Hiroshi Yoshimura (吉村弘) - Wet Land (1993) [Full Album]

should be asleep

Video link: https://www.youtube.com/watch?v=Z3m7HXeiHpg

Creator Brief

Do not copy it directly

Compare before copying

Verdict

Do not copy it directly

Why

Signals are mixed: 1.5K/day velocity and 3.26% engagement.

Best angle

Study the hook and pacing first; treat the topic as unproven for your channel.

Risk

Copying the surface topic may miss the hook that actually worked.

Next action

Test a tighter title with one concrete outcome, a number, or a stronger curiosity phrase. This is the fastest improvement lever for underperforming packaging.

Evidence chain

Why this decision is credible

Methodology

Comparable sample

Fact

11 videos

YouTube Data API

Related public videos used as the local benchmark set.

Velocity proxy

Inference

1.5K/day

Derived estimate

Views divided by public publish age. Useful directionally, not private Studio data.

Engagement rank

Derived

P75

Public metrics

Likes and comments benchmarked against the related sample. Current engagement: 3.26%.

Channel size proxy

Derived

908%

Public views

This video views compared with the average related video. Subscribers are not required.

Deep Video Analysis

Why this video will spread or stall

Built from public video data and content signals. Private retention, revenue, and real traffic-source data require YouTube Studio access, so those sections are clearly modeled as analyst inference.

Effect score

100/100

Creator Brief

Do not copy directly yet

Decision first: use the metrics below as evidence, but start from whether this idea is worth your next upload.

Add to compare

Why

1.5K/day public view velocity + 3.26% engagement + browse traffic hypothesis

Suggested angle

Broad appeal storytelling: Make "hiroshi" the visible promise, then add a stronger result or contrast than "Hiroshi Yoshimura (吉村弘) - Wet Land (1993) [Full Album]".

Risk

The title does not make the viewer payoff concrete enough.

Next action

Show the payoff, conflict, or final result first; spend the first 15 seconds proving why viewers should stay.

Watch metric

First-day velocity, like rate, and comments per 1K views.

Content-led verdict

Likely to stay limited

/100 content virality

The content does not yet give viewers or the algorithm a strong enough reason to click, stay, and share.

Why this video may not go viral

Specific numbers, timeframes, or ranked framing make the idea easier to understand and share.

The topic is legible to a target audience: AI / productivity.

The description gives YouTube more context for matching the video to viewers.

Why it may not go further

The title does not make the viewer payoff concrete enough.

The packaging has limited curiosity tension.

The content angle may be too neutral to spark strong reactions.

There is little public timing signal in the content metadata.

Title: Hiroshi Yoshimura (吉村弘) - Wet Land (1993) [Full Album]

Topic read: AI / productivity

Keyword signals: hiroshi, yoshimura, hiroshi yoshimura, green, wet land

Description depth: 349 chars

Content virality: high means the public title, topic, hook, timing, and format show more breakout signals.

Effect score: combines reach, velocity, engagement, and comment depth to judge actual video impact.

Search readiness: checks whether title, description, tags, hashtags, and chapters support discoverability.

Copywriting & Hook

Hook type

Specificity hook

Title length

54 chars

Mobile-friendly title length
Uses specificity through numbers
Viewer payoff could be more explicit
Description gives search/session context

Content Strategy

Topic: AI / productivity

Format: Broad appeal storytelling

Viewer job: Get entertained or satisfy curiosity

Repeatability: Medium-high: repeatable with new angles

Add a sharper repeatable format so the next upload is easier to systemize.

Traffic & Video Effect

Primary traffic hypothesis

Browse - Traffic quality looks moderate

Search23%

Browse44%

Suggested26%

External7%

Likely Video Timeline

0:00-0:15

Hook

Open with the strongest curiosity or payoff from the title.

0:15-0:45

Context

Make the promise behind "Hiroshi Yoshimura (吉村弘) - Wet Land (1993) [Full Album]" concrete and remove setup friction.

