Best open shops & malls Shah Alam (MY) near you

Popular open shops and malls in Shah Alam Malaysia : Avoid busy hours by visiting shopping malls during the quiet days as indicated below.

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

AI
(Shopping)
No.2G Jalan Saujana Indah 1 Taman Perindustrian Saujana Indah
5.0

Bateriku TTDI Jaya is most popular around 5 PM on Mondays. Visitors usually stay 20 min here. It's most quiet on Sundays.

For more info visit the website or checkout Google Maps.

(Shopping center)
14\/9, Jalan Perbadanan
4.0

SACC Mall is most popular around 2 PM on Sundays. Visitors usually stay 30 min to 4 hr here. It's most quiet on Mondays.

For more info visit the website or checkout Google Maps.

(Shopping center)
7, Jalan Pinang A 18\/A
4.0

Ole Ole Shopping Centre is most popular around 6 PM on Sundays. Visitors usually stay 15 min to 1,5 hr here. It's most quiet on Mondays.

For more info visit the website or checkout Google Maps.

(Shopping)
No.38 , Block D Plaza Jelutong No. 5C , Persiaran Gerbang Utama Bukit Jelutong,
4.9

Roxxi Gallery Collection PLT is most popular around 3 PM on Wednesdays. Visitors usually stay 15 min to 1,5 hr here. It's most quiet on Tuesdays.

Google Maps

(Shopping)
11 & 13, Jalan Singa J 20\/J
4.0

Shah Alam Car Accessories is most popular around 2 PM on Saturdays. Visitors usually stay 15 min to 1 hr here. It's most quiet on Thursdays.

For more info visit the website or checkout Google Maps.

(Shopping center)
Jalan Tengku Ampuan Zabedah E 9\/E
4.4

Plaza Shah Alam is most popular around 7 PM on Sundays. Visitors usually stay 30 min to 1,5 hr here. It's most quiet on Mondays.

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 Shah Alam, Malaysia. 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.