Some questions we’ve helped our clients answer.

Quality Research Matters.

We believe that meaningful understanding comes from more than just data points. At Notion Research, we specialize in high-quality research beyond surface-level observations. We delve deep, using rigorous qualitative and quantitative methodologies and insightful analysis, to discover the nuanced motivations and behaviors that drive your users.

What names resonate more with our target market?

As part of a strategic renaming initiative, we were tasked with uncovering how different name options resonated with our target audience. To answer this, we designed a qualitative user testing where participants were presented with a series of name options in varying sequences.

Through qualitative user testing, we presented name options in varied sequences and gathered insights by asking targeted questions about perception, relevance, and emotional impact.

How does someone decide on higher education? What resources do they seek out for information?

We set out to understand how prospective students make decisions about degrees and institutions. Specifically, when they're unsure of what or where to study. Through a targeted survey, we uncovered what influences their choices, from trusted resources to key moments of receptiveness. These insights helped the institution refine its marketing funnel and better align messaging with the student decision-making journey.

Does our website menu align with our user’s mental models?

We were tasked with improving the structure of a complex website menu to better align with user expectations and behavior. Our process began with extensive research into industry best practices for organizing large menus, analyzing how similar businesses structured their navigation to improve usability, ease of access, and accessibility.

We gathered insights on how users naturally categorized information and navigated content, revealing patterns in user behavior and friction points. Based on this research, we delivered a clear, data-driven recommendation for rebuilding the menu that aligned with user mental models and improved overall site navigation.