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A/B Testing Workflow Diagram

The experiment lifecycle from hypothesis to traffic split to statistical decision.

Free to start · Fully editable · Export GIF, MP4, PNG & SVG

What's in this template

7 connected components you can rename, recolor, and extend with AI.

Hypothesis & MetricControl (A)Variant (B)Traffic SplitAnalytics PipelineSignificance CheckShip / Rollback

An A/B testing workflow diagram outlines the lifecycle of a controlled experiment, from forming a hypothesis to shipping a winning variant. Its key steps include defining a hypothesis and success metric, building control and variant experiences, splitting traffic, collecting data through an analytics pipeline, checking statistical significance, and deciding whether to roll out, iterate, or roll back.

Growth teams, PMs, and experimentation engineers use an A/B testing workflow to make evidence-based product decisions instead of shipping on gut feel. It is the backbone of conversion optimization programs and feature launches, keeping experiments rigorous and results trustworthy from one run to the next.

Great for

  • Conversion optimization
  • Feature launch validation
  • Growth experiments
  • Pricing tests
  • Experimentation onboarding

Make your own version with AI

Prefer to start from your own content? Describe it in one sentence and Infogiph generates a a/b testing workflow diagram you can edit and animate. For example:

“A/B Testing Workflow Diagram showing Hypothesis & Metric, Control (A), Variant (B), Traffic Split, Analytics Pipeline and Significance Check”

Try it in the AI roadmap maker, or read How to make a roadmap.

How to customize this template

  1. Open it in the canvas with Use this template.
  2. Use the Timeline style for date-driven roadmaps, and keep far-off items as themes rather than committed features.
  3. Name your activation event in the onboarding flow, and give the step with the biggest drop-off its own node.
  4. Only add pain points to a journey map when research supports them, and keep the source handy for reviews.
  5. In the Feature Prioritization Matrix Diagram, show the RICE score, reach times impact times confidence divided by effort, so anyone can check the ranking.
  6. Export a PNG or SVG for docs and slides, or a GIF or MP4 to keep the animation.

Frequently asked questions

What is an A/B testing workflow?+

It is the repeatable process for running a controlled experiment: form a hypothesis, build a control and variant, split traffic between them, measure results, and decide based on statistical significance.

What are the steps of an A/B test?+

The steps are defining a hypothesis and success metric, creating the control and variant, randomly splitting traffic, collecting data, checking for statistical significance, and shipping or rolling back the change.

What is statistical significance in A/B testing?+

It is the confidence that an observed difference between variants is real and not due to random chance, commonly judged with a p-value below 0.05 or a confidence interval that excludes zero.

How long should an A/B test run?+

Run a test until it reaches a pre-calculated sample size and covers full business cycles, typically at least one to two weeks, to avoid stopping early on noisy results.

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