🧫 Multivariate Test (MVT)

Multivariate Test (MVT)#

An experiment varying several elements at once to estimate combined effects.

Important

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What it is#

A multivariate test (MVT) varies several page elements at once and tests their combinations, to learn not just which single change helps but how elements interact. Where A/B compares whole versions, MVT decomposes the page into factors.

How it works#

Choose the elements to vary — say headline, button colour, image — and form the combinations. With two options each, that is \(2 \times 2 \times 2 = 8\) versions; users are split across them and the metric measured per combination.

Full vs fractional factorial#

A full factorial MVT tests every combination, giving the cleanest read on main effects (each variable alone) and interaction effects (how they combine) — but the count explodes. A fractional factorial tests a chosen subset, cutting traffic and complexity at the cost of resolving some interactions.

Why interactions matter#

The payoff is the interaction. A landing-page test might find a strong headline worth +10%, a green button +5% and a lifestyle image +2% individually — yet the combination of all three lifts conversion +25%, more than the parts suggest. That synergy is invisible to separate A/B tests.

The cost#

MVT needs much larger samples (variants multiply fast), is harder to design and analyse, and carries the same multiple-comparisons false-positive risk. Use it to fine-tune many elements once you have the traffic; use A/B for big, single-design changes.

Theme: A/B Testing & Experimentation · All terminology

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Mind map — connected ideas

A/B/n Test · A/B Testing · Traditional A/B Test (Fixed-Horizon A/B Test) · Conversion Rate (CR) · Type I Error · Online Experimentation Platforms

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A/B Testing · A/B/n Test · Bayesian Sequential Testing · Bayesian Stopping Rules · Conversion Rate Uplift · Fixed-Horizon Testing · Group Sequential Testing · Online Experimentation Platforms · Optimizely · Risk of Peeking · Sequential Testing (also called sequential analysis) · Stopping Rules · Traditional A/B Test (Fixed-Horizon A/B Test) · Treatment Effect