Personalized Gifting – AI-Enabled Mobile App

Personalized Gifting – AI-Enabled Mobile App

Finding the perfect gift is often a guessing game. The Personalized Gifting app aimed to eliminate that uncertainty by using AI and image recognition to deliver curated gift suggestions—especially in fashion categories like T-shirts. The app’s core idea was to analyze user or recipient preferences and recommend similar items available online or in physical stores, making the entire experience thoughtful, efficient, and user-centric.

As the UX Lead, I played a pivotal role throughout the design journey. I conducted design workshops to align stakeholders, uncover user needs, and define feature priorities. Through JAD sessions, I collaborated with business analysts, developers, and designers to co-create the app's architecture and requirements. I designed wireframes to visualize key user flows, focusing on clarity and usability, and worked closely with the development team to ensure design fidelity during implementation.

One of the key innovations was the image recognition engine, which allowed users to snap a picture or upload an image of a clothing item they liked. The AI would then match and suggest similar items—personalizing the gifting experience in a way traditional recommendation engines couldn't. In addition, shoppers could discover styles for themselves, while retailers gained a new channel for product visibility and conversion.

The design process followed an iterative approach, with rounds of feedback and usability testing to ensure the app felt intuitive, reliable, and visually appealing. The outcome was an elegant, AI-powered app that not only reduced the guesswork in gifting but also created a bridge between sentiment and smart shopping.

ROI

• Increased Gift Purchase Conversion Rate: Personalized suggestions reduced drop-offs and indecision, boosting gift purchase completions.
• Retailer Partnerships: Enhanced visibility for clothing brands led to potential monetization through affiliate models or sponsored placements.
• Higher User Engagement: The app’s novelty and emotional relevance increased user session times and retention.
• Scalable Recommendation Engine: The same tech could be expanded to include other product categories (gadgets, books, accessories).