About

Conversion Rate (CVR) quantifies the fraction of visitors who complete a desired action. A miscalculated CVR leads to flawed budget allocation: you either overspend on underperforming channels or starve high-performers of capital. The formula is deceptively simple - CVR = (C ÷ V) × 100 - yet errors compound when comparing variants or projecting required traffic. This tool computes CVR, Revenue Per Visitor (RPV), and Cost Per Conversion (CPC) with zero rounding drift. It also runs a pooled-proportion z-test for A/B comparisons so you avoid calling winners on noise.

Limitations: the calculator assumes independent visitor sessions and does not adjust for returning-user overlap or multi-touch attribution. For campaigns with conversion windows exceeding 30 days, delayed conversions will understate your true CVR. Pro tip: always segment by traffic source before drawing conclusions from aggregate rates.

Formulas

The primary conversion rate equation:

CVR = CV × 100

Where C = number of conversions and V = total number of visitors.

Revenue Per Visitor:

RPV = RV

Where R = total revenue generated from those visitors.

Cost Per Conversion:

CPC = SC

Where S = total campaign spend.

For A/B testing, the pooled-proportion z-test statistic:

z = p_A − p_B√p_pool⋅(1 − p_pool)⋅(1n_A + 1n_B)

Where p_pool = (C_A + C_B) ÷ (n_A + n_B). A |z| ≥ 1.96 indicates statistical significance at α = 0.05.

Reverse calculator (visitors needed for target CVR):

V_needed = CCVR_target ÷ 100

Reference Data

Industry	Channel	Median CVR (%)	Top 25% CVR (%)	Bottom 25% CVR (%)
E-commerce (General)	Organic Search	2.5	4.3	1.1
E-commerce (General)	Paid Search	1.8	3.6	0.7
E-commerce (General)	Social Media	1.2	2.4	0.5
E-commerce (General)	Email	4.2	7.8	1.9
SaaS	Free Trial → Paid	6.0	12.0	2.5
SaaS	Landing Page	3.0	7.1	1.2
Finance	Organic Search	3.1	5.5	1.4
Finance	Paid Search	2.4	4.8	0.9
Healthcare	Organic Search	3.4	5.8	1.6
Healthcare	Paid Search	2.8	4.5	1.0
Education	Landing Page	2.8	5.6	1.0
Real Estate	Organic Search	1.7	3.2	0.6
Travel	Paid Search	2.1	4.0	0.8
Travel	Email	3.7	6.5	1.5
B2B Services	Organic Search	2.2	4.7	0.9
B2B Services	LinkedIn Ads	2.7	5.2	1.1
Legal	Paid Search	3.3	6.1	1.3
Non-profit	Email	5.0	9.0	2.0
Automotive	Paid Search	1.5	3.0	0.5
Media & Publishing	Organic Search	1.0	2.2	0.3

Frequently Asked Questions

Conversion attribution windows cause discrepancies. A visitor arriving on day 28 who converts on day 32 appears in the monthly cohort but not in the weekly one. Aggregate monthly CVR also smooths out weekday/weekend variance. For accurate comparison, always use the same time window and ensure your analytics platform's attribution window matches your conversion cycle length.

The minimum sample depends on your expected CVR. For a true rate around 2%, you need roughly 9,604 visitors to achieve a 95% confidence interval of ±0.28 percentage points (using the formula n = z² × p × (1−p) / E² with z = 1.96 and E = 0.0028). Lower expected CVRs require larger samples. Below 500 visitors, any observed rate is essentially noise.

Branded search traffic typically converts at 3-5× the rate of display ad traffic because user intent differs fundamentally. Blending all sources into one CVR masks channel performance. A falling aggregate CVR might actually reflect increased top-of-funnel spend (more cold traffic) rather than a worsening user experience. Always segment by source before optimizing.

RPV equals CVR × Average Order Value (AOV) divided by 100. Two campaigns can have identical CVRs but wildly different RPVs if AOV differs. A campaign with CVR = 1.5% and AOV = $200 yields RPV = $3.00, outperforming one with CVR = 3.0% and AOV = $40 (RPV = $1.20). RPV is the superior metric for budget allocation decisions.

The pooled-proportion z-test assumes independent Bernoulli trials. It breaks down when: (1) the same user appears in both variants (contaminated split), (2) conversions are not binary (e.g., multiple purchases per session), or (3) sample sizes are very small (n < 30 per variant), where Fisher's exact test is more appropriate. It also does not account for sequential testing - if you peek at results daily, use a sequential testing correction to control false-positive inflation.

Google's 2017 study of 11 million mobile pages found that as load time increases from 1 to 3 seconds, bounce probability rises 32%. Portent's 2019 analysis showed each additional second of load time reduces CVR by an average of 4.42%. A page loading in 2 seconds has roughly 2× the CVR of one loading in 5 seconds, all else equal. Measure Core Web Vitals alongside CVR to isolate UX friction from offer weakness.