MaxDiff, short for maximum difference scaling, is a quantitative research technique used to measure the relative preference, importance, or appeal of items across a defined set. Participants are shown small subsets of items and asked to identify which they find most and least appealing, a forced-choice format that eliminates the acquiescence bias common in Likert-scale surveys. Because every item is evaluated multiple times across different subsets, MaxDiff produces interval-level scores that can be ranked and compared across segments. In consumer insights and market research, MaxDiff is widely used for feature prioritisation, message testing, concept screening, and brand attribute ranking, making it a reliable tool for enterprise teams that need defensible, decision-ready preference data.