The vocabulary, defined precisely
Every jargon term used across our blog and docs, defined the way we actually mean it, grounded in Traqlyte's own data model, not a generic dictionary entry.
Core concept
Assignment
The binding of one user to one cohort under a specific campaign version: created once, never rewritten.
Campaign
The container for one experiment: its factors, variants, cohorts, and the version history that makes it auditable.
Cohort
One locked combination of variants (one per factor) that a visitor can actually be assigned to.
Control cohort (holdout)
A cohort deliberately excluded from every treatment, so it can serve as the untouched baseline lift is measured against.
Factor
One dimension you're testing (like CTA color or headline copy) with two or more variants.
Variant
One concrete value a factor can take, such as "Blue" for a CTA-color factor.
Experiment design
Full factorial design
Testing every combination of every factor's variants at once, so both main effects and interactions are measurable.
Fractional factorial design
A deliberately reduced subset of a full factorial design that still estimates main effects at a fraction of the traffic cost.
Multi-armed bandit
An assignment strategy that shifts traffic toward better-performing variants as a test runs, instead of a fixed split.
Interaction effect
When one factor's effect depends on which variant of another factor is present: exactly what A/B testing structurally can't see.
Statistics
Lift
The incremental improvement a treatment cohort produces over control, the number an experiment actually exists to measure.
Sample ratio mismatch (SRM)
When traffic actually observed across cohorts deviates from the intended split: a red flag for a broken randomizer, not a real effect.
Statistical power
The probability a test will detect a real effect of a given size, if one truly exists, given your sample size.