What it is
Grouping users by shared behaviors, goals, and contexts (what people do and need, not demographics alone) and describing each group in a persona. A persona built without evidence is a proto-persona: hypotheses to label and test, not a finding.
Why use it
Without a shared picture of differences that matter, teams design for an imagined average user. Evidence-based segments keep discussion on needs and give later methods a defined user.
Use this when
- Research shows distinct groups with different needs or workflows
- The team disagrees about who the product is for
- A journey map, story map, or prioritization needs a defined user
- Different groups need different experiences or support
You may not need this when
- Users are uniform in the aspects that matter
- Evidence is too thin; a labeled proto-persona may do
- Validated, current personas already cover this scope
Dependencies — what you need
- Synthesized research showing behaviors and needs, not only demographics
- Agreement on the dimensions that distinguish segments
- A plan to keep personas current or retire them
People involved
- Design
- Research
- Product
- Analytics
- Stakeholders
Typical outputs
- Behavioral segments with their evidence
- Personas: goals, context, needs, pain points
- Which segments the work is, and is not, designed for
- Evidence gaps flagged for research
Template
Personas & Segments template
A fill-in structure for running this method: what to prepare, what to do, what to record, and how to read the result.
How AI can help
AI as augmentation — not replacement
- Cluster coded findings into candidate segments, for the team to test against raw data
- Draft personas with each statement tied to evidence
- Flag persona statements with no evidence
- Suggest research that would firm up a proto-persona
AI prompt
A prompt for any AI assistant. It works only from material you paste in, keeps assumptions apart from findings, and leaves the decisions to you.