Analysis: Kansei engineering aims to link a consumer's emotional responses to the features of a product or service
By Kevin D. Delaney and Colm O'Kane, TU Dublin
Why have car companies developed car faces that look meaner, angrier and, at times, even downright evil? Why does your coffee pot look happy? Why does a customer buy a Dyson instead of a Nilfisk or Hoover vacuum cleaner?
Companies always strive to produce better looking and easier-to-use products that are attractive to the customer segment that they are targeting. In doing so, they must try to understand how to link a customer's emotional responses to the properties and characteristics of a product, building or even a service that is being developed .Knowing what customers' responses will be means that products can be designed to be the best fit possible between what's expected and what's received in terms of design.
Renowned tidying expert Marie Kondo travels the world inspiring people to retain only those belongings that "spark joy" for them. Apple focus both on developing good products and creating great user experiences, from the moment the product is unpacked. Customers purchase products which "feel" better than the alternatives, and are often unable to explain why.
Design engineers must understand how to link a customer's emotional responses to the characteristics of the product or service that is being developed
In the modern environment, simply making products that work well and meet user expectations is no guarantee of success. In order to prioritise human experiences over product features, product developers have shifted their emphasis to the experiences users gain from product interactions. For successful outcomes, design engineers must try to understand how to link a customer's emotional responses to the characteristics of the product or service that is being developed.
Japanese companies are well known for their product engineering across multiple industries. Their post-war economy evolved from an initial focus on manufacturing through product development to the current emphasis on research, development and product and service innovation. Globally impactful contributions in these areas have included the "kanban" just-in-time manufacturing system, the Total Quality Management approach to product quality control, "kaizen" continuous improvement and the "kansei" approach to user-centred design.
Kansei is the impression somebody gets from a certain artefact, environment or situation using all of their senses of sight, hearing, feeling, smell, taste as well as their recognition. Kansei engineering is a Japanese design methodology which aims to link a consumer’s emotional responses to the properties and features of a product or service. By doing so, products can be designed to be the best fit possible between what’s expected and what’s received in terms of design.
Kansei is the impression somebody gets from a certain artefact, environment or situation
Dr Mitsuo Nagamachi developed the kansei engineering system in Japan more than 50 years ago. Since then, it has been applied to the development of many products such as the Mazda MX-5 Roadster, the Boeing 787 interior design and the operator controls of Komatsu construction equipment. Since being introduced to Europe about 25 years ago, this concept and closely related fields are known by terms such as affective engineering, affective ergonomics and emotional engineering.
Once the product to be designed is identified (for example, rubber boots for young children), kansei engineering involves the following steps:
(1) Kansei (or customer feeling) words and product images are collected and grouped before a representative for each group is selected by experts. Example adjectives might include modern, elegant and comfortable.
(2) Design attributes of the target product likely to have a major effect on the customer's emotional response are collected and several options for each proposed. Examples may include colour, form, texture etc.
(3) A set of products, either real or virtual, are created based on the attributes prioritised in stage 2, and shown to study participants. For example, red rounded toe boot, blue rounded toe boot, red pointed toe, red rounded toe etc
(4) A questionnaire is constructed based on the relationship between kansei words and sample images and potential users invited to evaluate the image-word relationships. Statistical methods help establish a link between the kansei words and product attributes. For example, the round toe shaped boots are perceived as comfortable.
(5) Additional analysis can be performed to see if any words are perceived in the same way and can help to define additional experiments to validate the model and refine it further, essentially training it to give more appropriate results.
(6) Results are presented in a readable, accessible format, using such tools as bar and/or radar charts to interpret, explain, and check the results.
A series of 1990 Mazda ads featuring a Kansei engineering tagline
Initially, the process involved a significant amount of subjective input by observers of a relatively small participant group. With the proliferation of multimedia data sources and the ease of harvesting data using AI and machine learning, the volume of useful, processable data has increased significantly. Big Data can be easily harnessed to generate better, sounder, more sophisticated results.
These techniques are becoming more accessible for even small companies as they strive to provide the best utilization and satisfaction to their customers. Digital tools can be used to create multiple versions of products with different attributes; just think of how you can use an app to virtually customise your own room in terms of furniture, wall colours and floor covering.
Dr Kevin D. Delaney is a lecturer and member of the Product Design and Development Research Group at the School of Mechanical and Design Engineering at TU Dublin. Dr Colm O'Kane is Senior Lecturer in Mechanical and Design Engineering, Chair of Product Design and member of the Product Design and Development Research Group at the School of Mechanical and Design Engineering at TU Dublin
The views expressed here are those of the author and do not represent or reflect the views of RTÉ