# /Digital-marketing-pro:landing-page-audit Human Guide

## What This Is For
Audit a landing page across six conversion dimensions — above-fold clarity, trust signals, form friction, message match against the upstream ad or email, page speed, and mobile experience. It gives the agent a clearer input/output frame for conversion optimization: what context to ask for, what decisions to make, and what usable artifact to return.

Use this as a human-readable version of the /Digital-marketing-pro:landing-page-audit agent skill. It is meant for marketers, operators, founders, and other non-coders who want the workflow without reading agent-specific implementation instructions.

## When To Use This
- Use this when you need a repeatable process for /digital-marketing-pro:landing-page-audit.
- Use this when the task needs judgment, examples, constraints, or a clear output format rather than a one-off prompt.
- Use this when you want to hand an AI assistant enough context to produce a usable marketing artifact.

## When Not To Use This
- Do not use this when you only need a quick factual answer.
- Do not use this when the work depends on private data you cannot share with the assistant.
- Do not use this as a replacement for legal, compliance, financial, or medical review.

## What You Need Before Starting
- The goal or business outcome you want.
- The audience, customer segment, or market context.
- Any source material the assistant should respect, such as notes, briefs, examples, URLs, or brand guidance.
- Constraints such as tone, length, channel, deadline, region, or approval requirements.
- A clear definition of what a good final answer should look like.

## Step-By-Step Workflow
1. State the job clearly: "Use the /Digital-marketing-pro:landing-page-audit guide to help me with..."
2. Add context: audience, goal, offer, channel, source material, and constraints.
3. Ask the assistant to identify missing inputs before producing the final output.
4. Have the assistant follow the skill-specific guidance below.
5. Review the result against the final checklist and ask for revisions where needed.

## Skill-Specific Guidance
- **Landing page URL**: The page to audit
- **Traffic source**: Where visitors come from (paid search, social ads, email, organic)
- **Target action**: Desired conversion (form submit, purchase, signup, download, call)
- **Ad copy or email**: The upstream message driving traffic (for message match analysis)
- **Current conversion rate**: If known, for benchmarking
- **Above-fold clarity** (score 1-10): Headline clarity, value proposition, visual hierarchy, CTA visibility within first viewport
- **Trust signals** (score 1-10): Social proof, testimonials, logos, security badges, guarantees, reviews
- **Form friction** (score 1-10): Number of fields, field labels, error handling, progressive disclosure, mobile form UX
- **Message match** (score 1-10): Alignment between traffic source (ad/email) and landing page headline, imagery, offer
- **Page speed** (score 1-10): Load time, Core Web Vitals, render-blocking resources, image optimization
- **Mobile experience** (score 1-10): Responsive design, tap targets, scroll depth, mobile-specific CTAs
- Calculate overall score and benchmark against industry averages

## Decision Points And Nuance
The original skill emphasizes: Purpose, Input Required, Process, Output, Agents Used, Supporting file: skills/context-engine/compliance-rules.md, Section 1: Geographic Privacy Laws, 1.1 EU/EEA — General Data Protection Regulation (GDPR), 1.1b EU/EEA — AI Act Article 50 (Generative AI Disclosure), 1.1b.i — Article 50 implementing guidelines (FINAL, 2026).

Use these questions to steer the work:
- What is the intended audience or buyer?
- What source material must be preserved?
- What should the assistant optimize for: clarity, persuasion, accuracy, speed, creativity, or conversion?
- What examples represent the desired quality bar?
- What should the assistant avoid?

