The homepage hero promotes 'Wildly Comfortable. Super Natural.' without mentioning the $100 free shipping threshold, which is only disclosed in the top announcement bar and cart drawer, creating an expectation gap.
CURRENT — Hero missing shipping threshold
⚠ Free shipping threshold hiddenThe hero headline 'Wildly Comfortable. Super Natural.' does not mention the $100 free shipping threshold, which is only disclosed in the announcement …
RECOMMENDED — Hero shows free shipping threshold
Add shipping threshold to hero
FixInserting the free shipping threshold directly after the hero headline makes the offer immediately visible, aligning expectations with the actual policy.
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
Hero H1: 'Wildly Comfortable. Super Natural.'; body_sample includes 'Free ground shipping on orders over $100' and cart drawer text 'Spend more to earn free shipping! Shipping $5.00'.
Business case
If this change wins
$35,381 – $176,904
annual opportunity if it wins
Low
Effort — 0.5-2 days
not testable at current traffic
A/B test duration
Prioritisation
PXL score: 5 / 10
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
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 homepage hero promotes 'Wildly Comfortable. Super Natural.' without mentioning the $100 free shipping threshold, which is only disclosed in the top announcement bar and cart drawer, creating an expectation gap.
Current state
h1: Wildly Comfortable. Super Natural.; cta: SHOP MEN / SHOP WOMEN; notes: No mention of shipping threshold or costs in hero area.
Change
h1: Wildly Comfortable. Super Natural. Free Shipping Over $100; cta: SHOP MEN / SHOP WOMEN; notes: Add a subheadline or badge clarifying free shipping threshold to set expectations early.
Acceptance criteria
GIVEN a first-time visitor on the affected page
WHEN the change is live
THEN Add a subheadline or badge clarifying free shipping threshold to set expectations early,
with no regression at 375px and 1280px widths.
Tracking
event: cro_free_shipping_threshold_hidden 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
Low —
0.5-2 days
Test plan
299,882 visitors per variant
(95% significance, 80% power);
not testable at current traffic.
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 1.0-5.0% relative lift x $78 order value
The 1.0–5.0% relative-lift band is an assumption bounded by severity (High), 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, 5.0% lift
299,882
Sample per variant, 1.0% lift
7,353,946
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.