name: abm-landing-page
description: Create personalized ABM (Account-Based Marketing) landing pages for specific prospects. Takes a LinkedIn URL, analyzes their background, and creates a targeted landing page that feels authentic (not AI-generated). Trigger words: "create landing page", "personalized page", "abm", "prospect page", "target page for"
allowed-tools: Bash, Read, Write, Edit, WebFetch, WebSearch, Task
ABM Landing Page Skill
Create highly personalized landing pages for specific prospects that maximize conversion while avoiding AI detection patterns.
Workflow
Step 1: Profile Analysis
Given a LinkedIn URL, extract:
- Current role & company - What do they do day-to-day?
- Past experience - What tools/platforms have they used?
- Pain points - Based on job descriptions, what problems do they face?
- Industry jargon - What specific terms would they use?
- Certifications - What credentials do they have?
Use the LinkedIn profile to understand their world deeply.
Step 2: Create Segment-Based URL
NEVER use the person's name in the URL. Create a segment that looks like a category page:
| Bad |
Good |
/for/jon |
/for/uipath-certified |
/for/sarah-smith |
/for/rpa-consultants |
/for/john-doe |
/for/enterprise-it-leaders |
The URL should look like it's targeting a role/segment, not an individual.
Step 3: Content Guidelines
DO:
- Use industry-specific jargon only insiders would know
- Reference specific tools/products they've used (e.g.,
idx_aaname, DU model, Orchestrator)
- Write conversational, slightly imperfect copy
- Vary sentence length and structure
- Include specific scenarios ("Saturday 2am. The upgrade failed.")
- Use casual language ("Classic.", "Ship it and hope.")
DON'T:
- Use emojis or icon grids
- Use buzzwords like "10x", "revolutionary", "transform", "self-healing"
- Use repetitive sentence structures
- Use overly polished, perfect prose
- Use generic marketing speak
- Mention the person's name anywhere on the page
Step 4: Page Structure
app/for/[segment-name]/
page.tsx # Server component with metadata + JSON-LD schema
client.tsx # Client component with UI
page.tsx Template (with SEO/AEO optimizations)
import { Metadata } from "next";
import SegmentPageClient from "./client";
export const metadata: Metadata = {
title: "For [Segment] | Mediar",
description: "[Short, casual description of the pain point]",
robots: "noindex, nofollow", // Private page - don't index
};
// JSON-LD Schema for AI/search crawlers
const jsonLd = {
"@context": "https://schema.org",
"@type": "Article",
headline: "[Page headline]",
description: "[Description]",
datePublished: "2026-01-20",
dateModified: "2026-01-20",
author: { "@type": "Organization", name: "Mediar", url: "https://mediar.ai" },
publisher: { "@type": "Organization", name: "Mediar", url: "https://mediar.ai" },
mainEntity: {
"@type": "FAQPage",
mainEntity: [
// Add FAQ items based on their pain points
{
"@type": "Question",
name: "[Question they'd ask]",
acceptedAnswer: { "@type": "Answer", text: "[Direct answer]" },
},
],
},
};
export default function SegmentPage() {
return (
<>
<script
type="application/ld+json"
dangerouslySetInnerHTML={{ __html: JSON.stringify(jsonLd) }}
/>
<SegmentPageClient />
</>
);
}
client.tsx Structure
Use semantic HTML for AI crawlers:
<article>
<header> {/* Hero section */}
<h1>...</h1>
<p>Updated <time dateTime="2026-01-20">January 2026</time></p>
</header>
<section> {/* TL;DR */}
<h2>TL;DR</h2>
<ul>...</ul>
</section>
<section> {/* Pain points */}
<h2>...</h2>
</section>
<section> {/* Comparison - use <table> not divs */}
<h2>...</h2>
<table>...</table>
</section>
<section> {/* Social proof */}
<h2>...</h2>
</section>
<section> {/* Demo/Video */}
<h2>...</h2>
</section>
<section> {/* CTA */}
<h2>...</h2>
</section>
</article>
Section Order:
- Header/Hero - One punchy question about their main pain point + visible date
- TL;DR - 3-4 bullet key takeaways (AI loves this)
- Pain Points - 4-6 specific scenarios they'd recognize (no icons)
- Comparison - Their current tool vs Mediar (use
<table>, not divs)
- Social Proof - Testimonials from similar roles
- Demo/Video - Concrete example relevant to their work
