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It's been a while since my last post.
It's been a while since my last post.
In this article, I've taken a slightly different look at everyday life in Japan using "YouTube data."
This is a verification of generally known information.
Please take a look at the analysis results.
It is widely recognized that video viewing traffic exhibits
specific peak times when user activity is concentrated.
It is widely recognized that video viewing traffic exhibits
specific peak times when user activity is concentrated.
To verify this, empirical data analyzed using PLT Logic revealed that three major peak lines—"morning," "late afternoon," and "night"—appear consistently almost every day. (See figure below: PLT Logic observation data)
In all the videos analyzed, it was confirmed that viewership was concentrated during peak hours.
In all the videos analyzed, it was confirmed that viewership was concentrated during peak hours.
In fact, observational data shows that the number of viewers during peak hours at night can reach approximately seven times that of off-peak hours.
In fact, observational data shows that the number of viewers during peak hours at night can reach approximately seven times that of off-peak hours.
This clearly demonstrates the phenomenon of a massive number of users simultaneously viewing screens during times when people's "free time" (intermittent free time) overlaps.
Let's analyze this behavior in more detail.
AM 7:00 – AM 11:00
AM 7:00 – AM 11:00
The morning peak varies depending on the day of the week, but it usually starts around 7:00 AM, and tends to peak between 9:00 AM and 11:00 AM on weekdays.
This time slot corresponds to so-called "break time," including commuting, household chores, and rest periods.
Many people are thought to be using smart devices to access various information such as videos, articles, and navigation systems while traveling by train, bus, or car. Therefore, "multitasking viewing" (watching videos while doing something else) is likely to be active during this time.
Anticipated user profiles:
* People with busy schedules
* People who want to maintain their mood and motivation
* People who have a habit of watching videos at a fixed time every day
* People who use smart devices on a daily basis
Primary Video Genres Observed via PLT Logic:
* Educational videos (instructional and learning materials)
* News and informational videos
* Music and entertainment videos.
PM 15:00 – PM 18:30
PM 15:00 – PM 18:30
Looking at the graph for this time period, we can see that the number of viewers is gradually increasing.
This suggests that users are casually browsing their devices at home or on the go.
Viewers responded to a wide range of content genres, including:
* Music and entertainment videos
* News and informational videos
* Educational videos (learning materials)
Furthermore, although there is no confirmation at this time, since this period coincides with the end of school and work hours, there may be an increase in viewing of anime and anime-related music videos among younger generations.
Inferred User Profile:
* Students and working adults on their way home
* People with established viewing habits
* People seeking relaxation time
* Others: Users of smart devices, PCs, and smart TVs
Viewers during this time slot appear to be watching videos for a short break after completing their daily goals and routines
Compared to the morning, viewers during this time slot are likely "light users" enjoying short periods of leisure time.
PM 19:00 – PM 22:30
PM 19:00 – PM 22:30
During this time slot, viewership increased significantly across all genres, recording the highest traffic figures of the day.
Traffic from various video sources, including information gathering, entertainment, education, and music, concentrated during this period, resulting in a sharp upward trend in PLT Logic metrics.
Furthermore, although not yet confirmed, it is strongly predicted that continuous viewing of "Shorts" (short videos) will accelerate, given that this time slot is ideal for personal leisure time.
Inferred User Profile:
*Individuals with ample free time
*Individuals with established viewing habits
*Individuals seeking a period of relaxation
*Individuals actively searching for fresh information
*Individuals engaging in fan activities ("Oshi-katsu")
The consumed genres span an incredibly wide spectrum:
*Entertainment videos
*Music videos
*News and informational videos
*Educational videos (learning materials, etc.)
*Fan-targeted videos ("Oshi" videos)
summary
summary
These genres are actively watched, and while there's no concrete evidence, the rapid and continuous consumption of sports-related content and short videos is a notable characteristic.
This concludes my brief analysis report.
However, a closer look at the actual data reveals that this phenomenon is not merely a series of numbers, but something grand and dramatic.
Millions of people are watching completely different content at the exact same time.
As I looked at this vast amount of data, a profound thought suddenly crossed my mind:
"Behind this enormous video market, how many creators are pouring their sweat, tears, and dreams into their works?" It evoked a strange mix of anxiety and anticipation.
In this constantly evolving video market, what future do you envision, and what hopes do you have?
The next time you enjoy a video, try to imagine what's happening behind the scenes.
It will surely change your perception of your usual screen time.
Please try it.
Until next time.
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