"The quality of product research directly impacts the outcome of the entire design process. As AI tools become increasingly embedded across different phases of the product design process, including the research phase, it's vital to establish a clear, intentional research process that maximizes design efficiency while reducing business risk from poorly informed or incorrect decisions In this article, I want to share a 3-stage framework I use for AI-powered research."
"Why: It will help you create context both for yourself and AI. And AI works best with context. You don't have to make the research brief too fancy. It's okay to prepare a one-page research brief that will summarize the key points about your research: Product / feature being studied Research goal (decision you want to make based on your research) Target users (who, context of use) Research stage (Exploratory, Concept validation, Usability testing, Post-launch learning, etc)."
A three-stage framework for AI-powered product research emphasizes intentional, contextualized research to improve design outcomes and reduce business risk. The first stage is creating a concise research brief outlining the product or feature, the research goal, target users and their context, and the research stage. Context enables AI to generate more relevant insights and supports clearer decision-making. A one-page brief suffices to align objectives and streamline AI-assisted research. Embedding AI across research phases requires defined processes to maintain research quality, maximize design efficiency, and prevent decisions based on incomplete or incorrect information.
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