How to Choose the Right AI Persona?

Question Type

User Manual Question


Quick Answer

atypica provides two major types of AI personas: Public Persona Library (300,000+) and Custom Personas.

Recommended Selection Logic:

  • General research: Use Public Persona Library directly (fast, broad coverage)
  • Specific needs: Create custom personas (upload interview data or use Social Media Scout)

In short: For most cases, the Public Persona Library is sufficient; only create custom personas when you specifically need to simulate particular real users.


Detailed Explanation

Public Persona Library: 300,000+ Pre-Built Personas

Characteristics:

  • Quantity: 300,000+ covering diverse demographics
  • Source:
    • ✅ Built based on real research contexts (each persona corresponds to 1 real research question)
    • ✅ Built based on real social media observations (each persona has 3000-word observation record)
  • Quality:
    • ✅ Consistency score of 80 (close to real human baseline of 81)
    • ✅ Stable quality, validated
  • Visibility: Shared by all users (both free and paid versions can use)

Use Cases:

Examples:

  • Test sparkling coffee new product pricing (select 10-15 target demographics)
  • Understand fitness app user needs (select fitness enthusiast personas)
  • Explore Gen Z consumption preferences (filter 18-25 age personas)

Advantages:

  • ✅ Ready to use immediately, no creation needed
  • ✅ Broad coverage, virtually any demographic available
  • ✅ Stable quality, already validated
  • ✅ Low cost, no additional creation cost

Custom Personas: Tailored for Specific Needs

Characteristics:

  • Quantity: Created based on your needs
  • Source: Based on your provided data (interview transcripts, social media observations)
  • Quality: Depends on your provided data quality
  • Visibility: Completely private, only you can use (team version can share with team)

Use Cases:

Examples:

  • Import 500 member interview data to test new product (simulate real members)
  • Observe "camping enthusiasts" on Xiaohongshu, create personas (not in public library)
  • Continuously track fixed user group's changing needs (multiple reuses)

Creation Methods:

  1. Upload Interview Transcripts: Upload real interview text or audio, AI auto-generates persona
  2. Social Media Scout: Let AI observe target demographics on social media, generate personas

Advantages:

  • ✅ Fully customized, meets your specific needs
  • ✅ Data privacy, protects sensitive information
  • ✅ Reusable, forms company's "user assets"
  • ✅ Team sharing, improves collaboration efficiency

Decision Framework: Which Should I Choose?

Scenario 1: General Product Testing


Scenario 2: Specific Demographics (Not Found in Public Library)


Scenario 3: Simulate Real Customers


Scenario 4: Team Collaboration Research


Best Practices

Recommended Strategy: 80% Public + 20% Custom


Combined Use Case

Case: Healthy Snack Product R&D


Frequently Asked Questions

Q1: Is the Public Persona Library quality reliable?

Reliable, close to real human performance.


Q2: When do I need to create custom personas?

Only needed for specific requirements.


Q3: Is custom persona creation cost high?

Depends on your data and usage frequency.


Q4: Will custom personas be visible to other users?

No, completely private.


Q5: Can free version use Public Persona Library?

Yes, free version can also use Public Persona Library.


Q6: Can I "bookmark" public personas to my library?

Yes, use "My Persona Library" function.


Final Takeaway

"Core logic for choosing AI personas: Use Public Persona Library for most cases (fast, sufficient), create custom personas only for specific needs (customized, in-depth). The 300,000+ public library already covers common demographics; only need custom for niche groups, real customer simulation, team collaboration, etc."

Remember:

  • ✅ Public Persona Library: 300,000+, ready to use, suitable for 90% general research
  • ✅ Custom personas: Fully customized, suitable for specific needs (niche groups, real customers, team collaboration)
  • ✅ Recommended strategy: 80% public library, 20% custom
  • ✅ Create once, use many times, more cost-effective with use

Related Questions:


Related Feature: AI Persona Three-Tier System Document Version: v2.1 Updated: 2026-02-02 Update Notes: Updated terminology and platform information

Last updated: 2/9/2026