Published version comparison

Landing Page Conversion Critique Prompt

1.0.02.0.0

Source version 1.0.0

Published

Initial: Initial published snapshot.

Destination version 2.0.0

Published

Major: Replace the legacy Landing Page Conversion Critique Prompt template with a domain-specific input, evidence, authority, safety, workflow, output, and verification contract.

Public field comparison

Title Unchanged

1.0.0
Landing Page Conversion Critique Prompt
2.0.0
Landing Page Conversion Critique Prompt

Summary Changed

1.0.0
Review a landing page for clarity, friction, proof, CTA strength, section order, and conversion blockers.
2.0.0
Audit a landing page’s message match, value proposition, proof, calls to action, friction, section order, and conversion risks using supplied page evidence and performance context.

Share-purpose line Changed

1.0.0
2.0.0
Use this prompt to turn landing page copy, screenshots, analytics, and campaign context into an evidence-labeled conversion critique, prioritized recommendations, and a testable implementation brief.

Best use cases Changed

1.0.0
Landing Page Messaging
Landing Page Conversion Critique
Requirements Clarification
Output Quality Review
Review Checklist Building
Implementation Planning
2.0.0
Pre-launch landing page conversion audits
Evidence-based landing page messaging critiques
Paid-traffic message-match reviews
CRO experiment and validation planning
Landing page redesign prioritization
Conversion-focused implementation handoffs

Variables Changed

1.0.0
Goal or task
Current context
Constraints
Files, data, or examples
Definition of done
2.0.0
Landing page materials
Conversion goal and primary CTA
Target audience and traffic context
Offer and business constraints
Performance evidence
Compliance and brand requirements

How to Use Changed

1.0.0
Replace every bracketed placeholder before running. Give the model enough context to inspect assumptions, ask only blocking questions, and produce a concrete deliverable. For code prompts, include relevant files, errors, logs, and test commands.
2.0.0
In ChatGPT, replace every bracketed variable with your landing page materials and campaign context. Provide inspectable copy, screenshots or exports, the conversion goal and CTA, audience and traffic details, plus any analytics, research, experiment history, constraints, and compliance requirements available. Redact personal or confidential data, then run the prompt. If only a URL is provided, paste or upload the relevant page content because ChatGPT must not assume it can access the live page.

Example use case Changed

1.0.0
Use this when you need a production-ready cro result in Marketing, not a generic brainstorm. The expected output should include findings, implementation steps, risks, and verification checks.
2.0.0
A growth team is preparing to revise a paid-search landing page for a B2B software trial. They provide ChatGPT with desktop and mobile screenshots, page copy, ad-group messaging, audience research, CTA destination, form fields, funnel analytics, heatmap summaries, brand rules, and privacy constraints. The prompt returns an evidence-labeled page map, CRO scorecard, prioritized conversion findings, supported copy alternatives, experiment designs, and an implementation verification register without claiming that changes were launched or improved conversion.

Difficulty Unchanged

1.0.0
Expert
2.0.0
Expert

Tool Unchanged

1.0.0
ChatGPT
2.0.0
ChatGPT

Prompt type Unchanged

1.0.0
cro
2.0.0
cro

Tags Changed

1.0.0
chatgpt
Marketing
landing page
conversion
2.0.0
chatgpt
Marketing
landing page
conversion rate optimization
CRO audit
ab-testing

SEO title Unchanged

1.0.0
Landing Page Conversion Critique Prompt | AMO.ng
2.0.0
Landing Page Conversion Critique Prompt | AMO.ng

SEO description Changed

1.0.0
Review a landing page for clarity, friction, proof, CTA strength, section order, and conversion blockers.
2.0.0
Audit landing page clarity, proof, CTAs, friction, section order, and conversion risks with evidence-based recommendations and validation checks.

Prompt-body line comparison

Removed Added Unchanged context

Act as a senior Marketing specialist using ChatGPT. Your task is: [Goal or task].
Critique the supplied landing page as a conversion journey. Diagnose what is observable, distinguish evidence from hypotheses, and produce recommendations that a copywriter, designer, marketer, or product team can review and implement.

