The argument in one line.
Posting volume tells you nothing about audience quality; the only signal that matters is whether the people commenting on your content match the buyer profile you actually want to reach.
Read if. Skip if.
- You post on LinkedIn regularly but cannot tell whether your audience is buyers or competitors watching you.
- You have an offer and want data on which content angles attract the right commenters.
- You are learning Claude Code and want a practical end-to-end project that produces something immediately usable.
- You are willing to spend roughly $5-6 on Apify scraping credits to get 30 days of real audience data.
- You do not have an existing LinkedIn presence with enough comment history to analyze.
- You want strategy theory rather than a hands-on screen-share build.
The full version, fast.
Most LinkedIn creators optimize hooks when the real problem is audience mismatch. This video walks through a five-step Claude Code pipeline: define your ICP from your offer description, scrape 30 days of posts and comments via Apify, classify every commenter as buyer/peer/creator/competitor/unknown, render a branded HTML dashboard, and generate a content brief with three angles to lean into and three to cut. The live result: 44% buyer commenters, 40% competitors, and the discovery that format was not the problem.
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01 · Claude Code Reads Your LinkedIn
Hook and promise: Claude analyzed 1,500 posts and identified which ones to stop writing.

02 · Setting Up Claude Code
Open Claude Code desktop app, create a new project folder called LinkedIn Analyzer.

03 · The Full Build Game Plan
Six-step plan: define ICP, scrape posts and comments, analyze job titles, classify against ICP, render dashboard, extract content patterns.

04 · How to Define Your ICP
ICP Discovery prompt: feed Claude your offer description, it returns buyer psychology, trigger event, exact language, negative ICP.

05 · How to Set Up Apify
Apify is a scraper marketplace with a Claude Code MCP connector. Free $5 per week. Connect via the connectors menu.

06 · Scraping Posts and Comments
30 days of LinkedIn posts and comments scraped to CSV. Result: 45 posts, 1,586 comments, 1,135 unique commenters. Cost: $5.67.

07 · How to Classify Commenters
Commenter Classifier prompt reads CSV, checks job title and bio against ICP, assigns BUYER/PEER/CREATOR/COMPETITOR/UNKNOWN with confidence.

08 · Analyzing the Audience Results
44% buyers, 40% competitors and peers. Hooks landing in the industry echo chamber. Fix: shift CTAs away from founder-flex content.

09 · How to Build the Dashboard
Audience Dashboard prompt: buyer % headline, commenter breakdown chart, best/worst posts by buyer engagement, 30-day trend line. Single HTML file.

10 · Adding Your Design System
A design system file (bold retro typography, orange/cream/black) passed to Claude Code so the dashboard renders on-brand.

11 · Reviewing the Live Dashboard
42% ICP engagement displayed. Full post-performance table, buyer trend line, best/worst posts with audience split percentages.

12 · How to Generate Content Brief
Content Brief Generator: top 5 vs bottom 5 posts by buyer engagement, pattern extraction, 3 angles to lean into, 3 to cut, reusable template appended to the dashboard.

13 · Content Angles and Template
Key finding: format was right, messaging was wrong. Beginner language attracts buyers; flexing repels them. Draft Monday post generated.

