1. Performance
Fast Response Times: The platform must load pages and return recommendations
within 2-3 seconds under typical load.
High Throughput: The system must handle a minimum of X transactions per second
(depending on expected traffic).
Low Latency: Recommendation engine responses should have a latency of less than
100 milliseconds.
2. Scalability
Elastic Infrastructure: The platform should handle traffic spikes during events like
holiday sales or flash sales (e.g., Black Friday).
Data Growth Handling: The system must efficiently manage an expanding product
catalog and customer base over time.
3. Availability
Uptime Guarantee: Ensure 99.9% availability (or higher) with minimal downtime for
maintenance.
Failover Mechanisms: Implement redundant servers and disaster recovery plans to
ensure business continuity.
4. Security
Data Protection: All user and transaction data must be encrypted during transmission
(TLS/SSL) and at rest.
Fraud Prevention: Integrate systems to detect and prevent fraudulent transactions or
malicious activities.
Privacy Compliance: Ensure compliance with GDPR, CCPA, or other applicable data
protection laws.
5. Usability
Intuitive Design: Provide a user-friendly interface for customers to navigate easily.
Accessibility Standards: Meet WCAG 2.1 guidelines to ensure inclusivity for users with
disabilities.
Personalization: Deliver personalized recommendations that are contextually relevant to
user preferences.
6. Maintainability
Modular Architecture: The platform should use a microservices or modular design to
make updates and maintenance easier.
Automated Testing: Implement CI/CD pipelines with automated testing to ensure
smooth deployments.
7. Reliability
Fault Tolerance: The system should degrade gracefully in case of partial failures (e.g.,
fallback recommendations if a service goes down).
Error Handling: Implement robust logging and error-handling mechanisms for quick
resolution of issues.
8. Interoperability
API Integration: The platform must support seamless integration with third-party
payment gateways, shipping services, and marketing tools.
Platform Compatibility: Ensure compatibility across browsers, devices, and operating
systems.
9. Legal and Ethical Compliance
Transparent Algorithms: Ensure the recommendation engine avoids bias and meets
ethical AI standards.
Copyright Compliance: Verify that all product listings and recommendations adhere to
copyright and trademark laws.
10. Customer Support
Monitoring and Alerts: Implement real-time monitoring tools to detect issues before
customers do.
Service Level Agreements (SLAs): Define clear SLAs for response and resolution times.
By emphasizing these NFRs, you demonstrate a comprehensive, future-proof, and
customer-focused vision for the platform, inspiring investor confidence.