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Essay topics:

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Impressions
Using Google Sheets or Excel, I recommend creating a data tracker for every video you publish, and if you've already been actively uploading, recording data for videos in the past 90-365 days as well. I'm going to have you add columns for every metric we talk about in this post, but start with views and impressions. You'll want to look at each video's first 24 hours, 7 days, and 28 days. Beyond 28 days performance gets weird and a lot less predictable, so if you want to track data past there that's totally up to you. Fill out the spreadsheet with all your video data, and break it up by quarters of the year (Q1 - Jan-March, Q2 - April - June, Q3 - July - Sept, Q4 - Oct - Dec). At the end of each quarter's data, keep track of average AND median performance. Outliers (videos that explode or totally flop) will skew average so it's important to pay attention to median performers as well.
With regard to impressions, we're looking for the videos that perform above median at 24h/7d/28d, and particularly ones that grow faster further in their lifespan. For the 7 and 28 day measurements, I like to also include a % change between the last measurement so I can look for videos that are not just getting the most impressions, but are actively growing after upload day. Record first-day performances are great, but if they spike and die they're not really carrying their weight. Take note of videos that have above-median increases in impressions over their first 7 and 28 days, and record any patterns you see. These are topics to double down on.

Click Through Rate
Add that CTR column to your data sheet! And yep, to all three measurement periods. As with impressions, take note of videos that are doing better on clicks, but that's not the main thing I wanted to look at here. There's a functionality in the back-end of Studio that you'll find really useful here: Groups.
To access Groups you'll want to go to the "SEE MORE" link at the bottom of the main graphs on your Analytics tab. Go over to the drop-down menu where you can view metrics and get it set to CTR. Now, see that text in the upper right hand corner? Where it says "COMPARE TO..."? Yeah. Click on that. Another menu will come up, with 3 options. "ALL", "VIDEOS" and "GROUPS". If you haven't made a Group before, this is where you do it. Just go to the Groups tab and at the bottom it says "CREATE NEW GROUP" in big letters. Can't miss it. What I like to do when I'm upping my thumbnail and title game is basically create new groups and put ALL the videos that fit a certain category into it. Any - and I mean ANY - patterns in your existing titles and thumbnails (language used, caps versus no caps, questions, exclamation, face in thumbnail, no face in thumbnail, color of background, you get the idea) can be made into a group. THEN, you can choose that group as what you're comparing to baseline CTR data to see what elements of your titles and thumbnails are ACTUALLY causing people to click. Kill a few hours doing this. Seriously. You'll find stuff that might surprise you. Take notes on what elements result in the highest CTR on your videos, and then test. For your next 10 videos, try and incorporate one of the elements you found using this method, then log them in your baseline tracker spreadsheet. See how they compare to your average and median performance. Repeat this with as many of the elements you've found, and over time your thumbnail game will really start to crush it.