## Common Mistakes
- The user must provide (or will be prompted for):
- | **Penalty Range** | Up to EUR 20 million or 4% of global annual turnover, whichever is higher. Supervisory authorities may also issue warnings, bans on processing, and orders to erase data. |
- **Treat the carve-out as conditional, not a free pass.** "Human-reviewed" requires named accountability. Don't claim editorial responsibility unless a named editor is willing to be on the record.
- | **Consent Model** | Opt-out. No prior consent required to send commercial email. Recipients must be given a clear way to opt out, and opt-out requests must be honored within 10 business days. |
- | **Consent Model** | Opt-out for sale/sharing of personal information. Opt-in required for consumers under 16 (under 13 requires parental consent). "Sharing" includes cross-context behavioral advertising. |
- | **Consent Model** | Opt-in. Consent must be free, informed, and unambiguous for a specific purpose. Legitimate interest is available as an alternative basis but requires a Legitimate Interest Assessment (LIA). |
- | **Penalty Range** | Up to 2% of revenue in Brazil, capped at BRL 50 million (~USD 10 million) per violation. ANPD may also issue warnings, publicize violations, and block or delete data. |
- | **Email Rules** | Specified Electronic Mail Act: opt-in required for commercial email. Sender ID and unsubscribe required. APPI requires specifying the purpose of use at collection. |

## Copy-And-Paste Prompt
```text
Use the /Digital-marketing-pro:landing-page-audit human guide.

My goal:
[Describe the business outcome]

Audience:
[Describe who this is for]

Context and source material:
[Paste notes, examples, links, or existing copy]

Constraints:
[Tone, length, channel, timeline, must-include items, must-avoid items]

Before producing the final output, ask me for any missing information that would materially improve the result.
```

## Final Checklist
- [ ] The output matches the original goal.
- [ ] The audience and context are reflected in the answer.
- [ ] Important constraints and source material were preserved.
- [ ] The assistant made the relevant decisions explicit.
- [ ] The final artifact is ready to use, review, or hand to the next person.

## Source
This guide was generated from the indranilbanerjee/digital-marketing-pro skill entry for `landing-page-audit`.

## Source Skill Notes
These notes preserve the nuance from the original skill. Use them as supporting reference when the workflow above feels too generic.

# /digital-marketing-pro:landing-page-audit

## Purpose

Evaluate a landing page across six key conversion dimensions and deliver a scored assessment with specific, actionable recommendations to improve conversion rate.

## Input Required

The user must provide (or will be prompted for):

- **Landing page URL**: The page to audit
- **Traffic source**: Where visitors come from (paid search, social ads, email, organic)
- **Target action**: Desired conversion (form submit, purchase, signup, download, call)
- **Ad copy or email**: The upstream message driving traffic (for message match analysis)
- **Current conversion rate**: If known, for benchmarking

## Process

1. **Load brand context**: Read `~/.claude-marketing/brands/_active-brand.json` for the active slug, then load `~/.claude-marketing/brands/{slug}/profile.json`. Apply brand voice, compliance rules for target markets (`skills/context-engine/compliance-rules.md`), and industry context. **Also check for guidelines** at `~/.claude-marketing/brands/{slug}/guidelines/_manifest.json` — if present, load restrictions and relevant category files. Check for custom templates at `~/.claude-marketing/brands/{slug}/templates/`. Check for agency SOPs at `~/.claude-marketing/sops/`. If no brand exists, ask: "Set up a brand first (/digital-marketing-pro:brand-setup)?" — or proceed with defaults.
2. **Above-fold clarity** (score 1-10): Headline clarity, value proposition, visual hierarchy, CTA visibility within first viewport
3. **Trust signals** (score 1-10): Social proof, testimonials, logos, security badges, guarantees, reviews
4. **Form friction** (score 1-10): Number of fields, field labels, error handling, progressive disclosure, mobile form UX
5. **Message match** (score 1-10): Alignment between traffic source (ad/email) and landing page headline, imagery, offer
6. **Page speed** (score 1-10): Load time, Core Web Vitals, render-blocking resources, image optimization
7. **Mobile experience** (score 1-10): Responsive design, tap targets, scroll depth, mobile-specific CTAs
8. Calculate overall score and benchmark against industry averages
9. Prioritize recommendations by expected conversion impact

## Output

A structured landing page audit containing:

