Lab LCP on /en-us/news is 12.2s, far above the 2.5s good threshold, causing most mobile visitors to bounce before content appears.
CURRENT — 12
scroll ↕ — this is the live page
⚠ LCP 12.2s on newsThe page's largest content element, the news headline, takes 12.2 seconds to paint on a mid-range phone. This is far above the 2.5-second 'good' …
✓ Fast loadMain content appears in under 2.5s on mobile.
FixOptimize the critical rendering path by deferring non-critical JavaScript and inlining essential CSS. Preload the hero image and use modern formats like WebP with proper dimensions. Implement lazy loading for below-the-fold content to prioritize the main headline. These changes should bring LCP under 2.5 seconds, keeping visitors engaged.
Evidence
Observed on the live site Verified by measurement
✓ Flagged independently by 1 of 7 analysts
Lighthouse (mobile emulation, single synthetic run via DataForSEO): Largest Contentful Paint 12.2 s against a ‘good’ threshold of 2500ms. Lab data, not real-user field data — confirms the defect class, not the field percentile.
Business case
If this change wins
0 – 0
orders per 1,000 visitors
Medium
Effort — 2-5 days
Not A/B testable
At typical traffic
Detecting this needs about 124,891 visitors per variant. Ship it as a sequenced change and log the date instead.
Prioritisation
PXL score: 5 / 10
Assessed from the live page
Question
Answer
Points
Is the change above the fold?
Yes
1
Is the change noticeable in under 5 seconds?
Yes
2
Does it add or remove an element?
Yes
1
Does it run on a high-traffic page?
No
0
Verified by direct technical measurement?
Yes
1
Criteria that need your data
4 of these could not be answered from the live page.
Session recordings, survey or support themes, and analytics access would
raise the confidence of this ranking — they do not indicate a weaker
finding.
Question
Answer
Points
Discovered via user testing?
No
0
Discovered via qualitative feedback (survey, support)?
No
0
Supported by heatmaps or session recordings?
No
0
Found via digital analytics or real-user field data?
Lab LCP on /en-us/news is 12.2s, far above the 2.5s good threshold, causing most mobile visitors to bounce before content appears.
Current state
notes: Largest Contentful Paint 12.2 s (lab, mobile on /en-us/news)
Change
notes: Largest Contentful Paint ≤ 2500ms (good)
Acceptance criteria
GIVEN a first-time visitor on the affected page
WHEN the change is live
THEN Largest Contentful Paint ≤ 2500ms (good),
with no regression at 375px and 1280px widths.
Tracking
event: cro_lcp_12_2s_on_news on interaction with the
changed element; verify it fires in BOTH variants before opening traffic.
Success metric
conversion rate on the affected step
QA checklist
Chrome / Safari / Firefox · 375px + 1280px ·
keyboard reachable · screen-reader name present · no CLS introduced
Effort
Medium —
2-5 days
Test plan
124,891 visitors per variant
(95% significance, 80% power);
37 days.
Rollback
Feature-flag the change; revert the flag if the primary metric
drops for 3 consecutive days.
1,000 visitors × baseline conversion × relative lift
= 2,448,000 annual visits to this page (measured organic traffic) x 2.00% conversion x 2.0-8.0% relative lift. Supply an average order value to state this in money.
The 2.0–8.0% relative-lift band is an assumption bounded by severity (Urgent), not a prediction.
The baseline conversion rate is an assumption — the client did not supply one, so an industry-typical 2.0% is used and labelled as such.
Why the range is conservative: Across 127,000 experiments, 12% produced a statistically significant improvement on the primary metric; a healthy programme win rate is 10-30%. Winning tests also overstate their true effect, so treat this as the prize if the change works — never expected revenue.
How effort is estimated
Bracket
Days
Typical scope
Low
0.5–2
copy, colour, labels, image swaps
Medium
2–5
layout shifts, form changes, new modules
High
5+
personalisation, funnel work, integrations
Assigned by matching the recommended change against these scopes; the estimate is a bracket, not a quote.
Sample size math
Two-proportion z-test, the standard pre-test sample-size calculation:
n = [z₀.₀₂₅·√(2·p̄·(1−p̄)) + z₀.₂₀·√(p₁(1−p₁)+p₂(1−p₂))]² / (p₁−p₂)²
Baseline conversion
2.0% (assumed)
Significance / power
95% / 80%
Sample per variant, 8.0% lift
124,891
Sample per variant, 2.0% lift
1,941,808
Halving the minimum detectable effect roughly quadruples the sample required, which is why the conservative figure is so much larger.
What PXL is
PXL is CXL's prioritisation framework: binary questions instead of subjective 1–10 guesses, weighted toward evidence.
Findings discovered by inspection score zero on all four evidence questions — that is the honest signal, not a defect. Findings verified by direct measurement earn the extension point and, where real-user field data is involved, the analytics point.