abm-landing-page - SKILL.md Agent Skill

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:

URL uses segment name, not person's name
No person's name appears anywhere on page
No emoji icons in content
No generic buzzwords (10x, revolutionary, transform, unlock, empower)
Sentence lengths vary significantly
Some sentences are short. Really short.
Industry jargon is specific and accurate
Copy has personality quirks (em-dashes, fragments, casual asides)
Transitions aren't too smooth/perfect
Specific scenarios beat generic benefits

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