Technical Insights
Practical field notes for teams diagnosing email deliverability, DNS authentication, sender reputation, Linux, MTA, cloud, monitoring, and DevOps failures.

Articles on email deliverability, DNS, Linux, MTA operations, DevOps, monitoring, and incident recovery.
Short, practical guidance for teams that need to diagnose, repair, and run production email systems.
Browse by issue, provider, workflow, or stack area when you need a fast starting point for investigation.
Analytics & Optimization · Mar 28, 2026 · 13 min readEmail CTA Optimization: Message Match, Hierarchy and Measurement
A production guide to choosing, building and measuring email actions without reducing the decision to button color.
Analytics & Optimization · Mar 26, 2026 · 13 min readRevenue per Subscriber: Cohorts, Margin and Incrementality
A finance-ready approach to subscriber economics that distinguishes gross attributed revenue from incremental, mature contribution.
Analytics & Optimization · Mar 19, 2026 · 12 min readCTR vs CTOR: Calculate and Diagnose Email Engagement
A measurement guide that keeps click-through and click-to-open denominators explicit and prevents privacy-distorted opens from producing false creative conclusions.
Analytics & Optimization · Mar 10, 2026 · 13 min readEmail Campaign Performance Analysis: A Diagnostic Scorecard
A measurement framework that reconciles transport, safety, interaction and business outcomes without relying on opens alone.
Analytics & Optimization · Feb 25, 2026 · 13 min readApple Mail Privacy Protection: Measure Email Beyond Opens
A technical guide to Apple Mail Privacy Protection, proxy image requests, open-event limits and safer campaign measurement.
Analytics & Optimization · Feb 13, 2026 · 13 min readEmail Attribution Models: Measuring Incremental Revenue
A measurement guide that separates attribution credit from causal lift and connects email touchpoints to revenue, margin, cohorts and holdout evidence.
Analytics & Optimization · Feb 10, 2026 · 15 min readEmail A/B Testing: A Practical Experimentation Guide
A practical method for designing email experiments that separate useful evidence from noise, including assignment, metrics, guardrails and rollout decisions.