[Name] Zara Digital Closet
[Type] Concept Design
[Roll] AI UX Designer
[Tools] Figma
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PROBLEM
Customers often struggle to keep track of their past purchases and integrate new items seamlessly into their existing wardrobe. Moreover, they may spend significant time searching for outfit inspiration that aligns with their preferences. This lack of integration between physical and digital shopping experiences can lead to underutilized clothing and missed sales opportunities.
CONTEXT
Inditex, the parent company of brands such as Zara, Massimo Dutti, Bershka, and more, aims to leverage digital innovation to enhance the customer experience. The idea is to create a digital closet feature within the app ecosystem, where all past and new purchase items from any Inditex brand can be stored. This digital space will provide personalized outfit suggestions, recommend new items, highlight trends, and make the shopping journey more interactive and tailored.
GOAlS
- Create a platform that catalogs all purchases from Inditex brands.
- Provide users with personalized, daily or weekly outfit suggestions.
- Recommend new items based on current trends and user style.
- Offer a fun, engaging onboarding wizard to gather user style preferences.
MARKET & COMPETITOR A.
The fashion industry has seen a surge in digital wardrobe apps and personalized shopping experiences. Competitors like H&M offer tailored recommendations, and smaller fashion tech startups provide digital closet functionalities. However, many lack multi-brand integration at the scale Inditex can provide. This cross-brand capability positions Inditex’s digital closet as a unique, powerful tool.
- Digital Closet Feature: Automatic cataloging of all past and future purchases.
- Outfit Suggestions: AI-powered recommendations based on user preferences and purchase history.
- User Style Onboarding: A 3-step wizard to identify style preferences.
- New Item Recommendations: Suggestions for new items across Inditex brands.
- Trend Highlights: Weekly updates on trending pieces that match user interests.
MVP
- Automatic Purchase Integration: Connects seamlessly with Inditex purchase data.
- User Profile Customization: Users can input favorite categories and indicate disliked styles.
- Style Quiz: Engaging quizzes to refine AI recommendations.
- Outfit Suggestions: Daily or weekly customized outfit ideas.
- Cross-Brand Recommendations: New item suggestions spanning all Inditex brands.
FEATURES
TOOLS & TECHNOLOGY
- Artificial Intelligence and Machine Learning: To analyze purchase data and generate personalized recommendations.
- Data Integration APIs: For seamless syncing of purchase history across brands.
- Mobile App Development Frameworks: To build a smooth user experience.
- UX/UI Design in Figma.
- Cloud Services: To store user data securely and enable efficient AI processing.
RESEARCH & IDEATION
Initial research focused on understanding consumer pain points regarding wardrobe management and shopping for new outfits. Surveys and focus groups highlighted that users appreciate personalized recommendations but often find them too generalized. Competitor apps like those from H&M and ASOS were analyzed for insights into what features customers engage with and where gaps exist.
- User-Centric Design: Ensure an intuitive and seamless user interface.
- Personalization through AI: Use artificial intelligence to tailor suggestions based on user preferences, wardrobe history, and shopping habits.
- Comprehensive Brand Integration: Connect the digital closet with all Inditex brands, creating a unified
ecosystem.
KEY CONCEPTS
COMPETITIVE ADVANTAGE
Inditex’s ability to leverage its wide array of brands within a single app creates unparalleled convenience and variety for users. This ecosystem approach can keep customers engaged longer, foster brand loyalty, and drive sales by suggesting cross-brand combinations and purchases. The seamless link between past purchases and new recommendations ensures that each customer feels understood and valued.
