The homepage email signup form asks only for an email address, which is the minimum viable field set, but the lack of a trust layer (e.g., privacy note, incentive) may reduce opt-in rates.
CURRENT —
scroll ↕ — this is the live page
⚠ Single-field email captureThe homepage email signup form asks only for an email address, which is the minimum viable field set, but the lack of a trust layer (e.g., privacy …
RECOMMENDED —
Fix
Evidence
Observed on the live site
✓ Flagged independently by 1 of 7 analysts
The homepage has a form with 1 input, no labels, and submit button 'Sign Up'. The body sample shows 'Subscribe to our emails Sign Up'.
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: 3 / 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?
No
0
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 email signup form asks only for an email address, which is the minimum viable field set, but the lack of a trust layer (e.g., privacy note, incentive) may reduce opt-in rates.
Current state
h1: Wildly Comfortable. Super Natural.; cta: Sign Up; notes: Single email field, no visible privacy policy link or incentive (e.g., discount) near the form.
Change
h1: Wildly Comfortable. Super Natural.; cta: Sign Up for 10% Off; notes: Add a privacy note ('We respect your inbox') and a clear incentive (e.g., 'Get 10% off your first order') to increase signup conversion.
Acceptance criteria
GIVEN a first-time visitor on the affected page
WHEN the change is live
THEN Add a privacy note ('We respect your inbox') and a clear incentive (e.g., 'Get 10% off your first order') to increase signup conversion,
with no regression at 375px and 1280px widths.
Tracking
event: cro_single_field_email_capture 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.