Big Data Tips from Frescobaldi and Ferrari

First thing this week is to say Thank You -- to those of you who read these posts, those who comment, and those who challenge us with your queries. We'll be taking a break from Enolytics 101 next week to spend time with family for the Thanksgiving holiday, and we'll be Giving Thanks for this new community that's growing and evolving this year.

There's lot of work to do before the end of the year, and one of the presentations I'm anticipating the most is in early December at Wine2Wine, VinItaly International's conference in Verona that's dedicated to the business of the industry.

I was asked to pull together a panel on big data to discuss how conference attendees (mainly Italian wine brands) can use big data in order to sell more wine in the U.S.

So on this panel, team leaders from Ferrari and Frescobaldi wineries will speak to how they utilize B2B data for the U.S. market; Ferrari will also discuss the impact of their social media success (think Emmy Awards, Lindsey Vonn, and some 90+ million impressions).

My contribution will be to add the consumer perspective from our data partners, and to explore how the B2B applications jive with B2C.

Here specifically are the queries we're making on behalf of those two brands, of wine consumer data records within the U.S.

  • 3 Most popular wine styles by each producer (according to consumers)
  • 3 Most popular wines by each producer (according to consumers)
  • 3 Worst rated wines by each producer (according to consumers)
  • Top 3 markets of consumption for each producer (according to consumers)
  • Select 1 wine from each producer and pull the 5 most common words that consumers use to describe that wine
  • Heatmaps for each producer, visualizing market-specific popularity among consumers

Frescobaldi and Ferrari already have an understanding of these queries from the B2B perspective. What's new is seeing the queries from the perspective of the consumer.

It should be interesting! And I'm looking forward very much to sharing with you the results.

PS Several of you have asked about the "moonshot" question I mentioned last week, on how big data can help design wine labels that are more consumer-appealing. Meininger's Wine Business International, whose editor-in-chief Felicity Carter is the fourth member of our big data panel, published my more detailed explanation of the question this week.

Thank you, as always, for reading these posts --