Too often we think that if we make a decent data visualization, it’s a guarantee that people will stop, look, and listen. There’s a big chasm between information and action. The bridge across that chasm is engagement. The brilliant Alli Torban joins me today to explore how we can more effectively address engagement with interventions targeted for the particular kind of audience you’re trying to reach. Those four audience types, and what you can do to engage them, are:

Interested & Focused (e.g. a board director reading an annual report): Reduce the friction with clean, approachable charts and clear information. No “chart junk”!

Interested & Distracted/Overwhelmed (e.g. a CEO or Executive Director): “What’s in it for me?” – put the viewer at the center of the chart by highlighting what they specifically need to know.

Disinterested & Focused (e.g. a reader of a general magazine, a high-net worth donor seeking a fitting recipient): Offer a “welcoming gesture.” Make your chart inviting, artistic, or story-driven. This is data art – engaging in its own sake.

Disinterested & Distracted (everyone on social media!): It has to be eye-catching, tastefully animated, entertaining, unique or unusual. Stop the scroll! Check out the fascinating animated chart I reference here.

Alli Torban is an Information Design Consultant in Washington, D.C. where she helps researchers get more engagement with their work by creating data visualizations, infographics, and data art. She’s worked with clients like P&G, Axios, Michael J Fox Foundation, and Data Literacy. Alli is also the host of the popular podcast Data Viz Today, which has been downloaded over 150,000 times. In her spare time, she loves designing tessellations and reading to her two young daughters. Find her at or on Twitter and Instagram with @allitorban.

One thing you can do right now:
One thing you can do right now:

Go back to an existing visualization from your team or organization. Identify which quadrant the intended audience falls into. Then see if you can adjust the graph to better fit that quadrant. Or if you nailed it (good job!) see if you can adapt the visualization to another quadrant.


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