Be a YouTube mrBeast
The goal of this study is to analyze the variables that contributed to YouTubers’ success in 2023, specifically their subscribers and earnings. Before identifying those variables, we have to establish the measure of success.
Some questions I would like to have answered:
- Who are the most successful YouTubers?
- Do variables such as category, country, or uploads have an impact on success?
- What advice can we offer YouTubers who want to be more successful?
The dataset I used, Global YouTube Statistics 2023, was collected on the top 995 YouTubers from various sources by the creator. I found this dataset on Kaggle here. The YouTubers each represent a separate record in the dataset and there is representation from many different countries and categories of channels. A small number of records had to be removed due to errors alongside some quantitative value errors imputed with the mean of the columns.
Keep in mind, throughout this analysis I will refer to ‘Highest Yearly Earnings’ as earnings. It is an estimation of the highest earnings the YouTuber will make in the year.
The top five countries by subscribers parsed from the dataframe shows a positive correlation between subscribers and earnings. It is clear that the US and India are the most successful in the YouTube community, respectively, making up 311 and 166 YouTubers out of the total. The more YouTubers a country has, the higher the number of subscribers and earnings.
The dataset was ranked and sorted by subscriber count. If more subscribers means more earnings, then the top 10 YouTubers with the most subscribers should be the ones with the most earnings, correct?
That turned out not to be the case. As we can see above, we have our top 10 YouTubers ranked by subscribers on the left, and our top 10 YouTubers ranked by earnings on the right. US & India YouTubers comprise 80% of both charts. Only three of the YouTubers are common to both graphs: T-Series, Cocomelon - Nursery Rhymes, and SET India. The most interesting part about this, in my opinion, was our number one earnings spot on the chart to the right turns out to be KIMPRO, which is not from either the US or India, nor from any of those top five countries we saw in the first figure.
After analyzing box plots between subscribers and earnings, I found that there were five countries in particular that had an interesting difference in their distribution of data for earnings compared to other similar countries in terms of subscribers. I won’t take up this entire blog with that huge chart, but it can be found here.
Country Subset Analysis:
Comparing the five countries to the rest of the countries revealed that they had close to triple the mean earnings for their YouTubers than the other countries. Clearly, one’s country does have an impact on success l as a YouTube. I wanted to explore this even further, so I took a look at the numerical correlations to earnings and subscribers in a heat map.
In the figure above, we have the subset of countries on the left and the rest of the countries on the right separated into heat maps. The variables that stick out instantly are subscribers for the last 30 days and video views for the last 30 days compared to earnings. We see that the subset countries have a higher correlation than the others. These could signal opportunities to increase earning potential in these countries by focusing on subscribers and video views within the 30 days of this trend. The rest of the countries saw a higher correlation than the subset in video views to subscribers. To my surprise, uploads had a very low correlation with any country’s success.
Category has been a topic that we’ve neglected thus far in our analysis, and I was curious to see if there were any implications for success. I thought it might be important for a creator to understand early in their journey that success may be dependent on particular categories.
We saw that some categories performed better in earnings per subscriber than others. Although Gaming was in the top five categories in terms of subscribers, it drops lower when we evaluate the earnings potential and share of the dataset. The top three categories for earnings were Entertainment, Music, and People & Blogs, as you can see here.
I wanted to find some way to measure YouTubers in a different way other than subscribers or earnings. I combined them both (earnings / subscribers) to create a new metric in tracking success in YouTubers, and then I mapped the top 10 to see if there were similarities with what YouTubers we’ve seen thus far.
As shown, KIMPRO still remains in the top 10, alongside two more from the top 10 earnings chart, DaFuq!?Boom! And KL BRO Biju Rithvik. Another purely created feature I thought would be interesting is 'links' from the About portion of the YouTuber channel. I manually added the number of links to each from the top 10 earnings table, and we get the visual below.
Interestingly, I found that there was a positive correlation with subscribers and video views, and little with earnings. In the future, I would like to explore this further, possibly by web scraping all the YouTubers for their link counts.
So what conclusions can we draw about our initial questions? Keep in mind, these conclusions are based off of the information we have from this dataset which is for 2023.
Who are the most successful YouTubers?
- Top 3 in subscribed: T-Series, Mr. Beast, and Cocomelon - Nursery Rhymes
- Top 3 in earnings: KIMPRO, DaFuq!?Boom!, and T-Series
- Top 3 countries: US, India, and Brazil
- Top 3 categories: Entertainment, Music, and People & Blogs
Do variables such as category, country, or uploads affect success?
- Countries can show varying levels of success, and YouTubers shouldn’t limit themselves based on country.
- Subscribers and video views gained in the last 30 days showed the highest correlation with an increase in earnings in certain countries.
- It could be possible to use VPNs to achieve gains outside the country of origin.
- YouTube may promote certain Youtubers depending on the country.
- There also could be nationalistic effects with Youtuber pride.
- Some categories may outperform others in terms of earnings vs. subscriber correlation. If the goal is to maximize earnings, then it may be beneficial to choose a category like Entertainment.
- Uploads had little effect on subscribers and earnings.
How can we advise YouTubers to be more successful?
- We can evaluate their earnings per subscriber.
- Data can show trends specific to individual countries.
- If earnings are the target, pick a category that has higher earnings.
- Adding links can help subscribers and video views.
- More data (Expand data to top 10,000… 100k.. 1mil… etc.., more variables, video length, video title, number of comments, etc.)
- Dive further into defining viral (How do we quantify when and how countries have that 30 day trend?)
- Time data (Look into time series to track trends and YouTubers over time rather than a specific point in time.)
- Multi-platform analysis (What impact does Tik-Tok, Instagram, Snapchat, Twitter, etc. have on their Youtube channel?)
Featured Image by Freepik