By Philip Burgess - UX Research Leader For years, UX research has been seen as a primarily qualitative practice — interviews, usability tests, field observations. But as digital products scale and data becomes more accessible, analytics is now a critical part of UX research . The ability to measure, track, and visualize user behavior brings depth, rigor, and credibility to our findings. So what exactly is UX Research Analytics , and how can it transform the way organizations

By Philip Burgess - UX Research Leader When organizations think about UX research, they often picture usability testing or surveys. But UX research is a much broader practice — and at its heart, it comes down to two complementary approaches: qualitative and quantitative . Both types are essential. Qualitative research uncovers the “why” behind user behavior, while quantitative research validates the “how much” and “how often.” Together, they give teams the insight needed

By Philp Burgess - UX Research Leader Why this matters: Teams often use these terms interchangeably, which leads to fuzzy goals, mismatched methods, and weak decisions. This guide clarifies the major UX Research Styles , when to use them, and how to explain each to stakeholders. A simple mental model Think in two dimensions across the product lifecycle: Problem space → understand people, contexts, needs, opportunities Solution space → design, test, and measure solutions Life

By Philip Burgess - UX Research Leader Quantitative UX research is all about uncovering the “what” and “how much” behind user behavior. It leverages data from surveys, experiments, analytics, and large-scale usability testing to generate statistically valid insights. While qualitative research explains the why , quantitative research measures the scale and impact . AI can supercharge this work by helping UX researchers craft better survey questions, analyze large datasets, i

By Philip Burgess - UX Research Leader Artificial Intelligence is becoming a powerful partner for UX researchers, not a replacement. With the right prompts, AI can accelerate analysis, uncover themes, draft reports, and even suggest new research questions. Below are 50 of the best AI prompts for qualitative UX research , organized by stage of the research process. 1. Research Planning “Suggest 5 open-ended interview questions to understand user frustrations with [product/feat

By Philip Burgess - UX Research Leader AI isn’t replacing UX research—but it can amplify our workflows if used thoughtfully. The key? Knowing how to prompt effectively so the output supports research goals without introducing bias or over-simplification. Here are some of the the best UX Research AI prompts—plus why they matter and examples you can use right away. 1. Planning & Scoping When time is short, AI can help frame a structured research plan. Prompt Example: “Create a

By Philip Burgess - UX Research Leader Usability testing is the cornerstone of great UX—rich with user feedback, interaction pain points, and design validation. But once the sessions are over, one thing looms large: the dreaded usability report . For many UX researchers, analyzing sessions, pulling quotes, tagging issues, and building a report can take hours —sometimes days . But what if AI could automate that process without sacrificing depth? Here’s how we used AI to automa

By Philip Burgess - UX Research Leader Competitive audits are essential for identifying UX opportunities, understanding market standards, and guiding product differentiation. But let’s be honest—they’re time-intensive, messy, and often hard to scale across multiple competitors and platforms. This case study explores how our team leveraged AI tools to cut audit time in half , enhance pattern recognition, and deliver richer, more actionable insights to stakeholders. The Challen

Philip Burgess - UX Research Leader Large Language Models (LLMs) like ChatGPT, Claude, and Gemini are transforming the digital landscape—and UX research is no exception. As these tools become more embedded in our workflows and the products we help shape, every UX researcher needs to understand what they are, how they work, and what they mean for our craft. This isn’t just about learning a new tool. It’s about understanding the new terrain of human-computer interaction . What