The approach
User interviews tap into customer sentiment.
I planned and led a team in conducting in-depth discovery interviews with IT executive and leadership level clients across industries. The interviews covered clients' current research process: how they currently found, evaluated, and used information, and where things broke down. The second was how they were already using AI tools in their work, if at all. The third was what they would expect from an AI research experience built directly into the platform. The fourth was trust: whether they would rely on AI-generated answers from the company, and what would make them hesitate.
Build shared understanding with the project team.
Rather than handing the team a report and moving onto a new project, I designed and facilitated a series of several synthesis workshops with product, UX colleagues and other key stakeholders. Each workshop focused on key themes that came out of the interviews. Participants worked directly with interview excerpts and observations, grouped and discussed what they saw, and arrived at insights and implications together.
This approach gave the team firsthand exposure to what clients were saying, built shared understanding across product and design, and meant the resulting insights were ones the team owned rather than ones they were asked to accept.
Impact
The insights and themes from this research helped shape the direction of the company’s first generative AI research assistant, which later launched to clients. The launch of the product included high priority features from the findings with a solid roadmap and plan to keep addressing other high value client needs. The team’s solution became one of the most frequently used resources the platform offered.