Find what slows the experience.
Measure mobile and desktop performance before speed becomes a growth problem, with lab and field evidence kept apart.
The problem this capability addresses
One speed score cannot describe every user experience
The short answer
Alesta records mobile and desktop performance evidence while keeping controlled lab measurements separate from real-user field data. If field data is unavailable, that absence remains visible instead of becoming an estimated result.
Lab tests help reproduce conditions, while field data reflects eligible real-user samples over time. Combining them into one unlabeled number can send a team toward the wrong diagnosis.
Evidence and inputs
- Lab observations
- Controlled mobile and desktop runs expose diagnostic timing, rendering, and resource conditions.
- Field eligibility
- Available public field evidence is recorded separately, including the state where a site or URL has no qualifying sample.
What you can review
- Device-specific view
- Mobile and desktop observations remain distinct so a strong result on one does not hide weakness on the other.
- Evidence-aware diagnosis
- The review identifies observed constraints and labels unavailable field evidence without fabricating it.
A reviewable workflow
- 01
Run the public test
Collect controlled observations for the submitted website on the available device profiles.
- 02
Check evidence state
Separate lab results, field results, and unavailable data before interpreting the page.
- 03
Review likely constraints
Connect rendering, image, font, and script observations to a practical investigation order.
Boundaries and limitations
- Lab is not field data
- A controlled run cannot establish how every production visitor experiences the site.
- Field data can be absent
- CrUX eligibility and sample availability are external conditions, so a missing value must not become an invented score.
How this capability is different
Performance tests delivery, not search coverage
SEO reviews crawl and on-page search signals. Performance focuses on how the public site loads and renders, with measurement types kept explicit.
Questions this page answers
What is the difference between lab and field performance data?
Lab data comes from a controlled test. Field data aggregates eligible real-user experiences. They answer related but different questions.
What happens when field data is unavailable?
Alesta records the evidence as unavailable and keeps the lab observations separate. It does not estimate a field result.
Continue with supporting resources
- Browse implementation guides
Use the guide hub for practical baseline and review workflows.
- Prepare for a domain baseline
Gather the context that helps a performance observation become useful.
- AI marketing audit guide
Place performance evidence inside a wider marketing review.
Choose the next step
Inspect performance with the right evidence label
Start from the domain, compare mobile and desktop observations, and confirm which measurements are lab or field data.