User Persona Creation

Table of Contents

• Overview
• When to Use
• Quick Start
• Reference Guides
• Best Practices

Overview

User personas synthesize research into realistic user profiles that guide design, development, and marketing decisions.

When to Use

• Starting product design
• Feature prioritization
• Marketing messaging
• User research synthesis
• Team alignment on users
• Journey mapping
• Success metrics definition

Quick Start

Minimal working example:

# Gather data for persona development

class PersonaResearch:
    def conduct_interviews(self, target_sample_size=12):
        """Interview target users"""
        interview_guide = {
            'demographics': [
                'Age, gender, location',
                'Job title, industry, company size',
                'Experience level, education',
                'Salary range, purchasing power'
            ],
            'goals': [
                'What are you trying to achieve?',
                'What's most important to you?',
                'What does success look like?'
            ],
            'pain_points': [
                'What frustrates you about current solutions?',
                'What takes too long or is complicated?',
                'What prevents you from achieving goals?'
            ],
            'behaviors': [
                'How do you currently solve this problem?',
                'What tools do you use?',
// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

Best Practices

✅ DO

• Base personas on real research, not assumptions
• Include 2-3 primary personas
• Make personas specific and detailed
• Include direct user quotes
• Update personas based on new data
• Share personas across organization
• Use personas for all product decisions
• Include both goals and pain points
• Create personas for different user types
• Document research sources

❌ DON'T

• Create personas without research
• Create too many personas (>4 primary)
• Make personas too generic
• Ignore data in favor of assumptions
• Create personas, then forget them
• Use personas only for design
• Make personas unrealistically perfect
• Ignore secondary users
• Keep personas locked away
• Never update personas