What Does Sincerity Sound Like? Designing Brand Personality Using Audio

Brands increasingly use audio logos, short and distinctive sonic signatures, as central elements of their identity across advertising, digital products and services, and points of sale. Listeners readily infer a brand's personality from these few seconds of sound, so design choices shape how a brand is perceived. Yet empirical guidance about which sound properties convey which personality is limited, and whether such guidance would improve on designers' intuition and experience is an open question. We compile a novel dataset of 696 audio logos and combine interpretable acoustic features, grounded in music theory and perception, with flexible machine-learning models to identify the sound properties associated with each brand personality dimension. We translate these relationships into directional design insights and test the Sincerity insights in a field experiment in which professional sound designers redesign unreleased audio logos to sound more sincere. Designers' unaided intuitions align with many of the identified relationships, but designers who receive the insights are more likely to adjust features in the recommended directions and make larger adjustments. Their redesigns are rated significantly more sincere than the originals and marginally more sincere than logos redesigned without the insights, with no detectable shifts in other personality dimensions and no loss in design diversity. These findings show that data-driven insights can sharpen, rather than replace, professional intuition in designing sound to convey brand personality.