Conversations: Spilling the Data Science Tea

Tea is pretty simple stuff, right? Pour hot water over some leaves and suddenly you have a fantastic caffeinated beverage. It’s an ancient tradition that has been a part of billions of peoples’ daily rituals for years. So how do you innovate that which has existed for almost all of human history?

The Art of Tea is trying to push this centuries-old beverage a little further into the modern era, not by changing anything about the tea itself, but rather the way in which it ends up in your cup. By using a more modern and analytical approach to marketing and selling tea, the Art of Tea is leveraging current-day business practices to change the

We sat down with Madison Way — Marketing Coordinator at the Art of Tea — to find out a little bit more about how they work!

Humanlytics: What’s the industry standard with regards to data science and predictive analytics?

Art of Tea: Tea is an old school industry. (It’s literally ancient.) Companies within the industry get most of their data from trade magazines, not data analytics done in-house.

H: In that case, how do you see your industry adapting and changing in response to the rise of data science and predictive analytics?

AoT: A lot of the tea and coffee space is focused on the fall of soda/sugary drinks and how to capitalize on that. Yet very few companies are actively looking into the data behind this change.

H: Are you “changing the game” in any particular way, especially with regards to using data science/predictive analytics?

AoT: Tea is an agricultural product, so our team is constantly forecasting sales in order to avoid shortages.

H: How do use data science and predictive analytics to make that happen?

AoT: Not often enough. We use Google Analytics and often work with SEO teams, but we could be doing more in the way of making data-informed decisions.

H: What tools do you/your company use for data science and/or Predictive Analytics?

AoT: We use Hubspot Analytics and Google Analytics.

H: How can businesses like yours use data science to make products/services better and more accessible for the average consumer?

AoT: We’d use data science to better understand our Wholesale and Retail customers, predict which ingredients and teas will rise in popularity, and better forecast our sales.

H: Do you have any personal thoughts on the future of data science, machine learning, predictive analytics, artificial intelligence, or anything like that?

AoT: I’m personally excited for the rise of “Big Data” and am open to sharing my personal information for the good of Big Data.

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