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A/B Testing Core Web Vital (Per-User) Calculator

Estimate the per-user Core Web Vital improvement from an A/B test and its potential time, conversion, and revenue impact.

Your Details

Overview

Use this A/B Testing Core Web Vital calculator to compare a control and variant on a per-user basis. Enter the measured Core Web Vital values, variant traffic, conversion rates, and value per conversion to estimate performance improvement and potential test-period impact.

How it works

The calculator subtracts the variant metric from the control metric to find the per-user change. It then multiplies that difference by the number of variant users to estimate the aggregate time reduction. Conversion lift is calculated from the difference between the two conversion rates relative to the control rate. Estimated incremental value equals the estimated additional conversions among variant users multiplied by the value per conversion.

How to use this calculator

  1. 1Choose the Core Web Vital measured in your experiment.
  2. 2Enter the average control and variant metric values using the same data source.
  3. 3Add the number of users exposed to the variant.
  4. 4Enter the observed conversion rates for control and variant.
  5. 5Add an average value per conversion if you want an estimated commercial impact.
  6. 6Review the per-user improvement alongside the conversion and value estimates.

Example Calculation

Core Web Vital

lcp

Users exposed to variant

10000

Control metric value

3000

Variant metric value

2400

Control conversion rate

3%

Variant conversion rate

3%

Value per conversion

$50

Per-user metric improvement

+600 ms

Reducing LCP from 3,000 ms to 2,400 ms saves an estimated 600 ms per variant user. Across 10,000 users, that is about 6,000 seconds of aggregate time saved; the conversion difference represents about 20 additional conversions and $1,000 in estimated value.

Frequently asked questions

What is a per-user Core Web Vital improvement?

It is the difference between the average metric value for one user in the control and one user in the variant. For LCP and INP, a positive result means the variant is faster.

Which Core Web Vitals can I compare with this calculator?

You can use it for LCP, INP, or CLS, provided both test groups use the same measurement method and time period.

How should I enter CLS values?

For consistency with the millisecond-style input, multiply the CLS score by 1,000. For example, enter 120 for a CLS value of 0.120 in both control and variant fields.

Does a better Core Web Vital always increase conversions?

Not necessarily. Faster or more stable experiences may help users, but conversion results also depend on audience, test design, page content, pricing, and many other factors.

What does total user time saved mean?

It is the per-user reduction in the entered metric multiplied by the number of users exposed to the variant. It is an aggregate estimate, not the amount of time each individual necessarily notices.

Should I use lab data or field data?

Either can be useful, but compare like with like. Field data reflects real users, while lab data is controlled and may be more useful for diagnosing implementation changes.

Is the estimated incremental value a forecast?

It is a simple estimate based on the observed conversion-rate difference, variant user count, and value per conversion. It should not be treated as a guaranteed future outcome.

Explore Related Calculators

A/B Testing Sample Size CalculatorEstimate the number of visitors each variation needs to detect a meaningful change in conversion rate with your chosen confidence and statistical power.Calculate →A/B Testing Sample Size (Monthly) CalculatorEstimate the visitors needed for an A/B test and how many months of traffic you may need to detect a meaningful conversion-rate change.Calculate →A/B Testing Sample Size (Annual) CalculatorEstimate the visitor sample and annual traffic needed to run an A/B test with a chosen conversion rate, detectable lift, confidence level and power.Calculate →A/B Testing Statistical Significance CalculatorCompare two conversion rates and estimate whether the difference is statistically significant at a chosen confidence threshold.Calculate →

Assumptions and warnings

Assumptions

  • Control and variant metric values were collected using the same Core Web Vital definition, device mix, and measurement method.
  • Lower metric values represent a better experience for LCP and INP; CLS values should be entered on a consistent scaled basis.
  • All users exposed to the variant are treated as having the same average per-user metric change.
  • Estimated conversion value uses the value per conversion you enter and does not include costs, refunds, or other business effects.
  • Results describe the measured test period and may not represent future traffic or user behavior.

Warnings

  • A/B test differences should be checked for statistical significance before being treated as reliable.
  • This calculator provides estimates only; changes in conversion or revenue can have causes other than Core Web Vital performance.