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Landing page teardown, ranked by fix value

The page converts worse than it should. Get a section-by-section teardown with fixes ranked by value — not a vague 'improve clarity above the fold'.

The prompt — copy and run it

You are a conversion copy specialist tearing down a landing page. I will paste the page copy and context. Produce:

A) A SECTION-BY-SECTION TABLE: section, the job it should be doing, what is working, the specific problem classified (clarity / relevance-to-traffic-source / anxiety / friction / missing proof), and a concrete rewrite suggestion — not 'make it better'.
B) The TOP 5 FIXES ranked by expected impact against effort, with reasoning tied to my stated traffic source and conversion goal. Do not cite invented conversion statistics; where the impact rationale needs data I did not provide, say exactly what to pull.
C) A MESSAGE-MATCH CHECK: does the first screen answer the intent of the ad, email, or search that brings the traffic I described? If the traffic intent is unknown, name the exact report to check before touching the page.

My inputs: [PASTE: page copy top to bottom, traffic sources and their messages, conversion goal, current conversion rate if known]

Rules: Do not invent, estimate, or fabricate any statistic, benchmark, or performance figure — if a number is not in the material I give you, write "not provided" and flag it. Mark every claim I should verify in my analytics or source systems before it is published or presented. Never include customer personally identifiable information or client-confidential terms.

How to use this prompt

  1. Copy the full prompt above with the Copy button.
  2. Add your context. This prompt runs as-is — paste it, then add the specific details, data, or files it should reason over.
  3. Paste into ChatGPT, Claude, or Gemini and run. Read the reality guardrail below before you act on the output.

Why this prompt works

Teardowns fail as feedback when everything is priority one. Grading each section against its specific job — and forcing message-match against the actual traffic source — finds the leak that generic best-practices audits miss, which is usually the gap between the ad's promise and the page's first screen.

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Reality guardrail: this prompt makes the model reason from data you paste — it does not source or verify facts for you. Check every claim, keep confidential data out of consumer AI tools, and follow your employer's AI-use policy.

Frequently asked

When should I use this prompt?

The page converts worse than it should. Get a section-by-section teardown with fixes ranked by value — not a vague 'improve clarity above the fold'.

Why does this prompt work?

Teardowns fail as feedback when everything is priority one. Grading each section against its specific job — and forcing message-match against the actual traffic source — finds the leak that generic best-practices audits miss, which is usually the gap between the ad's promise and the page's first screen.

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PromptSharp prompts are drafted with AI assistance and human-reviewed. They structure how a model reasons over data you provide — they do not source or verify facts for you, and you own every output. Nothing here is financial, legal, tax, or investment advice. Never paste confidential, client, or material non-public information into consumer AI tools; follow your employer's AI-use policy. © 2026 PromptSharp.