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Study Groups (Step 1c)

Study Groups is the third step of the Brief. Here you turn the demographics and screeners you just defined into segments — each with its own persona and tailored scenes. See Study groups (concept) for the underlying idea; this page is the how-to.

To split your audience into meaningful segments so each kind of respondent gets a relevant survey — while every segment stays measured on the same scales for comparability. Groups are optional: skip them for a single undifferentiated audience.

  1. Choose Add Study Group.
  2. Give the group a name — for example, Millennial Male or Metro Gen-Z.
  3. Define its conditions using your demographic choice-fields and/or screener answers (e.g. region = Metro and age_band = 18-26 and gender = Male).
  4. Repeat for each segment you want to tailor for.
  5. Mark one group as the default (see below).

If you define no groups at all, vDynamiq uses a single implicit “All Respondents” group — everyone qualified takes the same survey.

  • Segment on things that change the story, not everything you collected. You don’t need a group for every demographic combination — only the splits that warrant different framing.
  • Keep conditions mutually clear. Overlapping conditions make routing ambiguous; aim for segments a respondent falls cleanly into.
  • Always designate a default the moment you have more than one group.
  • Fewer, meaningful groups beat many thin ones. Each group is a persona and a set of scene variants to review — and very small segments yield noisy results.
  • Group conditions read from choice demographic fields and screener answers — make sure the attributes you want to segment on were defined as choice fields in Audience.
  • Name groups the way you’ll talk about them in the readout (Metro Gen-Z Male), so results are easy to discuss later.
  • You can revisit groups after seeing the personas — if a persona feels off, the group definition is often the thing to adjust.

Once your groups are set, vDynamiq generates one persona per group, and later gives each scene a variant per group.