Flagship diagnostic

HAAM Quality Scan

The Quality Scan is the front door for buyers who know their website is underperforming but do not yet know where the real damage is. It packages a serious diagnostic request around the signals HAAM can actually improve.

Diagnostic intent

Hidden digital quality debt

This public tool is designed to capture a sharper lead, prepare the right review context, and route the visitor toward a credible HAAM audit, sprint, or implementation conversation.

SaaS teams

Useful when the team needs a clearer outside signal before spending more time or budget.

cultural institutions

Useful when the team needs a clearer outside signal before spending more time or budget.

public-facing organizations

Useful when the team needs a clearer outside signal before spending more time or budget.

redesign leads

Useful when the team needs a clearer outside signal before spending more time or budget.

Inputs

What the visitor provides

The tool keeps the intake small enough to complete, but specific enough to support useful follow-up.

  • Website URL
  • Main user journey
  • Business goal
  • Market or language context

Review model

What HAAM should inspect

The first version collects the request. A full backend can attach evidence collection, screenshots, scoring, and reviewer approval behind the same page.

  • Core Web Vitals and mobile performance risk
  • WCAG-facing accessibility issues and obvious blockers
  • Trust cues, consent clarity, proof, contact, and legal surface
  • Page weight, image bloat, JavaScript weight, and third-party scripts
  • AI readability, entity clarity, structured content, and answer-engine fit
  • CTA clarity, form friction, and journey completion risk

Lead magnet output

What the prospect should receive

The goal is not a giant automated report. The goal is a compact, credible artifact that makes the next conversation easier.

  • Prioritized diagnostic brief
  • Recommended audit or sprint scope
  • Buyer-ready PDF outline
  • Start-project prompt prefilled with the right context

Example findings

The language should be specific, conservative, and useful

These examples show the type of signal the tool is meant to surface. Real findings should only be sent after evidence is collected and reviewed.

Example 1

The main conversion journey depends on unclear calls to action across multiple pages.

Example 2

Page weight and script volume are likely weakening mobile trust before the offer is understood.

Example 3

The site does not make its entity, proof, and next step clear enough for AI-mediated discovery.

Conversion path

Route the visitor into a serious project request

The call to action preloads the selected tool into HAAM start flow so the request has context before a conversation begins.

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