vivy-yi Topic Analysis (话题分析)
Overview
Topic analysis is the systematic examination of content themes, subject matters, and conversation trends on Xiaohongshu to understand what resonates with audiences, identify emerging opportunities, and make data-driven content planning decisions.
When to Use
- Identifying trending topics and themes
- Analyzing which topics drive engagement
- Researching audience interests and preferences
- Evaluating content topic performance over time
- Planning content around proven themes
- Discovering content gaps and opportunities
- Measuring brand topic alignment
Core Pattern
Before: Random content, guessing topics, inconsistent themes After: Data-driven topics, proven themes, strategic content
5 Topic Dimensions:
- Performance Topics (high engagement, proven winners)
- Trending Topics (rising popularity, time-sensitive)
- Evergreen Topics (consistent performance, reliable)
- Niche Topics (underserved, opportunity-rich)
- Brand Topics (core to brand identity, strategic)
Quick Reference
| Topic Type | Engagement | Competition | Longevity | Best For |
|---|---|---|---|---|
| Performance | High | Varies | Varies | Capitalize on success |
| Trending | Spike | Low-Medium | Short | Timely content |
| Evergreen | Consistent | High | Long | Sustainable growth |
| Niche | Medium | Low | Medium | Differentiation |
| Brand | Building | Varies | Long | Brand positioning |
Implementation
Step 1: Collect Topic Data
Data Sources:
- Your content performance by topic
- Competitor topic analysis
- Platform trending topics
- Audience questions and requests
- Search trends and suggestions
- Seasonal topic patterns
Build Topic Database: Track: Topic name, post count, avg engagement, trend direction, last covered, priority
Step 2: Analyze Topic Performance
Topic Metrics:
- Engagement rate per topic
- Reach and impressions
- Follower growth by topic
- Save and share rates
- Comment sentiment by topic
- Conversion rate by topic
Performance Categories:
- Star topics (top 10% performers)
- Strong topics (top 25%)
- Average topics (middle 50%)
- Weak topics (bottom 25%)
- Avoid topics (consistently underperform)
Step 3: Identify Topic Trends
Trend Analysis:
- Rising topics (momentum increasing)
- Stable topics (consistent performance)
- Declining topics (losing interest)
- Seasonal patterns (predictable cycles)
- Viral spikes (sudden popularity)
Trend Detection:
- Week-over-week change
- Month-over-month change
- Seasonal comparison (same period last year)
- Platform trend alignment
Step 4: Map Topics to Content Strategy
Topic Allocation:
- 40% Star topics (proven winners)
- 30% Trending topics (timely relevance)
- 20% Evergreen topics (consistency)
- 10% Experimental topics (innovation)
Content Calendar Integration:
- Schedule star topics during peak times
- Plan trending topics while hot
- Evergreen topics for consistency
- Test topics in low-risk time slots
Step 5: Monitor Topic Saturation
Saturation Indicators:
- Declining engagement on topic
- Increased competition
- Audience fatigue (comments like "again?")
- Diminishing returns over time
Refresh Strategy:
- New angle on same topic
- Different format (video vs post)
- Update with new information
- Pause over-saturated topics
Real-World Impact
Topic Analysis Results:
- Content engagement +40% from topic optimization
- Follower growth +60% from trending topics
- Saved 50% time on content planning
- Identified 15 underserved niche topics
Related Skills
REQUIRED: Use data-analytics (quantitative analysis) REQUIRED: Use content-performance-analysis (topic-specific metrics)
Recommended:
- trend-analysis, audience-research, content-strategy