Market Mirror

Inspiration

People often make poor shopping decisions not because they lack information, but because emotions take over in the moment. We wanted to build a tool that helps people recognize emotional patterns behind their spending before habits repeat.

What it does

Market Mirror analyzes shopping behavior to detect emotional and behavioral patterns like impulse spending and stress-driven purchases. It reflects these insights back to users with clear visuals and personalized suggestions.

How we built it

We process uploaded or simulated shopping data using Snowflake for scalable analysis and pattern detection. Gemini converts these patterns into simple, human-readable insights shown in a clean web interface.

Challenges we ran into

Shopping data can be inconsistent, and emotional signals are hard to measure directly. We also had to make sure feedback felt supportive rather than judgmental.

Accomplishments that we're proud of

We built a system that connects emotional patterns to real shopping behavior in a clear and understandable way. We also designed insights that help users pause and reflect instead of reacting impulsively.

What we learned

Emotions play a major role in spending decisions, even when people believe they are being rational. Personalized feedback is far more effective than generic budgeting tips.

What's next for Market Mirror

We plan to add real-time impulse-risk alerts during online shopping. Long term, Market Mirror can expand into other emotion-driven decisions beyond spending.

Built With

• gemini
• react
• snowflake
• typescript