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Fields help you capture metadata to organize project data consistently - like spreadsheet headers. All fields have a title and a property. Fields live on data objects and by default, unique to each project. You can use fields to help segment and categorize whole pieces of data at a high-level.

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Difference between a field and a tag

A tag and a field serve different purposes in your raw data. While tags analyze the content of your data, fields describe the data source itself and provide context around it.

Field

  • Used to structure and categorize your raw data at a high-level. As a field lives across all data in a project, some examples of information you would capture as a field include the research method used, interview date, usability testing score, segment, and net promoter score.

Tag

  • Used to group highlights and track themes within a single piece of raw data or across a set of data.  They help you thematically group bite-size information captured within different pieces of data within a project. 
Tags And Fields Differences Pn

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Create data fields for a project

Data fields are useful for categorizing your raw data by research method, interview date, usability testing scores, segment, net promoter score, and more.
  • To add a field to your data, open a note within your project and click + New field.
  • From there, you can set a title, select a note field type, and enter a value to the note’s field.
  • When you add a new field to a note, it will also be added to all other notes in that project. The property added for this field will be unique to the note.

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Example of data fields you can use

See table below for some common examples of data fields you could use include to categorize your raw data in projects.