Best nightclubs in Seoul on Friday night (KR)

Nightclub crowd levels in Seoul South Korea on Friday night. Avoid empty clubs & enjoy the perfect night out at the popular times.

Adjust the filters to find for example your desired busy, quiet, expensive, or highly rated nightclubs.

Hongdae Club Aura (Clubs)
340
3.5

Hongdae Club Aura is most popular around 11 PM on Saturdays. It's most quiet on Sundays.

클럽끝판왕! 홍대클럽아우라!

For more info visit the website or checkout Google Maps.

클럽 아르떼 (Clubs)
1층 대동빌딩 지하 415 Gangnam-daero Seocho District, Seoul, South Korea
3.3

클럽 아르떼 is most popular around 1 AM on Saturdays. Visitors usually stay 1-3,5 hours here. It's most quiet on Mondays.

Club Arte Seoul 클럽 아르떼 서울 The Collaboration of Media Art, Music, State-of-the-art light system

For more info visit the website or checkout Google Maps.

NB2 (Clubs)
79 Wausan-ro
3.9

NB2 is most popular around 11 PM on Saturdays. Visitors usually stay 1-3 hours here. It's most quiet on Mondays.

Google Maps

Club Face Seoul (Clubs)
1309-8 Seocho-dong
2.4

Visitors usually stay 1,5-4,5 hours here.

클럽페이스는 지하1층 일렉존 (FACE) 지하2층 힙합존 (BADY) 를 운영중입니다 강남 최장수 클럽에서 함께하시죠 #강남클럽페이스 #페이스테이블 #페이스클럽 #faceclub #KOREACLUB #SEOULCLUB #GANGNAM CLUB

For more info visit the website or checkout Google Maps.

nb1 홍대 (Clubs)
South Korea, Seoul, Mapo-gu, Seogyo-dong, 362-4
3.5

nb1 홍대 is most popular around 11 PM on Fridays. Visitors usually stay 1-2,5 hours here. It's most quiet on Tuesdays.

Google Maps

Club Madholic (Clubs)
B1, 21
3.4

Club Madholic is most popular around 11 PM on Saturdays. Visitors usually stay 1,5-3,5 hours here. It's most quiet on Fridays.

매드홀릭 홍대 Madholic Hongdae (Q&A) Instagram : @madholic_hongdae

For more info visit the website or checkout Google Maps.

Missing venues? This is a free, but limited tool. Use the BestTime software get more world wide foot traffic data in Seoul, South Korea. Filter points of interest (venues) on foot traffic levels, day, time, dwell time, location, ratings, etc. BestTime provides retail foot traffic and foot traffic analytics.