As UX professionals continue to explore wider applications of AI in user experience research and design, Natural Language Processing (NLP), a specialized domain of AI, emerges as a key area of interest. In an article published in 2021 and authored by Rahman, Nwokeji, et al, an innovative methodology that integrates Natural language Processing (NLP) and Thematic Analysis (TA) was presented, see the Figure 1 below. This approach advocates for the use of NLP techniques to collect, synthesize, and prepare large volume of data for analysis, then Thematic Analysis is used to identify themes and derive insights, click here to read the article.
Although this methodology was original used in academic research, it has a wide range of applications in User Experience Research (UXR). For instance, it can be used by UXRs to sift through vast amounts of qualitative data to detect patterns and themes that from a large volume of user feedback, that otherwise would not be possible by relying only on traditional thematic coding or analysis. Other broad range of applications include Competitive Analysis, Neuro-Inclusive Design, etc.
Conventional qualitative UX methods often rely on smaller datasets, providing design insights based on data collected from a smaller sample size, usually between 5 to 12 participants, depending on the project scope. However, competitive product strategy, design recommendations, and insights can be derived from large volume of qualitative data e.g., user feedback found in surveys, product reviews, support tickets, customer complaints, forum discussions, etc. Integration of NLP and TA can be applied to identify common themes and patterns related to user needs, challenges, functional requirements, and pain points from large volumes of qualitative data. For instance, advanced NLP techniques such as Topic Modeling, Lemmatization, Sentiment Analysis, etc., could be used to cluster and summarize big data/large volume of user feedback, making it ready and easier for UX researcher to apply TA to derive insights. Through this methodology, ‘UX Professionals can uncover deep insights into what users truly value or struggle with in a product from a broader perspective. Simply put, it allows for the extraction of nuanced insights that might otherwise remain obscured.