6. Consider your target viewers. – Talking Charts Guidelines

Here is what to check:

Have you considered the visual literacy of your target audience, especially if you want to reach groups other than experts?

VisLiteracySurvey In a representative* survey, self-assessed numeracy correlated significantly with data reading performance (p = 0.009). Participants rating their numeracy high (37%) had a higher data reading score median, underscoring that this skill reflects the ability of someone to read and interpret data visualizations.

*representative sample of Austria’s age groups 18–74 years and their male/female gender split, with n = 438

VisWorkshops In our workshops, we observed that viewer demographics, especially among students, influenced the complexity of takeaway messages. While students mostly recalled basic visual features, more experienced groups like designers expressed higher semantic content. Though we did not test for visual literacy levels, we discuss that they may have shaped interpretation depth.

ClimateVisInterviews In our interviews, lay participants struggled with interpreting elements like uncertainty ranges or axes, even in simple line charts. Experts emphasized that chart designers often overestimate the visual literacy of general audiences.

Viewers with less experience in reading data visualizations may struggle when charts are too complex or demand high levels of statistical understanding. Considering different levels of visual literacy can help make information clearer and more likely to be understood by broader audience groups.

Have you considered the topic familiarity of your target audience?

VisWorkshops In workshops, only 70% of participants correctly interpreted a stacked bar chart which visualized the gender pay gap. Retired and student participants struggled most, often due to unfamiliarity with the term “gender pay gap” itself. A simple definition could have improved comprehension.

CrisisMapSensemaking In our studies on crisis maps, limited topic or geographic knowledge led to uncertainty and self-doubt among digital natives. The lack of orientation cues, such as country or city labels, often left viewers confused, highlighting the need for designs that are considerate of varying expertise levels.

SciAmInterviews Editors at the Scientific American aim to reframe recurring topics like climate change in new ways to avoid overwhelming readers and to reach new audiences. Familiar topics are revisited with new insights or visual styles to maintain engagement and fight misinformation.

Avoid assuming topic familiarity, since not all viewers share the same background knowledge. If a visualization assumes prior familiarity, such as with geography or domain-specific terms, some viewers may feel excluded or misinterpret the content. Clear labels and explanations can help prevent confusion.

Have you tailored content when you have knowledge of the audience’s needs or preferences?

VisProducerInterviews Practitioners noted that elements like percentages, probabilities, large numbers, or dual axes can confuse readers. When understanding a chart depends on grasping an unfamiliar mental concept, like grasping “How big is a billion?”, it can become harder for viewers to interpret the data.

Audience backgrounds, including demographic factors and cultural influences, shape how information is read or perceived. Being mindful of potential differences in interpretation, such as reading direction or color meaning, can help ensure that a visualization is understandable for different audience groups.

Have you provided clear explanations for concepts that may be less known (e.g., uncertainty ranges)?

ClimateVisInterviews Experts debated the value of visualizing uncertainty, noting that without clear explanation, it may be mistaken for unreliability. Some lay viewers misunderstood or distrusted uncertainty ranges and preferred simpler visuals. Experts recommended explaining uncertainty in accompanying text when it is not central.

VisProducerInterviews Data visualization practitioners were split on showing uncertainty, such as in climate-related future scenarios. While some saw it as essential to the chart’s message, others argued it required too much explanation. Shaded ranges were sometimes seen as intuitive, but most preferred explaining uncertainty in accompanying text.

If specific terms or concepts, such as uncertainty ranges, may be unfamiliar to some viewers, consider explaining them in surrounding text. This maintains clarity without overloading the visual, especially when the concept is not central to understanding.