Global & Regional Performance
Total Videos
Content Library
Total Views
Lifetime Views
Subscribers
Community Size
Engagement Rate
Audience Interaction
Top performer by views
Mukbang Fire Mara Spicy Chicken Black Bean Noodles TV by HIU 하이유
105.2K
Views
419
Likes
11
Comments
Opportunity for growth
LIVE MUKBANG! TOFU FIRE NOODLES Fried Chicken CVS EATING by HIU 하이유
1.2K
Views
22
Likes
1
Comments
Analysis of 44 long-form videos
Mukbang Fire Mara Spicy Chicken Black Bean Noodles TV by HIU 하이유
• Long videos make up 88% of total content
• Average performance: Lower than channel average
• Most common duration: Very Long (30+ min)
Upload patterns and optimal timing insights
Content distribution across 3 main categories
Key performance indicators and trends
Food dominates with 49% of content
Entertainment has highest avg views
Food shows strongest growth
Most used tags across 460 tag instances
13 tags in category
1 tags in category
1 tags in category
Comprehensive tag metrics and ROI analysis
| Tag | Usage | Avg Views | Engagement | Growth | ROI Score |
|---|---|---|---|---|---|
| #mukbangTop 1 | 73 | 25.9K | 0.79% | +69% | 8/100 |
| #hiuTop 2 | 50 | 24.5K | 0.85% | +77% | 9/100 |
| #하이유Top 3 | 50 | 24.5K | 0.85% | +77% | 9/100 |
| #challenge | 50 | 24.5K | 0.85% | +77% | 9/100 |
| #hiu english | 50 | 24.5K | 0.85% | +77% | 9/100 |
| #하이유 잉글리시 | 50 | 24.5K | 0.85% | +77% | 9/100 |
| #dona | 22 | 33.3K | 0.63% | +79% | 7/100 |
| #eating | 20 | 34.8K | 0.66% | +21% | 7/100 |
| #eating show | 20 | 35.5K | 0.69% | +15% | 7/100 |
| #chicken | 17 | 29.1K | 0.73% | +65% | 8/100 |
| #convenience store | 14 | 43.2K | 0.64% | +65% | 7/100 |
| #korean food | 11 | 32.3K | 0.70% | +234% | 7/100 |
| #asmr | 11 | 35.5K | 0.64% | +125% | 7/100 |
| #tteokbokki | 11 | 40.3K | 0.64% | +107% | 7/100 |
| #eating sound | 11 | 35.8K | 0.67% | +3% | 7/100 |
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
