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.

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.
Fieldsandtags Pn

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.

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.
Field titleField typeField value examples
DataSingle selectInterview, Survey, Document
PersonaSingle or multi-select
Region or MarketSingle selectAPAC, EMEA, AMER
Interview stageSingle selectScheduled, Conducted, Analyzed
Interview roundSingle selectRound 1, Round 2, Round 3