Go beyond LinkedIn: automated lead scraping and enrichment from Substack, communities, podcasts, and more

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The days of blasting generic LinkedIn InMails and hoping for the best are over. The real winners in sales are building AI-driven, automated lead generation engines that tap overlooked sources, enrich with context, qualify instantly, and engage across multiple channels, without feeling robotic.

We turned to experts to build an actionable and powerful playbook, perfect for capturing the intents signaled beyond LinkedIn.

Why look beyond LinkedIn?

LinkedIn is completely saturated.

Everyone’s fishing in the same pond, using the same scraping tools or enrichment playbooks.

Your prospects? They’re overwhelmed. Response rates drop. Competition skyrockets.

Your best leads might actually be elsewhere

Substack:
Newsletters reveal buyers’ interests. Scrape authors, engaged subscribers, or companies spotlighted in case studies.
Private communities:
Slack, Discord, Reddit, FB groups: goldmines for finding niche operators (founders, growth marketers, sales leaders…) & decision-makers sharing pain points in real time.
Podcasts:
Guests, hosts, and even frequent listeners signal very specific problems or growth stages. Perfect for automated lead generation with ultra-relevant hooks.
Product Hunt & Indie Hackers:
Startups actively launching, looking for traction, or hiring. Rich data for lead extraction with context no LinkedIn scraper will give you.
X (Twitter):
Threads about funding, hiring, GTM wins, or specific tools hint at warm, high-intent prospects.

Tutorial: step-by-step multichannel lead generation workflow

Step 1: capture Intent signals from hidden lead sources

Let’s move beyond typical LinkedIn lead scraping. Your best prospects leave footprints everywhere, you just need the right lead scraping tools and smart workflows to find them.

Tools stack:
- Native APIs (Substack, Podcast Index, Product Hunt)
- Custom scraping tools (ethical, public data only, stay compliant)
- Google Search API for mentions across the web

Why it works:

This gives you automated lead generation pipelines that go where your competitors don’t. That means less inbox fatigue, more relevant conversations, and higher response rates.

Step 2: centralize data into a lead table

Use n8n to automate everything:

Pull data from each API or scraper.
Clean it: normalize names, deduplicate, merge fields from multiple sources.
Store it all in Airtable or Google Sheets.

Best practice:

Each row = one unique lead with tags like “Substack subscriber,” “Product Hunt launch,” or “Podcast guest.” That context becomes fuel for hyper-personalized outreach later.

Step 3: enrich leads with contact & context info

Don’t settle for just a name and social handle. Use AI to instantly enrich leads with job titles, company info, tech stack, and social profiles.

Here’s your enrichment process:

In La Growth Machine, import your Lookalike Audience list and click “Enrich Leads”.
Use your enrichment credits to gather comprehensive prospect data:
- Verified emails with double verification (via 9 top-tier providers)
- Complete LinkedIn profiles (job title, company, industry, location, headline)
- Company intelligence (domain, size, recent activity)
Segment your enriched audience for maximum impact:
- High-priority targets: Verified email + exact job title match
- LinkedIn-first prospects: Strong profile data but no email found
- Nurture candidates: Partial matches worth long-term engagement

At this stage:

You have a clean, sales-ready database that goes way beyond typical lead scraping tools, already enriched and primed for action.

LGM’s Lookalike Search

Find new leads

Step 4: implement your qualification & scoring process

Not every lead deserves the same effort. Let your AI handle first-pass qualification.

Run each lead through GPT (or Claude) in n8n:
- Example prompt:

“You are a sales assistant for a SaaS company. Our ICP: SaaS founders, US/Canada, <$10M ARR, mentioned on Substack, Product Hunt, or podcasts. Does this lead match? Score 1–10, include match status and a short why.“

Results:
- GPT returns a JSON with score, match yes/no, and reasoning.
- Stored directly back into your Airtable/Sheet for smart routing.

Why it matters:

Your automated lead generation now auto-prioritizes who moves forward, so your human team only focuses on high-fit prospects.

Step 5: generate hyper-personalized icebreakers

Turn raw context into gold.

GPT reads signals like:
- “Mentioned Notion in a recent podcast.”
- “Launched on Product Hunt last month.”
- “Subscribed to Lenny’s Newsletter.”
It then writes a 1-line icebreaker.

e.g. “Saw your launch of FinOpsFlow on Product Hunt, congrats on top #3 product of the day!”
Stored in your lead table via n8n.

Every outreach touch feels handcrafted, even if it’s part of a scalable, AI lead enrichment system.

Step 6: launch multichannel campaigns in La Growth Machine

Import your leads

Go to Leads → Import leads → Import CSV
Upload your final CSV (or connect via API) directly into La Growth Machine
Output: Every lead now carries comprehensive data: first name, company, title, LinkedIn

URL, icebreaker, match score, all prepared for hyper-targeted sequencing

Create your sequence:
- LinkedIn visit → follow → like → connect (with icebreaker) → DM → email → even a Twitter DM if they’re active there.
- Use variables like [first name], [company name], [source], [icebreaker]
  - Lead variables (in purple) are information you’ve gathered on your leads after enriching their profile with LGM.
  - Identity variables (in yellow) are information on the person sending the message (you).
- You can use “Save & Preview” to check if your variables match your leads’ information perfectly.
Logic & testing:
- Add waits, smart branching (respond → nurture, no response → escalate to next channel).
- Run A/B tests on subject lines or opening lines, optimize on real engagement.

End result:

A sequence that executes multichannel outreach with precision, powered by LGM and your always-fresh data.

Step 7: monitor, optimize, repeat

Track all conversations, responses, status changes.
Continuous learning:
- Adjust GPT scoring logic based on who actually closes.
- Clone your best-performing flows for new verticals.

Always-on:

Your lead scraping, AI lead enrichment, and outreach now run 24/7, growing your pipeline without manual chase.

Sample stack & lightweight costs

Tool	Purpose	Est. cost/month
n8n	Automation + orchestration	$20
Substack / PH / Podcast APIs	Pull fresh data from alt sources	$0–$20
LGM	Lead scraping + enrichment tools	$70–$180
GPT-4 API	Scoring + icebreakers	$30
LGM	Multichannel outreach execution	$60

Takeaways

By combining lead scraping, AI lead enrichment, and smart automation, you’re crafting a pipeline that’s sharper, more relevant, and constantly self-improving.

Remember: you don’t have to build a perfect system from day one. Start small, automate one piece, test one sequence, enrich one dataset. Then layer on more channels, smarter scoring, and advanced triggers.

Because the truth is, scaling isn’t about sending more messages. It’s about sending the right message to the right person at the right time , powered by a stack that works even while you sleep. That’s how you close more deals, with less effort, and stay miles ahead of sales teams still stuck copy-pasting cold DMs.