What Catches the Eye? A Conjoint Study of Infographic Design Preferences

2026-05-26

AI Summary

This study addresses a critical gap in visualization research by moving beyond isolated examinations of individual visual attributes in infographics, which have limited explanatory power regarding how readers navigate trade-offs in multidimensional designs. For the first time in the field, choice-based conjoint analysis is introduced to systematically evaluate the relative influence of three design dimensions—comparison type, color scheme, and chart type—on overall user preference. Through a paired-comparison experiment simulating newspaper infographics on unemployment, the findings reveal that comparison type accounts for 58.5% of preference variance, with users strongly favoring percentage scales anchored to a reference point; chart type contributes 29.2%, while color exerts only a marginal effect. Beyond quantifying the importance hierarchy of design attributes, this work demonstrates the methodological promise of conjoint analysis for optimizing infographic design.

Abstract

Infographic designers balance many choices at once: chart type, color, and whether to add a benchmark or a scale. Past work studies these factors one at a time, so we know little about how readers weigh them against each other. We address this gap with a choice-based conjoint study (N = 65) in which participants viewed pairs of infographics on a mock newspaper page about unemployment. Each infographic varied across three attributes: comparison type (none, US average, percentage scale), color (red, blue), and graphic type (single icon, icon series, bar chart). Comparison type drove most of the preference variation (58.5%), followed by graphic type (29.2%) and color (12.3%). Readers favored percentage scale markers and benchmark comparisons; color had no practical effect. The percentage scale level adds axis information rather than a benchmark, so the comparison type result mixes two distinct ideas. A single topic and a narrow palette also limit external validity. We argue that conjoint analysis is a practical and underused tool for studying visualization preferences across many design dimensions.

Problem

• infographic design
• design preferences
• conjoint analysis
• visualization
• comparison type

Innovation

• conjoint analysis
• infographic design
• visualization preferences
• multi-attribute decision
• design evaluation