Personas

Synthesized archetypal user profiles created from research data, representing distinct user types to guide design decisions and align teams on who they are building for.

Process

Key Fields

Question it answers	Who are the key user types? What are their goals, behaviors, and pain points? How do they meaningfully differ?
Participants & timing	Derived from 20+ interviews or observation sessions · 2-3 weeks creation and iteration
AI compatibility	AI clusters interview transcripts into archetypes and generates persona bios; human validation of behavioral evidence is required.
Output	3-5 personas (poster, narrative, or card format), persona usage guide, data validation appendix

Use when

Product needs to serve distinct user types differently
Multiple teams use research and need shared alignment
Creating artifacts for handoff beyond the research team
Behavioral segmentation drives roadmap prioritization

Skip when

Primary user type is highly homogeneous
Research will be used immediately by a small co-located team
Insufficient qualitative depth to ground realistic profiles

Common Mistakes

Data disconnection

Creating personas based on stakeholder assumptions instead of research data. Anchor each persona to specific quotes, behavioral evidence, and interview artifacts.

Too many personas

Five or more personas dilute decision-making. Stay ruthlessly focused on 3-4 types that differ in ways relevant to design choices.

Creating an "average" person

A persona averaging all user traits becomes mediocre and unactionable. Preserve extreme differences (power user vs. novice, high anxiety vs. confident).