// 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"
Add and manage Lottie animations in the website using LottieFiles. Auto-activates when user asks about animations, lottie, motion graphics, or animated icons. Trigger words: "lottie", "animation", "animated icon", "motion graphic", "add animation", "lottiefiles"
Query PostHog for product analytics, create insights, dashboards, and track AI referral traffic. Auto-activates when user asks about analytics, user behavior, funnels, retention, AI traffic, or dashboards. Trigger words: "check posthog", "create insight", "analytics", "user behavior", "AI traffic", "dashboard", "funnel", "retention"
Create highly personalized landing pages for specific prospects that maximize conversion while avoiding AI detection patterns.
Given a LinkedIn URL, extract:
Use the LinkedIn profile to understand their world deeply.
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.
idx_aaname, DU model, Orchestrator)app/for/[segment-name]/
page.tsx # Server component with metadata + JSON-LD schema
client.tsx # Client component with UI
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 />
</>
);
}
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:
<table>, not divs)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]);
Before shipping, verify:
aaname, idx, anchor elements)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."
Keep them casual:
app/for/[segment]/components/LeadCaptureModal from components/landing/lead-capture-modalWhen user provides a LinkedIn URL:
page.tsx and client.tsx in app/for/[segment]/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 systems extract and synthesize answers. Your content needs to be:
When AI cites sources, it favors:
OLD: 2000-word SEO articles padded with fluff NEW: Dense, skimmable, fact-rich content with clear takeaways
Declining:
Rising:
| 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 |
Every ABM landing page MUST have:
<article>, <section>, <header>, <time>)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."
}
}
| 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 |
C:\Users\User\SEO & AI Search Optimization Cras.txtapp/compare/ directorycomponents/landing/lead-capture-modal.tsxposthog skill