Use Case
Best suited for large size organisations, spread out teams to aggregate qualitative data from diverse sources such as surveys, interviews, and focus groups to identify trends, improve services, and make data-driven decisions.
The tagging architecture has a lot of information that we care about consistently to improve our programs, so this will make it easier to spotlight and filter so the right view of all the information comes up at the right time.
Shirley Yan
Noora Health
Features
Automatically cluster data using tags applied during content creation, generating dynamic collection and listing pages. Filter and search clusters at micro or macro levels, providing a unified data repository.
Code sentences, phrases, or words within large bodies of text—such as interviews and reports—to uncover deeper qualitative insights.
Create, edit, delete, merge, or split tags and categories for flexible inductive and deductive coding, enabling efficient thematic analysis.
Use AI for content summaries on collection and listing pages, and to accelerate annotation by offering suggestions that help teams code faster.
FAQ