Context:
- Current situation: [Current context]
- Constraints: [Constraints]
- Available materials: [Files, data, examples, URLs, logs, notes]
- Success criteria: [Definition of done]
Inputs
Minimum inputs required for a reliable critique:
- Landing page copy, screenshots, document export, or other inspectable page representation: [Landing page materials]
- The intended conversion and primary call to action: [Conversion goal and primary CTA]
- Intended audience, awareness stage, traffic source, and campaign promise where known: [Target audience and traffic context]

Workflow:
1. Restate the objective in operational terms and identify any missing information that would block a reliable answer.
2. Make reasonable assumptions only when they are low risk, and label them clearly.
3. Produce the main deliverable for "Landing Page Conversion Critique Prompt" with enough detail that a skilled operator can execute it immediately.
4. Include edge cases, failure modes, dependencies, and tradeoffs that a junior prompt would usually miss.
5. Add a verification checklist with concrete tests, review questions, metrics, or acceptance criteria.
6. End with the smallest safe next action.
Useful supporting context:
- Offer details, pricing, funnel stage, technical limitations, deadlines, and other constraints: [Offer and business constraints]
- Analytics, heatmaps, recordings, research, experiment history, or benchmark data: [Performance evidence]
- Brand, accessibility, legal, privacy, and industry requirements: [Compliance and brand requirements]

Output format:
- Executive summary
- Detailed plan or implementation
- Risks and mitigations
- Verification checklist
- Next action
Input handling
1. Confirm that the page representation, conversion goal, and intended audience are sufficiently clear. If any of these are missing or materially contradictory, ask only the questions needed to unblock the critique.
2. If optional context is absent, continue with a heuristic review but label the limitation. Do not infer actual visitor behavior, conversion performance, statistical significance, technical behavior, or legal compliance from page copy alone.
3. Treat URLs as references unless their contents are actually available in the ChatGPT conversation. Never claim to have opened a URL, inspected a live page, used analytics, tested a form, or observed a device state unless corresponding content or execution evidence was supplied.
4. If screenshots, copy, analytics, or campaign claims conflict, record the conflict rather than silently choosing one version.

Do not give generic advice. Optimize for a production-quality cro outcome.
Evidence rules
Classify important statements as one of the following:
- Supplied fact: explicitly provided by the user or source material.
- Direct observation: visible in the supplied copy, screenshot, or page export; identify the section or quoted wording.
- Assumption: a bounded interpretation needed to proceed.
- Hypothesis: a plausible conversion effect that requires validation.
- Unknown: information not available from the inputs.
- Conflict: supplied sources that disagree.

Do not present heuristic judgments as measured behavior. Use calibrated confidence:
- High: supported by direct page evidence plus relevant performance or research evidence.
- Medium: supported by direct page evidence and established CRO reasoning, but not behavioral data.
- Low: dependent on missing audience, traffic, implementation, or performance information.

Critique workflow
1. Build a compact page map in displayed order. Identify the hero, problem framing, value proposition, benefits, product or service explanation, proof, objection handling, offer details, risk reversal, primary and secondary calls to action, form or checkout transition, and footer disclosures. Mark absent or unobservable elements.
2. Trace message match from traffic source or campaign promise to the hero. Check whether the visitor can quickly determine what is offered, for whom, the outcome, why it is credible, and what action to take. If acquisition context is unavailable, state that message match cannot be fully assessed.
3. Evaluate the value proposition for specificity, differentiation, relevance, concrete outcomes, and support. Flag vague superlatives, unsupported guarantees, internal jargon, feature-only language, and claims that exceed the supplied evidence.
4. Review information hierarchy and section order against likely visitor questions: relevance, problem recognition, mechanism, benefits, proof, objections, offer terms, risk, and action. Identify premature asks, buried differentiators, repetition, and transitions that create comprehension gaps.
5. Assess calls to action for prominence, action clarity, commitment level, consistency, destination expectation, and continuity with the offer. Examine competing actions and whether secondary calls to action help uncertain visitors or dilute the primary conversion goal.
6. Examine conversion friction, including unclear pricing or terms, excessive form demands, unexplained next steps, forced account creation, weak error recovery, distracting navigation, hidden conditions, anxiety near the decision point, and mismatches between CTA wording and the expected next screen. Only evaluate interactions visible in supplied evidence.
7. Audit trust and proof. Distinguish specific, attributable evidence from generic testimonials, decorative logos, unsupported counts, unverifiable badges, and claims lacking context. Note where proof appears too late, addresses the wrong objection, or creates privacy or endorsement concerns.
8. Review objection coverage and risk reversal for the stated audience and offer. Include cost, time, effort, fit, switching risk, security, privacy, cancellation, support, implementation, and outcome uncertainty only where relevant.
9. Inspect mobile and accessibility implications visible in the materials, such as reading order, text density, CTA discoverability, contrast concerns, ambiguous links, heading structure, form labeling, and reliance on color. Do not claim conformance without a proper accessibility test.
10. Identify ethical, legal, and reputational risks. Do not recommend fake scarcity, fabricated proof, disguised advertising, hidden charges, preselected consent, misleading guarantees, coercive defaults, or other dark patterns. Flag regulated, financial, health, privacy, testimonial, comparative, or performance claims for qualified human review when applicable.
11. Prioritize findings by expected conversion consequence, evidence strength, confidence, implementation effort, dependencies, and downside risk. Do not invent numerical uplift estimates. Separate quick corrections from structural redesigns and experiments.
12. Draft revised messaging only where the available offer and audience evidence supports it. Preserve important qualifications. For every material rewrite, identify the original issue, proposed wording, intended visitor response, supporting evidence, and claims requiring substantiation.
13. Create an implementation and validation plan. Distinguish deterministic corrections, such as a broken message hierarchy, from hypotheses that should be tested. Specify pre-launch QA, post-launch measurement, guardrail metrics, and stop or rollback conditions.

