2023: The year for YouTube virality — Mr. Beast’s next move after 120 MILLION subs
From kids to retirees, more and more people have now learned a thing or two about becoming established on YouTube. We’re way past the phase of discussing what thumbnails perform, which analytic metrics to keep an eye for, what keywords work for a certain niche etc. Once a channel establishes, it should scale up. This is a time when you’re no longer building a business, but the business is building you.
Millions of people have witnessed the growth of Mr. Beast’s YouTube channel from the get-go.
Jimmy Donaldson had indeed inspired millions with his success, and I personally admire his work & personality.
Borrowing Anil Agarwal’s brilliant blog post which keeps track of Mr. Beast’s subscriber numbers, here’s what his journey looks like to date:
As seen above, Mr. Beast grew consistently by a 10x multiplier from 2014 until 2017. From 2018 onwards, it’s harder to maintain such position since we’re dealing with millions.
Still, the numbers are impressive: 15 million additional subs from 2018 to 2019, 20 million for the subsequent year and 60 million for the next, before losing momentum in the last few years.
Realizing this, perhaps it has provided an impetus to scale up strategically. In the last 4 months from the time of writing, it appears that the company had already made a move to expand its team.
Now, what’s interesting is how revealing some of the job descriptions are.
Consider the points where I underlined here:
That one line alone, should be a powerful lesson to YouTube channels which are trying to scale. Take it from one of the best creators out there, that “video virality is purposeful.”
What that means is that behind every viral video is one or more purposes served.
The target audience are looking for something when spending their time on the platform, and they’ll definitely respond to content containing that ‘something’ — the factors that eventually made them click, engage, and keep watching.
In other words, creators need to design 4 things:
- Avatars representing the target viewers (i.e. understanding of marketing values, empathy maps and neuromarketing)
- Thumbnails that capture the brain’s attention without conscious awareness (i.e. understanding of neurodesign; things like pre-attentive attributes and principles of design)
- Thumbnails and titles that are hard to resist from not clicking once the brain is aware of them (i.e. understanding of the avatars on a deep level and the use of reporting metrics such as click-through rates)
- Content that’s strong enough to make the viewers engage and keep watching (i.e. understanding of engagement & retention factors)
The heart of all four is data.
“And now here is my secret, a very simple secret: It is only with the heart that one can see rightly.”
Antoine de Saint-Exupéry, The Little Prince
Without data as the heart, the very core that builds insights to our actions, we can’t see what works and what doesn’t.
Having a reliable data at hand not only helps guide decisions, it also challenges our assumptions or theories.
And this is the only way forward.
Whilst not all channel creators are aware of the importance of studying data, Mr. Beast’s team takes data seriously.
Leveraging on the data from the YouTube API, not only did they focus on data collection (extraction) and data processing, but the team is also tasked with
- data automation
- data documentation
- and data best practices around YouTube API.
They’re already building a system to manage data comprehensively. This successful company is already 10 steps ahead, while many other creators are still not aware of or casting doubt on the importance of data.
Revisiting 2 of the 4 design items mentioned above
- Avatars
I have already written a few articles touching heavily or briefly on avatars. If you’re interested, below are the links to my other articles:
2. Engagement Factors
In the context of YouTube content creation, engagement factors refer to the reasons why people hit the like and share buttons, and leave their comments for a video.
I have developed a custom automation tool which can analyze all comments from a single video, categorize them into themes and isolate the significant themes out from the rest.
This tool leverages YouTube API. Similar to what I did with my Twitter Avatar Research tool, this YouTube tool also utilizes an open source data analytics tool KNIME.
Let’s study Mr. Beast’s Reacts most popular video (57 million views) where he (Jimmy) and Chris reacted to videos showing different people having their lucky moments in different settings and contexts.
I was able to process all the comments data in around less than 10 minutes, and here’s some of the interesting things I found:
- People really enjoyed the presence of Chris in the react video:
- “I kept replaying chris at 2:20”
- “Has Chris got the pancake machine?”
- “Good job Chris & Jimmy!”
- “There’s a dog behind Chris!”
- “Lol the picture behind chris”
- “BUY CHRIS THE PANCAKE BOT”
- “Did Chris get his pancake printer?”
- “Chris is the smartest at everything.”
- “Jimmy and Chris make good content!”
- “7:04 my respect for Chris”
- “Chris becoming emo at the end.”
- “Yes Chris the rock did jump scare me too.”
- “Jimmy and Chris are making so good content!!!!!”
- “During the end giveaway chris activated his emo mode 7:50”
- “Chris and Jimmy, it got me.”
- “Me too I loveee chris and jimmy.”
- “Chris there’s a dog behind you.”
- “Jimmy did you get Chris the pancake thing.”
- “Get Chris the pancake thing.”
2. People noticing a particular moment from the react video:
- “1:47 Bro the guy fell and did a thumbs up!!!”
- “Respect for the UPS driver when he did a thumbs up”
- “When the UPS driver slipped he held up thumb sign”
- “The UPS driver when he fell put a thumbs up”
- “When the package guy did that thumbs up I laughed so hard for some reason”
- “When the delivery driver slipped he put his thumbs up”
- “1:47 the man gave a thumbs up to camera when package made it”
- “THE THUMBS UP FOR WORKER WHEN HE SLIPPED AND FELL”
- “It’s the thumbs up UPS driver gave when he fell for me”
- “When the person was falling and fell he did a thumbs up”
- “Did anyone notice that the UPS driver held a thumbs up when he fell and pushed box”
- “When the UPS driver fell with package he put a thumbs up if you didn’t notice”
- “Did anyone realize at 1:47 the man that fell did a thumbs up”
FINAL REMARKS
Whilst there are a few more themes revealed by my analysis, the two mentioned above are enough to justify these remarks:
- Firstly, a single moment that’s small but noticeable enough to evoke an emotion is all that it took for people to engage with a video. It’s obvious here that people either find the moment at the specific timeline point 1:47 as either really funny or really cute. Special moments like this are the key factors for Mr. Beast’s research team to selectively pick which videos to include for the Mr. Beast React’s channel. It keeps the viewers engaged — and the more engaged the audience is, the more viral the video gets since engagement feeds into the algorithm.
- Secondly, people watch a content because they enjoy some of the familiar faces in the video. In this case, people enjoyed Chris. (My tool also reveals a similar theme for Jimmy a.k.a Mr. Beast, but I didn’t include that here because I see that theme being recurrent in many videos of his already, including from the main channel.)
SCALING UP YOUR CONTENT WITH DATA-DRIVEN DECISIONS
Having a proper tool to automate data analysis is a great advantage to have when video virality is the goal.
If you haven’t got the skills nor the experience in building a customized data analytics tool for your business, hire someone who does!
At this point, you must be thinking
‘Nah.. I’m good where I am.’
But …
If one of the world’s largest content creators here is doing it, why shouldn’t you?
Let the data pave the way towards the foundation for your YouTube virality.
If you’re an owner of an already established YouTube channel, you’ve reached a stage where you have to let go of some things.
It’s time to let some parts of your business steer itself in an autopilot mode put in place via a data automation system.
It’s time to trust technology.
To trust DATA.
If you enjoy this article, you’ll definitely love this other YouTube article I wrote too:
Has this article changed how you view virality for YouTube content creation?
What is YOUR next move for YOUR business? Write a response to share feedback with me and the rest of the readers.
