The navigation provides direct links to external Yahoo properties (Finance, Sports, Mail) that bypass the homepage funnel, allowing users to leave the primary conversion path without engaging with the main content.


| 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 |
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? | No | 0 |
Result: 0.2 – 1.0 extra orders per 1,000 visitors
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.
| 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.
Two-proportion z-test, the standard pre-test sample-size calculation:
| 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.
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.
The full rubric is on the method page.