// Analyze the message match between your ads and landing pages. Checks if the promise in the ad copy carries through to the landing page headline, body, and CTA. Flags disconnects that kill conversion rates. Works with Google, Meta, and LinkedIn ads.
Search LinkedIn posts by keywords using Crustdata API directly, deduplicate and sort by engagement. Outputs to CSV or JSON. Use when researching LinkedIn content around specific topics.
Crawl a website's sitemap and blog index to build a complete content inventory. Lists every page with URL, title, publish date, content type, and topic cluster. Groups content by category and topic. Optionally deep-reads top N pages for quality analysis and funnel stage tagging. Use before SEO audits, content gap analysis, or brand voice extraction.
Mine the highest-converting ad angles from customer reviews, Reddit complaints, support tickets, and competitor ads. Extracts actual pain language, competitor weaknesses, and outcome phrases that real buyers use. Outputs a ranked angle bank with proof quotes and recommended ad formats per angle.
Scrape competitor ads from Meta and Google ad libraries, cluster by hook/angle/format, and surface new creative directions your team hasn't tested. Chains meta-ad-scraper and google-ad-scraper. Use when a marketing team wants to understand the competitive ad landscape before launching a campaign, or wants fresh creative inspiration from what's already working in the market.
Research a specific competitor across their website, reviews, ads, social presence, and pricing — then produce a structured sales battlecard with positioning traps, objection handlers, landmine questions, and win/loss themes. Chains web research, review mining, and ad intelligence. Use when sales needs competitive ammo or when entering a new market with established incumbents.
End-to-end champion/buyer/user job change signal composite. Takes a set of known people (past buyers, champions, power users), detects when they move to a new company, researches the new company for ICP fit, and drafts personalized outreach leveraging the existing relationship. Tool-agnostic — works with any people source, detection method, and outreach platform.
| name | ad-to-landing-page-auditor |
| description | Analyze the message match between your ads and landing pages. Checks if the promise in the ad copy carries through to the landing page headline, body, and CTA. Flags disconnects that kill conversion rates. Works with Google, Meta, and LinkedIn ads. |
| tags | ["ads"] |
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.
Parse the provided ads into:
| Ad ID | Platform | Headline | Body/Description | CTA | Landing Page URL | Conv Rate (if known) |
|---|
Run meta-ad-scraper and/or google-ad-scraper on the user's domain to capture active ads.
For each unique landing page URL:
Fetch: [landing_page_url]
Extract and score:
| 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] |
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]
| 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 |
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] |
# 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.
| 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 |
meta-ad-scraper, google-ad-scraper (if scraping own ads)