A/B Testing
Email testing and optimization
Multivariate Email Test Designer
Design a statistically valid multivariate email test — knowing when MVT is appropriate vs. A/B testing, how to structure a fractional factorial design for small lists, and how to interpret interaction effects that A/B tests cannot detect.
Email Design & Format A/B Test Designer
Design an A/B test that determines whether your email format — HTML vs. plain text, image-heavy vs. minimal, branded vs. personal — is helping or hurting conversion, with a methodology that isolates format from content.
Email Preheader Text A/B Test
Design an A/B test that determines whether your preheader is reinforcing or undermining your subject line — with variants that test the three strategic preheader functions and isolate the one that produces opens for your specific audience.
From Name & Sender Trust A/B Test
Test whether your sender name is building or eroding inbox trust — with variants designed to measure the recognition, authority, and relationship signals that determine whether subscribers open or archive before reading a word of content.
Email Personalization A/B Test Designer
Design a personalization A/B test that determines whether your personalization is adding genuine relevance or just the appearance of it — testing whether data-driven content changes produce measurable behavioral differences versus generic content.
Email Length A/B Test Designer
Design an A/B test that determines whether email length is limiting conversion — with a length variation that changes content depth, not just word count, and a measurement protocol that distinguishes length effects from content quality effects.
Send Time Optimization A/B Test
Design a send-time A/B test that produces a transferable timing insight for your specific audience — not a one-off result that works this week but changes with season, day of week, and list composition.
Email CTA Conversion A/B Test Designer
Design an A/B test that isolates whether your CTA copy, placement, or design is limiting email conversion — with variants built around specific friction hypotheses, not arbitrary copy changes.
Subject Line A/B Testing Framework
Build a subject line testing program that accumulates genuine learnings about your specific audience — not a random series of tests that produce contradictory results because they are testing different things without a unifying theory.
Email A/B Test Design Framework
Design a statistically valid email A/B test — with a single-variable hypothesis, a sample size calculation, a measurement protocol, and decision rules that tell you exactly when the result is conclusive and what to do with it.