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CHICME - Shopping Online

CHICME - Shopping Online

Geeko Tech .

Shopping免费v5.60
App Store
评分

4.8

83,067 条评分

星级

★★★★★

最近更新

2026年5月5日

发布日期

2015年8月8日

更新内容

v5.60

Good news! We’ve fixed bugs to enhance your app experience. Update now for the latest improvements and to explore our collections hassle-free.

应用信息

开发者
Geeko Tech .
分类
Shopping
价格
免费
版本
5.60
App ID
1023653825

简介

Chic Me is a global fashion retailer offering trendy, body-hugging styles clothing at ultra affordable prices. Download our free App to explore stunning Chic Me clothing that suits every occasion and every size to discover the beauty of your figure with prices 50-80% lower than in your local store. Ever since the debut in 2015, Chic Me believes every BODY is beautiful and dedicates to make women be free from the shackles of "Body Shame". We offer 20,000+ styles including dresses, tops, bottoms, shoes and accessories, with 1000+ new items arriving weekly. Beyond the latest daily wear, we also design special themed outfits and home decoration for every festival. Why the App? Even if you are already one of our 2 million Chic Me members, enjoy 35% off on your first order on our App! Share our app to your friends and both of you could earn extra points, and receive discounts up to 70% off. On our App, you can easily navigate and add everything you love to your wish-list, enjoy a fast and secure checkout, and track your order on the phone for just one click! Download and install now, Look Chic and Save Big on Chic Me App loved by 2 million loyal members. Join our community and meet beauty mavens worldwide! More Chic Me App perks: -Fast & Free Shipping over $69 -Free & Worry-Free Return within 30 Days -Accept PayPal, Klarna, Afterpay. 100% Secure and Fast checkout -24/7 Customer Service and Live Chat available -Regular Gift Coupons and Event Reminders -Track Your Order in real time -New Arrivals up to 70% Off

下载量预测

专业 · 预览

预估总下载量

6.2M4.2M11.9M
保守估计乐观估计

32K

低 / 月

47K

预估 / 月

91K

高 / 月

基于83,067 条评分
假设评分率1.4%
应用年龄131 个月

基于评分数量 ÷ 类别评分率估算,实际下载量误差可达 ±50%,与 Sensor Tower 方法一致。