Can eye-tracking data be measured to assess product design?: Visual attention mechanism should be considered

Eye tracking probes user's perception of real-time reaction to products, while conventional methods (i.e. interviews, focus group, questionnaires and so on) have generally failed because they depend on users' willingness and competency to describe how they feel when they are exposed to a product. Two tasks were designed to explore the indexes of eye movement that can reflect user experience of product, and analyse the attention captured by product attributes and goal-oriented. In task one, participants just browsed two smart phone pictures and evaluated the whole user experience. Binary choices were used in task two to ask participants to select the smart phone picture with higher user experience and then click the mouse. The results showed that in the browsing task, participants had shorter time to first fixation for the smart phone picture with higher level of user experience than the lower. And pupil dilated significantly when participants browse smart phone picture with lower level of user experience. In goal-oriented task, participants' attentions were dominated by visual perception of task driven, mainly reflected on longer fixation time and larger pupil diameter when looking at the smart phone with higher level of user experience. These results support the notion that we cannot assess product design just by several eye-movement indexes without considering the effects of visual attention mechanism.Relevance to industryThe appearance of product plays an important role to attract user's attention and stimulate their intention to experience. And vision is the main channel for users to obtain product information. Hence a thorough research on the inherent mechanism of vision perception can provide technical support for product designers, which in turn can attract more consumers to experience the product, even buy it. Moreover, the seller can find out the real buyers and predict their desired products by tracking user's eyes.