---
name: content-experimentation-best-practices
description: Structured guidance for designing, executing, and analyzing content experiments to improve conversion and engagement. Covers hypothesis frameworks, metric selection, sample size calculation, and st...
---

# content-experimentation-best-practices

Structured guidance for designing, executing, and analyzing content experiments to improve conversion and engagement. Covers hypothesis frameworks, metric selection, sample size calculation, and statistical significance testing across A/B and multivariate experiments Includes detailed resources on p-values, confidence intervals, power analysis, and Bayesian methods for interpreting results Provides CMS integration patterns for managing variants at the field level and connecting external...

# content-experimentation-best-practicesby sanity-io
Structured guidance for designing, executing, and analyzing content experiments to improve conversion and engagement. Covers hypothesis frameworks, metric selection, sample size calculation, and statistical significance testing across A/B and multivariate experiments Includes detailed resources on p-values, confidence intervals, power analysis, and Bayesian methods for interpreting results Provides CMS integration patterns for managing variants at the field level and connecting external...

`npx skills add https://github.com/sanity-io/agent-toolkit --skill content-experimentation-best-practices`Download ZIPGitHub

## Content Experimentation Best Practices

Principles and patterns for running effective content experiments to improve conversion rates, engagement, and user experience.

## When to Apply

Reference these guidelines when:

* Setting up A/B or multivariate testing infrastructure

* Designing experiments for content changes

* Analyzing and interpreting test results

* Building CMS integrations for experimentation

* Deciding what to test and how

## Core Concepts

### A/B Testing

Comparing two variants (A vs B) to determine which performs better.

### Multivariate Testing

Testing multiple variables simultaneously to find optimal combinations.

### Statistical Significance

The confidence level that results aren't due to random chance.

### Experimentation Culture

Making decisions based on data rather than opinions (HiPPO avoidance).

## References

Start with the reference that matches the current problem, such as design, statistics, CMS integration, or pitfalls. See `references/` for detailed guidance:

* `references/experiment-design.md` — Hypothesis framework, metrics, sample size, and what to test

* `references/statistical-foundations.md` — p-values, confidence intervals, power analysis, Bayesian methods

* `references/cms-integration.md` — CMS-managed variants, field-level variants, external platforms

* `references/common-pitfalls.md` — 17 common mistakes across statistics, design, execution, and interpretation

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**Source**: https://github.com/sanity-io/agent-toolkit/tree/HEAD/skills/content-experimentation-best-practices
**Author**: sanity-io
**Discovered via**: mcpservers.org