mcpField
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timing-analysis

timing-analysis

github.com/vivy-yiMarketing & growth508159 installsUpdated 40w ago
Repository

About timing-analysis

A timing-analysis skill for Xiaohongshu creators. It examines audience activity and tests posting windows to inform a content schedule suited to their account.

Key features

  1. 01Analyze audience activity patterns
  2. 02Test different posting times
  3. 03Compare time-based performance metrics
  4. 04Set primary and secondary slots
  5. 05Adapt schedules to seasons and events

Use cases

  1. 01Find suitable posting times for an account
  2. 02Compare weekday and weekend results
  3. 03Optimize a content calendar
  4. 04Adjust for holidays or trending events

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/vivy-yi/xiaohongshu-skills --skill timing-analysis

After installing, type/timing-analysisin Claude Code to confirm it loaded.

Details

From the project README

Timing Analysis (发布时机分析)

Overview

Timing analysis is the data-driven study of when Xiaohongshu audiences are most active and receptive to content, enabling strategic scheduling that maximizes reach, engagement, and conversion.

When to Use

  • Determining best times to post
  • Analyzing audience activity patterns
  • Scheduling content for optimal reach
  • Measuring time-based engagement
  • Testing different posting times
  • Optimizing content calendar timing
  • Understanding audience behavior

Core Pattern

Before: Post when convenient, inconsistent timing, missed opportunities After: Data-driven timing, peak engagement, strategic scheduling

3 Timing Dimensions:

  1. Time of Day (morning, afternoon, evening)
  2. Day of Week (weekdays vs weekends)
  3. Seasonality (monthly, quarterly patterns)

Quick Reference

Time SlotEngagementReachCompetitionBest Content Type
Morning (7-9 AM)MediumMediumLowEducational, tips
Lunch (12-1 PM)HighHighMediumEntertainment, light
Evening (7-9 PM)Very HighVery HighHighAll content types
Late Night (9-11 PM)MediumMediumLowCommunity, engagement

Implementation

Step 1: Analyze Audience Activity Patterns

Activity Tracking:

  • When followers are online
  • Peak engagement hours
  • Comment activity timing
  • Save and share timing
  • Live stream attendance

Tools:

  • Xiaohongshu analytics (when followers online)
  • Content performance by post time
  • Engagement rate by hour/day
  • Historical performance data
Step 2: Test Posting Times

A/B Testing Framework:

  • Test morning vs evening
  • Test weekday vs weekend
  • Test different days of week
  • Test same content at different times

Testing Variables:

  • Post time (primary variable)
  • Content type (keep consistent)
  • Day of week (test systematically)
  • Duration (run tests 2-4 weeks)
Step 3: Measure Time-Based Performance

Metrics by Time Slot:

  • Reach (impressions)
  • Engagement rate
  • Follower growth
  • Save rate
  • Share rate
  • Comment quality

Statistical Significance:

  • Test each time slot 5+ times
  • Calculate average performance
  • Identify outliers
  • Determine statistical winner
Step 4: Develop Optimal Timing Strategy

Optimal Schedule:

  • Primary posting times (best performance)
  • Secondary times (good performance)
  • Avoid times (consistently low performance)

Content Type Timing:

  • Educational: Morning/commute hours
  • Entertainment: Lunch/evening
  • Community building: Evening
  • Promotional: Evening/weekends
  • Live streams: Evenings/weekends
Step 5: Adapt to Seasonality

Seasonal Patterns:

  • Holiday behavior shifts
  • Season changes affect activity
  • Events and trends create timing opportunities
  • Back-to-school periods
  • Holiday shopping seasons

Real-Time Adaptation:

  • Monitor trending topics
  • Adjust for breaking news
  • Leverage cultural moments
  • Respond to audience activity shifts

Real-World Impact

Timing Optimization Results:

  • Engagement +35% from optimal timing
  • Reach +50% from strategic scheduling
  • Follower growth +25% from consistent timing
  • Saved time from efficient scheduling

Related Skills

REQUIRED: Use data-analytics (measure timing performance) REQUIRED: Use content-calendar (schedule optimized times)

Recommended:

  • audience-analysis, content-optimization, social-listening

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