“Kansei” comes from the Japanese characters “感” (feeling, sense, emotion, impression) “性” (quality, attribute). Academically speaking, Kansei is the tacit process of humans that is activated by interacting with artifacts or systems. Kansei is a fundamental mental process of communication between objects and humans. From a practical approach (engineering), Kansei is a methodology for product development that translates users’ feelings, impressions and emotions into design parameters.

There are two basic approaches to initialize any Kansei project. One approach uses data regarding sales of the targeted product/service to conduct a perceptual analysis correspondant to the intended market segment. The other approach uses a target semantic keyword of the product (desired affections to be perceived) for the design or re-design of the products/services.

The primary outcome is a series of recommendations highlighting the user’s perception of the products, strategies for re-design or marketise the products, etc.

An average of 1-3 months is required to estimate, classify, analyze and create strategies for each user group.

Analytics (which includes the application of Machine Learning, Artificial Intelligence, etc.) is a process that involves a systematic computational analysis of data to discover insights to help companies to make better decisions. Hence, Analytics complements the Kansei methodology by enhancing the sophisticated tasks by giving the technological capabilities to analyze, predict and optimize any requirement.

No, since Kansei is a user oriented methodology, it can be applicable to any industry.