine recommendations.
According to Bersofsky [VinSpin Founder], the wine industry has been ruled by small data for a long time. People have had very little to go on to work out whether a bottle of wine is good or not — really just the opinion of a handful of wine reviewers, whose descriptions may or may not be tacked up on the racks in the local liquor store. Such limited data made people very uncomfortable spending their money on a bottle.
The idea behind using big data here is to give a personalized wine experience to each consumer. The app focuses on marketing a wine recommendation engine that can be accessible anywhere, anytime. This will make it easy for the customer to get the right kind of reviews of the quality of a wine as well as the price of the wine.
In developing wine markets, such apps, with the aid of big data, could also teach the correct real time usage of each wine, i.e. correct wine-food pairings, traditional ideas about wine drinking, etc.
IntelligenceNODE believes that the real time uses of big data are quite mind boggling; we may not even have thought of all of these.