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2.0 Avatar Outfits Ideas💡

2.0 Avatar Outfits Ideas💡

A Roblox experience owned by Kushiis.

RoleplayENAvatar CustomizationFashion/StyleCatalog/Shop

Description (written by the developer; not a statement by this register)

❗!!!!THIS IS A HEAVILY WIP!!!!!!❗ ⭐Welcome to CNP 2.0, CNP Avatar Outfits! ⭐ 🛍️Step into a nostalgic world of style, where you’ll find a massive endless catalog of now over 180+ 2017s - 2019s inspired avatar outfits! There’s something here for every fashion lover.🛍️ 🔧Credits to all the original outfit inspirations and users!🔧 🏷️ Tags: Outfit Shop , Outfit Store , Outfit Ideas , Steal Outfits , Hair Combo , Catalog , Outfit Loader , Fits , Matching Outfits , Try on , Outfits , Matching , Hair , Hair Combos , Mall , Avatars , Hair Combo Shop , Aesthetic , Da Hood , dh style , ideas , tt , dh , Girl Outfit Ideas, Girl, Gothic , Emo , Grunge , Harajuku , realistic , NYC , Y2k , halloween , christmas , xmas, boy , dahood , Catalog creator , Retro , Classic , 2019 , 2.0 , 2017 , 2018

Last updated by the developer 7 Mar 2026, 23:43 UTC.

0
playing (measured 13 Aug 2026, 08:05 UTC)
1,483
lifetime visits
88%
liked (14 👍 / 2 👎)
11
favourites (7.4 per 1k visits)
4 July 2025
created (per Roblox)

Play on Roblox →

Live players over time

Growth

Growth history is still building. We hold one measurement for this entry. A trend needs at least two, taken days apart — so this will fill in on its own rather than being estimated. We do not publish numbers we have not measured.

Measurement log — every players count we have recorded
Measured (UTC)PlayersChange
13 Aug 2026, 08:050first reading

Concurrent players at each of our measurements (insert-on-change).

Badge funnel

Welcome to 2.0 Avatar Outfits Ideas! · welcome437 · 100.0% win
Thank You For Your Purchase! · other156 · 100.0% win
You met the creator !!! · other14 · 0.00% win

How many players have ever earned each badge — a proxy for how far players get before they stop. Steep drop-offs mark where a game loses people. Win rate is the past-day share of players who earned it; categories are assigned by a language model from each badge’s own name and description.