Enhancing UX Research Activities Using GenAI -- Potential Applications and Challenges

TL;DR

This paper explores how Generative AI, particularly Large Language Models, can support and improve UX research activities by making data processing more efficient, while emphasizing the need for researcher oversight.

Contribution

It presents practical use cases and an exploratory study demonstrating GenAI's potential to enhance UX research processes and efficiency.

Findings

GenAI supports various UX research tasks effectively.

LLMs can process large data sets more efficiently.

Researchers should review AI outputs for quality assurance.

Abstract

User Experience (UX) Research covers various methods for gathering the users' subjective impressions of a product. For this, practitioners face different activities and tasks related to the research process. This includes processing a large amount of data based on qualitative and quantitative data. However, this can be very laborious in practice. Thus, the application of GenAI can support UX research activities. This paper provides a practical perspective on this topic. Based on previous studies, we present different use cases indicating the potential of GenAI in UX research. Moreover, we provide insights into an exploratory study using GenAI along an entire UX research process. Results show that Large Language Models (LLMs) are useful for various tasks. Thus, the research activities can be carried out more efficiently. However, the researcher should always review results to ensure quality. In summary, we want to express the potential of GenAI enhancing UX research