Key Insights

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  There is a wide variety of tools for prototyping and solution space work, but the problem space lacks specialized, efficient tools.

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  Researchers spend significant time on foundational work like exploratory studies, persona creation, and mental mapping which current tools poorly support.

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  Data repositories for research findings are desired but hard to implement successfully across cross-disciplinary teams due to complexity and lack of tooling.

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  Language mapping using natural language processing to cluster keywords into narratives is a promising approach for understanding user thinking.

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  Searching and coding interview transcripts remain manual and time-consuming; new commercial-friendly tools like Delve show potential for improvement.

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  Defining research hypotheses collaboratively is key but not easily facilitated by existing tools—communication rather than tooling dominates.

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  Aligning user outcome assumptions with business outcome assumptions and visualizing these relationships helps prioritize prototypes and tests.

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  Organizing problem space research activities and linking them to business strategy and metrics remains a challenge that tooling could address.

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  Cross-functional team synthesis is difficult remotely and analog methods still hold value for collaborative research work.

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  Participants see value in tools that consolidate disparate research activities into a single, accessible system for clarity and decision-making.

Notable Quotes