For decades designers, marketers and executives have been designing presentations and reports and sharing them with co-workers and clients in order to create buy-in and motivate people to action. Although these presentations are generally carefully crafted, their effectiveness often varies. We have all been in the position of having to present important data many times throughout our careers. We all rely on tricks we have been taught to increase effectiveness of relaying our message. We have been told that having a strong title is critical and incorporating visuals is a must. But what visuals resonate the most and what titles are most effective? Is what we have been told true, and if so where is the proof?
In a recent study titled Beyond Memorability: Visualization Recognition and Recall, the authors Michelle A. Borkin, Zoya Bylinskii, Nam Wook Kim, Constance May Bainbridge, Chelsea S. Yeh, Daniel Borkin, Hanspeter Pfister and Aude Oliva pair eye-tracking research and qualitative research techniques to provide empirical proof of how to create a better presentation or report that will win over even the most skeptical people in the room. Below are the conclusions from their study.
We summarize below the key observations from our study. In addition to our experimental results shedding light on the fundamental theory of how visualizations are encoded, recognized, and recalled from memory, our results also provide direct quantitative empirical evidence in support of many conventional established qualitative visualization design and presentation guidelines.
The conclusions listed below, with related established design principles where appropriate, relate to having a good and clear presentation, making effective use of text and annotations, drawing a viewer’s attention to the important details, providing effective visual hooks for recall, and guiding the viewer through a visualization using effective composition and visual narrative.
- Visualizations that are memorable “at-a-glance” have memorable content. Visualizations that are most memorable “at-a-glance” are those that can be quickly retrieved from memory (i.e., require less eye movements to recognize the visualization). Importantly, when these visualizations are retrieved from memory, many details of the visualization are retrieved as well. Thus, participant-generated descriptions tend to be higher quality for these visualizations.
Titles and text are key elements in a visualization and help recall the message. Titles and text attract people’s attention, are dwelled upon during encoding, and correspondingly contribute to recognition and recall. People spend the most amount of time looking at the text in a visualization, and more specifically, the title. If a title is not present, or is in an unexpected location (i.e., not at the top of the visualization), other textual elements receive attention. As exhibited by these results, the content of a title has a significant impact on what a person will take away from, and later recall, about a visualization.
“Words on graphics are data-ink. It is nearly always helpful to write little messages on the plotting field to explain the data, to label outliers and interesting data points.” (Edward Tufte)
- Pictograms do not hinder the memory or understanding of a visualization. Visualizations that contain pictograms tend to be better recognized and described. Pictograms can often serve as visual hooks into memory, allowing a visualization to be retrieved from memory more effectively. If designed well, pictograms can help convey the message of the visualization, as an alternative, and addition to text.
“The same ink should often serve more than one graphical purpose. A graphical element may carry data information and also perform a design function usually left to non-data-ink. Or it might show several different pieces of data. Such multi-functioning graphical elements, if designed with care and subtlety, can effectively display complex, multivariate data.” (Edward Tufte)
- Redundancy helps with visualization recall and understanding. When redundancy is present to communicate quantitative values (data redundancy) or the main trends or concepts of a visualization (message redundancy), the data is presented more clearly as measured through better-quality descriptions and a better understanding of the message of the visualization at recall.
“Redundancy, upon occasion, has its uses; giving a context and order to complexity, facilitating comparisons over various parts of the data, perhaps creating an aesthetic balance.” (Edward Tufte) “Telling things once is often not enough: redundancy helps restore messages damaged by noise.” (Jean-Luc Doumont) Read more about the study here or read the full study here.