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.