A/B Test Setup & Experimentation FAQs

Question 1

Does it support multivariate testing (MVT)?

Accepted Answer

Yes, it provides guidance for A/B, A/B/n, and multivariate tests, including the traffic requirements and complexity considerations for each.

Question 2

How does this skill help with A/B testing?

Accepted Answer

It provides a comprehensive framework for experimentation, including hypothesis generation, statistical power calculation, and metric selection to ensure tests are valid.

Question 3

What are guardrail metrics?

Accepted Answer

Guardrail metrics are secondary data points (like bounce rate or support tickets) monitored to ensure that a variant doesn't cause unintended harm while trying to improve the primary metric.

Question 4

Can it calculate how long an A/B test should run?

Accepted Answer

Yes, it uses baseline conversion rates, daily traffic, and the minimum detectable effect (MDE) to estimate required sample sizes and test duration.

Question 5

What is the 'peeking problem' in A/B testing?

Accepted Answer

Peeking refers to stopping a test as soon as you see significance before reaching the pre-calculated sample size, which often leads to false positives and inflated results.

A/B Test Setup & Experimentation

About

Key Features

Use Cases

A/B Test Setup & Experimentation

About

Key Features

Use Cases