Transforming Retail Fashion Engagement

Transforming Retail Fashion Engagement

Project Summary

This innovative platform redefines customer engagement for a leading retail fashion brand by delivering personalized shopping experiences. Built with Spring Boot, GraphQL, and AWS, it evolved from ideation to a scalable, production-ready system through offshore development, offering interactive features, real-time workflows, and robust scalability to enhance user retention and marketing success.

Challenges

  • Overcoming fragmented user interactions and limited personalization in existing systems.
  • Ensuring scalability to handle high-traffic promotional events without performance degradation.
  • Integrating real-time, event-driven workflows for dynamic user engagement.
  • Managing diverse data types (user profiles, inventories, preferences) at scale.
  • Aligning with the client’s internal IT workflows for seamless integration and cost-effective delivery.

Solution

The platform was developed through a structured idea-to-MVP-to-stable-system approach, leveraging offshore expertise:

  • Ideation & Architecture: Collaborated with the client to define features like interactive product boards, quizzes, and dynamic feeds, designing a modular Spring Boot microservices architecture.
  • MVP Development: Built a lean MVP with core engagement features and REST APIs, using MySQL to store user data and validate the concept with early user feedback.
  • Stable System Development: Scaled the MVP with GraphQL APIs, MongoDB and Cassandra for data scalability, Kafka for real-time workflows, and AWS for high availability.
  • Personalized Features: Delivered interactive boards, quizzes, and feeds tailored to user preferences.
  • APIs & Integration: Implemented secure REST and GraphQL APIs for seamless integration with the client’s web and mobile apps.
  • Real-Time Workflows: Utilized Kafka for event-driven tracking and targeted promotions.
  • Data Management: Combined MySQL, MongoDB, and Cassandra for efficient handling of user profiles, inventories, and preferences.
  • Maintenance: Provided ongoing offshore support to optimize performance and support evolving needs.

Technology Stack

  • Backend: Spring Boot
  • APIs: REST, GraphQL
  • Databases: MySQL, MongoDB, Cassandra
  • Event Streaming: Kafka
  • Cloud: AWS (assumed for deployment, aligned with client’s ecosystem)
  • Frontend: Integrated with the client’s existing frontend

Outcome and Business Impact for the Client

The platform transformed the client’s retail engagement, achieving:

  • 30% Boost in Engagement: Personalized boards and quizzes increased user interaction time.
  • 20% Higher Conversions: Real-time Kafka-driven promotions enhanced marketing success.
  • 80% Operational Efficiency: Streamlined content and user management reduced overhead.
  • 99.9% Uptime: AWS-powered infrastructure ensured reliability during high-traffic events.
  • Scalable Growth: A robust foundation supported expansion into new markets and product lines.
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