Generative AI in developing User Experience Research Point of View: A NotebookLM case study

2026-05-29

AI Summary

This study addresses the challenges in user experience research (UXR)—notably, the lack of methodological rigor and protracted workflows that hinder timely support for product decisions, compounded by the added burdens of prompt engineering, data preprocessing, and result validation when applying generative AI. To overcome these limitations, this work proposes a structured approach that systematically integrates generative AI with a UXR point-of-view (PoV) construction framework. Leveraging Google NotebookLM, the method introduces five context-specific, phased prompts designed to collaboratively distill evidence-driven strategic insights across the four stages of PoV development. Evaluation on eleven UXR reports demonstrates that this approach effectively positions AI as an efficient collaborator, significantly enhancing both the efficiency and feasibility of UXR practices.

Abstract

User Experience Research (UXR) is currently undergoing a transition from traditional usability testing towards design-led and data-driven approaches, yet it faces an identity crisis due to a lack of methodological grounding in UXR and time-intensive methodologies which often lag behind product decision cycles. To address this, the UXR Point of View (PoV) framework formalises the UXR process by transitioning from raw data collection to forming an evidence-based PoV which drives strategic product impact. Furthermore, the use of GenAI in UXR has been investigated, but researchers often face increased work intensity when using GenAI, attributed to time spent on prompt engineering, data cleaning, and verification of AI outputs. This paper proposes and evaluates a formalised methodology for leveraging GenAI, specifically Google's NotebookLM, to augment the UXR PoV process. The methodology consists of five prompts across four stages: (1) leveraging the framework, (2) establishing roadmaps, (3) applying best-practices, and (4) crafting PoV narratives; and was tested on eleven UXR papers. Results showed that by using the proposed methodology, NotebookLM successfully leveraged the UXR PoV framework across all stages of PoV creation. These findings demonstrate that NotebookLM can serve as an effective collaborative partner in UXR, so long as it is provided with sufficient context and specific prompting.

Problem

• User Experience Research
• Generative AI
• Point of View framework
• methodological grounding
• work intensity

Innovation

• Generative AI
• User Experience Research
• Point of View framework
• NotebookLM
• Prompt engineering