This week we’d like to walk you through what it’s like to start a data project of your own.

Maybe it’s the timing of the New Year (and New Year’s resolutions) related to being smarter and more strategic with your business, but we’ve definitely seen an uptick of interest in 2020 in starting data-based projects.

The two most common requests we’ve heard?

1. We want to package and visualize data that we purchase. We spend a lot of money on it, but we know we aren’t maximizing its usefulness.”

2. “We want to dive deep into our DTC database to identify patterns of purchases, and to help us understand the best mix of offerings to our customers who are primed to receive them.”

Sound familiar?

We’re excited to say that you are not alone, and that we know how to help you.

In both of these cases, the process follows the same five steps. It starts with buy in, or a readiness at the senior level to dive into this work.

Let’s get started.

Step One: Buy In

It’s a fundamental first step. Even if you’ll be the contact person at your winery or organization who’s owning the project, you’ll need buy-in at the senior level. The most common obstacles we hear are concerns about privacy and budget, and we address them both thoroughly.

Step Two: Transferring the Data

In some cases, you’ll already own the data, and you’d transfer it to us usually as .csv files. In other cases – with a DTC platform such as Wine Direct, for example – we’d work together to acquire the data automatically and continuously through an API.

“API” is an acronym that means Application Program Interface, and it’s essentially the way that our system “talks” to the system that houses the data, in order to execute the transfer of files. The goal is that this set-up process happens only once; after that, it’s automated for efficiency.

Step Three: Data Prep

Once the data transfer is set up, we go through a process of “data prep,” also called transformation or massaging the data so that it’s in a consistent format.

As you can imagine, data within the wine industry exists in a wide range of formats; the goal here is to standardize  for efficiency, which makes it exponentially easier for you and for us.

Step Four: Interactive Dashboard

Once the data has been received and prepped, we use it to populate an interactive dashboard with your data that’s organized around KPIs (Key Performance Indicators) and detailed analysis on the different parts of your data. This includes (but is not limited to) trending and predictive analysis.

The goal here is for the dashboard’s interface to be both robust and easy to use, particularly for people (like me…) who aren’t trained in data analysis. Our intention is also to “populate” the dashboard with actionable insights that you can truly use on a day-to-day basis.

Believe me, I’ve been the guinea pig of the user experience more than once!

Step Five: Training and Maintenance

As time goes on, we’ll release updates and add new visualizations and features based on customer feedback.

Which means that there will be a program of training via webinars or other educational materials. The goal here, ultimately, is for you to feel comfortable using what we build with your data.

It’s a deeply felt objective, since data is only as good as its practical, real-world applications. If you aren’t using what we build with the data you provide, and if you aren’t learning from it, then we’ve failed in our goal.

How do these five steps sound to you?

Doable?

We hope so.

We’re here to help, and to show you that starting a data project of your own isn’t nearly as overwhelming as you might think.

I look forward to starting, or continuing, the conversation.

Thank you as always for reading –

Cathy