14 · How to Get All Prompts
CTA: all prompts and pre-built dashboard inside Claude Code Club ($9/mo on Skool).
Lines worth screenshotting.
- Optimizing hooks when you have an audience-mismatch problem is like fixing your delivery when no one wants the product.
- Classifying commenters by job title and bio rather than engagement count is the only way to separate buyers from spectators.
- A single $5 Apify scrape of 30 days of LinkedIn data produces 1,135 unique leads worth far more than the cost if even one converts.
- 44% buyer commenters sounds good until you notice 40% are competitors and peers watching the space.
- Format rarely explains LinkedIn performance gaps; the variable that actually moves buyer engagement is who you are speaking to.
- Beginner-facing copy outperforms founder-flex copy for attracting paying customers from educational communities.
- A design system file passed to Claude Code lets it generate branded HTML dashboards and landing pages without manual CSS work.
- Reverse-engineering your ICP from your offer description forces Claude to surface the exact language buyers use to describe their own problem.
- The negative ICP is as important as the positive one because those people are already in your comments distorting your signals.
- A content brief generated from your own data is more actionable than a generic strategy session because it is grounded in what already worked.
- The pipeline here is reusable monthly, turning audience quality into a trackable metric rather than a gut feeling.
- Writing for the person who has not started yet, rather than for your peers, is a concrete content directive that removes guesswork about what to post next.
Your comments are a lead list you have never mined.
Most creators optimize the wrong variable -- post format stays consistent while the audience receiving it drifts further from people who will ever pay.
- A hook built around a specific surprising data point creates immediate credibility and sets a clear expectation for what the video will deliver.
- Showing the complete plan before executing any step reduces anxiety because the scope feels known and the destination is visible.
- Reverse-engineering your ICP from your offer forces you to surface the trigger event: what happened in the last 30-90 days that made someone ready to buy now.
- The negative ICP field prevents the mistake of writing content that attracts people who look like buyers but will waste your time.
- 1,135 unique commenters from 45 posts is a real lead pool -- most creators treat these people as engagement metrics rather than as identifiable potential customers.
- Classification at scale reveals the ratio of buyers to industry watchers, which is invisible when you look at engagement totals alone.
- 44% buyers with 40% competitors is a specific actionable finding -- it tells you the hooks are working but the CTA framing is pulling the wrong crowd.
- A self-contained HTML file with embedded data is portable and shareable without any server or database -- Claude Code can generate it in one prompt given a CSV and a design file.
- Comparing your top-5 and bottom-5 buyer-engaging posts surfaces the variable that actually matters -- the contrast is what you cannot see by reading individual posts.
- A reusable post template modeled on your own winners is more reliable than a generic template because it is tuned to your voice and your audience.
- Beginner-facing language removes the primary psychological barrier to buying from an education offer -- the fear of being too new is the objection, not price.
- Writing for the person who has not started yet is a concrete directive that removes guesswork about what to post next.
Terms worth knowing.
- ICP (Ideal Customer Profile)
- A precise description of the person most likely to buy your offer, defined by job title, life situation, trigger event, and exact language they use to describe their problem.
- Apify
- A marketplace of pre-built web scrapers (called Actors) that can pull structured data from LinkedIn, Instagram, YouTube, and thousands of other sites via API.
- MCP connector
- A Model Context Protocol integration that lets Claude Code call external tools like Apify scrapers directly from the chat without leaving the interface.
- Commenter classifier
- A Claude prompt that reads a CSV of commenters and assigns each one a category (BUYER, PEER, CREATOR, COMPETITOR, UNKNOWN) based on job title and bio against a stored ICP.
- Negative ICP
- People who superficially resemble your ideal buyer but will not convert, typically peers or consultants in the same industry. Identifying them prevents wasted sales energy.
- Design system
- A file containing fonts, colors, spacing rules, and typographic templates that Claude Code can read and apply when generating HTML assets, ensuring on-brand output without manual styling.
Things they pointed at.
Lines you could clip.
“You might think you need better hooks to reach buyers, but the real problem is you do not know which posts are already attracting them.”
“Your content is working as a buyer magnet -- 44% of everyone who comments fits your ICP, but a striking 40% are competitors and peers.”
“When I flex about running my business, buyers actually collapse.”
“You have saved 40 AI tutorials this month, you have opened zero. There is only one thing that works.”
Word for word.
Don't just watch it. Burn it in.
See every word as it's spoken — crank it to 2× and still catch all of it. The same dual-channel trick behind Amazon's Kindle + Audible.
The bait, then the rug-pull.
What if the reason your LinkedIn posts are not converting is not the hook -- it is that 40% of your commenters are competitors watching you? This video builds the pipeline to find out: a Claude Code-powered audience quality dashboard that classifies every commenter against your ICP and hands you a content brief before Monday.
Named ideas worth stealing.
ICP Discovery Prompt
- Who is most likely to buy
- Job title and life situation
- Trigger event (last 30-90 days)
- Exact language they use
- What they have already tried
- Negative ICP
- Single sentence they would use to describe what they want
Feed Claude your offer description; it reverse-engineers a full buyer psychology profile including the exact words your prospect uses to describe their own problem.
Commenter Classifier
- BUYER
- PEER
- CREATOR
- COMPETITOR
- UNKNOWN
Reads a CSV of LinkedIn commenters, checks each person against the ICP, assigns a classification with confidence level and one-line reason.
Content Brief Generator
- Top 5 posts by buyer engagement
- Bottom 5 posts by buyer engagement
- What buyer-attracting posts share
- What low-performing posts share
- 3 angles to lean into
- 3 content types to cut
- Reusable post template
Compares your best and worst buyer-attracting posts to extract patterns, then generates a content brief and reusable template modeled on your actual winners.
How they asked for the click.
“If you want access to all the prompts I used today and the HTML dashboard along with all the lessons and done-for-you skills, just check the link in the description.”
Soft sell at end only. Claude Code Club at $9/mo on Skool. No mid-roll pitch. Clean execution.


































































