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Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallFaster ecommerce pages are associated with better conversion and revenue outcomes, but there is no universal percentage lift to expect. Results depend on which pages and performance measures improve, the audience and device, and whether the evidence comes from an experiment or an observed correlation. The useful question for a store is not simply whether speed matters, but where delay disrupts its own purchase funnel.
How site speed can affect the ecommerce funnel
A shopper may encounter delays on a product listing, a product detail page, the cart, or checkout. Friction at any of those steps can affect whether people continue, but an overall site-speed score cannot show which step is costing a particular store orders. Measure performance alongside stage-specific actions such as product-page views, add-to-cart activity, and completed purchases.
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Performance measures are not interchangeable. Largest Contentful Paint (LCP) tracks when the main visible content appears; responsiveness and server latency describe different parts of the experience. A result tied to one measure should not be presented as proof that every kind of delay has the same commercial effect.
The Tool Desk
Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →What published studies found—and what their numbers mean
The figures below describe different populations, page changes, metrics, and study designs. Treat them as evidence that performance can matter, not as interchangeable forecasts for another store.
#1 Best Overall
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| Study | Reported result | What was measured | Evidence and limits |
|---|---|---|---|
| Google-commissioned study summarized by web.dev | 8.4% increase in retail conversion rate | Each of four metrics improved by 0.1 seconds on every page across the user journey: First Meaningful Paint, estimated input latency, observed load, and maximum server latency. | Research by 55 and Deloitte covered 37 leading European and American brand sites and more than 30 million user sessions. Mobile load times were monitored hourly for 30 days at the end of 2019. The result does not mean that saving 100 ms on any single page yields an 8.4% sales increase. First Meaningful Paint is now deprecated. |
| Nuvemshop, 2026 | 8.9% relative increase in mobile session-to-paid-order conversion and 8.4% increase in cart engagement | Mobile visitors arriving from Google organic search to a cohort of Brazilian stores active in January 2025 and January 2026. Nuvemshop also reported LCP health rising from 57% to 96%. | A year-over-year cohort comparison, not a controlled test isolating speed as the cause of the conversion difference. |
| Farfetch | 1.3% average conversion-rate decrease per additional 100 ms of LCP beyond 2.5 seconds; separately, an A/B test reported a 1–5% conversion uplift. | The first figure is a company-specific statistical correlation. The separate test followed product-page improvements that shaved more than 600 ms. | Do not combine the correlation with the A/B-test result or generalize either as a forecast. The uplift was reported at Farfetch’s defined confidence level. |
| Rakuten 24 | 33.13% increase in conversion rate and 53.37% increase in revenue per visitor | A high-traffic landing page in a one-month 50/50 A/B test. In a mobile load test, the optimized version loaded 0.4 seconds earlier. | The company reported no functional or visual differences between the versions. These are results from that test, not expected gains for other retailers. |
Why the Google-commissioned 8.4% figure needs its conditions
The retail result in the 2020 web.dev summary applied only when all four measured metrics improved by 0.1 seconds on every page in the journey. The summary states: “Every page across the user journey had to improve each of these metrics by 0.1 seconds in order for these positive impacts to be observed.” It describes a multi-metric, journey-wide change—not a rule that a 100 ms improvement to one page or one metric adds 8.4% to sales.
Why the other results cannot be compared at face value
Nuvemshop’s figures compare the same cohort across two January snapshots, but other changes over a year could also affect outcomes. Farfetch reported both an association between LCP and conversion and a separate A/B-test result; correlation and experiment are different forms of evidence. Rakuten 24’s unusually large reported lift came from one landing-page test. Each number uses its own conversion definition, audience, page scope, and conditions.
Rank #2
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How to find where speed is affecting your store
- Connect field performance to funnel outcomes. Join real-user performance data with analytics at a pageview or session level, then examine outcomes such as progression to product pages, add-to-cart events, and paid orders. Farfetch integrated page-level performance with funnel metrics; Rakuten 24 combined field metrics with internal analytics.
- Break results down by journey stage and audience. Compare mobile and desktop, traffic source, geography, and page type—such as listing, product, cart, or checkout. An aggregate score can conceal a problem that matters only to a particular stage or group.
- Identify the actual LCP element on important layouts. The largest visible element can vary with carousels, banners, transitions, and section order. Nuvemshop found that these layout choices could lead browsers to identify an unexpected element as LCP. Check real pages and templates rather than assuming the same element is responsible everywhere.
- Prioritize visible imagery. Images in the first screen can be delayed if they are lazy-loaded or lack priority signals. Nuvemshop described removing lazy loading from first-screen imagery and adding priority signals; Farfetch described loading critical images early while lazy-loading non-critical images. Apply this selectively: content below the fold can still benefit from lazy loading.
- Set performance budgets for journey pages. Use targets to detect regressions, but judge changes against the user experience and business outcomes for the page concerned. Farfetch described budgets across journey pages, and its findings suggested that metrics could matter differently at different stages.
- Protect price and inventory accuracy when changing caches. Faster delivery is not a win if shoppers see stale pricing or stock information. Pair cache changes with safeguards that keep consequential product data current.
How to evaluate an optimization result
Before treating a performance change as a business result, record what changed and how the outcome was measured. This makes an internal test more useful than importing another retailer’s percentage.
- Performance change: Specify the metric, the size of the change, and the pages affected; do not substitute a general “faster” label for a measured result.
- Audience: Note device, traffic source, and geography.
- Funnel outcome: Define conversion precisely—for example, session-to-paid-order conversion—and state which journey event is being analyzed.
- Evidence type: Label the finding as a correlation, cohort comparison, or controlled experiment. Keep these categories distinct when reporting results.
- Observation window: State the period and whether the comparison spans different seasons or other changes that may affect demand.
These details help a team decide whether an improvement is worth expanding. They also prevent a performance metric from being mistaken for a business outcome: faster rendering is a technical result; more completed orders must be measured separately.
Quick Recap
Rank #4
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Rank #3
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