How is Performance measured in Jurnii UX

Overview

Jurnii UX measures performance as a relative benchmark across your competitive set, not as a direct reflection of real user (field) experience. The performance category equates to 20% of your Jurnii score.

We’re deliberately transparent about this:

Performance in Jurnii is designed to answer “how do you compare vs your competitors?”, not “what exact experience is every user having?”

Why Jurnii Uses Lab Data (Not Field Data)

Performance data typically comes in two forms:

• Field data (e.g. CrUX / real user metrics)

• Lab data (controlled, simulated testing environments)

Jurnii uses lab data, and this is a structural decision.

The Limitation of Field Data

Field data (such as Chrome UX Report / Origin data) is:

• Aggregated at the domain level

• Not available at page or journey step level

This means:

• You cannot isolate performance for specific flows like Registration or Deposit

• It blends all pages into a single average

Since Jurnii focuses on journey-step-level analysis, field data cannot provide the required level of granularity.

How Jurnii Measures Performance

1. Journey Step-Level Testing

Each step in a journey (e.g. Registration page, Deposit page) is tested individually.

This allows us to:

• Compare like-for-like pages across competitors

• Identify where performance issues exist within key conversion flows

2. Lighthouse-Based Lab Testing

We use Lighthouse in a controlled lab environment to generate performance scores.

Testing conditions are standardised to ensure fairness:

• Mobile testing

  • Device: iPhone 13 Pro (emulated)

  • Network: Simulated Slow 4G

  • CPU: 4× slowdown

• Desktop testing

  • Resolution: 1920×1080

  • Network: Simulated cable connection

  • CPU: Standardised environment

This setup simulates a realistic mid-tier user experience, rather than ideal conditions.

3. Controlled Benchmarking Environment

Every brand in your competitive set is tested under:

• The same environment

• The same throttling conditions

• The same testing window

This is critical.

Even if absolute scores may differ from real-world user data in specific regions or conditions:

The relative performance gap between brands is consistent, fair, and meaningful

Interpreting Performance Scores

Performance scores in Jurnii should be viewed as:

• Comparative, not absolute

• Directional, not exact real-user replication

• Indicative of competitive gaps, not standalone truth

Scores may be more volatile than other categories due to:

• Dynamic content

• Third-party scripts

• Infrastructure variability

That’s expected — and accounted for in how results are interpreted.

Accessibility Considerations

Alongside performance, Jurnii also evaluates accessibility factors, including:

• Colour contrast issues (aligned with WCAG standards)

• Missing or incorrect ARIA labels

• Other usability-impacting accessibility gaps

These are benchmarked in the same way:

• Against your competitors

• Highlighting opportunities to outperform the market

Why This Approach Matters

If we relied purely on field data:

• You’d get accurate averages, but no actionable insight at journey level

By using lab data:

• You get step-level visibility

• You can pinpoint exactly where performance impacts conversion

• You can clearly see where competitors outperform you

Key Takeaway

Jurnii UX performance analysis is built for competitive benchmarking at journey level.

It doesn’t try to replace your existing tools — instead, it complements them by answering a different, more strategic question:

“Where are we slower than our competitors in the moments that actually matter?”