Abstract
AbstractUser-generated product reviews are valuable information resources about what users like about the product, their pain points, and overall product use cases. This information is valuable for product developers and designers for future product improvements. This research paper discusses the user journey mapping approach for analyzing product reviews. It proposes a method for structuring large amounts of user reviews and putting them on the journey map, classifying touchpoints, pain points, and product advantages. Machine learning algorithms on Apple Earpods Max noise-canceling headphone reviews are used to classify user-generated product reviews and validate the journey map. Created journey map showed a positive potential for the given approach to make sense of large amounts of user-generated content and give quantifiable proof of a user journey map.KeywordsUser experience knowledgeUser journey mapUser review analysis
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call