- CTA - Simple, low-commitment ask
Step 5: PostHog Tracking
Track page views and CTA clicks with segment identifiers (not personal info):
useEffect(() => {
if (posthog) {
posthog.capture("segment_page_viewed", {
page: "/for/[segment]",
segment: "[segment_identifier]",
});
}
}, [posthog]);
Anti-AI Detection Checklist
Before shipping, verify:
Example Pain Points by Role
UiPath Developer
- Selector maintenance (
aaname, idx, anchor elements)
- Exception handling (try-catch everything)
- Document Understanding training
- Orchestrator updates/maintenance windows
- Version compatibility issues
- Teaching junior devs best practices
Power Automate User
- Desktop flow reliability
- Connection refresh issues
- Premium connector costs
- Flow run history limits
- Debugging cloud flows
IT Manager (RPA)
- Bot licensing costs ($420/bot/month)
- Infrastructure overhead
- Scaling attended vs unattended
- Security/compliance concerns
- Measuring ROI
Finance/Ops (End User)
- Manual data entry between systems
- Copy-paste errors
- Month-end close delays
- Report generation time
- Audit trail requirements
Copy Style Guide
Headers
- Questions work well: "What if selectors just worked?"
- Casual statements: "The stuff that eats your week"
- Direct: "Same task, different approach"
Descriptions
Write like you're talking to a colleague:
Too polished (AI-sounding):
"Our advanced AI-powered automation platform revolutionizes enterprise workflow management through intelligent self-healing capabilities."
Better (human):
"You know the drill. Chrome updates, your idx_aaname breaks. Someone touches the DOM, your anchor element vanishes. We got tired of it too."
CTAs
Keep them casual:
- "Book 15 min" (not "Schedule Your Personalized Demo Today")
- "Or check the code" (not "Explore Our Open Source Repository")
- "See how we handle it" (not "Discover How Our Platform Transforms Your Workflows")
File Locations
- Landing pages:
app/for/[segment]/
- Shared components: Use existing components from
components/
- Lead capture: Use
LeadCaptureModal from components/landing/lead-capture-modal
Quick Start
When user provides a LinkedIn URL:
- Visit the profile and extract role, experience, skills
- Identify their likely pain points based on tools they've used
- Create segment name from their role (e.g., "uipath-certified", "rpa-consultants")
- Generate
page.tsx and client.tsx in app/for/[segment]/
- Run dev server and preview in browser
- Iterate based on feedback
SEO & AI Search Optimization (AEO)
AI systems (ChatGPT, Perplexity, Claude, Google AI Overviews) now extract and cite content. Traditional SEO focused on ranking in Google's 10 blue links. Now you're also optimizing for:
- AI Overviews (Google's AI-generated summaries)
- ChatGPT/Bing Chat responses
- Perplexity, Claude, Gemini and other AI assistants
- Traditional search (still matters, but shrinking share of clicks)
Key Concepts
1. Answer Engine Optimization (AEO)
AI systems extract and synthesize answers. Your content needs to be:
- Directly answerable - Clear, concise statements that AI can quote
- Well-structured - Headers, lists, tables that parse cleanly
- Authoritative - Cited sources, credentials, E-E-A-T signals
2. What AI Models Prioritize
- Recency - Fresh, updated content (datestamps matter)
- Specificity - Detailed, niche expertise over generic coverage
- Consensus - Information that aligns with authoritative sources
- Structure - Schema markup, FAQs, clear hierarchies
3. Citation Optimization
When AI cites sources, it favors:
- Original research/data
- First-hand expertise
- Unique perspectives not found elsewhere
- Well-organized reference content
Tactical Changes
Content Format
OLD: 2000-word SEO articles padded with fluff
NEW: Dense, skimmable, fact-rich content with clear takeaways
Structure That Works
- Lead with the answer (inverted pyramid)
- Use descriptive H2/H3s that could be standalone queries
- Include "What is X" and "How to Y" sections
- Add FAQ schema for common questions
- Tables for comparisons (AI loves structured data)
Technical Must-Haves
- Schema markup - FAQ, HowTo, Article, Organization
- Fast load times - AI crawlers have timeouts
