AI Email Campaign Optimization Full Syllabus

Module 1: Introduction to AI in Email Marketing

• Role of AI in email campaigns
• Traditional vs AI-powered campaigns
• Benefits: Personalization, Timing, Subject lines, Segmentation
• Real-world case studies: Amazon, Netflix, Shopify, Grammarly

Module 2: Understanding Email Campaign Structure

• Key components of an email campaign:
  • Subject line
  • Email body
  • Call to Action (CTA)
  • Timing and frequency
  • Target audience and segmentation
• Funnel-specific emails: Welcome, Nurture, Conversion, Retention, Win-back

Module 3: Data Collection & Preparation

• What data powers AI in email:
  • Open rate, Click-through rate, Bounce rate
  • Subscriber metadata (location, time zone, device)
  • CRM behavior (pages visited, cart, support tickets)
  • Purchase history and preferences
• Cleaning and organizing email engagement data
• Privacy compliance: GDPR, CCPA

Module 4: Segmentation with AI

• Predictive segmentation
  • High openers vs cold leads
  • VIP vs one-time buyers
  • Cart abandoners vs loyal subscribers
• Behavioral segmentation with clustering (K-means, DBSCAN)
• Lookalike audience modeling

Module 5: AI for Subject Line & Email Copywriting

• Using NLP for writing compelling subject lines
• GPT & LLM-based content generation
• A/B testing AI-generated content
• Tools: Copy.ai, Jasper, ChatGPT, Phrasee, Mailchimp AI

Module 6: Optimal Send-Time Prediction

• How timing affects open & click rates
• AI models for best-time-to-send per user
• Time zone & behavior-based automation
• Tools: Mailchimp Send Time Optimization, MoEngage AI

Module 7: Predictive Analytics for Campaign Performance

• Open/click rate prediction using ML
• Conversion probability estimation
• Regression models for revenue prediction
• Using past performance to guide future campaigns

Module 8: Personalization with AI

• Dynamic content generation (products, text, CTAs)
• AI-powered product recommendations in emails
• AI segmentation-driven personalization
• Real-time personalization examples

Module 9: AI Tools & Automation Platforms

• AI platforms for email:
  • Mailchimp, Klaviyo, ActiveCampaign
  • HubSpot AI, Salesforce Einstein
  • Omnisend, Sendinblue with AI
• Integration with Zapier, Integromat, APIs
• Building custom email AI logic with Python + Flask

Module 10: Measuring & Improving Campaigns

• Metrics that matter (beyond open rate)
• Use of AI in identifying underperforming content
• Reinforcement learning in email sequences
• AI in churn prediction from email behavior
• Retargeting strategies using email engagement insights

Module 11: Ethical AI Emailing

• Avoiding AI spam
• Human touch in AI-written content
• Privacy-aware content personalization
• Giving subscribers control over personalization