Do video length and upload day matter in your YouTube niche? A fairer comparison than raw views
"Post on Thursdays." "Keep it under ten minutes." Advice like this rarely comes with numbers from your niche. You can check it with public data, but sorting videos by views and looking at what the top ones share gives the wrong answer. This post shows a fairer comparison: views per day, each video measured against its own channel, medians, and a count next to every number. Why raw views mislead…
This report compares YouTube channel performance metrics, specifically view counts and video lengths, across various niches. The study reveals that raw view counts can be misleading due to several factors such as video age, channel size, and outliers.
Medians are used instead of raw views to provide a more accurate comparison, as they are less impacted by outliers. The analysis also highlights the survivorship bias in the data, as creators often delete unsuccessful videos and re-upload successful ones.
To conduct the study, the author recommends selecting specific channels that regularly publish content within the same niche, collecting data for a full year, and then analyzing data based on video length and weekday uploads. The data is then divided into four buckets based on video length and each day of the week, and medians are calculated for each bucket.
Key findings include video age being the most significant factor influencing view count, followed by channel size. The report suggests that videos older than a year have collected views over a longer period, giving them an advantage in view count. Additionally, larger channels tend to have more views on their weaker uploads compared to smaller channels with their best-performing videos.
In conclusion, the study emphasizes the importance of using normalized metrics, such as views per day, instead of raw views to get a more accurate comparison of channel performance in a specific niche.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
