ux-researcher-designer

Use the persona_generator.py script with a list of user data dictionaries containing fields like age, usage_frequency, features_used, and pain_points. Run 'python scripts/persona_generator.py' for formatted output or add the 'json' argument for JSON output.

The generator accepts user records with demographics (age, location), behaviors (usage_frequency, features_used, primary_device), and pain_points. Optional interview insights with quotes, motivations, and goals enrich the psychographic profile.

The script uses heuristic rules on usage patterns: daily users with many features become power users, mobile-dominant users become mobile-first, work-context users become business users, and others default to casual users.

No, the script uses only Python standard library modules (json, collections, random, typing). It runs on any Python 3 installation without pip installs.

Archetype identification uses simple heuristics rather than clustering algorithms, so results may not capture nuanced segments. Confidence scoring is based only on sample size thresholds (high above 50 users), and qualitative synthesis remains shallow without rich interview data.