Ali Fakhar
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How to audit a landing page for conversion with AI

  • Level: Beginner
  • A few hours to set up

Ali Fakhar · Updated: Sept 2026

The short answer

Give a model the page text, a mobile screenshot, the ad that sends traffic and the page’s goal. Ask it to check message match, offer clarity, proof, form friction and the call to action, quoting the page for each finding. Prioritise the fixes yourself and test the biggest one.

On this page

At a glance

The marketing problem
Landing pages often lose visitors for ordinary reasons: the headline does not match the ad, the offer is vague, proof is missing or the form asks too much. A structured review finds these quickly; deciding what to change, and proving it worked, still needs data.
Who this is for
Performance marketers, growth marketers and founders sending paid or campaign traffic to a page.

What you need

Before you start

  • A single, clear goal for the page: one conversion action
  • Analytics on the page: conversion rate and, ideally, scroll or heatmap data
  • Permission to run an A/B test or a clean before-and-after comparison

What goes in

  • The full page text and a mobile screenshot
  • The ad, email or post that sends traffic to it
  • Page analytics for the last 30 days
  • Customer language from reviews or interviews, if you have it

How it works

  1. 01 · ToolCapture the page and its context
  2. 02 · AI stepAudit against a conversion checklist
  3. 03 · AI stepDraft rewrite options
  4. 04 · You decideChoose what to test
  5. 05 · OutputTest and record
  • Tool
  • AI step
  • You decide
  • Output

Step by step

  1. 01 Tool

    Capture the page and its context

    Save the page text, take a mobile screenshot, and collect the ad or email that sends traffic and the page’s conversion data.

  2. 02 AI step

    Audit against a conversion checklist

    Ask for a score and a quoted finding per checklist item, so every point can be checked against the page.

    Prompt to copy

    You are reviewing a landing page whose goal is [goal] for [audience], arriving from this ad: [paste ad]. Check the page against: 1) message match with the ad, 2) whether the headline states a specific outcome, 3) clarity of the offer and the next step, 4) proof near the claims, 5) objections left unanswered, 6) form length and friction, 7) the call to action on mobile. For each, give a score from 1 to 5, quote the part of the page you are judging and suggest one specific fix. Then list the three fixes likely to matter most, with your reasoning. Page text: [paste] (mobile screenshot attached)

  3. 03 AI step

    Draft rewrite options

    Ask for alternatives to the weakest sections, built from customer language and approved facts.

    Prompt to copy

    For the top three issues, write two alternative versions of the affected section, using this customer language where it fits: [paste quotes]. Keep claims to these approved facts: [paste].

  4. 04 You decide

    Choose what to test

    Pick the change with the largest likely effect that you can measure. Check facts and brand voice in the rewrite.

  5. 05 Output

    Test and record

    Run an A/B test or a clean before-and-after comparison, then record the result and the decision next to the audit.

Where a person decides

A marketer decides which fixes to make and judges the test result against the agreed metric.

What to watch for

  • A model cannot see your traffic quality; a good page converts poorly with the wrong audience.
  • Screenshots miss interaction problems such as slow loading or forms that break on some devices.
  • Checklist advice stays generic until it is tested on your audience.

How to tell it is working

  • Every finding quotes the page or points to the screenshot.
  • The chosen change is tested with enough traffic to decide, or compared before and after with the same traffic source.
  • Lead quality is checked, not only conversion rate.

An illustrative example

Input

Illustrative: a demo-request page for a fictional analytics tool, reached from a LinkedIn ad that promises “reports in five minutes”.

Output

Message match scored low because the headline never mentions reporting time; the form asks for seven fields; two rewritten headlines and a shorter form are proposed, and the headline change is chosen for the first test.

Want this running in your team?

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