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The A/B Test Significance Calculator determines whether your test has reached statistical significance, accounting for sample size, conversion rate difference, and one-sided vs two-sided hypotheses. Stops bad tests early, extends good ones appropriately.
Standard significance threshold met. Ship B, but run for another week if business cycles matter (weekends, paydays, etc).
Running a CRO program?
Our CRO engagements produce 3-5 significant winners per quarter with disciplined testing.
CRO servicesInput current metrics — no signup, no data saved to servers. Everything runs in your browser.
Results update live as you change inputs. See verdicts, benchmarks, and context, not just raw numbers.
Follow the "What this means" recommendations. Share with your team or bring to your next strategy review.
Determine when to call an A/B test
Pre-test: calculate required sample size
Audit existing tests for premature conclusions
Set minimum detectable effect for future tests
Most A/B tests are called too early or run too long. Both mistakes cost money — early calls lead to false winners that revert; long runs waste testing capacity. Our calculator asks for visitor counts and conversion counts for control and variant, then returns confidence level, required sample size to reach significance, and an honest recommendation: declare winner, keep running, or call it inconclusive. Based on standard two-proportion z-test.
Our CRO & Analytics service takes this to the next level — full audit, strategic roadmap, and senior operators executing the work. Starts at $6k/month, quarterly contracts.
Yes — 100% free, no signup, no email wall. We built it because our operators needed it and decided to share.
No. All calculations run entirely in your browser. Nothing is sent to or stored on any server.
Reach out — we will share an embed snippet for teams that want to use this inside their own workflows.
Yes. No signup required, no data collected, nothing sent to our servers. Everything runs in your browser. We publish free tools because they build trust with operators who might eventually hire us — that's the entire business model.
The math is correct and the formulas are standard. The output is only as good as the inputs you provide — garbage in, garbage out applies here like anywhere. We recommend calibrating with at least 3 months of real data before making major decisions based on the results.
The tool lives at a stable URL that you can share with your team. We don't currently offer embeds, but the output is shareable via the copy button on calculator results. For white-label or embedded versions, contact us directly.
Three reasons. First, they help operators make better decisions even if they never hire us. Second, they let us show our thinking publicly — the frameworks behind these tools come straight from our client engagements. Third, they attract the kind of operators who later become great clients.
The free tools cover standard scenarios. For custom analysis — multi-channel attribution, cohort LTV modeling, MMM — we do this as part of paid engagements. Our CRO & Analytics service starts at $6k/month and includes custom dashboarding plus BigQuery setup if needed.
Real benchmarks by industry, traffic source, and AOV tier — plus what "good" actually looks like.
Bounce rate benchmarks by industry and page type — with diagnostic framework for high bounce.
The average cart abandonment rate is 70%. Here are the specific fixes that actually recover revenue.
Most A/B tests produce inconclusive results because they're designed poorly. Here's the discipline that changes that.
Patient organic growth that compounds month over month.
Google, Meta, TikTok. Systems that scale without fatigue.
More revenue from the traffic you already earn.
DTC brands doing $1M–$50M. Acquisition, retention, margin.
Category-defining consumer brands. Brand + performance balanced.
Fashion & apparel brands. Content velocity + seasonal campaigns.