0:45-70%

Proof / delivery

Escalate stakes or evidence every 20-40 seconds.

70%-90%

Payoff

Deliver the result, reveal, ranking, or key lesson before attention drops.

Final 10%

Next action

Use one CTA tied to the viewer intent: comment, compare, subscribe, or click related video.

Audience Drop-off Over Time

Public-data inference, not private YouTube Studio retention.

High confidence

Likely biggest leak

Hook

Hook is the likely biggest leak: 15% more viewers may leave around 0:00-0:15.

Show the payoff, conflict, or final result in the first shot before explaining background.

0:00-0:15 · Hook

Stage loss 15% · cumulative loss 15%

Medium

Retained viewers85%

The title/opening promise may be too broad, so cold viewers can leave before context lands.

0:15-0:45 · Setup

Stage loss 6% · cumulative loss 21%

Low

Retained viewers79%

Public metadata suggests the viewer job is reasonably clear after the hook.

25% · First proof

Stage loss 7% · cumulative loss 28%

Low

Retained viewers72%

The first content beat needs escalation; flat pacing here usually creates the largest audience leak.

50% · Midpoint

Stage loss 10% · cumulative loss 38%

Medium

Retained viewers62%

Lower comment depth suggests weaker emotional or identity tension through the middle.

75% · Payoff build

Stage loss 9% · cumulative loss 47%

Low

Retained viewers53%

If the payoff is not explicit, late retention likely depends on personality rather than structure.

Final 10% · CTA / next video

Stage loss 7% · cumulative loss 54%

Low

Retained viewers46%

The ending may be watched by a small core; generic CTA will not recover earlier losses.

Keywords & Video Effect

hiroshiyoshimurahiroshi yoshimuragreenwet landwetlandwetlandmixrain1993spring

Reach

4.8M

Large public demand signal

Velocity

1.5K/day

Velocity is modest or aged

Like rate

3.17%

Strong satisfaction signal

Comment rate

0.045%

Needs stronger comment trigger

Strong video effect: reach and audience response both look healthy.

SEO & Keyword Coverage

Modeled from title, description, tags, hashtags, and chapter signals.

Search readiness

100/100

46 tags

0 hashtags

Title keyword fit

7/6

Core search terms appear in the title.

Description depth

Moderate

Enough context for search and session matching.

Chapters

Present

Timeline metadata can improve scanability.

Tags / hashtags

46 / 0

Metadata provides extra topical hints.

Next Upload Brief

A product-style action plan for the next test, based on the current video's public signals.

Next title angle

Make "hiroshi" the visible promise, then add a stronger result or contrast than "Hiroshi Yoshimura (吉村弘) - Wet Land (1993) [Full Album]".

Opening shot

Show the payoff, conflict, or final result first; spend the first 15 seconds proving why viewers should stay.

Distribution bet

Prioritize thumbnail/title contrast and a curiosity gap.

Success metric

Scale the format with a controlled variation. Watch like rate, comment rate, and first-day velocity against this benchmark.

Use this analysis

Turn the diagnosis into a reusable workflow

Save the brief, monitor the video/topic, and create an alert so this analysis becomes an ongoing research asset.

Open Workspace

Deep analysis Next moves Analytics Insights Checklist

🎯 What To Do Next

Packaging strategy

High impact

Test a tighter title with one concrete outcome, a number, or a stronger curiosity phrase. This is the fastest improvement lever for underperforming packaging.

Audience response

Quick win

Engagement is only 3.26%. Add a clearer opinion, stronger hook, or a more specific viewer prompt in the first 30 seconds.

Distribution timing

Test next

Publishing time looks favorable. Keep the timing stable and test whether topic/thumbnail changes move the result more than timing does.

Search and description support

Maintain

Description support is solid. Preserve structure, links, and timestamps when repeating this format.

