Why did my YouTube Shorts animation skit channel drop from around 1,800 views to 500-700 views, and how should I diagnose it?

Short Answer

In short, a drop from roughly 1,000-1,800 views to 500-700 views on animation skit Shorts does not prove your channel is broken or punished, but you should stop anything that looks like artificial engagement, compare Shorts-specific analytics, and test whether your newer hooks still match the animation, anime, and music audience you built. The detailed breakdown below shows how to separate a normal Shorts testing dip from a content-pattern problem, and how to rebuild with cleaner experiments.

What Probably Happened

For Shorts, YouTube is not simply handing every upload to the same fixed audience. YouTube’s own recommendation explanation says recommendations rely on many signals, including watch behavior, watch time, likes, dislikes, shares, and satisfaction signals. For Shorts specifically, YouTube Studio gives creators metrics such as how often a Short was shown in the feed and how many viewers chose to view instead of swiping away. That means a few hundred fewer views may reflect a weaker first-second test, a narrower audience match, or a new upload being tested with a different viewer pocket.

The deleted cross-comments between two channels are unlikely to explain the entire view drop by themselves, but they are still a bad habit to continue. YouTube’s fake engagement policy warns against anything that artificially increases views, likes, comments, subscribers, or other metrics. Normal replies to real viewers are fine. Repeatedly using one account to make another account look busier can create noisy signals and, if pushed too far, can become a policy risk rather than a growth strategy.

Animation skit Shorts also have a special problem: viewers judge them almost instantly. If the first beat is setup instead of payoff, the character design is unclear on a phone screen, the caption arrives late, or the joke depends on knowing the creator already, many people swipe before the skit has a chance. A Short can be technically better than older clips and still perform worse if the opening frame is less readable or the premise is less instantly recognizable.

Use Analytics First

Do not start by changing everything. Pick the last 10-20 Shorts and put them into a simple comparison table: topic, length, first visual, first line, sound style, average view duration, average percentage viewed, shown in feed, chose-to-view or stayed-to-watch rate, likes per view, comments per view, and subscribers gained. YouTube Help explicitly recommends comparing Shorts with Shorts because audience behavior differs across formats.

The key split is reach versus response. If shown-in-feed dropped but the people who saw the video still watched strongly, YouTube may not have enough recent evidence about the right audience, or the topic may be narrower than the earlier skits. If shown-in-feed is normal but chose-to-view or stayed-to-watch is weaker, the first second is the main suspect. If viewers start but average percentage viewed collapses, the premise may be clear but the middle is too slow, repetitive, or confusing.

For animation skits, look for patterns instead of single-video explanations. Did the better clips start with a face, conflict, recognizable character, exaggerated reaction, or readable caption? Did the weaker clips start with a title card, slow pan, long intro, or vague setup? Did the successful clips appeal to one audience, while the newer clips mix animation, anime references, and hip-hop jokes in a way that is funny to you but less specific to a viewer group?

How To Rebuild

Run a two-week reset with clean signals. Post without self-commenting from another channel, do not ask friends to spam-watch, and do not repost the same clip repeatedly with tiny changes. Reply to real comments from the same creator account, pin a useful or funny comment when it adds context, and let the data reflect actual viewer behavior.

Then test one variable at a time. For example, make three Shorts with the same recurring character but different opening structures: instant conflict, punchline-first rewind, and exaggerated visual reaction. Keep length similar so retention comparisons are fair. If you want faster iteration, draft the clips in YumCut to test captions, hook wording, pacing, and multilingual variants before committing hours to polished animation.

For skit channels, repeatable formats matter more than random topic chasing. Build two or three series containers: a recurring character misunderstanding internet slang, an anime-style overreaction to normal school or family moments, or a music-culture joke told through a visual gag. A series gives viewers a reason to recognize the channel, while each Short still needs to stand alone for someone seeing you for the first time. You can test the workflow in YumCut for rough prompt-to-video concepts, but manually review every joke, visual beat, and caption so the final animation still feels like your voice rather than generic AI filler.

What To Avoid

Avoid assuming every view drop is a shadowban. A fall from 1,800 to 700 views is frustrating, but it is still enough data to learn from. The more useful question is whether the newer Shorts are being shown less, swiped away faster, watched for less time, or failing to convert casual viewers into subscribers.

Avoid chasing comments as the main fix. Shorts often get fewer comments per view than regular videos, and academic research comparing Shorts with regular YouTube videos found that Shorts generally attract more views and likes per view but fewer comments per view. For a small animation channel, a low comment count is not automatically a failure. Prioritize watch behavior, repeatable characters, clear opening visuals, and clean audience fit.

Also avoid over-automating animation comedy. AI tools can help create drafts, alternate hooks, captions, translations, and rough visual concepts, but they cannot reliably judge whether a joke lands, whether a cultural reference reads correctly, or whether a recurring character is becoming memorable. Use automation for volume and variation, then use manual review for taste, timing, originality, and platform policy safety.