A guide for UX teams and PMs to strategically combine research methods and modes across surfaces to generate actionable insights - without unnecessary overhead or resource overload. As Nielsen Norman Group emphasizes, integrating quantitative and qualitative research allows teams to uncover not only patterns in user behavior but also the...
A practical playbook for UX teams (and PM’s doing it themselves) to run smarter user tests with less overhead. Why Testing Feels Hard in Enterprise (and How to Make it Easier) Small UX teams in enterprise companies often support multiple product managers, competing priorities, and limited bandwidth. The reality:...
The New Imperative-Time-to-Right & Trust UX research has long been centered around selecting the right methods to gather, synthesize, and share user insights. But with the accelerating integration of AI, the core focus has shifted. Success is no longer just about speed to market-it's about getting it right...
A look at what keeps powerful findings from shaping product decisions There's no shortage of good research. There's just a shortage of good use of research. As a UX researcher, I’ve seen this happen over and over. We spend weeks on a study, pull together...
In today’s fast-paced app development world, relying on assumptions about what your users need can lead to missed opportunities. Instead of guessing, imagine having access to real-time, user-prioritized feedback to guide your product decisions. Guessing what users want often results in: * Roadmaps that miss the mark with users * Misspent...
Generative AI is transforming product development—but not without challenges. It’s enabling teams to work smarter, innovate faster, and enhance user experiences, but navigating its complexities is key to long-term success. Here are five challenges product teams should be aware of when adopting AI: 1) Addressing Bias in AI...
Generative AI is revolutionizing the way we design, market, and refine products. It’s giving teams the tools to better understand users, create more meaningful experiences, and connect with audiences in new ways. From improving designs to boosting engagement and expanding your reach, AI is opening up exciting opportunities. Here...
Artificial intelligence is eating the world. The pace at which machines have recently been able to achieve human or even superhuman performance on tasks previously requiring human intelligence has been breathtaking. AI has the potential to become a profoundly useful assistant and tool in almost every aspect of human life,...
Key webinar takeaways from a discussion around the intersection of UX and AI. Explore the implications of LLMs and generative AI in UX design.
Sign in or subscribe for access to the webinar recording and more free UX content from Pulse Labs. This insightful 45-minute conversation hosted by Pulse Labs, is designed for UX researchers looking to navigate the rapidly evolving landscape of AI-driven applications. During the session, we hosted a dynamic, moderated discussion...
Based on this week’s keynote address, Google Cloud Next 2024 is slated to be a hotbed of cutting-edge AI solutions, and many of these advancements represent potential for the User Experience research community. We’ve identified a few key takeaways that could inform future practices to gain UX insights...
In Pulse IQ, one component of the research design that we call “self-directed” is to let users decide what they want to do on an assigned AI platform. While the topics and interests they chose vary, overall we see certain topics and use cases emerge as the most popular. The...
While AI in its current consumer form is relatively new, many people feel they have seen it already and in many places beyond the platforms offering LLM capabilities. * Many users (22%) state that their first interaction with AI was via assistants, smartphones, and apps that have been on the market...
Hallucinations - an industry term used to describe the situation where an AI platform generates responses that are inaccurate or don't make sense but are presented as factual - is an area where platforms and the public may not see the same thing. * Only 5% of user interactions...
We gathered 4,200 responses from the four leading AI platforms and had 400+ users pick which ones they preferred. The emerging winner so far is GPT-4, but it’s a close race. GPT-4 leads the way, with responses preferred 55% of the time. That's a significant advantage...
While GPT-4 does very well overall in the comparison rating, there was a consensus among those who DIDN'T prefer GPT-4 responses as to why: GPT-4 is not preferred when there is “TMI” or “too much information.” Implication Striking the balance of “just enough” information - but not too...
In blinded side-by-side testing, users select their preferred AI response to a series of queries and describe why. As a result, we see how the four platforms compare across hundreds of users and various question types. * Bard stood out for responses that were viewed as most complete, accurate, and relevant....
