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

topic-analysis