How to Build an AI-Powered Email Scheduling Assistant

Simple Summary

An intelligent email scheduling optimizer that helps users send emails at the most effective times, improving open rates and engagement.

Product Requirements Document (PRD)

Goals:

• Develop an intelligent system to optimize email send times
• Improve email open rates and engagement for users
• Provide a user-friendly interface for email scheduling
• Ensure scalability and security of the application

Target Audience:

• Professionals and businesses who rely heavily on email communication
• Marketing teams looking to improve email campaign effectiveness
• Individuals seeking to optimize their email productivity

Key Features:

1. AI-powered send time optimization
2. User-friendly email composition and scheduling interface
3. Analytics dashboard for email performance
4. Integration with popular email providers (Gmail, Outlook, etc.)
5. Customizable scheduling preferences
6. Mobile app for on-the-go email management

User Requirements:

• Ability to compose and schedule emails within the application
• Automatic suggestions for optimal send times
• Easy-to-understand analytics on email performance
• Seamless integration with existing email accounts
• Customization options for scheduling preferences
• Secure handling of email data and user information

User Flows

1. Email Composition and Scheduling:

   • User logs in to the application
   • Composes a new email
   • AI suggests optimal send time
   • User accepts or modifies the suggested time
   • Email is scheduled and sent at the specified time

2. Analytics Review:

   • User navigates to the analytics dashboard
   • Views overall email performance metrics
   • Drills down into specific email campaigns or time periods
   • Adjusts scheduling preferences based on insights

3. Account Integration:

   • User accesses settings page
   • Selects "Add New Email Account"
   • Chooses email provider and grants necessary permissions
   • Application syncs with the new email account

Technical Specifications

Frontend:

• React for web application
• React Native for mobile app
• Redux for state management
• Chart.js for analytics visualizations

Backend:

• Node.js with Express.js
• PostgreSQL for primary database
• Redis for caching and job queuing
• Machine Learning model (TensorFlow.js) for send time optimization

APIs and Services:

• Gmail API, Outlook API for email integration
• SendGrid or Mailgun for email sending
• Auth0 for authentication
• AWS S3 for file storage

DevOps:

• Docker for containerization
• Kubernetes for orchestration
• CI/CD pipeline using Jenkins or GitLab CI

API Endpoints

• POST /api/auth/register
• POST /api/auth/login
• GET /api/user/profile
• PUT /api/user/settings
• POST /api/emails/compose
• GET /api/emails/scheduled
• PUT /api/emails/:id/reschedule
• GET /api/analytics/overview
• GET /api/analytics/email/:id

Database Schema

Users:

• id (PK)
• email
• password_hash
• name
• settings_id (FK)

Emails:

• id (PK)
• user_id (FK)
• subject
• body
• recipients
• scheduled_time
• sent_time
• status

EmailAccounts:

• id (PK)
• user_id (FK)
• provider
• access_token

Analytics:

• id (PK)
• email_id (FK)
• opens
• clicks
• replies

File Structure

Implementation Plan

1. Project Setup (1 week)

   • Initialize repository and project structure
   • Set up development environment and tools
   • Create initial documentation

2. Backend Development (3 weeks)

   • Implement user authentication and authorization
   • Develop core email scheduling and management APIs
   • Set up database and ORM
   • Integrate with email service providers

3. Frontend Development (3 weeks)

   • Create responsive UI components
   • Implement email composition and scheduling interface
   • Develop analytics dashboard
   • Integrate with backend APIs

4. Machine Learning Integration (2 weeks)

   • Develop and train initial ML model for send time optimization
   • Integrate ML predictions into scheduling logic
   • Implement feedback loop for model improvement

5. Testing and QA (2 weeks)

   • Write and run unit tests
   • Perform integration testing
   • Conduct user acceptance testing
   • Address bugs and performance issues

6. Deployment and DevOps (1 week)

   • Set up production environment
   • Configure CI/CD pipeline
   • Implement monitoring and logging
   • Perform security audits

7. Beta Testing and Iteration (2 weeks)

   • Release to a limited user group
   • Gather feedback and usage data
   • Implement improvements and fix issues

8. Launch and Marketing (1 week)

   • Finalize documentation and help resources
   • Prepare marketing materials
   • Launch product and monitor performance

Deployment Strategy

1. Use containerization (Docker) for consistent environments
2. Deploy backend services to Kubernetes cluster on AWS EKS
3. Use AWS RDS for PostgreSQL database
4. Implement Redis caching layer with AWS ElastiCache
5. Deploy frontend to AWS S3 with CloudFront CDN
6. Set up auto-scaling for backend services
7. Implement blue-green deployment for zero-downtime updates
8. Use AWS CloudWatch for monitoring and alerting
9. Implement daily database backups to S3
10. Use AWS WAF for additional security layer

Design Rationale

• React and Node.js chosen for their robust ecosystems and developer productivity
• PostgreSQL selected for its reliability and support for complex queries needed for analytics
• Machine learning integration allows for personalized scheduling optimization
• Containerization and Kubernetes provide scalability and ease of deployment
• Separation of frontend and backend allows for independent scaling and development
• Analytics dashboard empowers users with actionable insights
• Mobile app ensures users can manage emails on-the-go
• Emphasis on security (Auth0, WAF) protects sensitive email data