The article page displays multiple H1s, creating a rotating hero effect that confuses the primary topic and dilutes the article's focus, undermining the visitor's expectation of a single clear story.
CURRENT — Multiple H1s
⚠ Rotating hero headlinesThe page displays multiple H1s in a rotating hero, confusing the primary topic.
RECOMMENDED — Single H1 Focus
Add focus label
FixAdd a label emphasizing a single story focus to demonstrate the recommendation.
Both are photographs of the live page — the right side has the
change applied in the browser.
Evidence
Observed on the live site
✓ Flagged independently by 1 of 7 analysts
H1s: ['J.J. McCarthy to miss Broncos game, reportedly ‘not comfortable’ after injury', 'Raiders still not ready to name starting quarterback after final preseason game', 'NFL Preseason Blitz: Falcons QB Tua Tagovailoa booed in Miami return, but shows a little improvement']
The page shows three H1s, likely from a carousel or related stories, which can confuse users about the main article.
Business case
If this change wins
0.2 – 1.0
orders per 1,000 visitors
Low
Effort — 0.5-2 days
Not A/B testable
At typical traffic
Detecting this needs about 315,206 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?
Yes
1
Verified by direct technical measurement?
No
0
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?
The article page displays multiple H1s, creating a rotating hero effect that confuses the primary topic and dilutes the article's focus, undermining the visitor's expectation of a single clear story.
Current state
h1: Multiple H1s (three headlines); cta: Sign in / Watch / Schedule / Get Fantasy Plus / Watch on X; notes: The page shows three H1s, likely from a carousel or related stories, which can confuse users about the main article.
Change
h1: J.J. McCarthy to miss Broncos game, reportedly ‘not comfortable’ after injury; cta: Read the full story; notes: Ensure only one H1 is present, matching the article's title, and remove or demote other headlines to H2s to maintain clarity and focus.
Acceptance criteria
GIVEN a first-time visitor on the affected page
WHEN the change is live
THEN Ensure only one H1 is present, matching the article's title, and remove or demote other headlines to H2s to maintain clarity and focus,
with no regression at 375px and 1280px widths.
Tracking
event: cro_rotating_hero_headlines on interaction with the
changed element; verify it fires in BOTH variants before opening traffic.
Success metric
organic sessions for the affected pages
QA checklist
Chrome / Safari / Firefox · 375px + 1280px ·
keyboard reachable · screen-reader name present · no CLS introduced
Effort
Low —
0.5-2 days
Test plan
315,206 visitors per variant
(95% significance, 80% power);
duration depends on traffic.
Rollback
Feature-flag the change; revert the flag if the primary metric
drops for 3 consecutive days.
1,000 visitors × baseline conversion × relative lift
= per 1,000 visitors at an assumed 2.00% baseline conversion rate and a 1.0-5.0% relative lift
The 1.0–5.0% relative-lift band is an assumption bounded by severity (High), 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, 5.0% lift
315,206
Sample per variant, 1.0% lift
7,729,571
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.