Multivariate Testing
Multivariate testing without the traffic tax
Pit up to five named variants against each other in one experiment, on copy, CTAs, paywalls, or prices, and let Bayesian stats call the winner on the revenue that matters, even at modest traffic.
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More than A/B, when two isn't enough
Some ideas need more than one challenger. Run an A/B/n test with up to five variants in a single experiment, control plus four, so you compare several headlines, button styles, or price points side by side instead of chaining sequential A/Bs.
- Up to five variants per experiment
- Element, CTA, and price-test experiment types
- One shared control, judged the same way
Name variants so results make sense
Give each variant a real name, hero-blue, price-29, long-copy, instead of a lettered placeholder. The name flows through to the results table and the exposure charts, colour-coded, so a glance tells you which idea is winning.
- Editable, human-readable variant names
- Colour-coded variants across results and charts
- Per-variant uplift, chance to win, and split
Sound results at real-world traffic
More variants split your traffic thinner, so weak stats hurt. StatsKit uses Bayesian analysis to give a readable chance-to-win from your first conversions and judges by net revenue per 1,000 visitors, so a multivariate test stays actionable instead of running forever.
- Bayesian engine tuned for low volume
- Weighted traffic split you control
- Revenue-tied winner, not vanity clicks
Frequently asked questions
What is multivariate testing?
Multivariate (A/B/n) testing compares more than two variants of the same element in one experiment. StatsKit supports up to five variants per test, each with its own name and traffic weight.
How is it different from A/B testing?
A/B compares two variants; multivariate compares several at once against a shared control. In StatsKit it's the same builder, you just add more variants, up to five.
Do I need a lot of traffic?
More variants need more traffic to separate, but StatsKit's Bayesian stats and revenue-based scoring give you a usable read earlier than significance-only tools.
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