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A/B Test Sample Size Calculator

Before launching a conversion A/B test, you need an approximate sample size.

Campaign workspace

A/B Test Sample Size Calculator

Structured inputs and readable results — copy URLs, scan limits, and review findings without digging through JSON.

Approximate equal-allocation sample size from baseline rate, MDE, and power.

Results

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Results appear here

Fill the form and run the tool — outputs are structured cards, not a raw JSON dump.

Free · API · MCPToolYour platform

Use A/B Test Sample Size Calculator three ways

The free A/B Test Sample Size Calculator on this page works in your browser. The same workflow is available via REST API for apps and via MCP for Cursor, Claude, and other agents — one API key, one plan, one quota. This tool is part of the marketing-apis module under Marketing Tools.

  • 1. Get an API keySign in and open Dashboard → API Keys (works for REST and MCP).
  • 2. Call or connectUse the REST API from your server, or paste the MCP URL into your agent config.
  • 3. Same qualityOutput matches the free web tool across all three surfaces.
Manage API keysMCP setupAPI referenceCreate free account

What is A/B Test Sample Size Calculator?

Before launching a conversion A/B test, you need an approximate sample size. ToolYour A/B Test Sample Size Calculator uses a two-proportion equal-allocation formula from baseline rate, MDE (relative by default), alpha, and power — returning per-variant and total n. It is an approximation, not a sequential-testing or Bayesian engine. Same route via REST and MCP (POST /api/v1/marketing-apis/ab-test-sample-size-calculator).

What are common questions about A/B Test Sample Size Calculator?

What is MDE?

Minimum detectable effect. By default treated as relative lift (e.g. 0.1 = +10% relative). Set absolute mode when you want additive points.

Defaults for alpha and power?

alpha 0.05 and power 0.8 unless you override.

Can I use this for a multi-variant (A/B/C/D) test?

The formula is two-proportion (A vs B). For more than two arms, use dedicated experimentation software that accounts for multiple comparisons.

What are the key features of A/B Test Sample Size Calculator?

Two-proportion formula

Transparent z-based n estimate for planning traffic.

How do you use A/B Test Sample Size Calculator?

Enter baseline rate and MDE

Use historical conversion as baseline.

Plan traffic

Ensure you can reach n per variant before deciding.

Why this tool exists

Launching a conversion A/B test without an approximate sample size means either running it too short (underpowered, noisy result) or too long (wasted traffic on a settled question). A/B Test Sample Size Calculator exists to give a quick two-proportion estimate from baseline rate and minimum detectable effect before you commit traffic.

Problems it solves

Teams frequently call a test 'done' when it hits statistical significance early, without ever checking whether they had enough traffic planned to detect the effect size they actually cared about. Planning sample size upfront avoids both underpowered tests and endless, indecisive ones.

Common use cases

  • In-house CRO team: estimating how many visitors per variant are needed before greenlighting a landing page test.
  • Agency growth retainer: setting client expectations on test duration before launch, based on their actual traffic volume.
  • Pre-launch: confirming a planned test window has enough expected traffic to reach the required sample size.
  • Agent/MCP: an agent estimating sample size as one step in a test-planning playbook, before a human commits the traffic split.

Honest scope

This is a two-proportion, equal-allocation approximation (default alpha 0.05, power 0.8) — useful for quick planning, not a substitute for dedicated stats tooling on complex designs: more than two arms, clustered units (e.g. by account rather than by visitor), or sequential peeking need a different methodology.

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