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Conversion Rate Calculator

Calculate your conversion rate from visitors and conversions, find how much traffic you need to reach a goal, or compare A/B test variants. Includes industry benchmarks for e-commerce, SaaS, landing pages, and more.

Total number of visitors or sessions
Purchases, signups, leads, downloads — any desired action
Estimates only. For statistical significance in A/B tests, use a dedicated experimentation platform.

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How to Use This Calculator

Tab "Calculate Rate"

Enter your total visitors (or sessions) and number of conversions. The calculator shows your conversion rate as a percentage, the inverse ratio (1 in every X visitors converts), and how your rate compares to industry benchmarks.

Tab "Traffic Needed"

Enter your target number of conversions and your expected conversion rate. The calculator shows exactly how many visitors you need. Optionally enter your current traffic to see the gap and what-if scenarios at different rates.

Tab "A/B Test Comparison"

Enter visitors and conversions for Variant A (control) and Variant B (challenger). The calculator computes each rate, the absolute difference in percentage points, the relative lift, and a simple confidence indicator based on sample size.

The Formulas

Conversion rate:
Conversion Rate = Conversions / Visitors × 100%

Required traffic:
Required Visitors = Target Conversions / (Conversion Rate / 100)

Expected conversions:
Expected Conversions = Current Traffic × (Conversion Rate / 100)

Relative lift (A/B test):
Lift = (Rate B − Rate A) / Rate A × 100%

Absolute difference:
Difference = Rate B − Rate A (in percentage points)

All calculations are universal and work for any type of conversion: purchases, signups, leads, downloads, or any other desired action.

Worked Examples

Example 1 — E-commerce: 50,000 visitors, 1,250 purchases

An online store receives 50,000 visitors in a month and records 1,250 completed purchases.

Visitors50,000
Conversions (purchases)1,250
Conversion rate1,250 / 50,000 × 100 = 2.50%
Visitors per conversion1 in every 40
Industry benchmarkE-commerce 1–3% — within range

At 2.5%, this store is performing well within the typical e-commerce range. To increase revenue without more traffic, even a 0.5 percentage point improvement (to 3%) would add 250 extra sales per month.

Example 2 — Traffic needed: 2,000 sales at 3% conversion rate

A SaaS company wants 2,000 new trial signups per month and expects a 3% conversion rate from website visitors.

Target conversions2,000
Expected conversion rate3%
Required traffic2,000 / 0.03 = 66,667 visitors
At 5% rate instead2,000 / 0.05 = 40,000 visitors
At 1% rate instead2,000 / 0.01 = 200,000 visitors

At a 3% conversion rate, the company needs roughly 66,667 monthly visitors. Improving the rate to 5% would cut the required traffic by 40% — often easier than generating 26,000 additional visitors.

Example 3 — A/B test: 2.5% vs 3.2% conversion rate

A landing page A/B test runs with 10,000 visitors per variant. Variant A (the control) gets 250 conversions and Variant B gets 320.

Variant A visitors10,000
Variant A conversions250 (2.50%)
Variant B visitors10,000
Variant B conversions320 (3.20%)
Absolute difference+0.70 percentage points
Relative lift(3.2 − 2.5) / 2.5 × 100 = +28.0%
Sample size10,000 per variant — good confidence

Variant B shows a 28% lift over the control. With 10,000 visitors per variant, this is a meaningful sample. Over the combined 20,000 visitors, switching to B would yield roughly 140 additional conversions.

Understanding Conversion Rates

What Is a Conversion Rate?

A conversion rate is the percentage of visitors who complete a desired action. That action can be anything: making a purchase, signing up for a free trial, submitting a lead form, downloading a resource, or subscribing to an email list. It is the single most important metric for measuring how well your website turns visitors into customers or leads.

Why Conversion Rate Matters More Than Traffic

Doubling your traffic is expensive and slow. Doubling your conversion rate has the same effect on revenue but is often achievable through optimisation: better headlines, clearer calls-to-action, faster page load times, and improved user experience. A site with 10,000 visitors at 5% converts the same as a site with 50,000 visitors at 1%.

What Affects Conversion Rate?

Key factors include traffic source (organic search converts higher than social), device (desktop typically outperforms mobile), page speed (every second of delay drops conversions 7%), trust signals (reviews, security badges), price, and call-to-action clarity. Industry and product type set the baseline; optimisation moves you above it.

A/B Testing Basics

An A/B test splits traffic between two versions of a page (or element) to measure which performs better. The control (A) is your current version; the challenger (B) is the variation. For reliable results, each variant needs at least 1,000 visitors, ideally 5,000 or more. Run the test for at least one full business cycle (typically 1-2 weeks) to account for day-of-week effects.

Improving Your Conversion Rate

Start by measuring your current rate, then test one change at a time: headline copy, button colour, form length, social proof placement, or page layout. Focus on high-impact pages first (landing pages, pricing pages, checkout). Even small improvements compound over time — a 0.5 percentage point increase on 100,000 monthly visitors means 500 extra conversions every month.

Frequently Asked Questions

Divide the number of conversions by the total number of visitors, then multiply by 100. For example: 500 signups from 20,000 visitors = 500 / 20,000 × 100 = 2.5%. A "conversion" is any action you define as valuable: a purchase, signup, download, or lead form submission.
The average e-commerce conversion rate is 1–3%. Top-performing stores achieve 3–5%. Rates vary by product category, price point, and traffic source. Luxury goods convert lower (under 1%) while impulse purchases convert higher. Focus on your own trend over time rather than exact benchmarks.
At minimum, 1,000 visitors per variant. For high confidence, aim for 5,000 or more per variant. The smaller the expected improvement, the larger the sample you need. A test detecting a 50% lift needs fewer visitors than one detecting a 5% lift. Run tests for at least 7–14 days to capture weekly patterns.
Both are valid, but be consistent. Sessions (visits) are more common because a returning visitor who converts on their second visit still counts. Unique visitors give a person-level view. Most analytics tools default to sessions. The important thing is to use the same metric across all your comparisons.
Click-through rate (CTR) measures how many people click on a link, ad, or email out of those who saw it. Conversion rate measures how many visitors complete a desired action on your site. CTR gets people to your page; conversion rate measures what they do after arriving. Both are important at different stages of the marketing funnel.

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