- Clean HTML - Semantic markup over div soup
- Indexable content - No JS-only rendering for critical content
What's Declining vs Rising
Declining:
- Keyword stuffing (AI understands semantics)
- Thin affiliate content (AI prefers primary sources)
- Link farms/PBNs (less weight in AI training data curation)
- Click-bait titles (AI evaluates content quality, not CTR)
Rising:
- Topical authority - Deep coverage of your niche
- Brand mentions - Even without links, mentioned brands get cited
- Community presence - Reddit, forums, discussions influence AI
- Multi-format content - Video transcripts, podcasts feed AI training
Quick Wins
- Add FAQ sections with natural questions
- Update publish dates and content regularly
- Create comparison tables for your category
- Write definitive "What is X" explainers
- Get mentioned in Reddit/forum discussions
- Claim and optimize your knowledge panel
- Use structured data aggressively
Key HTML Tags Reference
| Tag/Attribute |
Purpose |
<article> |
Semantic content wrapper |
<time datetime=""> |
Machine-readable dates |
<h1> - <h3> |
Clear hierarchy (one H1) |
<ul>, <ol> |
Lists AI can parse |
<table> |
Comparisons, data |
itemscope/itemprop |
Inline microdata |
application/ld+json |
Structured data blocks |
Minimum Viable Implementation
Every ABM landing page MUST have:
- One JSON-LD block per page (Article or FAQPage)
- Semantic HTML (
<article>, <section>, <header>, <time>)
- Clear H1 → H2 → H3 hierarchy
- Visible "Updated: [date]" near title
- TL;DR or Key Takeaways at top
FAQ Schema Template
Add questions based on their pain points:
{
"@type": "Question",
"name": "How does Mediar handle selector maintenance?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Mediar uses AI to locate UI elements by their visual appearance and context, not brittle selectors. When Chrome updates or the DOM changes, the AI adapts automatically."
}
}
Schema Types by Page
| Page Type |
Recommended Schema |
| ABM Landing Page |
Article + FAQPage |
| Compare pages |
ComparisonTable or ItemList |
| Case studies |
Article with author, datePublished |
| How-to content |
HowTo schema |
| Solutions pages |
Article or Service schema |
Resources
- Anti-AI detection research: https://octet.design/journal/how-to-detect-ai-content/
- SEO/AEO guide:
C:\Users\User\SEO & AI Search Optimization Cras.txt
- Existing landing pages to reference:
app/compare/ directory
- Lead capture component:
components/landing/lead-capture-modal.tsx
- PostHog setup: See
posthog skill
1---2name: abm-landing-page3description: Create highly personalized landing pages for specific prospects that maximize conversion while avoiding AI detection patterns.4---5
6---
7name: abm-landing-page
8description: Create personalized ABM (Account-Based Marketing) landing pages for specific prospects. Takes a LinkedIn URL, analyzes their background, and creates a targeted landing page that feels authentic (not AI-generated). Trigger words: "create landing page", "personalized page", "abm", "prospect page", "target page for"
9allowed-tools: Bash, Read, Write, Edit, WebFetch, WebSearch, Task
10---
11
12# ABM Landing Page Skill
13
14Create highly personalized landing pages for specific prospects that maximize conversion while avoiding AI detection patterns.
15
16## Workflow
17
18### Step 1: Profile Analysis
19
20Given a LinkedIn URL, extract:
21
221. **Current role & company** - What do they do day-to-day?
232. **Past experience** - What tools/platforms have they used?
243. **Pain points** - Based on job descriptions, what problems do they face?
254. **Industry jargon** - What specific terms would they use?
265. **Certifications** - What credentials do they have?
27
28Use the LinkedIn profile to understand their world deeply.
29
30### Step 2: Create Segment-Based URL
31
32**NEVER use the person's name in the URL.** Create a segment that looks like a category page:
33
34| Bad | Good |
35|-----|------|
36| `/for/jon` | `/for/uipath-certified` |
37| `/for/sarah-smith` | `/for/rpa-consultants` |
38| `/for/john-doe` | `/for/enterprise-it-leaders` |
39
40The URL should look like it's targeting a role/segment, not an individual.