Returning (and New) Viewers
First, let's add Returning Viewers to your spreadsheet. I also track both Returning and New Viewers in a separate spreadsheet meant to ONLY measure how different videos bring people back and/or reach new eyeballs. You may find that certain topics reach a TON of regular viewers of your channel but don't expand, and others only reach your diehards on upload day but grow bigger over the long haul. It is so unbelievably important to keep track of these things though, better to have hard numbers than qualitative judgments. Let's first talk about different situations your channel may be in and what you need to look at more before you decide which type of viewer you need more.
1. I get decent views on some of my videos, but I'm struggling to break 100/1,000/10,000 subscribers.
2. In this case, you need to go hard on Returning Viewers. Take note of what topics generate more Returning Viewers in the first 24 hours and double down on those. That'll increase viewer loyalty. You might be asking, why are the first 24 hours so important? Well, most of your returning viewers are going to watch a new upload in the first 24 hours to 7 days. Both of these periods are important, but your superfans are more likely to try and tune in on upload day, meaning doubling down on topics that drive more Returning Viewers in the first 24 hours will better target your most loyal fans. And the better you drive returning viewers and focus your channel, the clearer data YouTube has on who to recommend your videos to. This is one of the only actionable ways I've found to increase video impressions.
3. I get decent views on some of my videos, but none of them are breaking out anymore (channel starting to stagnate)
1. This tells me you're experiencing something I've fought recently. Returning viewers are great, but they're not the only thing you want to focus on. Even your most loyal viewers will sometimes fall off of your content. Their interests change, or life happens. People eventually stop watching. That's just life. That only becomes a problem for your channel growth if you're not replacing them faster than they're leaving. It's hard to perfectly measure the rate at which viewers drop off, but this is a case where you definitely want to measure how your videos are reaching new viewers.
Okay. So how do I find these metrics?
Under the "SEE MORE" in any video's analytics, you can use that drop down menu for metrics and under "Reach" you'll find Returning Viewers and New Viewers towards the bottom. For a time period these will show you how many viewers came back to your channel for the given video, and how many new viewers it reached. Look for patterns in topics/formats/videos that drive more of each, and even take note of the new:returning ratio. Some topics will drive more of both, some topics will only drive more of one. The best balance I've found for running an edutainment style channel is to keep New Viewers a little bit higher per day than Returning, but you'll have to experiment to see which does the best for your baseline in your niche. If you haven't already sensed a pattern, the key to running a successful channel is becoming a good data scientist. Your numbers are your friend, and can tell you a lot about what moves to make next to keep your channel growing.

End Screen Clicks
Watch sessions. We hear it a lot, but it sounds kinda vague. It's one of the reasons why people talk about audience retention so much- you keep viewers on the platform longer, YouTube will reward you. But let me paint two different scenarios: let's say you have two different 15 minute videos.
Video A: Average view duration - 10 minutes
Video B: Average view duration - 5 minutes
At face value, Video A should be better than Video B, right? But let's dig deeper. Let's say Video A has high retention, but after watching it, people get sorta tired and leave YouTube. Video B has a higher dropoff rate, BUT it sends viewers down rabbit holes of suggested videos. We don't get to see watch session data as creators (hopefully one day, but not yet), but let's say the data is as follows:
Video A: Session time - 10 minutes
Video B: Session time - 45 minutes
Video B gets recommended with this data, even though it has a lower view duration. For whatever reason, even though people leave this video, they stay on the platform, and YouTube sees this pattern. So it continues to recommend the video. Now what if there was a way to control what the videos people watch in session were?
This is where end screens come in, and is why audience retention is important. It's not enough to keep them on one video, you need to keep them watching more videos. Good audience retention is still important, but think of it as a tool to help shape the watch session a viewer has. And if you keep them watching your videos, YouTube is likely to continue recommending them your content. If you gave them a good enough experience to keep watching your videos, you likely won a returning viewer. You see how these metrics all work together?

As always, add End Screen Clicks to your spreadsheet. You can find this data in that same drop down menu under "SEE MORE" for a given video's analytics. It's in one of the rightmost columns under "End Screens". I will usually add Average Percentage Viewed to the spreadsheet here as well, simply because you'll see a general correlation between how much of a video is watched, and how many end screen clicks it gets. Watch for patterns in your videos around audience retention and end screens if you're already using them. If you're not, start. Controlling that watch session is HUGE, and can account for massive baseline improvement.
What we're going to work on here is developing good end screen calls-to-action. You want to seamlessly transition from your content into your end screen pitch, and use the pitch as a hook to basically further sell the video you're sending viewers to. And yeah, you want to pick a specific video, not an auto-generated one. Build the watch session with intentional video uploads. It will make your channel a much more well-curated infrastructure for viewers to fall down rabbit holes. As you make tweaks to your pitch, do the same style for 5-10 videos and watch your data. Some patterns I usually see are that shorter videos tend to have a higher proportional end screen click rate, simply due to it being easier for viewers to get to the end.
Tracking these metrics and baseline in general is pivotal to understanding what's working and what's not on your channel, and that's really the first step towards unlocking much faster growth. By doing this and implementing a few other content strategy principles I went from 5,000 subscribers and maybe 500 views a day across my channel to 30,000+ views a day and a full-time income in just 3 months last year. If you want to see what I learned in my first year as a full-time creator, I made a post at the end of last year: https://www.reddit.com/r/NewTubers/comments/zcxup2/i_became_a_fulltime_…

