This chapter explores rapid descriptive sensory analysis methodologies (Check-All-That-Apply (CATA), Free Choice Profile (FCP), Flash Profile (FP), Pivot Profile, and Napping®) as efficient alternatives to traditional methods. These techniques enable the collection of reliable data using untrained panels or consumers, reducing time and costs in food product development. Their theoretical foundations, practical applications, and limitations are discussed: CATA is notable for its simplicity, using predefined lists of terms; FCP captures individual perceptions through free vocabulary; FP combines direct comparison with spontaneous description; Pivot Profile compares samples to a reference product; and Napping® maps similarities among products in a two-dimensional space. Practical aspects highlight the importance of selecting appropriate participants, designing balanced sessions, and employing specific statistical analyses. A case study with muffins illustrates how these techniques discriminate between formulations with different sugar content: CATA identified key attributes (“sweet” and “moist”), FP detected textural differences, and Napping® confirmed similarity-based groupings. In conclusion, these methodologies offer agility without compromising rigor, making them ideal for the food industry. Their selection depends on the study objectives, product complexity, and available resources. Future research could integrate them with advanced sensometric tools to enhance accuracy and product development.