Skip to content

KhushiBajpai2003/Myntra-HackerRamp-2024

 
 

Repository files navigation

Trend Generation and User Engagement: The Challenge of Trend Discovery for Gen Z

Problem Statement

Fashion trends evolve rapidly, and traditional methods for trend forecasting often fall short in addressing the fast-changing interests of Gen Z, a demographic known for its diverse fashion sense. The challenge is to effectively identify and predict trends that resonate with this dynamic audience.

Why Current Methods Fall Short

  • Slow Trend Analysis: Traditional methods are often lagging behind real-time trends.
  • Lack of Real-Time Engagement: Limited user interaction and participation.
  • Limited User Participation: Current platforms do not engage users actively in the trend discovery process.

Solution

Our app addresses these challenges by creating an interactive platform where Gen Z users can participate in fashion challenges and discover trends based on real-time user interactions.

Key Features

  • Fashion Challenges: Users can participate in themed challenges such as “Vintage Revival” and sketch challenges such as “Fusion Fiesta” by submitting their fashion images.
  • User Interactions: Other users can like and comment on submissions, creating a dynamic and engaging experience.
  • Trend Analysis: Winners are determined based on the number of likes and comments, as well as the uniqueness of the submission, identified through feature extraction techniques.
  • Trend Discovery: The most popular and unique submissions help identify emerging fashion trends.

Benefits

For Myntra

  • Myntra Catalog Promotion: Enhanced visibility for Myntra’s catalog through user-generated content.
  • Enhanced User Engagement: Increased user interaction and engagement on the platform.
  • User-Curated Trend Generation: Identification of trends directly influenced by users, leading to potential increases in sales.
  • Streamlined Creative Ideas: Fresh and innovative ideas directly from the user base.

For Users

  • Personalized Fashion Choices: Tailored fashion recommendations based on user interactions and preferences.
  • Outfits at Discounted Prices: Earn points through participation which can be redeemed for discounts.
  • Recognition: Gain nationwide recognition for their creativity and style.
  • Platform for Designing Minds: A space for budding designers to showcase their talent.

Objectives Achieved

  • Boosting User Creativity: Encouraging users to showcase their talent through various challenges.
  • Discovery of New Trends and Designs: Identifying and promoting new fashion trends.
  • Spike in User Engagement: Increased user participation and interaction on the platform.

Future Possibilities

  • Curating Challenges: Designing challenges based on increasing user demand and preferences.
  • Generating Multiple Images: Utilizing top unique designs to generate additional fashion images.
  • Outfit Generation Bot: Creating outfits using user-specific design features through advanced AI bots.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contributors

Acknowledgements

About

No description or website provided.

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 90.0%
  • Java 10.0%