The prominent shipping delay notice creates immediate purchase anxiety, undermining the hero's comfort message and increasing cart abandonment.
Current state
h1: Wildly Comfortable. Super Natural.; cta: SHOP MEN / SHOP WOMEN; notes: Delay notice appears in top bar, above the hero, without any mitigating trust element.
Change
h1: Wildly Comfortable. Super Natural.; cta: SHOP MEN / SHOP WOMEN; notes: Soften the delay with a reassurance line: 'Free shipping & 30-day returns' or 'Orders ship within 30 days – free returns if not perfect.'
Acceptance criteria
GIVEN a first-time visitor on the affected page
WHEN the change is live
THEN Soften the delay with a reassurance line: 'Free shipping & 30-day returns' or 'Orders ship within 30 days – free returns if not perfect.',
with no regression at 375px and 1280px widths.
Tracking
event: cro_shipping_delay_warning 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
118,817 visitors per variant
(95% significance, 80% power);
40 days.
Rollback
Feature-flag the change; revert the flag if the primary metric
drops for 3 consecutive days.
annual visits × baseline conversion × relative lift × order value
= 2,160,000 annual visits x 2.10% conversion x 2.0-8.0% relative lift x $78 order value
The 2.0–8.0% relative-lift band is an assumption bounded by severity (Urgent), not a prediction.
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
2.1%
Significance / power
95% / 80%
Sample per variant, 8.0% lift
118,817
Sample per variant, 2.0% lift
1,847,435
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.