Assessment of Customer Emotional States While Interacting with Digital Touchpoints of E-Commerce Product Pages: A Kansei Engineering Approach

Abstract

The study proposes a method for the assessment of e-shop product pages (PPs) through individual assessments of the touchpoints (TPs) customers interact with while using a PP (e.g., product title, main image, image gallery, Buy Box, rating/reviews number, product description, specifications, cross sales/recommended products, video, and product warnings) rather than an assessment of the product page as a whole. A specific Kansei list is created, customer preferences are collected, and touchpoints can be classified as positive, neutral, or negative (pain points). The assessment method was applied to the assessment of PPs of craft beer e-retailers. Once pain points were identified, two distinct types of TPs among them were individually analyzed (one visual, the Image gallery, and one textual, the Product description.) In both cases, a set of PPs were employed as stimuli and design elements that were deemed preferable by the customers were identified through Partial Least Squares analysis. The results provided valuable recommendations to web designers, content creators, and retailers for improving their PP content by taking into consideration the customers' emotional states and preferences.