AI Marketing Playbook #001: Review Your Landing Page Like a Senior Performance Marketer
Review your landing page with AI using an expert marketing framework to improve messaging, reduce conversion friction, and boost performance.
Most landing page reviews start with the wrong questions. Should the button be green or blue? Is the hero image big enough? Those things matter a little, but they're almost never why a campaign wins or loses.
The real question is simpler and harder: does this page match the audience you paid to bring here, answer the objection they walked in with, and give them a reason to trust you before they act? Get that wrong and no button colour will save you.
This is where AI earns its keep — not as a replacement for marketing judgment, but as a fast second opinion. Paste in a URL and some context, and it'll spot patterns and challenge assumptions a lot quicker than a full stakeholder review meeting will.
Below is a prompt built to do that: review a landing page the way a performance marketer would, not the way a designer would.
Copy the Prompt
Act as a Senior Performance Marketing Consultant with more than 20 years of experience in B2B and B2C marketing. Review my landing page as if you were personally accountable for its conversion rate.
- Landing Page: [PASTE URL]
- Target Audience: [Describe your ideal customer]
- Traffic Source: [Google Ads, LinkedIn Ads, Meta Ads, Organic Search, Email, etc.]
- Campaign Objective: [Generate leads, sell products, book demos, increase sign-ups, etc.]
- Main Competitors: [List 2-3, if known]
- Common Objections: [What do prospects usually hesitate on before buying?]
Evaluate the page across these areas, grouped for a clear read:
First Impressions- What a visitor understands in the first 5 seconds
- Headline effectiveness and message-to-market fit
- Visual hierarchy — what draws the eye first, and does it matter
- Trust and credibility signals (or the lack of them)
- Conversion friction — anything that adds hesitation or extra steps
- Missing information a skeptical buyer would want before converting
- Alignment between the page and the traffic source it's built for
- The user journey from click to conversion
- Mobile experience specifically (not just "is it responsive")
- Clarity and placement of every CTA
For each issue found:
- Explain why it matters, in one sentence
- Rate impact: High / Medium / Low
- Give one practical fix, not a list of options
- Suggest how to test whether the fix actually works
Flag explicitly where you're making an assumption because you don't have access to my analytics, CRM, or past test results — don't present a guess as a fact.
Finish with:
- The five highest-priority fixes, ranked
- Three A/B test ideas
- An overall score out of 10, with one line on what's capping the score
Feed It More Than a URL
A prompt is only as good as the context behind it. Don't just drop in a link and hope for the best — tell it who the page is for, what it's competing against, and what your buyers actually hesitate on. That last one matters more than people think: an AI reviewing a page cold will often recommend generic best practices (more testimonials, longer copy, a bigger hero image) that have nothing to do with why your specific prospects aren't converting.
Example inputs:
- Landing page: www.example.com
- Audience: Marketing Directors at B2B SaaS companies with 50–500 employees
- Traffic: LinkedIn Ads
- Goal: Book a product demo
Don't Let AI Make the Final Call
Here's the mistake to avoid: treating every recommendation as gospel because it came out formatted like an expert audit.
AI doesn't know your win rate, your sales team's objection-handling calls, your last three A/B tests, or why that "ugly" form actually converts better than the sleek one you tested against it. It's reasoning from patterns, not from your data.
So use it to generate a shortlist of hypotheses, then check those hypotheses against what you actually have: conversion rate, bounce rate, scroll depth, heatmaps, session recordings, search terms, lead quality. If the AI says your headline is weak but your heatmaps show everyone reads it and converts anyway, trust the heatmap.
The goal isn't to implement everything the review suggests. It's to find the handful of recommendations your data can actually back up.
The Bottom Line
Run this before you scale spend, not after. A five-minute AI review before increasing a Google Ads or LinkedIn budget is one of the cheapest insurance policies in performance marketing — it won't catch everything, but it'll catch the obvious mismatches between your page and your traffic before you pay to find out the hard way.
Treat it as a second set of eyes, not the marketer in the room. The campaigns that actually perform still come down to real data, real customer conversations, and testing — AI just helps you get to the right questions faster.