![淀川あやめ[泉北3000系・YouTubeチャンネル本部]](/_next/image?url=https%3A%2F%2Fyt3.ggpht.com%2FaC5kfDeRSs0rnxsHM0RYSOMAy3fka-IQsrvaHZgRZla84EifMg8--2VBSnVgo6EuQhH8UZC0CA%3Ds800-c-k-c0x00ffffff-no-rj&w=2048&q=75)
Global & Regional Performance
Total Videos
Content Library
Total Views
Lifetime Views
Subscribers
Community Size
Engagement Rate
Audience Interaction
Top performer by views
【フルHD】南海電鉄泉北線7000系・3000系(区間急行) 通過シーン
37
Views
2
Likes
1
Comments
Opportunity for growth
【フルHD】京王電鉄京王線5000系(区間急行) つつじヶ丘(KO14)駅停車
1
Views
0
Likes
0
Comments
Analysis of 16 long-form videos
【フルHD】南海電鉄泉北線7000系・3000系(区間急行) 通過シーン
• Long videos make up 32% of total content
• Average performance: Better than channel average
• Most common duration: Short Long (1-3 min)
Upload patterns and optimal timing insights
Content distribution across 3 main categories
Key performance indicators and trends
Vehicle dominates with 63% of content
Lifestyle Sociology has highest avg views
Vehicle shows strongest growth
Most used tags across 135 tag instances
15 tags in category
Comprehensive tag metrics and ROI analysis
| Tag | Usage | Avg Views | Engagement | Growth | ROI Score |
|---|---|---|---|---|---|
| #南海Top 1 | 13 | 19 | 0.00% | +100% | 0/100 |
| #nankaiTop 2 | 13 | 19 | 0.00% | +100% | 0/100 |
| #京王Top 3 | 11 | 2 | 0.00% | +0% | 0/100 |
| #京王線 | 11 | 2 | 0.00% | +0% | 0/100 |
| #keio line | 11 | 2 | 0.00% | +0% | 0/100 |
| #準急 | 10 | 12 | 0.00% | +304% | 0/100 |
| #semi express | 10 | 12 | 0.00% | +304% | 0/100 |
| #高野線 | 9 | 16 | 0.00% | +100% | 0/100 |
| #koya line | 9 | 16 | 0.00% | +100% | 0/100 |
| #堺東 | 8 | 15 | 0.00% | +100% | 0/100 |
| #sakai-higashi | 8 | 15 | 0.00% | +100% | 0/100 |
| #3000系 | 6 | 22 | 0.00% | +100% | 0/100 |
| #3000 | 6 | 22 | 0.00% | +100% | 0/100 |
| #8000系 | 5 | 10 | 0.00% | +1250% | 0/100 |
| #8000 | 5 | 10 | 0.00% | +1250% | 0/100 |
Strategic recommendations and performance highlights
Top 5 by view count
Top 5 by like count
Top 5 by comment count
Top 5 by engagement rate
Peak performance metrics across all categories
Top performers across multiple categories
Performance analysis and recommendations
