Application Ranks by Major Online Services
E-commerce Entertainment Game
TOP 10 LIST FOR MOBILE APPLICATION Dec 2020
RANK APPLICATION UNIQUE USER REACH RATE
1 쿠팡(Coupang) 18,650,371 43.1
2 당근마켓 - 우리 동네 중고 직거래 벼룩장터 14,476,010 33.5
3 쉽고 편한 모바일쇼핑. 11번가 10,190,677 23.6
4 쇼핑을 다 담다.G마켓 8,499,132 19.7
5 위메프 - 특가대표 7,549,115 17.5
6 타임커머스 티몬 6,593,239 15.2
7 모바일 쇼핑은 옥션 6,019,972 13.9
8 GS SHOP - 당신의 가장 좋은 선택을 만듭니다 5,093,972 11.8
9 CJmall 4,284,785 9.9
10 홈앤쇼핑 - 오직 앱에서만! 10%할인 + 10%적립 4,215,935 9.7
Source: Nielsen Korea Digital Media Dept.
Panel Info: Android OS or iOS Mobile User, 10,000 in total.
Limited only to Mobile Apps existing on both Android OS and iOS

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Data and reports provided by this website are the properties of Nielsen Koreanclick, an internet media research & consulting service provider. The data and reports include prospective views for various industries that may have influences on upcoming businesses of related companies or their financial status. One who uses the data and reports, however, should keep it in mind that there exists various unknown and/or uncontrollable variables that may affect the outcomes of the businesses not in the same way as the data and reports exhibit.

We, Nielsen Koreanclick, offer statistical estimation for usage and behavior patterns of domestic internet users in Korea. The estimation offered may differ from the actual data due to the existence of various factors causing statistical deviation, including sampling errors. In addition, the methodologies used for our studies may result in different conclusions compared to those of complete enumeration surveys such as ‘site-centric’ or ‘browser-centric’ researches because of the differences in measuring targets(we exclude usage data at public locations such as schools, PC café and outside of Korea) and measuring standards(we only measure completed pages as valid but not requested pages)

Please note that Mobile data is weighted data based on Android and iOS populations surveyed through population estimation, so there may be data limitations due to measurement OS limitations and statistical weighting. In particular, in measuring the usage behavior of apps and Web within Mobile, the use of other services through the In-App Browsing method of individual apps is measured by the traffic within that app.

Depending on the operating policies of Android OS and IOS, measurement techniques and methods may change in the future. Due to differences in measurement techniques and methods, data validation standards are applied differently depending on how the smartphone OS measures, which can overestimate the estimated users and time of a particular application.