Functional requirements of Online Product Recommendation System with non-functional

Functional Requirements

1. User Management:
   • Account Creation: Allow users to create accounts using email, social media, or mobile numbers.
   • Profile Management: Users can manage and update their profiles, including personal information, preferences, and purchase history.
   • Authentication & Authorization: Secure login/logout functionality with role-based access control for users and administrators.
2. Data Collection and Integration:
   • User Behavior Tracking: Track user interactions such as clicks, views, searches, and purchases.
   • Product Data Integration: Integrate with product databases to access product details, categories, and availability.
   • External Data Sources: Optionally integrate with external data sources for additional user and product information (e.g., social media activity).
3. Recommendation Algorithms:
   • Collaborative Filtering: Use collaborative filtering algorithms to recommend products based on similar user behavior and preferences.
   • Content-Based Filtering: Recommend products based on the attributes of the products that the user has shown interest in.
   • Hybrid Models: Combine collaborative and content-based filtering for more accurate recommendations.
   • Personalized Recommendations: Provide personalized product suggestions based on individual user profiles and behavior.
4. Recommendation Display:
   • Homepage Recommendations: Display recommended products on the homepage based on user preferences and recent activity.
   • Product Pages: Show related or recommended products on individual product pages.
   • Search Results: Integrate recommendations into search results to suggest relevant products.
   • Email Recommendations: Optionally send personalized product recommendations via email.
5. User Feedback and Interaction:
   • Feedback Collection: Allow users to provide feedback on recommendations to improve the accuracy of suggestions (e.g., thumbs up/down, ratings).
   • Preference Management: Enable users to set and update their preferences to refine recommendations.
6. Performance Tracking and Analytics:
   • Recommendation Performance: Track the performance of recommendations in terms of click-through rates, conversion rates, and user engagement.
   • A/B Testing: Support A/B testing to evaluate the effectiveness of different recommendation algorithms or strategies.
   • Analytics Dashboard: Provide a dashboard for administrators to view metrics related to recommendation performance and user behavior.
7. Admin Panel:
   • Dashboard: A central dashboard for administrators to manage recommendation settings, view performance metrics, and configure algorithms.
   • User Management: Admins can manage user accounts, including permissions and roles.
   • System Configuration: Allow admins to configure system settings, integrate data sources, and manage recommendation algorithms.
8. Security and Compliance:
   • Data Encryption: Implement encryption for sensitive user data, including personal and behavioral information.
   • Access Control: Enforce role-based access controls to protect data and system features.
   • Compliance: Ensure compliance with data protection regulations (e.g., GDPR, CCPA) and privacy policies.

Non-Functional Requirements

1. Performance:
   • Speed: Ensure fast load times for recommendations, including quick response times for real-time recommendations.
   • Scalability: The system should handle increasing numbers of users, products, and interactions without performance degradation.
2. Security:
   • Data Protection: Implement robust encryption and secure storage for sensitive user data, including behavioral and personal information.
   • Access Control: Ensure strict role-based access controls to prevent unauthorized access to data and system features.
   • Transaction Security: Securely handle all interactions and transactions related to recommendations.
3. Usability:
   • User Interface: Design an intuitive and user-friendly interface for displaying recommendations and managing user preferences.
   • Accessibility: Ensure the platform is accessible to users with disabilities, following WCAG guidelines.
4. Reliability:
   • Uptime: Aim for high availability with minimal downtime to ensure continuous access to recommendations.
   • Backup and Recovery: Implement regular backups and a disaster recovery plan to protect data and ensure business continuity.
5. Maintainability:
   • Code Quality: Maintain clean, well-documented code to facilitate easy updates and maintenance.
   • Modularity: Design the system in a modular way to allow for easy addition of new features, algorithms, or data sources.
6. Compatibility:
   • Cross-Browser Support: Ensure compatibility with major web browsers (e.g., Chrome, Firefox, Safari, Edge).
   • Mobile Responsiveness: The platform should be fully functional on various mobile devices and screen sizes.
7. Localization:
   • Multilingual Support: Provide the platform in multiple languages if serving a diverse user base.
   • Regional Customization: Allow for region-specific recommendations and content, including localized product availability and preferences.
8. Analytics and Reporting:
   • Data Insights: Provide actionable insights into recommendation performance, user engagement, and system usage.
   • Custom Reporting: Allow administrators to generate and customize reports based on specific criteria.