Interview Analysis
Last updated
Last updated
Yazi's AI Analysis transforms raw interview data into structured, actionable insights through an intelligent 4-phase categorization system. The product automatically analyzes interview conversations, categorizes questions and answers, and presents findings through an interactive interface that allows users to explore patterns, drill down into specific insights, and validate AI classifications.
When: Automatically triggered once 20-30 questions have been collected Purpose: Create meaningful question categories that reflect the research objectives
Process:
AI analyzes the research brief, survey questions, and sample of actual questions asked
Generates 10-18 specific, actionable question categories (avoiding overly broad categories)
Categories are tailored to the specific research context and objectives
Example Categories:
"Affordability and Financial Considerations"
"Product Features and Policy Options"
"Claims Experience and Resolution"
Purpose: Classify every question into exactly one category
Process:
Each AI interviewer question is analyzed and assigned to a single question category
Uses single-select classification (one question = one category)
Updates the messages table with category assignments
Purpose: For each question category, identify patterns in how people respond
Process:
Groups all answers by their associated question category
AI analyzes answer patterns within each question category
Generates 12-18 specific answer categories per question category
Categories are granular and specific (e.g., "Capitec Bank pricing" rather than "competitor pricing")
Example Answer Categories for "Affordability" Questions:
"Direct Cost Sensitivity"
"Premium vs. Cost Comparison"
"Specific Competing Expenses"
Purpose: Tag each answer with relevant categories (can be multiple)
Process:
Each individual answer is processed and can receive multiple category tags
Uses multi-select classification (one answer = multiple possible categories)
Calculates proportions showing what percentage of answers fall into each category
Displays: All question categories with count of questions in each
Numbers: Show how many questions have been classified into that category
Interaction: Click any category to filter the view and see its specific answer categories
Active State: Selected category highlighted in blue theme
Displays: Answer categories relevant to the selected question category
Progress Bars: Show proportion of answers in each category (green theme)
Percentages: Display both count and percentage of total answers
Interaction: Click any answer category to see specific citations/examples
Active State: Selected category highlighted in green theme
Displays: Actual question-answer pairs that exemplify the selected categories
Color-Coded Tags:
Blue tags = Question categories
Green tags = Answer categories
Editable: Users can click tags to reassign questions/answers to different categories
Copy Function: Each citation can be copied for use in reports
Users can drill down from broad themes to specific examples: Question Category → Answer Categories → Individual Citations
Users can modify category assignments by clicking tags
Changes are immediately reflected in the interface
Proportions and counts update automatically
All AI classifications can be manually reviewed and corrected
Color-coded system makes it easy to distinguish question vs. answer categories
Clear visual hierarchy helps users understand relationships
Switch between different question categories to explore different aspects of the research
Each question category reveals its own unique set of answer patterns
Multiple answer categories per response capture nuanced insights
Speed: Automated categorization reduces analysis time from days to hours
Consistency: AI ensures consistent categorization criteria across large datasets
Depth: Captures nuanced patterns that might be missed in manual analysis
Flexibility: Easy to explore different angles and drill down into specific insights
Actionable Insights: Specific, granular categories provide clear direction for action
Evidence-Based: Every insight backed by actual customer quotes and examples
Comprehensive: Captures the full spectrum of customer feedback and sentiment
Professional Presentation: Clean, interactive interface suitable for stakeholder presentations
This AI Analysis product represents a significant advancement in qualitative research, combining the depth of human insight with the scale and consistency of artificial intelligence.