ux-researcher-designer

Run the persona_generator.py script with a list of user data dictionaries containing fields like age, usage_frequency, features_used, and pain_points. The script analyzes patterns, identifies an archetype, and outputs a formatted persona or JSON with the 'json' argument.

The generator expects a list of user dictionaries with fields such as age, usage_frequency, features_used, primary_device, usage_context, tech_proficiency, and pain_points. Interview insights with quotes, motivations, and goals are optional but enrich the psychographics.

The script identifies four archetypes: power_user, casual_user, business_user, and mobile_first. Archetype selection uses heuristics based on usage frequency, feature usage count, primary device, and usage context.

No, the script uses only Python standard library modules: json, typing, collections, and random. It runs with any standard Python 3 installation without installing additional dependencies.

The archetype identification uses simple heuristics rather than statistical clustering, so results may not reflect nuanced segments in large datasets. Confidence scoring is based only on sample size thresholds, with high confidence requiring more than 50 users.