Product pages do not display size availability upfront, forcing users to click through to select a size and potentially discover their size is unavailable, causing friction and potential abandonment.
CURRENT —
scroll ↕ — this is the live page
⚠ Size availability not shownProduct pages do not display size availability upfront, forcing users to click through to select a size and potentially discover their size is …
RECOMMENDED —
Fix
Evidence
Observed on the live site
✓ Flagged independently by 1 of 7 analysts
On the Anytime Ankle Sock product page, the CTA is 'Get Notified' instead of 'Add to Cart', indicating the product is out of stock, but the page does not show which sizes are unavailable until the user interacts with the size selector. The shop-all page includes a size filter, but individual product pages do not list available sizes in the main content.
Business case
If this change wins
$35,381 – $176,904
annual opportunity if it wins
Medium
Effort — 2-5 days
not testable at current traffic
A/B test duration
Prioritisation
PXL score: 4 / 10
Question
Answer
Points
Is the change above the fold?
No
0
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?
Product pages do not display size availability upfront, forcing users to click through to select a size and potentially discover their size is unavailable, causing friction and potential abandonment.
Current state
h1: Anytime Ankle Sock; cta: Get Notified; notes: No size availability shown on the product page; users must click to see sizes and may find their size is not available.
Change
h1: Anytime Ankle Sock; cta: Add to Cart; notes: Display available sizes and stock status directly on the product page, e.g., 'Sizes: S, M, L' or 'Out of stock' to reduce friction.
Acceptance criteria
GIVEN a first-time visitor on the affected page
WHEN the change is live
THEN Display available sizes and stock status directly on the product page, e.g., 'Sizes: S, M, L' or 'Out of stock' to reduce friction,
with no regression at 375px and 1280px widths.
Tracking
event: cro_size_availability_not_shown 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
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.