By Philip Burgess - UX Research Leader UX research is not only about what users do  but also about what they believe, prefer, and expect . While behavioral analytics reveals the actions people take, attitudinal analytics  uncovers the perceptions that drive those actions. Together, they give researchers the full picture: behavior explains the what , and attitudes explain the why . What Is Attitudinal Analytics? Attitudinal analytics is the structured measurement of user belie

By Philip Burgess - UX Research Leader In UX research, it’s not enough to know what users say — we need to understand what they actually do. That’s where behavioral analytics  comes in. By tracking clicks, navigation paths, drop-offs, and interactions, behavioral analytics helps researchers uncover hidden friction, validate qualitative findings, and quantify the real impact of design decisions. What Is Behavioral Analytics? Behavioral analytics is the process of collecting an

By Philip Burgess - UX Research Leader Surveys are one of the most widely used UX research tools — and for good reason. They scale quickly, capture a broad range of user opinions, and provide quantifiable data that can validate or complement qualitative insights. But not all surveys are created equal. Poorly designed surveys risk producing noise instead of clarity. Done well, UX research surveys can be a powerful way to connect user experience with business outcomes. Why Use

By Philip Burgess - UX Research Leader In UX research, we often ask: “Which design works best for users?”  While qualitative methods help us uncover why users struggle , A/B testing allows us to validate those findings at scale and connect them directly to business outcomes. What Is A/B Testing in UX Research? A/B testing (also called split testing ) is a controlled experiment where you compare two or more design variants  to see which one performs better against a defined go

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

Philip Burgess - UX Research Leader As artificial intelligence (AI) continues to enter the UX world, many researchers are asking: What exactly is the difference between AI-powered research and traditional UX research?  Are we evolving or replacing our practice? The answer lies not in opposition—but in augmentation. Traditional UX Research: Depth Through Human Empathy Traditional UX research is rooted in human-centered principles . Whether it's moderated interviews, contextual

By Philip Burgess - UX Research Leader In the ever-evolving landscape of UX research, artificial intelligence isn’t just a trend—it’s a transformation. From streamlining analysis to unlocking new capabilities, AI is redefining how researchers work, where we spend our time, and what’s possible within our processes. From Labor-Intensive to Lightning Fast Historically, UX research has been time-consuming. Transcribing interviews, synthesizing insights, coding data, and writing r

By Philip Burgess - UX Research Leader AI is quickly becoming an essential partner for UX researchers. From brainstorming research questions to synthesizing findings, the right prompts can unlock faster insights and help teams scale research impact. Below is a curated list of 100 AI prompts for UX research , organized into categories you can use throughout the research lifecycle. Research Planning & Strategy Generate research questions about [specific feature/product]. Create

By Philip Burgess - UX Research Leader How to Ask Smarter Questions in an AI-Augmented Workflow As UX research evolves in tandem with AI, the way we ask questions is changing. Prompts—whether used in generative tools, synthesis engines, or stakeholder conversations—are becoming the new currency of insight. But not all prompts are created equal. The best prompts don’t just extract data. They unlock meaning. Whether you're guiding AI tools to generate personas, summarize interv

By Philip Burgess - UX Research Leader What the Balance Looks Like As AI continues to reshape the landscape of design and decision-making, UX research stands at a pivotal crossroads. The question is no longer whether machine intelligence will play a role—it already does. The real question is: how do we balance the precision of algorithms with the depth of human empathy? This isn’t a story of replacement. It’s a story of integration. Empathy Isn’t Optional At its core, UX rese

By Philip Burgess - UX Research Leader Why Human-Centered Insight Still Matters in an AI-Driven World The rise of AI has sparked a wave of speculation across industries, and UX research is no exception. With machine learning models capable of parsing user behavior, generating personas, and even predicting design outcomes, it’s fair to ask: will AI replace UX researchers? The short answer? No. But the long answer is far more interesting—and essential for leaders navigating the

By Philip Burgess - UX Research Leader As AI continues to reshape industries, UX researchers face a pivotal opportunity: not just to adapt, but to lead. In AI-first organizations—where machine learning, automation, and predictive systems drive product strategy—the role of UX research is evolving from tactical support to strategic stewardship. Here’s what that future looks like. From Usability to Explainability Traditional UX research has focused on usability, clarity, and sat