Ad-to-LP Auditor — fix the #1 conversion killer — Claude Skill
A Claude Skill for Claude Code by Gooseworks — run /ad-to-landing-page-auditor in Claude·Updated Apr 10, 2026
Audit ad-to-landing-page message match for paid campaigns
- Audits every ad against its landing page on 6 dimensions
- Scores message match from 0-60 with rating tiers
- Reviews landing page friction: forms, CTAs, social proof
- Identifies critical disconnects with rewrite suggestions
- Outputs a prioritized fix list by conversion impact
Who this is for
What it does
Find the exact message disconnect between your paid ads and the page they land on.
Before scaling spend, audit every ad-LP pair to make sure every dollar lands on a coherent experience.
Take over an account and quickly score every ad-LP combination before deciding what to fix.
How it works
Take ads and landing page URLs as input
Fetch each landing page and extract content elements
Score message match across 6 dimensions per ad-LP pair
Identify friction points on each landing page
Output prioritized fixes with rewrite suggestions
Metrics this improves
Works with
Want to use Ad-to-Landing Page Auditor?
Choose how to get started.
Install and run this skill locally on your computer.
Open a terminal on your computer and paste this command:
This downloads the skill with all its files to your computer:
Add -g at the end to make it available in all your projects.
Start Claude Code, then type the command:
Ad-to-Landing Page Auditor
The #1 reason ads get clicks but not conversions: the landing page doesn't deliver on the ad's promise. This skill audits the full click path — from ad copy to landing page experience — and flags every disconnect.
Core principle: A great ad with a mismatched landing page is worse than a mediocre ad with a matched one. Message match is the single biggest conversion lever most startups ignore.
When to Use
- "Why are my ads getting clicks but no conversions?"
- "Audit my ad-to-landing page flow"
- "Check message match on our campaigns"
- "My conversion rate is low — help me figure out why"
- "Review our landing pages for our ad campaigns"
Phase 0: Intake
- Ad data — One of:
- Ad copy + landing page URLs (manual list)
- CSV export from ad platform
- "Scrape my active ads" (uses ad scrapers on your domain)
- Platform(s) — Google Search / Meta / LinkedIn / All
- Conversion goal — What should happen after someone clicks? (Demo / Trial / Purchase / Download)
- Known conversion rates? — Current click → conversion rate per ad/LP
Phase 1: Ad Inventory
If User Provides Ad Data
Parse the provided ads into:
| Ad ID | Platform | Headline | Body/Description | CTA | Landing Page URL | Conv Rate (if known) |
|---|
If Scraping Own Ads
Run meta-ad-scraper and/or google-ad-scraper on the user's domain to capture active ads.
Phase 2: Landing Page Audit
For each unique landing page URL:
Fetch: [landing_page_url]
Extract and score:
2A: Content Elements
| Element | Found? | Content |
|---|---|---|
| Hero headline | [Y/N] | "[Text]" |
| Subheadline | [Y/N] | "[Text]" |
| Primary CTA | [Y/N] | "[Button text]" |
| CTA above fold | [Y/N] | — |
| Social proof | [Y/N] | [Logos / testimonials / metrics] |
| Benefit list | [Y/N] | [Key benefits listed] |
| Form / Sign-up | [Y/N] | [Field count: N] |
| Video | [Y/N] | — |
| Trust signals | [Y/N] | [Security badges, guarantees] |
2B: Message Match Scoring
For each ad → landing page pair, score on:
| Dimension | Score (1-10) | Criteria |
|---|---|---|
| Promise continuity | [X] | Does the LP headline deliver on the ad's promise? |
| Language match | [X] | Does the LP use the same words/phrases as the ad? |
| Visual continuity | [X] | Does the LP feel like a continuation of the ad? (Not assessable for search) |
| CTA alignment | [X] | Does the LP's ask match what the ad implied? |
