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Consumr.AI Onboarding
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What is Consumr.AI
The Big Idea
Why Not Synthetic or Traditional Research
How It All Fits Together
How the Product Evolved
Your First Run
Start Here
Core Concepts
Data Foundations
Portfolio
Segments
Inputs & Audience Sizing
Reports
AI Twins
Respondents & Extrapolation
Core Concepts
How-To Guides
Build a Portfolio
Create Segments — the 4 Methods
Build & Tune an AI Twin
Converse with a Twin
Run Qualitative Research
Run Quantitative Research
Test Creative & Concepts
Read & Interpret Results
Worked Example: The GEICO Skewness Loop
How-To Guides
Research Methods
Qualitative Methods
Quantitative Methods
Choosing the Right Method
Research Methods
Philosophy & Positioning
Synthetic vs Traditional vs Consumr.AI
Direction Over Accuracy
Privacy-Safe by Design
Premium Positioning & AI-Hype Skepticism
How We Think & Work
How We Write & Communicate
Philosophy & Positioning
Objection Playbook
Common Objections & Counters
Correct vs Incorrect Usage
Objection Playbook
Statistics Primer
RFM
Sampling & Sample Size
Central Limit Theorem
Normal Distribution & Standard Deviations
Accuracy vs Precision
Margin of Error & Confidence Interval
Design Effect (DEFF)
Extrapolation & Census Data
Six Sigma & DMAIC Thinking
Statistics Primer
Reference
Glossary
UI Map
Internal Tools, Access & Reporting Bugs
Roadmap & Known Issues
Open Questions
session-notes
Session Notes
Reference
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Core Concepts