TikTok post·Other·Slideshow·Vintage Camera Filters·dazzcam.td

“A filter showcase slideshow you can use to promote a vintage film camera app - it hooks with a camera sticker overlay on a collage, followed by a sequence of high-grain retro photos.”

Watch on TikTok - @dazzcam.td

A filter showcase slideshow you can use to promote a vintage film camera app - it hooks with a camera sticker overlay on a collage, followed by a sequence of high-grain retro photos. - slide 1
10× outlier1/15
42K
Views
2K
Likes
6
Comments
83
Shares
816
Saves
Outlier score
10×

2/5 reach magnitude vs the account's own baseline.

Pull score
5/5

How hard it moved viewers to save, share, and comment.

Why this qualified

Running 10x the account's own baseline, this post reached 42K views against the 4.2K a normal post there sees. That is the whole test for an outlier in Handler - reach measured against the account's own median rather than against other accounts, so a small account with a genuine breakout still qualifies while a big account coasting on its size does not.

A vintage film camera app is the product on screen. Where reach gets a post seen, Pull - here 5/5, 13.5% weighted - is what says viewers acted on it, since saves and shares weigh in hardest and a save is the clearest sign a viewer means to come back.

Underneath the two scores sit the actual counts - 2K likes, 6 comments, 83 shares, and 816 saves - the raw engagement Handler reads to place the post in its niche.

The full breakdown - why the hook works, the comment-intent read, and the ready-to-shoot dupe kit - lives inside Handler.

How this post compares

0.1x
vs pool median views
Top 83%
reach multiple in niche
Top 40%
Pull in niche

Its 42K views run about 0.1x the median of recent outliers in the library. That reach multiple ranks in the top 83% of the 354 other outliers we currently track. Its Pull score sits in the top 40% of that same set.

Saves did the heaviest lifting on its Pull score - the action TikTok rewards most. It is one of the few Slideshow breakouts among recent outliers in the library, just 14% of the pool.

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Want to dupe these outliers for your own app?

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