- Overall conversion score (1-10) with industry benchmark comparison
- Dimension-by-dimension scoring with evidence and screenshots/notes
- Top 5 priority fixes ranked by expected impact
- Detailed recommendations per dimension with implementation guidance
- Message match analysis with specific misalignment callouts
- Mobile-specific issues and fixes
- Quick wins vs. major redesign items

## Agents Used

- **analytics-analyst** — Performance scoring, conversion benchmarking, data-driven recommendations
- **brand-guardian** — Brand consistency, trust signal assessment, message alignment
- **cro-specialist** — Conversion scoring, form friction analysis, A/B test sample size calculation, above-fold hierarchy, CTA optimization

---

## Supporting file: skills/context-engine/compliance-rules.md

# Compliance Rules Reference

This file is the canonical compliance ruleset for the Digital Marketing Pro plugin. All marketing modules MUST check outputs against these rules before delivery. Rules are structured for programmatic consumption by the context engine.

---

## Section 1: Geographic Privacy Laws

### 1.1 EU/EEA — General Data Protection Regulation (GDPR)

| Field | Detail |
|---|---|
| **Region** | European Union / European Economic Area (27 EU member states + Iceland, Liechtenstein, Norway) |
| **Law** | General Data Protection Regulation (GDPR) |
| **Year Enacted** | 2016 (enforced May 25, 2018) |
| **Consent Model** | Opt-in. Explicit, informed, freely given, specific, and unambiguous consent required before processing personal data. Consent must be as easy to withdraw as to give. Legitimate interest may apply in narrow B2B contexts but requires a documented balancing test. |
| **Email Rules** | Prior opt-in required for all marketing emails. Soft opt-in exception: existing customers may be emailed about similar products/services if given an easy opt-out at collection and in every message. Every email must include sender identity, physical address, and a functional unsubscribe mechanism honored within 30 days. |
| **Cookie/Tracking Rules** | Prior consent required for all non-essential cookies and trackers (ePrivacy Directive). Cookie banners must allow granular choice (accept/reject by category). Pre-ticked boxes are invalid. Analytics cookies require consent unless strictly necessary. Server-side tracking of personal data still requires a lawful basis. |
| **Penalty Range** | Up to EUR 20 million or 4% of global annual turnover, whichever is higher. Supervisory authorities may also issue warnings, bans on processing, and orders to erase data. |
| **Key Marketing Impact** | Double opt-in is industry standard. All lead forms need clear consent checkboxes (not bundled). Data Processing Agreements required with every martech vendor. Privacy policy must disclose all data recipients. Cross-border data transfers require adequacy decisions, SCCs, or BCRs. Right to erasure means suppression lists must be maintained. Profiling for ad targeting requires explicit consent or legitimate interest with opt-out. |

### 1.1b EU/EEA — AI Act Article 50 (Generative AI Disclosure)

| Field | Detail |
|---|---|
| **Region** | European Union / European Economic Area |
| **Law** | Regulation (EU) 2024/1689 — Artificial Intelligence Act, Article 50 (Transparency obligations for providers and deployers of certain AI systems) |
| **Applicable** | **2 August 2026** (transparency obligations); general-purpose AI obligations applied 2 Aug 2025; high-risk system obligations 2 Aug 2027 |
| **Scope** | All generative-AI outputs distributed in EU markets — no minimum spend threshold, advertising not exempted. Both providers (AI developers) and deployers (advertisers, brands) bear obligations. |
| **Disclosure Requirements** | (a) AI-generated or AI-manipulated content **must be marked in a machine-readable format** using open, interoperable standards. **C2PA (Coalition for Content Provenance and Authenticity) is the emerging backbone.** Marking must be technically robust and survive routine processing. (b) Deepfakes (synthetic audio/image/video resembling real persons, objects, places, or events) must be **visibly disclosed**. (c) AI-generated text on matters of public interest must be disclosed unless human-reviewed and the brand assumes editorial responsibility. |