GiftGenius App Design

Mobile App

Role:

Product & Lead Designe

Time:

4 weeks

Year:

2026

Overview

GiftGenius is an all-in-one AI-powered platform that delivers personalized gift recommendations based on relationship, context, and user intent. I led the UX strategy and end-to-end product design, from user research and prompt framework development to interaction design and system structuring.

The experience follows three stages: Explore, where users start with a gifting need; Understand, where the AI learns about the recipient, occasion, preferences, and budget; and Recommend, where it turns those inputs into personalized, confident purchase suggestions.

GiftGenius is an AI-powered gift decision assistant designed for users who feel anxious about choosing gifts, especially across different relationships and limited budgets.

The experience follows three stages: Explore, where users start with a gifting need; Understand, where the AI learns about the recipient, occasion, preferences, and budget; and Recommend, where it turns those inputs into personalized, confident purchase suggestions.

I conducted user research with 12 participants aged 22–30, combining contextual inquiry, think-aloud protocols, and surveys to uncover behaviors, pain points, and decision-making patterns throughout the gifting journey. I then synthesized the findings into target user scenarios and profiles, identifying key friction points and opportunities for AI-assisted gifting.

Participants were asked to find a gift using only AI platforms. Users are forced to constantly switch between AI conversations and e-commerce platforms, repeatedly re-entering information, validating needs, and making decisions across systems—resulting in significant cognitive and decision-making overload.

User Research

I conducted user research with 12 participants aged 22–30, combining contextual inquiry, think-aloud protocols, and surveys to uncover behaviors, pain points, and decision-making patterns throughout the gifting journey. I then synthesized the findings into target user scenarios and profiles, identifying key friction points and opportunities for AI-assisted gifting.

Systems that understand users often can’t complete transactions,

 while systems that complete transactions don’t truly understand users.

The opportunity in gifting is not more options, but a continuous decision experience that integrates understanding, judgment, and purchase into a single flow.

Participants were asked to find a gift using only AI platforms. Users are forced to constantly switch between AI conversations and e-commerce platforms, repeatedly re-entering information, validating needs, and making decisions across systems—resulting in significant cognitive and decision-making overload.

Structured Questioning:

Understand user needs through three core dimensions:

relationship, closeness, and budget / desired vibe.

Questions are primarily multiple-choice, with optional free input—keeping the flow efficient without feeling rigid.

Low-Cost Interaction:

Interactions are designed around selection over typing, balancing speed with meaningful personalization.

I analyzed how users naturally ask AI for gift recommendations and designed a structured, high-signal questioning framework based on these real-world patterns.

Competitive Analysis

Systems that understand users often can’t complete transactions,

 while systems that complete transactions don’t truly understand users.

The opportunity in gifting is not more options, but a continuous decision experience that integrates understanding, judgment, and purchase into a single flow.

Design Strategy & Solution

Structured Questioning:

Understand user needs through three core dimensions:

relationship, closeness, and budget / desired vibe.

Questions are primarily multiple-choice, with optional free input—keeping the flow efficient without feeling rigid.

Low-Cost Interaction:

Interactions are designed around selection over typing, balancing speed with meaningful personalization.

Auto-Generated Profile

After each conversation, the AI extracts recipient preferences and generates memory cards on the home screen. Users can reuse them in future gifting moments without re-answering basic questions.

Context-Aware Prompts

Quick-entry suggestions update dynamically with seasons and events (e.g., Valentine’s Day, graduation), helping users start faster


Zero-Frictions Start

No onboarding or learning curve—users can begin a conversation immediately and refine intent as they go.

Floating Comparison Layer

About 60% of users reported difficulty comparing options when new questions push key content upward in chat-based interfaces.

To support side-by-side evaluation, products are displayed in a floating overlay, keeping the core dialogue anchored while enabling efficient comparison and decision-making.

Dynamic Guidance

After each response, the system surfaces the next best prompt, helping users move forward continuously through the decision process.


Auto-Generated Memory

After each conversation, the AI extracts recipient attributes and saves them as reusable profile cards—reducing repeated input in future scenarios.