Depletion Data Case Study: Insights from Within the Winery Itself

Let me start with the two questions that we’ve been working on for wineries this week:

  1. How can I use the data I already have?

  2. What can I learn from my depletion data specifically?

Now let’s look at the “sub questions,” or the subtext, that are driving those two main questions:

  1. How can I maximize my own resources, so I don’t have to spend a ton of money to figure out the data thing?

  2. My reality is that I need to make the same presentation to distributors over and over, just in different markets. Can I template that presentation, but change out the variables when I need to?

Fair enough, right? And maybe they even sound familiar, or are topics you could relate to, yourself.

So let’s take them one at a time.

Using the Data You Already Have

A winery already has data, probably quite a lot of it in fact, including depletions, ecommerce sales, viticultural analysis, location inventory and FOB changes.

The benefit of all this data? You already own it, so you don’t have to go out and pay someone else to provide it. If you could export it to an Excel or csv file, then we can start to work with it.

That’s the foundation.

The next step is using your data, which is where we come in as we start to work with the spreadsheets. Our team cleans the data, packages it, and then visualizes it in a dynamic and interactive dashboard.

Using Depletion Data Specifically

Let’s take one example – depletion data – and how this actually looks. The image above is a screenshot from a dashboard that we’re developing.

Here are four things to notice:

  1. This is just one screen, and one visualization, taken from one set of data. There are practically innumerable iterations of what you can visualize.

  2. Notice the various fields, like those running down the left-hand side of the image. These are dynamic, which means that if you click on any of the fields, the visualization to the right changes to reflect your selection. Filter by distributor, for example, and the visualization of performance adjusts to the distributor you’ve selected. Filter by state, as this example is, and the visualization adjusts to California, say, or Georgia (shown here).

  3. Notice the colors, which indicate in this case different wines, which makes it easy to see variations in volume. Green for cabernet sauvignon, for example, blue for chardonnay, and so on.

  4. The trend line, which is the bottom chart, shows rolling twelve-month analysis. This removes seasonality from the equation, which gives you a more comprehensive view of your performance over time, as opposed to being overly influenced by performance during, say, Q4.

You can start to see, I think, how you can build a template for the presentations you need to make again and again, as I mentioned at the top. The key is being able to select the fields according to what you need to know, and in which market.

It’s up to you. It happens dynamically. And you can drive the dashboard to where you need it to go.

Does that make sense?

Please let me know. We’d love to hear your thoughts and suggestions for how this could be useful to you.

Thank you for reading, as always –

Cathy

Previous
Previous

Data + Wine + Love: The Entrepreneurial Team at the Heart of Enolytics

Next
Next

This Was One of the Hardest Things I’ve Ever Done. Here’s Why It Was Worth It. (Probably.)