Personalized 1000 Cold Emails Using This

Personalized 1000+ Cold Emails Using THIS AI System (FREE TEMPLATE)

Before you run this

By default this skill uses local CSV files for its data (input and output) — nothing to connect, works offline, your data stays on your machine. The CSVs live next to the skill in ./data/ (input: data/input.csv, output: data/output.csv), or point it at any path you like.

If you'd rather read/write a Google Sheet instead, just say so and I'll switch you over. It's a one-time setup: you'll paste a Google service-account JSON (or authorize once), share your Sheet with that account's email, and give me the Sheet URL. After that it behaves exactly the same, just backed by your Sheet. Say "use Google Sheets" to start that, or "keep CSVs" (default) to just go.

What this does

Takes a list of Apollo/LinkedIn search URLs, scrapes hundreds of leads from each one (via Apify), filters to people who have both a company website and an email, then deep-crawls up to 3 internal pages per company website. Each page gets summarized by GPT-4.1. Those summaries get fed into a second GPT-4.1 call that writes a hyper-personalized two-paragraph multiline icebreaker for each lead — one that sounds like you actually read their site, because you did.

End result: data/output.csv with one row per lead, including first_name, last_name, email, website_url, headline, location, phone_number, and multiline_icebreaker. Import directly into Instantly, Smartlead, etc.

Flow at a glance:

1. Read search URLs from data/search_urls.csv
2. Call Apify scraper for each URL (returns leads with org data)
3. Filter: keep only leads with both organization.website_url and email
4. For each lead — scrape their homepage, extract all internal links, normalize to relative paths, deduplicate, take up to 3
5. Fetch each sub-page HTML, convert to Markdown
6. Summarize each page with GPT-4.1 (structured JSON {"abstract": "..."})
7. Aggregate all abstracts for the lead
8. Generate multiline icebreaker with GPT-4.1 (structured JSON {"icebreaker": "..."})
9. Write output row to data/output.csv

When to use this

• You're running a cold email campaign and want icebreakers that actually don't sound like icebreakers
• You have 100-1000+ leads to personalize and doing it by hand isn't realistic
• You want a fully local, auditable pipeline you can tune (swap models, change prompts, adjust crawl depth)

Required env vars

OPENAI_API_KEY=your_openai_api_key
APIFY_API_TOKEN=your_apify_api_token

Add to .env or export in your shell. No Google OAuth needed by default.

Step-by-step procedure

Step 1 — Populate search URLs

Edit data/search_urls.csv. One row per search. Column: URL.

These are Apollo or LinkedIn Sales Navigator search URLs that the Apify actor knows how to paginate. Example: an Apollo search URL filtered to "CEO" + "web development agency".

Step 2 — Scrape leads

python scripts/scrape_leads.py --input data/search_urls.csv --output data/leads_raw.csv

Calls the Apify jljBwyyQakqrL1wae actor for each URL (synchronous, blocks until done). Writes all returned leads to data/leads_raw.csv. Skips any lead missing organization.website_url or email.

Fields written: first_name, last_name, email, headline, city, country, organization_website_url.

Step 3 — Generate icebreakers

python scripts/generate_icebreakers.py --input data/leads_raw.csv --output data/output.csv

Loops over each lead. For each one:

• Scrapes their homepage
• Extracts all <a href> links, normalizes to root-relative paths, deduplicates
• Fetches up to 3 internal sub-pages
• Converts each page's HTML to Markdown
• Summarizes each page with GPT-4.1 (one API call per page)
• Aggregates all abstracts, sends to GPT-4.1 to generate the multiline icebreaker
• Appends the result row to data/output.csv

Errors on individual lead pages are skipped (won't crash the whole run). Leads where all pages fail get an empty icebreaker field flagged as scrape_error.

Step 4 — Import to your outreach tool

data/output.csv columns: first_name, last_name, email, website_url, headline, location, phone_number, multiline_icebreaker.

The multiline_icebreaker field contains the full two-paragraph opener, newlines included (CSV-quoted). Map it as a custom variable in Instantly/Smartlead.

Node map (original n8n workflow)