Definition
Email predictive send time uses machine learning models trained on individual subscriber behaviour to determine when each person is most likely to open and engage with an email. Rather than sending all subscribers at the same fixed time, predictive send time analysis examines historical patterns for each subscriber — what time of day they open, what day of week, how long after delivery they typically engage — and schedules delivery accordingly.
How It Works
- The model analyses each subscriber's open timing across multiple sends
- It identifies individual engagement windows rather than relying on aggregate patterns
- Predictive scheduling queues each email for delivery during that subscriber's highest-probability window
- Models improve over time as more engagement data accumulates per subscriber
Best Practices
- Predictive send time requires sufficient historical data per subscriber — minimum 5-10 tracked opens — before reliable predictions can be made
- Fall back to segment-level optimal times for subscribers without sufficient individual data
- Monitor whether predictive send time actually improves engagement compared to fixed-time sending through controlled testing
- Consider list segmentation by timezone as a simpler alternative when predictive ML tools are not available
Related Glossary Terms
Back-in-Stock
Back-in-stock email alerts notify waiting subscribers when inventory returns. Conversion rates reach 25–40% for well-timed alerts with urgency and exclusivity messaging.
Dynamic Content
Dynamic content in email refers to content blocks that change based on subscriber data, behavior, or preferences within a single email send.
Email Browser Push
Comparing email marketing with browser push notifications as complementary channels for subscriber engagement and re-engagement.
Email Bulk vs Triggered
The distinction between broadcast campaigns sent to large segments simultaneously and triggered messages sent in response to individual subscriber actions or events.
Email Campaign Diminishing Returns
The principle that each additional email send generates less incremental revenue or engagement as frequency increases and inbox competition grows.
Email Campaign Timing
Campaign timing strategy and optimisation including optimal send time analysis, time-based triggers, timing A/B testing methodology, and send time personalisation.