41
42### Step 3: Content Guidelines
43
44#### DO:
45- Use industry-specific jargon only insiders would know
46- Reference specific tools/products they've used (e.g., `idx_aaname`, `DU model`, `Orchestrator`)
47- Write conversational, slightly imperfect copy
48- Vary sentence length and structure
49- Include specific scenarios ("Saturday 2am. The upgrade failed.")
50- Use casual language ("Classic.", "Ship it and hope.")
51
52#### DON'T:
53- Use emojis or icon grids
54- Use buzzwords like "10x", "revolutionary", "transform", "self-healing"
55- Use repetitive sentence structures
56- Use overly polished, perfect prose
57- Use generic marketing speak
58- Mention the person's name anywhere on the page
59
60### Step 4: Page Structure
61
62```
63app/for/[segment-name]/
64 page.tsx # Server component with metadata + JSON-LD schema
65 client.tsx # Client component with UI
66```
67
68#### page.tsx Template (with SEO/AEO optimizations)
69
70```tsx
71import { Metadata } from "next";
72import SegmentPageClient from "./client";
73
74export const metadata: Metadata = {
75 title: "For [Segment] | Mediar",
76 description: "[Short, casual description of the pain point]",
77 robots: "noindex, nofollow", // Private page - don't index
78};
79
80// JSON-LD Schema for AI/search crawlers
81const jsonLd = {
82 "@context": "https://schema.org",
83 "@type": "Article",
84 headline: "[Page headline]",
85 description: "[Description]",
86 datePublished: "2026-01-20",
87 dateModified: "2026-01-20",
88 author: { "@type": "Organization", name: "Mediar", url: "https://mediar.ai" },
89 publisher: { "@type": "Organization", name: "Mediar", url: "https://mediar.ai" },
90 mainEntity: {
91 "@type": "FAQPage",
92 mainEntity: [
93 // Add FAQ items based on their pain points
94 {
95 "@type": "Question",
96 name: "[Question they'd ask]",
97 acceptedAnswer: { "@type": "Answer", text: "[Direct answer]" },
98 },
99 ],
100 },
101};
102
103export default function SegmentPage() {
104 return (
105 <>
106 <script
107 type="application/ld+json"
108 dangerouslySetInnerHTML={{ __html: JSON.stringify(jsonLd) }}
109 />
110 <SegmentPageClient />
111 </>
112 );
113}
114```
115
116#### client.tsx Structure
117
118Use semantic HTML for AI crawlers:
119
120```tsx
121<article>
122 <header> {/* Hero section */}
123 <h1>...</h1>
124 <p>Updated <time dateTime="2026-01-20">January 2026</time></p>
125 </header>
126
127 <section> {/* TL;DR */}
128 <h2>TL;DR</h2>
129 <ul>...</ul>
130 </section>
131
132 <section> {/* Pain points */}
133 <h2>...</h2>
134 </section>
135
136 <section> {/* Comparison - use <table> not divs */}
137 <h2>...</h2>
138 <table>...</table>
139 </section>
140
141 <section> {/* Social proof */}
142 <h2>...</h2>
143 </section>
144
145 <section> {/* Demo/Video */}
146 <h2>...</h2>
147 </section>
148
149 <section> {/* CTA */}
150 <h2>...</h2>
151 </section>
152</article>
153```
154
155**Section Order:**
1561. **Header/Hero** - One punchy question about their main pain point + visible date
1572. **TL;DR** - 3-4 bullet key takeaways (AI loves this)
1583. **Pain Points** - 4-6 specific scenarios they'd recognize (no icons)
1594. **Comparison** - Their current tool vs Mediar (use `<table>`, not divs)
1605. **Social Proof** - Testimonials from similar roles
1616. **Demo/Video** - Concrete example relevant to their work
1627. **CTA** - Simple, low-commitment ask
163
164### Step 5: PostHog Tracking
165
166Track page views and CTA clicks with segment identifiers (not personal info):
167
168```tsx
169useEffect(() => {
170 if (posthog) {
171 posthog.capture("segment_page_viewed", {
172 page: "/for/[segment]",
173 segment: "[segment_identifier]",
174 });
175 }
176}, [posthog]);
177```
178
179---
180
181## Anti-AI Detection Checklist
182
183Before shipping, verify:
184
185- [ ] URL uses segment name, not person's name
186- [ ] No person's name appears anywhere on page
187- [ ] No emoji icons in content
188- [ ] No generic buzzwords (10x, revolutionary, transform, unlock, empower)
189- [ ] Sentence lengths vary significantly
190- [ ] Some sentences are short. Really short.
