Data Viz Audience considerations

When I prepare a conference talk or a workshop, I am tailoring my talk or workshop to the expected audience. For example, I will add details about the country or city the conference is in. Adding pictures of the town, or in case of my workshops use data from that city to use as examples or exercises for the participants. Thinking about who is in the audience helps them to relate more to my talk/workshop and hopefully pay closer attention.

The same is true if you create a visualization. You need to think about who the audience of your visualization is. The first Step, when Iā€™m tasks to create a visualization is to think about or ask the customer who the target audience for that visualization is.

Choosing an audience will help you keep on track

Choosing an audience will inform the questions you ask your data and the questions you try to answer in your exploratory analysis. It will help you keep on track and evaluate your findings.

When you get stuck, knowing who your audience is and maybe even evaluate or change your question to ask the data helps you.

Much of visualization design is about figuring out the audience (Nathan Yau)

You will most definitely refine your audience once you're in the exploratory analysis stage.

The more you know about your audience, the easier it is to design visualizations for it.

You want to relate back to your audience when you analyze the data for the first time.

While doing the exploratory analysis, you want to relate back to your audience and think about the questions they might have for the data. I formulated a few already, so here is my first initial list of questions I want to ask the data.

Next Steps is to find more data

The next step after I have my audience and already a few starting questions are to evaluate if I have enough data already or if I need to look for additional datasets I can use to answer these questions.