>> CONTENT_ENTRY
MAIL_MERGE
Last updated on
Overview
MAIL_MERGE is a robust mail merge application built with the MERN stack that enables users to send personalized mass emails efficiently. The system leverages Redis and BullMQ for sophisticated job queue management, ensuring reliable email delivery at scale.
Features
- Personalized Mass Emails: Merge template variables with recipient data for tailored messaging
- Job Queue Management: Utilize Redis and BullMQ for asynchronous email processing
- Template System: Create and manage reusable email templates
- Recipient Management: Organize and segment contact lists
- Delivery Tracking: Monitor email sending status and delivery reports
- Retry Logic: Automatic retry mechanism for failed emails
Tech Stack
- Frontend: React with modern UI components
- Backend: Node.js with Express
- Database: MongoDB for data persistence
- Queue Management: Redis + BullMQ for job processing
- Email Service: Integration with SMTP providers
Architecture
The application follows a microservices-inspired architecture:
- API Layer: Express server handling REST endpoints
- Queue Manager: BullMQ processes email jobs from Redis
- Email Worker: Background jobs that handle email sending
- Frontend: React application for user interface
Getting Started
Prerequisites
- Node.js v16+
- MongoDB instance
- Redis instance
Installation
git clone <repository>
cd mail-merge
npm install
cd client && npm install && cd ..
Environment Variables
Create a .env file in the root directory:
MONGODB_URI=mongodb://localhost:27017/mailmerge
REDIS_URL=redis://localhost:6379
SMTP_HOST=your-smtp-host
SMTP_PORT=587
SMTP_USER=your-email
SMTP_PASS=your-password
Running the Application
npm run dev
Usage
- Create an email template with merge fields like
{{firstName}},{{email}} - Upload a CSV file with recipient data
- Review the merge preview
- Schedule or send immediately
- Monitor delivery status in real-time
Performance Considerations
- BullMQ handles concurrent email sending with configurable concurrency
- Redis caching for template and recipient data
- Batch processing capabilities for large datasets
Status: Active Development
Repository: [GitHub Link]