Friendly Faces for Big Data in Wine

When you're trying something new, it helps to find friendly faces who get you.

You know the ones. They're the people who speak your language, who nod their heads in understanding, who offer the appropriate "fill in" when you're stuck for a word.

With Enolytics, the "new" we're trying to do is build a data model that pieces together different sources of wine consumer behavior.

Because it's new, it takes some explaining and it doesn't always click as quickly or easily as we'd like. (That's part of the point of this Enolytics 101 series, in fact: to explain and share the topics and questions that we're hearing on a weekly basis.)

The good news is that there are people working in wine who get big data, and who get the benefits of an integrated data model. Today I'd like to take a moment to notice a quirk that those "friendly faces" seem to have in common:

Many of them tend to come from a background or previous job in CPG, or Consumer Packaged Goods, and they are used to making important business decisions based on data rather than gut or sentiment. They are looking for insights to give them an edge.

The data environment in wine is different than in CPG. We can spend many hours speculating on why that's so, but the point is that having access to more consumer data seems to come as something of a relief to these "friendly faces” and we’re very happy to see it.

What questions can we help you with? Where can we offer you some relief? I’d be very glad to hear about it. 

Thank you for reading --