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Essays by user Sasuke0789 :

Comments

Grammar and spelling errors:
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...ressions Using Google Sheets or Excel, I recommend creating a data tracker for e...
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...pan. For the 7 and 28 day measurements, I like to also include a % change between...
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... change between the last measurement so I can look for videos that are not just g...
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Line 10, column 188, Rule ID: EN_GB_SIMPLE_REPLACE
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...on clicks, but thats not the main thing I wanted to look at here. Theres a functi...
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Suggestion: Can't; Cannot
...;CREATE NEW GROUP' in big letters. Cant miss it. What I like to do when Im uppi...
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...pos; in big letters. Cant miss it. What I like to do when Im upping my thumbnail ...
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...t a certain category into it. Any - and I mean ANY - patterns in your existing ti...
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Line 11, column 1037, Rule ID: THREE_NN[1]
Message: You used three nouns after one another, and this might decrease readability. You might consider rewording the sentence.
...e that group as what youre comparing to baseline CTR data to see what elements of your titles and...
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Line 11, column 1427, Rule ID: THREE_NN[1]
Message: You used three nouns after one another, and this might decrease readability. You might consider rewording the sentence.
...sing this method, then log them in your baseline tracker spreadsheet. See how they compare to your average a...
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Line 14, column 56, Rule ID: EN_GB_SIMPLE_REPLACE
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... Returning Viewers to your spreadsheet. I also track both Returning and New Viewe...
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...which type of viewer you need more. 1. I get decent views on some of my videos, ...
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...ho to recommend your videos to. This is one of the only actionable ways Ive found to increase v...
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...ound to increase video impressions. 3. I get decent views on some of my videos, ...
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...t anymore channel starting to stagnate 1. This tells me youre experiencing some...
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... reaching new viewers. Okay. So how do I find these metrics? Under the 'SE...
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Suggestion: this metrics;
...ng new viewers. Okay. So how do I find these metrics? Under the 'SEE MORE' in any...
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Suggestion: videos'; video's
... Under the 'SEE MORE' in any videos analytics, you can use that drop down m...
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... style channel is to keep New Viewers a little bit higher per day than Returning, but youl...
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...an Video B, right? But lets dig deeper. Lets say Video A has high retention, but aft...
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Suggestion: this metrics;
...ely won a returning viewer. You see how these metrics all work together? As always, add En...
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... columns under 'End Screens'. I will usually add Average Percentage Vie...
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...deos and watch your data. Some patterns I usually see are that shorter videos ten...
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Suggestion: this metrics;
...or viewers to get to the end. Tracking these metrics and baseline in general is pivotal to u...
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...a few other content strategy principles I went from 5,000 subscribers and maybe 5...
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...nths last year. If you want to see what I learned in my first year as a full-time...
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...n my first year as a full-time creator, I made a post at the end of last year: ht...
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Transition Words or Phrases used:
actually, also, but, first, if, look, may, really, so, still, then, well, i mean, in general, with regard to

Attributes: Values AverageValues Percentages(Values/AverageValues)% => Comments

Performance on Part of Speech:
To be verbs : 42.0 7.0 600% => Less to be verbs wanted.
Auxiliary verbs: 28.0 1.00243902439 2793% => Less auxiliary verb wanted.
Conjunction : 79.0 6.8 1162% => Less conjunction wanted
Relative clauses : 31.0 3.15609756098 982% => Less relative clauses wanted (maybe 'which' is over used).
Pronoun: 188.0 5.60731707317 3353% => Less pronouns wanted
Preposition: 225.0 33.7804878049 666% => Less preposition wanted.
Nominalization: 25.0 3.97073170732 630% => Less nominalizations (nouns with a suffix like: tion ment ence ance) wanted.