191- [ ] Industry jargon is specific and accurate
192- [ ] Copy has personality quirks (em-dashes, fragments, casual asides)
193- [ ] Transitions aren't too smooth/perfect
194- [ ] Specific scenarios beat generic benefits
195
196---
197
198## Example Pain Points by Role
199
200### UiPath Developer
201- Selector maintenance (`aaname`, `idx`, anchor elements)
202- Exception handling (try-catch everything)
203- Document Understanding training
204- Orchestrator updates/maintenance windows
205- Version compatibility issues
206- Teaching junior devs best practices
207
208### Power Automate User
209- Desktop flow reliability
210- Connection refresh issues
211- Premium connector costs
212- Flow run history limits
213- Debugging cloud flows
214
215### IT Manager (RPA)
216- Bot licensing costs ($420/bot/month)
217- Infrastructure overhead
218- Scaling attended vs unattended
219- Security/compliance concerns
220- Measuring ROI
221
222### Finance/Ops (End User)
223- Manual data entry between systems
224- Copy-paste errors
225- Month-end close delays
226- Report generation time
227- Audit trail requirements
228
229---
230
231## Copy Style Guide
232
233### Headers
234- Questions work well: "What if selectors just worked?"
235- Casual statements: "The stuff that eats your week"
236- Direct: "Same task, different approach"
237
238### Descriptions
239Write like you're talking to a colleague:
240
241**Too polished (AI-sounding):**
242> "Our advanced AI-powered automation platform revolutionizes enterprise workflow management through intelligent self-healing capabilities."
243
244**Better (human):**
245> "You know the drill. Chrome updates, your idx_aaname breaks. Someone touches the DOM, your anchor element vanishes. We got tired of it too."
246
247### CTAs
248Keep them casual:
249- "Book 15 min" (not "Schedule Your Personalized Demo Today")
250- "Or check the code" (not "Explore Our Open Source Repository")
251- "See how we handle it" (not "Discover How Our Platform Transforms Your Workflows")
252
253---
254
255## File Locations
256
257- Landing pages: `app/for/[segment]/`
258- Shared components: Use existing components from `components/`
259- Lead capture: Use `LeadCaptureModal` from `components/landing/lead-capture-modal`
260
261---
262
263## Quick Start
264
265When user provides a LinkedIn URL:
266
2671. Visit the profile and extract role, experience, skills
2682. Identify their likely pain points based on tools they've used
2693. Create segment name from their role (e.g., "uipath-certified", "rpa-consultants")
2704. Generate `page.tsx` and `client.tsx` in `app/for/[segment]/`
2715. Run dev server and preview in browser
2726. Iterate based on feedback
273
274---
275
276---
277
278## SEO & AI Search Optimization (AEO)
279
280AI systems (ChatGPT, Perplexity, Claude, Google AI Overviews) now extract and cite content. Traditional SEO focused on ranking in Google's 10 blue links. Now you're also optimizing for:
281
282- AI Overviews (Google's AI-generated summaries)
283- ChatGPT/Bing Chat responses
284- Perplexity, Claude, Gemini and other AI assistants
285- Traditional search (still matters, but shrinking share of clicks)
286
287### Key Concepts
288
289#### 1. Answer Engine Optimization (AEO)
290
291AI systems extract and synthesize answers. Your content needs to be:
292- **Directly answerable** - Clear, concise statements that AI can quote
293- **Well-structured** - Headers, lists, tables that parse cleanly
294- **Authoritative** - Cited sources, credentials, E-E-A-T signals
295
296#### 2. What AI Models Prioritize
297
298- **Recency** - Fresh, updated content (datestamps matter)
299- **Specificity** - Detailed, niche expertise over generic coverage
300- **Consensus** - Information that aligns with authoritative sources
301- **Structure** - Schema markup, FAQs, clear hierarchies
