Goal

Understand why users uninstall the app.

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Result

We gained a clear understanding of the reasons behind uninstalls, leading to a shift in product strategy (details below).

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Approach
The project began with a simple yet critical question: Why do users uninstall the app?

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Our data analyst conducted an in-depth analysis of user data but faced challenges. Most users uninstalled the app shortly after installing, leaving behind minimal data for analysis.

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Recognizing that data alone wasn’t providing answers, we organized a cross-functional workshop with UX, data, market research, and product teams. By blending qualitative insights with quantitative data and collaborative brainstorming, we uncovered a key insight: uninstall rates were notably high in the Shoes and Fashion categories.

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Further analysis revealed that Shoes and Fashion had recently grown into Idealo's third-largest category. Since Idealo was originally designed for tech products, this rapid growth in fashion caught us by surprise.

Data also showed that fashion shoppers differed from our core user base. They primarily arrived via social media ads and lacked brand loyalty—some didn't even recognize the Idealo brand.

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To explore this further, we conducted user tests that examined the entire customer journey, starting with social media ads. The findings were eye-opening, uncovering multiple significant usability issues specific to fashion products.

One major issue was with marketing practices. Ads often highlighted the lowest available price for a product, which frequently applied to uncommon sizes. For example, an ad for Jordan sneakers might display a price for a child’s size. Users would click the ad expecting that price, only to discover their size was much more expensive. This created a misleading experience and left users feeling deceived.

 

Impact
This project led to a significant shift in our product strategy. We moved away from a "one-size-fits-all" model to developing tailored solutions for key product categories.

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Key Changes Implemented:

• Workshop with the marketing team to design more user-friendly ads.

• Workshop with the fashion content team to improve how products are presented on the platform.

• Redesign of product page size filters for easier navigation.

• Improved variant selection on product pages.

• Collaboration with the machine learning team to enhance product recommendations in cross-navigation.

 

These changes directly addressed user pain points and reduced uninstall rates by 11%.