Performance on vocabulary words:
No of characters: 8792.0 965.302439024 911% => Less number of characters wanted.
No of words: 1845.0 196.424390244 939% => Less content wanted.
Chars per words: 4.76531165312 4.92477711251 97% => OK
Fourth root words length: 6.55388916521 3.73543355544 175% => OK
Word Length SD: 3.51126787204 2.65546596893 132% => OK
Unique words: 666.0 106.607317073 625% => Less unique words wanted.
Unique words percentage: 0.360975609756 0.547539520022 66% => More unique words wanted or less content wanted.
syllable_count: 2562.3 283.868780488 903% => syllable counts are too long.
avg_syllables_per_word: 1.4 1.45097560976 96% => OK

A sentence (or a clause, phrase) starts by:
Pronoun: 36.0 1.53170731707 2350% => Less pronouns wanted as sentence beginning.
Article: 3.0 4.33902439024 69% => OK
Subordination: 10.0 1.07073170732 934% => Less adverbial clause wanted.
Conjunction: 41.0 0.482926829268 8490% => Less conjunction wanted as sentence beginning.
Preposition: 12.0 3.36585365854 357% => Less preposition wanted as sentence beginnings.

Performance on sentences:
How many sentences: 100.0 8.94146341463 1118% => Too many sentences.
Sentence length: 18.0 22.4926829268 80% => The Avg. Sentence Length is relatively short.
Sentence length SD: 57.0852651741 43.030603864 133% => OK
Chars per sentence: 87.92 112.824112599 78% => OK
Words per sentence: 18.45 22.9334400587 80% => OK
Discourse Markers: 1.08 5.23603664747 21% => More transition words/phrases wanted.
Paragraphs: 23.0 3.83414634146 600% => Less paragraphs wanted.
Language errors: 26.0 1.69756097561 1532% => Less language errors wanted.
Sentences with positive sentiment : 46.0 3.70975609756 1240% => Less positive sentences wanted.
Sentences with negative sentiment : 16.0 1.13902439024 1405% => Less negative sentences wanted.
Sentences with neutral sentiment: 38.0 4.09268292683 928% => Less facts, knowledge or examples wanted.
What are sentences with positive/Negative/neutral sentiment?

Coherence and Cohesion:
Essay topic to essay body coherence: 0.00627677717891 0.215688989381 3% => OK
Sentence topic coherence: 0.00219510950809 0.103423049105 2% => OK
Sentence topic coherence SD: 0.0218410638362 0.0843802449381 26% => Sentences are similar to each other.
Paragraph topic coherence: 0.00115974561147 0.15604864568 1% => OK
Paragraph topic coherence SD: 0.00543968909342 0.0819641961636 7% => Paragraphs are similar to each other. Some content may get duplicated or it is not exactly right on the topic.

Essay readability:
automated_readability_index: 10.3 13.2329268293 78% => Automated_readability_index is low.
flesch_reading_ease: 70.13 61.2550243902 114% => OK
smog_index: 3.1 6.51609756098 48% => Smog_index is low.
flesch_kincaid_grade: 7.9 10.3012195122 77% => OK
coleman_liau_index: 10.39 11.4140731707 91% => OK
dale_chall_readability_score: 6.89 8.06136585366 85% => OK
difficult_words: 276.0 40.7170731707 678% => Less difficult words wanted.
linsear_write_formula: 10.5 11.4329268293 92% => OK
gunning_fog: 9.2 10.9970731707 84% => OK
text_standard: 11.0 11.0658536585 99% => OK
What are above readability scores?

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Maximum four paragraphs wanted.
It is not exactly right on the topic in the view of e-grader. Maybe there is a wrong essay topic.

Rates: 11.2359550562 out of 100
Scores by essay e-grader: 1.0 Out of 9
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Note: the e-grader does NOT examine the meaning of words and ideas. VIP users will receive further evaluations by advanced module of e-grader and human graders.