Bayesian or sequential statistics
On this pageWhat it is
What it is
Statistics engines decide whether the difference between two versions is real or just chance. A traditional method expects you to fix a sample size in advance and look only at the end. Looking early and stopping when the numbers look good raises the chance of a false win. Bayesian and sequential methods are designed for results that are checked while the test is running. Convert Experiences, OmniConvert, Optimizely and VWO are examples of tools listed with this feature.
Why it matters
Most business owners check a test early, because waiting is hard. A suitable statistics method means those early looks do not distort the answer, so you can act with more confidence and stop tests sooner. You need it if you run tests regularly and report to people who ask for an update. If you run a few tests and wait until the planned end, a traditional method can be enough.
What to check
- Which method does the tool use, and does it explain the results in plain language?
- Does the tool show a probability of winning, a confidence level or both?
- Can you set rules for when a test is allowed to end?
- Are there warnings when a test has too little traffic to be reliable?
Tools with Bayesian or sequential statistics
Runs A/B and multivariate tests on websites to track visitor behaviour and optimise conversion rates.
A/B testing and experimentation platform with tiered plans, a free trial and an official MCP server.
A/B testing, web personalisation and on-site surveys all combined in one ecommerce-focused platform.
Experimentation and personalisation platform for testing websites and features, sold through a sales conversation.