Can generated interview reports show data visualization results? For example: gender ratio, age distribution, platform usage frequency distribution, etc.
Question Type
User Manual Question
Core Answer
Currently mainly text reports, data visualization is on the roadmap.
Current Support:
- ✅ Interview records and insights (text)
- ✅ Highlight conversation excerpts (quotes)
- ✅ Consensus and disagreements (text summary)
- ⏳ Data visualization (planned)
If Visualization Needed:
- Current reports focus on text insights
- Can request AI to generate data summaries in report dialogue
- Future will support basic visualization (2026 Q2-Q3)
Current Report Content
1. Text-based Content (Supported)
User Profile Description
Interview Insights
2. Structured Data (Currently Presented as Text)
Example: Price Acceptance Analysis
If Visualized, Would Be:
- Bar chart: Acceptance at different prices
- Pie chart: User type distribution (Price-sensitive 40%, Health-anxious 40%, Social early-adopter 20%)
Data Visualization Planning (Future)
Planned Feature 1: User Profile Visualization
Demographic Visualization:
- Age distribution (pie chart)
- Gender ratio (pie chart)
- City distribution (map/bar chart)
- Income distribution (bar chart)
Example:
Planned Feature 2: Attitude Distribution Visualization
Acceptance Visualization:
- Product acceptance (radar chart)
- Pricing acceptance (bar chart)
- Feature need priorities (horizontal bar chart)
Example:
Planned Feature 3: Opinion Comparison Visualization
Consensus vs Disagreement:
- Consensus points (green highlight)
- Disagreement points (red annotation)
- Opinion evolution (timeline)
Example:
Planned Feature 4: Behavior Pattern Visualization
Usage Frequency:
- Platform usage frequency (stacked bar chart)
- Consumption frequency (line chart)
- Decision pathway (flow chart)
Example:
Current Workarounds
Option 1: Use AI to Generate Visualization Suggestions
In Report Dialogue:
Option 2: Request Custom Report Format
Contact Customer Service:
- If you are enterprise user
- Need specific format visualization reports
- Can customize development
Why No Visualization Currently?
Reason 1: Primarily Qualitative Research
atypica's Core Value:
- Deep dive into "why"
- Understand user motivations and attitudes
- Provide insights rather than statistics
Qualitative vs Quantitative:
- Qualitative: 5-10 in-depth interviews, extract insights
- Quantitative: 100+ survey, statistical distribution
atypica is Qualitative-focused:
- Sample size: 5-10 people (not suitable for statistical visualization)
- Output: Insights and recommendations (text more appropriate)
Reason 2: Small Sample Size
Statistical Significance:
- 5-10 person data not suitable for percentage statistics
- "2/5 people like" more accurate than "40% like"
- Avoid misleading (small sample doesn't represent population)
Exception:
- If large-scale testing (50+ people)
- Future may consider visualization
Reason 3: Insights > Numbers
What Matters is Insights:
Risk of Visualization:
- Over-focus on numbers
- Ignore underlying "why"
When Will Visualization Launch?
Roadmap
Phase 1 (Current):
- Focus on qualitative insights
- Text reports primary
- Support export HTML/PDF
Phase 2 (Planned):
- Basic visualization
- User profile distribution
- Attitude acceptance charts
- Consensus vs disagreement comparison
Phase 3 (Future):
- Advanced visualization
- Interactive charts
- Dynamic data exploration
- Custom report generation
Expected Launch Time:
- Phase 2: 2026 Q2-Q3
- Phase 3: 2026 Q4-2027 Q1
Common Questions
Q1: Why no charts like survey tools?
Core Difference:
- Survey tools: Quantitative research (100+ people), suitable for statistics
- atypica: Qualitative research (5-10 people), suitable for insights
Analogy:
- Survey: Physical exam report (blood pressure, blood sugar data)
- atypica: Doctor diagnosis (why is blood pressure high? How to treat?)
Q2: Is chart with 5-10 person data meaningful?
Limited Statistical Significance:
- 2 out of 5 = 40% (sounds like a lot)
- But sample too small, can't represent population
More Appropriate Expression:
- "2 out of 5 people think it's expensive"
- Rather than "40% think it's expensive"
Recommendation:
- If need statistical analysis → Use survey tools (100+ people)
- If need insights digging → Use atypica (5-10 people)
Q3: Can I create charts myself?
Yes. Steps:
AI Can Help You:
- Request AI to organize data in report dialogue
- AI will provide data in table format
- Can manually create charts or use other tools
Q4: Does enterprise version have custom visualization?
Can Be Customized:
- Contact enterprise customer service
- Explain visualization needs
- Customize report format development
Applicable Scenarios:
- Need to report to board
- Specific industry report format
- Large-scale repeated research
Best Practices
Recommendation 1: Focus on Insights Rather Than Numbers
Don't Ask:
- "What percentage of users like it?"
Ask:
- "Why do users like/dislike it?"
- "What are differences between user segments?"
- "How to optimize product?"
Recommendation 2: Use Surveys for Statistics
Scenario Division:
- atypica: Explore "why" (5-10 people depth)
- Survey tools: Validate "how many" (100+ people statistics)
Combined Use:
- atypica explore insights
- Survey large-scale validation
- atypica dig deeper into anomalies
Recommendation 3: Tell Story with Text
Good Report:
Story > Numbers
Bottom Line
"atypica focuses on insights rather than statistics, 5-10 in-depth interviews not suitable for charts. What matters isn't 'how many people', but 'why'."
Remember:
- ✅ Current: Text reports, focus on insights
- ✅ Future: Basic visualization (2026 Q2-Q3)
- ✅ Workaround: Request AI to organize data in report dialogue
- ✅ Qualitative ≠ Quantitative: atypica is not survey tool
- ✅ Insights > Numbers: Focus on "why"
Related Feature: Plan Mode, Report Doc Version: v2.1