302
303#### 3. Citation Optimization
304
305When AI cites sources, it favors:
306- Original research/data
307- First-hand expertise
308- Unique perspectives not found elsewhere
309- Well-organized reference content
310
311### Tactical Changes
312
313#### Content Format
314
315**OLD:** 2000-word SEO articles padded with fluff
316**NEW:** Dense, skimmable, fact-rich content with clear takeaways
317
318#### Structure That Works
319
320- Lead with the answer (inverted pyramid)
321- Use descriptive H2/H3s that could be standalone queries
322- Include "What is X" and "How to Y" sections
323- Add FAQ schema for common questions
324- Tables for comparisons (AI loves structured data)
325
326#### Technical Must-Haves
327
328- **Schema markup** - FAQ, HowTo, Article, Organization
329- **Fast load times** - AI crawlers have timeouts
330- **Clean HTML** - Semantic markup over div soup
331- **Indexable content** - No JS-only rendering for critical content
332
333### What's Declining vs Rising
334
335**Declining:**
336- Keyword stuffing (AI understands semantics)
337- Thin affiliate content (AI prefers primary sources)
338- Link farms/PBNs (less weight in AI training data curation)
339- Click-bait titles (AI evaluates content quality, not CTR)
340
341**Rising:**
342- Topical authority - Deep coverage of your niche
343- Brand mentions - Even without links, mentioned brands get cited
344- Community presence - Reddit, forums, discussions influence AI
345- Multi-format content - Video transcripts, podcasts feed AI training
346
347### Quick Wins
348
3491. Add FAQ sections with natural questions
3502. Update publish dates and content regularly
3513. Create comparison tables for your category
3524. Write definitive "What is X" explainers
3535. Get mentioned in Reddit/forum discussions
3546. Claim and optimize your knowledge panel
3557. Use structured data aggressively
356
357### Key HTML Tags Reference
358
359| Tag/Attribute | Purpose |
360|--------------|---------|
361| `<article>` | Semantic content wrapper |
362| `<time datetime="">` | Machine-readable dates |
363| `<h1>` - `<h3>` | Clear hierarchy (one H1) |
364| `<ul>`, `<ol>` | Lists AI can parse |
365| `<table>` | Comparisons, data |
366| `itemscope/itemprop` | Inline microdata |
367| `application/ld+json` | Structured data blocks |
368
369### Minimum Viable Implementation
370
371Every ABM landing page MUST have:
372
3731. One JSON-LD block per page (Article or FAQPage)
3742. Semantic HTML (`<article>`, `<section>`, `<header>`, `<time>`)
3753. Clear H1 → H2 → H3 hierarchy
3764. Visible "Updated: [date]" near title
3775. TL;DR or Key Takeaways at top
378
379### FAQ Schema Template
380
381Add questions based on their pain points:
382
383```json
384{
385 "@type": "Question",
386 "name": "How does Mediar handle selector maintenance?",
387 "acceptedAnswer": {
388 "@type": "Answer",
389 "text": "Mediar uses AI to locate UI elements by their visual appearance and context, not brittle selectors. When Chrome updates or the DOM changes, the AI adapts automatically."
390 }
391}
392```
393
394### Schema Types by Page
395
396| Page Type | Recommended Schema |
397|-----------|-------------------|
398| ABM Landing Page | Article + FAQPage |
399| Compare pages | ComparisonTable or ItemList |
400| Case studies | Article with author, datePublished |
401| How-to content | HowTo schema |
402| Solutions pages | Article or Service schema |
403
404---
405
406## Resources
407
408- Anti-AI detection research: https://octet.design/journal/how-to-detect-ai-content/
409- SEO/AEO guide: `C:\Users\User\SEO & AI Search Optimization Cras.txt`
410- Existing landing pages to reference: `app/compare/` directory
411- Lead capture component: `components/landing/lead-capture-modal.tsx`
412- PostHog setup: See `posthog` skill