The Apex Synapse logo Research Report

Email Deliverability Benchmarks

Campaign 1 · Last updated: 2025

Deliverability determines whether intelligence ever reaches its target. This campaign examines whether domain reputation and consistency — not message content — most strongly determine inbox placement, bounce rate, and spam likelihood. By isolating domain age and reputation across standardized send schedules, we reveal the system levers that shape trust at scale.

Inbox Lift (Aged vs New)
+25.8pp
Aged domains lead in inbox placement
Spam/Bounce Correlation
R² = 0.74
Consistency → trust linkage
Open Rate Delta
+13.3pp
Accessibility drives engagement

1. Executive Summary

Purpose. Determine whether domain reputation and consistency outweigh message content in driving inbox placement, bounce rate, and spam likelihood.

“Deliverability climbs with reputation and rhythm — not with message flair.”

2. Hypothesis & Theoretical Framework

Hypothesis. Inbox placement correlates more with domain reputation and consistency than with message content.

Theory Link. Providers’ ML classifiers reward consistent sender patterns and established domain signatures; volatility is treated as suspicious.

Predicted Outcome. Aged, consistent domains yield 20–30% higher inbox placement and 40% lower bounce/spam ratio vs. new domains, regardless of identical content.

Potential Impact. Improves Apex Engine’s send-time reputation module and provides priors for domain warm-up pacing.

Cohorts → Bandit Variants → Metrics

Domains: new vs aged · Message: constant (plain) · Scheduler: scheduler.emails for cross-domain parity · Reward: inbox rate → bandit_feedback.reward

3. Data & Metrics

  • Inbox Placement (%): Delivered to inbox vs. spam.
  • Bounce Rate (%): Failed deliveries (hard + soft).
  • Spam Rate (%): Filtered into spam folders.
  • Open Rate (%): Human engagement proxy.

4. Experiment Execution Plan

  • Define Variants: Domains — new (age < 14d) vs aged (>90d).
  • Sample Size: 4,000 emails per domain type.
  • Duration: 10 days continuous.
  • Measurement: Logged via send_events → inbox, spam, bounce, open.
  • Analysis: Compute inbox rate correlations vs domain consistency & reputation weight.

5. Results (Aggregate)

Domain Type Inbox % Spam % Bounce % Open %
New63.428.68.018.5
Aged89.28.42.431.8
Effect. Aged domains outperform new ones in inbox placement by +25.8pp, confirming the hypothesis.

6. Data Analysis & Interpretation Framework

  • Raw Analysis: Aggregated per domain group.
  • Model Feedback Loop: Retrain send-time and reputation weights using domain consistency as a feature.
  • Synapse Peer Review: Flag for inclusion in “Deliverability Maturity Matrix”.
  • System Learning Integration: Update scheduler bias toward stable send volume.

7. Insights & Discussion

  • High-volume, stable aged domains outperform any content tweaks on new domains.
  • Bounces and spam correlation: R² = 0.74, supporting consistency → trust linkage.
  • Open rates mirror inbox lift, proving accessibility, not creativity, drives engagement.
“Reputation builds faster through rhythm than reinvention.”

8. Ethical Considerations

  • Focus on sender system behavior.
  • Transparency in how reputation affects deliverability.

9. Contribution to the Synapse Ecosystem

  • Data Improvement: Strengthens domain reputation priors in the Apex engine.
  • Educational Value: Provides “Warm-up Blueprint” guidance for members.
  • Innovation Signal: Next: adaptive warm-up pacing via reinforcement learning.