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Philips Norelco Shavetopia [SZN 1]

Philips Norelco Shavetopia [SZN 1]

A Roblox experience owned by Philips Experience Hub.

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Philips Norelco Shavetopia [SZN 1] is a Roblox experience created on September 22, 2022. The game has accumulated 1,040,414 lifetime visits and 4,974 favorites. Currently, zero users are playing. The like percentage stands at 18%. The genre field is null. A description indicates the experience has moved to a Season 2 version.

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

MOVED TO: https://www.roblox.com/games/13084857922/Philips-Norelco-Shavetopia-SEASON-2

Last updated by the developer 5 Jun 2026, 15:12 UTC.

0
playing (measured 22 Aug 2026, 09:50 UTC)
1,040,414
lifetime visits
18%
liked (1,341 👍 / 5,946 👎)
4,974
favourites (4.8 per 1k visits)
22 September 2022
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 We do not publish numbers we have not measured.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
22 Aug 2026, 09:500first reading

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

Badge funnel

Welcome to Philips Norelco Shavetopia · welcome855,696 · 100.0% win
Rider · progression305,008 · 0.00% win
Hair Defender · progression142,720 · 0.00% win
Trimmer136,623 · 0.00% win
Shaving Spree · other66,819 · 0.00% win
Hairmergency Response Team · progression37,431 · 0.00% win
Blade Boss · collection22,338 · 0.00% win
Staching Staches · collection3,166 · 0.00% win
Blade Hunter · collection1,506 · 0.00% win
Sultan of Shave · collection1,199 · 0.00% win
Trim Tycoon · collection272 · 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.