Understanding how well your pages, ads and funnels convert visitors into customers is the most direct lever on revenue. A 1% improvement in conversion rate is often worth more than doubling your ad budget, yet most teams do not measure it rigorously. This calculator gives you an instant, accurate answer — and the tools to make confident decisions.
How it works
Conversion rate (CVR)
The core formula is beautifully simple:
CVR = Conversions / Visitors
Where conversions is any meaningful action — a purchase, a sign-up, a form submission or a trial start — and visitors is the number of sessions, page-views or impressions you are measuring over the same window.
Once you have the rate, the calculator extends it into three business-critical metrics:
- Revenue per visitor — CVR multiplied by your average revenue per conversion. This is the single number that lets you compare channels of different scale on equal terms.
- ROAS (Return on Ad Spend) — total revenue divided by total spend. If you know your cost per click and visitor volume, total spend = CPC × visitors.
- CPA (Cost per Acquisition) — total spend divided by total conversions, showing exactly what each customer costs you to acquire.
A/B test significance
Running a test with two variants and not knowing whether the difference is real or just noise is a costly mistake. The calculator uses a two-proportion z-test:
- Compute conversion rates pA and pB for control and variant.
- Pool them into a combined rate p = (cA + cB) / (nA + nB).
- Standard error: SE = sqrt( p(1-p) × (1/nA + 1/nB) ).
- Z-score: z = (pB - pA) / SE.
- Two-tailed p-value from the standard normal CDF.
A p-value below 0.05 means you can be at least 95% confident the difference is not due to chance. The relative uplift figure — (pB - pA) / pA — tells you the percentage improvement if the variant wins.
Worked example
A landing page receives 10,000 visitors in one month and records 320 purchases at an average order value of £49.99. The Google Ads campaign costs £0.85 per click.
| Metric | Calculation | Result |
|---|---|---|
| Conversion rate | 320 / 10,000 | 3.20% |
| Total revenue | 320 × £49.99 | £15,997 |
| Total ad spend | 10,000 × £0.85 | £8,500 |
| ROAS | £15,997 / £8,500 | 1.88× |
| CPA | £8,500 / 320 | £26.56 |
| Revenue per visitor | 3.20% × £49.99 | £1.60 |
At 1.88× ROAS the campaign is barely profitable after cost of goods. Simply lifting the conversion rate to 4% (a 25% relative increase) would push ROAS to 2.35× without changing spend.
A/B test example
You run two variants over two weeks. Control (A) sees 5,000 visitors, 150 conversions (3.0%). Variant B sees 5,000 visitors, 185 conversions (3.7%).
- Pooled rate: (150+185) / 10,000 = 3.35%
- SE: sqrt(0.0335 × 0.9665 × (1/5000 + 1/5000)) = 0.00360
- Z-score: (0.037 - 0.030) / 0.00360 ≈ 1.945
- p-value (two-tailed): ≈ 0.052
p > 0.05 — not statistically significant at the 95% level. Collect more data before deciding. The relative uplift is (3.7 - 3.0) / 3.0 = +23.3%, but we cannot yet rule out random variation with this sample size.