Marketing Calculators
A/B Test Calculator
Run a two-proportion z-test on A/B test results to check statistical significance, with a worked example and standard critical z-values by confidence level.
Bounce Rate Calculator
Calculate website bounce rate or email bounce rate with the correct formula for each mode, plus worked examples showing how the two metrics differ.
Conversion Lift Calculator
Calculate conversion lift between a test group and a control group, with worked examples showing how relative lift is derived from each group's conversion rate.
Customer Churn Calculator
Calculate customer churn rate and retention rate from starting customer count and customers lost, with worked examples across three different loss levels.
Customer Lifetime Value (CLV) Calculator
Project customer lifetime value from average purchase value, purchase frequency, and customer lifespan, with worked examples across different buying patterns.
Customer Retention Calculator
Calculate customer retention rate from starting customers, ending customers, and new customers acquired, isolating how many original customers actually stayed.
Email Click Rate Calculator
Calculate email click-through rate (CTR) and click-to-open rate (CTOR) with separate formulas and worked examples showing exactly how the two rates differ.
Email Open Rate Calculator
Calculate email open rate from emails opened and emails delivered, with worked examples and notes on how tracking-pixel blocking affects the number.
Email ROI Calculator
Calculate email campaign ROI from revenue and campaign cost, with worked examples showing how low send costs shape email's return relative to other channels.
LTV:CAC Ratio Calculator
Calculate the LTV to CAC ratio and see where it falls against standard thresholds for unhealthy, below-target, healthy, and very-high acquisition economics.
Marketing ROI Calculator
Calculate marketing ROI from revenue and campaign cost, with worked examples showing how the profit-to-cost ratio translates into a percentage return.
Turning Campaign Data Into a Decision
Marketing generates a constant stream of metrics — open rates, bounce rates, churn, lift — and the hard part is rarely calculating them, it's knowing which ones actually indicate a decision worth making. These calculators run the standard formulas behind marketing performance metrics, including the statistical significance testing that separates a real A/B test result from noise.
Popular Marketing Calculators
Eleven tools span campaign metrics, retention, and testing:
- Marketing ROI Calculator — measures return generated per dollar of marketing spend.
- LTV:CAC Ratio Calculator — compares customer lifetime value against acquisition cost, a core health metric for growth spend.
- A/B Test Calculator — checks whether a test result is statistically significant given sample size and observed difference.
- Customer Churn Calculator — measures the rate at which customers stop purchasing or using a service.
- Email Open Rate Calculator — calculates the percentage of sent emails that were opened for a given campaign.
Why a "Winning" A/B Test Can Still Be a False Positive
A test showing one variant outperforming another isn't automatically meaningful — statistical significance depends on sample size as much as the size of the difference observed, and a small sample can easily show an apparent 20% lift that's really just random variation. This is exactly why A/B test calculators check for statistical significance rather than just comparing raw conversion numbers, and why ending a test the moment it first shows a "significant" result (rather than at a pre-determined sample size) is a well-documented way to draw false conclusions from what's actually still noise.
Frequently Asked Questions
What's considered a healthy LTV:CAC ratio?
3:1 or higher is a commonly cited benchmark, meaning a customer generates at least three times what it cost to acquire them over their lifetime.
Why do email open rates vary so much depending on where they're measured?
Open rate tracking relies on a tracking pixel loading, which privacy features in some email clients (like Apple Mail Privacy Protection) can trigger automatically regardless of whether a human actually opened the email, inflating measured open rates.
Explore More
Running paid ad campaigns too? See the Advertising Calculators, or check broader business metrics in the Business Calculators.