Authority and safeguards
- Provide analysis, proposed copy, test designs, and implementation instructions only. Do not claim to edit, publish, approve, deploy, contact users, launch experiments, or change analytics configuration.
- Require explicit human approval before public copy changes, tracking changes, experiments, legal claims, pricing changes, or collection of additional personal data.
- Minimize exposure of personal or confidential information. Recommend redaction or aggregation if analytics exports, recordings, testimonials, or form data contain personal data.
- Stop and flag the issue if the requested recommendation depends on deceptive practices, unverifiable claims, undisclosed material terms, or sensitive regulated advice.
- Any recommendation with meaningful conversion, revenue, compliance, accessibility, or brand risk must include a review owner and a rollback or recovery condition.

Required deliverable
A. Scope and evidence status
- State the conversion goal, audience, traffic context, page version, materials reviewed, materials unavailable, assumptions, unknowns, and conflicts.
- State clearly whether the result is a heuristic critique, an evidence-supported diagnosis, or a combination.

B. Page and persuasion map
- List sections in current order.
- For each section, record its apparent job, visitor question addressed, primary claim, proof used, CTA relationship, and any missing transition.

C. CRO scorecard
Assess only observable criteria: message match, value-proposition clarity, audience relevance, differentiation, information hierarchy, CTA clarity, commitment fit, proof quality, objection handling, offer transparency, friction, readability, mobile implications, accessibility implications, and trust.
For each criterion provide a rating of Strong, Mixed, Weak, or Not assessable; the supporting evidence; the conversion implication; and confidence. Explain ratings rather than averaging them into an unsupported overall score.

D. Prioritized conversion findings
Provide a table with:
- Finding ID and page location
- Direct observation or supplied evidence
- Evidence classification
- Conversion hypothesis
- Affected audience or traffic segment
- Severity and confidence
- Recommended change
- Expected decision or behavior influenced
- Effort, dependencies, and downside risk
- Disposition: correct, prototype, test, research, retain, or blocked

E. Messaging and structure recommendations
- Show the current wording or issue, proposed wording or structural change, rationale, evidence basis, and substantiation needed.
- Provide a recommended section sequence when reordering is justified.
- Identify what should remain unchanged and why.

F. Experiment and research plan
For each test-worthy hypothesis, specify the control, proposed variant, primary metric, diagnostic metrics, guardrail metrics, target segment, instrumentation prerequisites, expected observation, decision rule, minimum runtime or sample-size caveat, and stop condition. If traffic volume or baseline data is unknown, do not prescribe false-precision sample sizes; request the data needed for power planning.

G. Implementation and verification register
For every approved candidate change, specify the owner or discipline, affected component, prerequisite, pre-launch check, expected result, actual result field, evidence to retain, rollback trigger, and status. Leave actual result as Not run unless execution evidence is supplied.
Include checks for copy accuracy, claim substantiation, CTA destination, form behavior, responsive presentation, analytics events, consent behavior, accessibility review, and legal or brand approval where relevant.

H. Decision-ready handoff
- List the five highest-priority actions in order, with rationale.
- Separate safe corrections from experiments and unresolved research questions.
- Name blocking decisions, required reviewers, and the smallest safe next action.

Completion standard
Do not say that a change was fixed, tested, validated, approved, launched, or improved unless the supplied evidence demonstrates that exact state. Label recommendations as Proposed, execution as Not run or Executed, and outcomes as Unverified or Verified with cited evidence. A complete critique must trace every high-priority recommendation to page evidence, a conversion hypothesis, an owner or decision point, and a concrete verification method.