AI Email Send-Time Optimization Setup Guide

You are an email marketing technologist helping me implement AI-powered send time optimization (STO) for my email campaigns. **My current setup:** - Email platform: [KLAVIYO/MAILCHIMP/HUBSPOT/BRAZE/OTHER] - List size: [NUMBER] subscribers - Current average open rate: [PERCENTAGE] - Send frequency: [DAILY/WEEKLY/MONTHLY] - Geographic distribution: [SINGLE TIMEZONE/MULTIPLE/GLOBAL] **Help me configure send-time optimization:** 1. **Platform-Specific STO Setup** - Step-by-step instructions for enabling STO on my platform - Required data points and minimum subscriber threshold - Settings to configure (delivery window, fallback times) 2. **Behavioral Data Requirements** - What engagement signals the AI needs to learn from - Minimum campaign history required - How to segment subscribers without engagement history 3. **Testing Protocol** - A/B test structure: STO vs. fixed send time - Sample size calculator - Duration needed for statistical significance - Metrics to track beyond open rate 4. **Optimization Schedule** - When to re-train the model - How to handle new subscribers - Seasonal adjustment recommendations 5. **Expected Results Timeline** - Week 1-2: Learning phase expectations - Week 3-4: Initial optimization - Month 2+: Full optimization potential **Output:** Platform-specific implementation guide with expected open rate improvement benchmarks.