📈 Performance Trends

Views Trend

Projected growth based on current velocity

Likes Trend

Like accumulation pattern

Engagement Trend

Combined engagement metrics

⚡ VELOCITY METRIC

views/day

1.5K

views per day

📈 STEADY

01M3M5M+

📈 ENGAGEMENT BREAKDOWN

percentile: 75%

Like Rate3.17%

Comment Rate0.045%

Overall Engagement3.26%

✍️ TITLE ANALYSIS

Score: 90/100

✅

Contains Number

Boosts CTR

❌

Power Words

Add emotional words

Read this as the explanation layer. The action plan above tells you what to change first; this section explains why the video likely behaved this way.

💎

Good Engagement

Engagement rate of 3.21% indicates quality content.

📈

Viral Success

Crossed 1M views — a notable achievement for any creator.

💡 Replication Checklist

Check packaging separately

Save the title and thumbnail pattern before assuming the topic was the only reason it worked.

Match audience fit

Reuse the format only if the promise also fits your niche, tone, and viewer expectation.

Test one variable

Change one thing first — title, topic angle, or thumbnail — so you know what actually moved performance.

Confirm with more examples

Use 3-5 comparable winners before turning one successful video into a content rule.

👥 Engagement Intelligence

AI Recommendations

📊 Advanced Video Analytics

Content Rhythm

Retention proxy

Retention and dropoff are modeled from public engagement, duration, and content structure. Private YouTube Studio retention curves are not available here.

Modeled Avg. Watch Time

2:59

Duration: 5:00

Modeled Completion Rate

59.5%

+16.7% vs category

Rating

Good Retention

Dropoff Trend

This Video Proxy

Category Avg

Modeled Comparison

Category Average

42.8%

Top Performers

68.5%

This Video

59.5%

Golden Retention

First 2 minutes show lower dropoff than category average — strong opening hook. Consider adding engagement elements at 50-60% mark to boost completion.

Optimization Tips

Modeled completion rate of 59.5% is performing well. To improve further, consider adding end-screen CTAs or suspense in the final 20%.

Traffic Sources

Estimated mix

Source mix is modeled from public video characteristics. YouTube Studio traffic-source data is private and is not available here.

Total Public Views

4.8M

Sources5 channels

Mobile

Mobile App

62.5%

3.0M

Desktop

Desktop Web

15.3%

737.7K

Tablet

385.7K

Other

Embedded/Other

385.7K

Smart TV

6.2%

298.9K

Mobile First

Estimated 62.5% mobile-weighted viewing. Optimize for vertical readability and mobile thumbnails.

Desktop + TV

Desktop and TV combined are modeled at 21.5%. Longer content may perform well here.

Top Channel

Mobile is the top modeled source at 62.5%. Treat this as a planning proxy.

Audience Demographics

Modeled estimate

Audience, geography, and active-hour data are public-data estimates based on title, topic, and visible metadata. They are not private YouTube Studio demographics.

Gender

Male 52%

Primary

⚧

Age

25-34

Largest group

👤

Interest

Entertainment

Top category

❤️

Peak Hours

16-20

Most active

🕐

Gender Distribution

Total

100%

Male 52.3%

Female 41.5%

Unknown 6.2%

Age Distribution

Under 18

15.5%

18-24

28.2%

25-34

32.8%

35+

23.5%

Audience Interests

EntertainmentMusicComedyVlogsReactionsSocial MediaScienceSportsTravelFood

Estimated Active Hours

This Video

Category Avg

0-4: 12%

0-4

4-8: 18%

4-8

8-12: 45%

8-12

12-16: 52%

12-16

16-20: 68%

16-20

20-24: 55%

20-24

Estimated Geographic Distribution

USUnited States

18.5%

INIndia

15.2%

GBUnited Kingdom

8.3%

BRBrazil

7.8%

JPJapan

6.5%

DEGermany

5.4%

FRFrance

4.2%

CACanada

3.8%

🎯

Modeled audience insight: Your content resonates most with male viewers aged 25-34. Peak engagement occurs during 16-20 hours. Entertainment is your strongest interest category.