In our testing, the top three types of question users submitted to the AI platforms were in the areas of:
Looking at differences by generation, we find:
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.
Across all users, the top three reasons for choosing a preferred AI response in our blinded tests are: 1. Feels accurate 2. Feels relevant 3. Feels complete In addition, among younger users, the attribute “feels human like” increases in importance. This video of a young user asking Bard for a
Microsoft’s investment in OpenAI has resulted in ChatGPT-4 powering Bing. However, looking at Microsoft users (defined by Windows PC or MS Tablet users), when presented with blinded responses from different platforms to the same prompts, they preferred GPT-4 and 3.5 over Bing's responses. The % is calculated
Our study captures hundreds of videos of actual user experiences with the four AI platforms. A unique and powerful aspect of Pulse IQ™️ is the ability to see these interactions in the moment. Two videos were chosen for each AI platform that demonstrate meaningful user insights. See what users see
The best product data is what you have at hand while you're sketching wireframes or tinkering with a prototype. Is "on-stage" too theatrical for someone visible on a video call? Does "off-stage" clearly mean muted and camera-off? These hyper-specific, time-sensitive questions hit mid-flow in
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
