Demand Analysis of Traditional Chinese Medicine Diet Recommendation App Based on AHP-KANO Model

Abstract

As an important part of traditional health concepts, traditional Chinese medicine diet has gradually attracted attention among modern young people. However, most of the existing diet apps focus on nutritional matching and calorie management, and lack accurate recommendations for the efficacy of traditional Chinese medicine ingredients, functional drinks and personalized conditioning needs, making it difficult to meet the diversified health expectations of users. Therefore, this paper proposes a demand analysis method based on the AHP-KANO model to construct the design framework of TCM diet recommendation app to improve product experience and user satisfaction. Firstly, the KANO model was used to identify and classify users' demand attributes for ingredient selection, ingredient function, functional beverages and beauty meal replacements, and refined the core user expectations. Secondly, the analytic hierarchy process (AHP) is used to rank the weights of different requirements and determine the key functions. Finally, the results are transformed into interactive design elements and system function modules to provide a basis for subsequent interfaces and interaction schemes. Through the survey and demand modeling of target users, a set of functional frameworks covering ingredient recommendation, efficacy query, personalized diet plan and interesting interaction was obtained, and an actionable priority distribution was formed. Demand analysis based on AHP-KANO model can effectively allow users to obtain multi-level needs in traditional Chinese medicine diet apps, solve the problems of single function and insufficient interaction in traditional diet applications, provide a scientific reference path for subsequent interaction design and system optimization, and also provide reference for the development of similar health apps.