---
title: "Google's own data: Rakuten and Vodafone Core Web Vitals A/B tests"
url: https://seomadman.com/studies/rakuten-vodafone-core-web-vitals-case-studies
section: studies
published: 2026-08-17T00:00:00.000Z
modified: 2026-08-17T00:00:00.000Z
author: Adam Hafez
topics: ["Technical SEO"]
---

# Google's own data: Rakuten and Vodafone Core Web Vitals A/B tests

## The short answer

Google's web.dev case study library documents two named, dated A/B tests. Rakuten 24 ran a month-long 50/50 split test and measured 53.37% more revenue per visitor and 33.13% higher conversion on the performance-optimized page. Vodafone Italy cut LCP 31% by moving a widget's rendering server-side and resizing its hero image, and measured 8% more sales.

## Key takeaways

- Rakuten 24 ran a month-long 50/50 A/B test and measured 53.37% more revenue per visitor and 33.13% higher conversion on the optimized version.
- Vodafone Italy's optimized page improved Largest Contentful Paint by 31% and measured 8% more total sales, plus gains in lead-to-visit and cart-to-visit rate.
- Vodafone's named changes were server-side rendering a widget and critical HTML, plus resizing, compressing and lazy-loading the hero image.
- Both tests split real production traffic 50/50 rather than comparing before-and-after periods, controlling for seasonality and traffic-mix shifts.
- Google selected and published both cases as examples of the pattern it wants publicised, so neither figure is a guaranteed or average effect size for every site.

Google runs a small library of named, dated case studies at web.dev/case-studies, each attached to
a real company and a real test. Two of them isolate Core Web Vitals specifically: Rakuten 24, a
Japanese e-commerce retailer, and Vodafone Italy. Unlike Deloitte's 37-site correlation study or
Shopify's aggregate LCP data covered on this site's [page speed and conversion rate
piece](/studies/page-speed-conversion-rate-impact/), these two are single-company A/B tests that
Google itself ran or reviewed and published under its own byline. Here is what each one actually
tested, in Google's own words.

## Rakuten 24: a month-long split test on one landing page

**The setup.** Rakuten's team picked a landing page with "significant traffic and conversion" so
the test could produce a meaningful sample, then split traffic 50/50 for a month: half of visitors
saw the original page (version B), half saw a performance-optimized version (version A) that was
otherwise unchanged. The write-up, credited to four named Rakuten and Google engineers and last
updated 24 August 2022, reports the optimized version's results relative to the original.

**The business numbers.** Version A delivered a 53.37% increase in revenue per visitor and a
33.13% increase in conversion rate, alongside a 15.20% increase in average order value, a 35.12%
reduction in exit rate, and a 9.99% increase in time on page.

**The performance numbers behind it.** The same optimized version cut Cumulative Layout Shift by
92.72%, improved First Input Delay by 7.95%, First Contentful Paint by 8.45%, and Time to First
Byte by 18.03%, relative to the unoptimized version. Separately, Rakuten also ran a field-data
correlation analysis (not the A/B test) across its real user population and found good LCP
associated with up to 61.13% higher conversion and 26.09% higher revenue per visitor, a wider,
noisier number that supports the same direction without being the headline A/B result.

## Vodafone Italy: three specific changes, an 8% sales lift

**The setup.** Vodafone's optimized and original pages ran as a 50/50 A/B split too, each getting
roughly 100,000 clicks and 34,000 visits a day from paid display, search, social and app traffic,
"visually and functionally identical" apart from the performance changes. Google published this
one on 17 March 2021.

**What actually changed.** Google names three changes, not a general "made it faster" claim:
moving the rendering logic for one widget from client-side to server-side, server-side rendering
the critical HTML, and hero-image work (resizing, SVG optimization, PNG compression and
viewport-based lazy loading for below-the-fold images).

**The result.** The optimized version improved Largest Contentful Paint by 31% and produced 8%
more total sales, plus a 15% uplift in lead-to-visit rate and an 11% uplift in cart-to-visit rate.
One honest wrinkle Google's own page reports: DOMContentLoaded actually increased 15% on the
optimized version even as LCP improved, a reminder that one metric moving well does not mean every
metric moves the same way.

## Why we care

**These are Google's own selected success stories, not a random sample.** Google chose to publish
Rakuten 24 and Vodafone Italy specifically because the numbers were good enough to make the point
Google wants to make: Core Web Vitals work pays off in revenue, not just rankings. That is a
legitimate reason to take Core Web Vitals seriously, and a bad reason to promise a client 53% more
revenue from a similar change; Rakuten's own field data on the same site showed a much wider range
of outcomes than its single A/B test headline.

**An A/B test beats a before/after comparison, which is why these numbers travel further than
Deloitte's or Shopify's.** Splitting live traffic 50/50 for the same weeks controls for
seasonality, marketing pushes and traffic-mix shifts that a simple before-and-after read cannot;
that is a stronger methodology than the correlational studies in our companion piece on [page speed
and conversion rate](/studies/page-speed-conversion-rate-impact/), even though the two named cases
here cover only two companies rather than dozens.

**Cite the company and the exact change, not just the percentage.** "31% faster, 8% more sales" is
Vodafone Italy's number for three named technical changes on one page in 2021. "53% more revenue
per visitor" is Rakuten 24's number for one landing page over one month. Neither is a general Core
Web Vitals multiplier; both are useful, specific, sourced evidence that the work matters.

## Frequently asked questions

### Were these controlled tests or just before-and-after comparisons?

Both were A/B tests. Rakuten 24 split traffic 50/50 between an optimized landing page and the original for one month. Vodafone Italy also ran a 50/50 split, serving roughly 100,000 clicks and 34,000 visits a day to each version, with the two pages "visually and functionally identical" apart from the performance work.

### What exactly did Vodafone change to cut LCP by 31%?

Per Google's write-up, three changes, moving the rendering logic for one widget from client-side to server-side, server-side rendering the critical HTML, and image work - resizing the hero image, optimizing SVGs, compressing PNGs and lazy-loading below-the-fold images by viewport.

### Do these figures apply to any site that improves Core Web Vitals?

No. Google chose these two cases to publish as success stories; it does not claim they represent a typical or average effect size. Rakuten 24's own field-data analysis (separate from its A/B test) found good LCP correlated with up to 61.13% higher conversion on some segments and lower gains on others, which is itself a sign the multiplier varies by site and traffic mix.

## Sources

1. [Rakuten 24 case study](https://web.dev/case-studies/rakuten) - Google web.dev (primary)
2. [Vodafone case study](https://web.dev/case-studies/vodafone) - Google web.dev (primary)