Methodology

How does Awesome.Digital analyze a website?

Awesome.Digital reads public website evidence, applies structured scoring, and uses an operator-reviewed diagnosis to turn the findings into a fix order.

Quick answer

Awesome.Digital combines crawl evidence, technical checks, content analysis, trust and profile signals, conversion-path review, and measurement readiness. The goal is not a longer report; it is a clearer first fix.

The analysis has three layers.

Crawl evidence

The scan inspects pages, metadata, schema, sitemap, robots policy, performance, links, and page-level text structure.

Signal scoring

Findings are organized across technical access, content structure, authority consensus, query coverage, and measurement readiness.

Operator diagnosis

An operator reviews the evidence to identify the real blocker and connect recommendations to a practical action plan.

Six fix lanes keep the diagnosis practical.

What the methodology avoids

  • No fake certainty when integrations or third-party data are missing.
  • No generic template diagnosis when an operator has not reviewed the evidence.
  • No score changes hidden inside narrative recommendations.
  • No recommendation without a reason it matters to discovery, trust, conversion, or measurement.

Start with the live scan.

Run the free preview, save the private growth snapshot, and use the evidence to decide whether a review or diagnostic sprint is worth doing.

Run Free AI Growth Scan →