When you’re creating content — whether it’s a film, a sales presentation, or an article on maximizing your Thanksgiving leftovers — it’s always important to consider who your audience is; this also holds true for data visualization. I’ve touched upon this in my previous blog posts, but let‘s take a closer look at the audience spectrum specific to data visualization.

Imagine a spectrum: On one end, let’s say the extreme left, we have the analysts — the scientists — starved of data and wanting as much of it as possible. In fact, there is too much data, and they need an easier way to scan it all to help illustrate relationships and patterns. This is where data visualization can help. The data is raw, and they are digging through it to discover their own conclusions, so a visualization that enables this exploration of the data is crucial. There are usually several dimensions squeezed into a small amount of space, so it’s important to balance the graphic — keeping it both compact and clean. Maps are one example — from heatmaps showing cancer rates across US districts to subway maps; interactive dashboards are another — from Google Finance to the range of examples that tableau presents. They don’t start out with any specific storyline, and the viewer has full control in navigating all the information.

On the other end of the spectrum, we have an audience who is not savvy with the data. They are usually presented with the results and conclusions of an analysis and need to be guided through a clear storyline and recognize a specific point. For this audience, it is crucial that only the important data stands out and that you highlight and make clear to them the relationships and patterns. The data is edited down to the bare essentials, and everything is designed to be as approachable as possible – meaning it’s easy to comprehend quickly and easily. Think of these types of visualizations as more like marketing material. The audience is not familiar with the information, they don’t have a lot of patience for it, and so you need to "advertise" the data and explain it as efficiently and as quickly as possible. In fact, examples can include advertisements, along with executive presentations and short, clear introductory graphics before articles.

But these are the extremes, and there are many degrees in between. To understand an audience who might fall between these two ends, look at the interactive charts by The New York Times. Its audience has a varying degree of interest and understanding of any given topic, but The NY Times does a great job of both grabbing your attention with something quick, fun, and engaging — catering to the right side of our spectrum — while offering lots of data underneath the surface for those leaning more toward the left.

It’s important to realize where your audience members fall on the spectrum and to tailor your visualization to meeting their needs: How much data do they need to see? How invested are they in the information? From my own experience, I can tell you that most audiences will lean heavily to the right, preferring curated storylines — so it might be a safe bet to skew in that direction. Better to have them ask for more data than to overwhelm them with too much.