| Specificity match | [X] | If the ad was specific ("for sales teams"), is the LP specific too? |
| Emotional match | [X] | If the ad used fear/urgency, does the LP carry that forward? |
Message Match Score: [Average/60]
Scoring Guide
| Score | Rating | Meaning |
|---|---|---|
| 50-60 | Excellent | Strong match — LP delivers on every ad promise |
| 40-49 | Good | Minor disconnects but overall coherent |
| 30-39 | Needs work | Noticeable gaps — visitor has to hunt for relevance |
| 20-29 | Poor | Ad and LP feel like different products |
| Below 20 | Critical | Complete mismatch — fix immediately |
Phase 3: Conversion Friction Analysis
Beyond message match, assess landing page conversion friction:
| Friction Type | Check | Status |
|---|---|---|
| Load time | Does the page feel heavy/slow? (Asset count proxy) | [Fast/Slow/Unknown] |
| Form length | How many fields before conversion? | [N fields] — [Appropriate/Too many] |
| CTA clarity | Is there one clear CTA or competing actions? | [Clear/Cluttered] |
| Above-fold conversion | Can someone convert without scrolling? | [Yes/No] |
| Social proof placement | Is proof near the CTA? | [Yes/No] |
| Navigation distraction | Does the LP have full site nav? (Should be minimal) | [Minimal/Full nav] |
| Mobile experience | Any mobile-unfriendly elements? | [Good/Issues] |
Phase 4: Output Format
# Ad-to-Landing Page Audit — [Product/Client] — [DATE]
Ads audited: [N]
Unique landing pages: [N]
Platform(s): [Google / Meta / LinkedIn]
Overall message match: [Score/60] — [Rating]
---
## Executive Summary
[3-4 sentences: Overall finding, biggest disconnect, top recommendation, estimated conversion impact]
---
## Audit Results by Ad → Landing Page Pair
### Ad 1: "[Ad headline excerpt]"
**Platform:** [Google Search / Meta / LinkedIn]
**Ad copy:**
> Headline: "[text]"
> Body: "[text]"
> CTA: "[text]"
**Landing page:** [URL]
> LP headline: "[text]"
> LP subhead: "[text]"
> LP CTA: "[button text]"
**Message Match Score: [X/60] — [Rating]**
| Dimension | Score | Issue |
|-----------|-------|-------|
| Promise continuity | [X/10] | [Specific finding] |
| Language match | [X/10] | [Specific finding] |
| CTA alignment | [X/10] | [Specific finding] |
| Specificity match | [X/10] | [Specific finding] |
| Emotional match | [X/10] | [Specific finding] |
**Disconnect found:** [Specific description of mismatch]
**Recommended fix:** [Specific change to ad or LP]
### Ad 2: ...
---
## Landing Page Friction Report
### [Landing Page URL]
| Friction Point | Status | Impact | Fix |
|---------------|--------|--------|-----|
| [Friction] | [Red/Yellow/Green] | [High/Med/Low] | [Specific fix] |
---
## Priority Fixes
### Critical (Fix This Week)
1. **[Ad/LP pair]:** [Specific mismatch] → [Specific fix]
- Est. conversion impact: [X% improvement]
### Important (Fix This Month)
2. **[Issue]:** [Fix]
### Nice-to-Have
3. **[Issue]:** [Fix]
---
## Rewrite Suggestions
### For [Ad or LP with worst match]:
**Current ad headline:** "[current]"
**Suggested ad headline:** "[rewrite that matches LP]"
OR
**Current LP headline:** "[current]"
**Suggested LP headline:** "[rewrite that matches ad]"
Save to clients/<client-name>/ads/ad-lp-audit-[YYYY-MM-DD].md.
Cost
| Component | Cost |
|---|---|
| Landing page fetching | Free |
| Ad scraping (if scraping own ads) | ~$0.40-1.00 (Apify) |
| Analysis | Free (LLM reasoning) |
| Total | Free-$1.00 |
Tools Required
- fetch_webpage — for landing page analysis
- Optional:
meta-ad-scraper,google-ad-scraper(if scraping own ads) - Apify API token — only if scraping ads
Trigger Phrases
- "Audit my ad-to-landing page match"
- "Why is my conversion rate so low?"
- "Check message match on our campaigns"
- "Do our landing pages match our ads?"
- "Run a CRO audit on our ad funnels"