Wish: Shop and Save

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30.0K+ Installs· 4.7 ★· 4 Steps· Lifestyle· Shopping

App Showcase: Wish: Shop and Save

App info

What it does

Wish is a mobile e-commerce platform that offers a vast, seemingly endless catalog of products at heavily discounted prices. It focuses on a visual, discovery-driven browsing experience, using features like shoppable video feeds and gamified daily deals to keep users engaged and encourage impulse buys. The core value proposition is finding a wide variety of items for significantly less than typical retail prices.

Where it shines

The app excels at creating an entertaining shopping loop that encourages daily return visits. The "Blitz Buy" feature (01:38) uses a spinning wheel to gamify the discovery of daily deals, making the act of finding a discount feel like a win. Furthermore, the "Wish Clips" video feed (05:31) transforms passive browsing into an engaging, TikTok-like experience. This allows products to be demonstrated in a real-world context, which is far more compelling than static images alone.

UX highlights

Monetization & growth

The app's monetization is based on direct sales of physical goods. There is no subscription model or paywall visible in this user journey. Instead, the strategy revolves around driving high-volume sales through aggressive pricing and constant promotions. A 15% off promo code is immediately offered to new users (01:25) to incentivize their first purchase. A points-based rewards program (05:10) and daily login bonuses further encourage repeat engagement and purchasing.

Who it’s for

Wish is clearly built for bargain hunters and shoppers who prioritize price above all else. The target user enjoys the thrill of discovery and is willing to browse extensively to find unique items and deep discounts. They are likely less concerned with brand names or expedited shipping, focusing instead on the value and variety offered.

Notes & opportunities

While the discovery-led approach is engaging, the initial "For You" feed can feel generic and overwhelming before the algorithm learns user preferences. The sign-up process had a minor hiccup with an authentication error on the first attempt (00:28), which could be a point of friction. Finally, the connection between the main feed and the "Wish Clips" feed could be stronger, perhaps by integrating clips more directly into the primary browsing experience.

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