Jose Wenzel  /  Case study

LinkedIn to verified email to AI icebreaker, ready for Instantly in one command.

An outbound lead pipeline that filters for verified emails only and ships a campaign-ready CSV with per-lead personalization. No more bounce-rate hits and no more generic merge tags.

The problem

Most cold email setups send to unverified emails (high bounce rate, sender reputation tanks within a week) and use generic merge tags like {{first_name}} that any recipient can see is automated. The agency wanted a higher-quality outbound source than typical Apollo scrapes, with real personalization per lead and a verified email on every row.

What I built

  1. LinkedIn Sales Nav scraping

    Takes a Sales Nav search URL and scrapes results through Vayne. Pulls clean profile data, not just names.

  2. Email verification

    Runs each lead through AnyMailFinder and drops anything not verified. The CSV that ships is 100% verified, so bounces stay near zero and sender reputation holds.

  3. AI icebreaker generation

    Claude reads each lead's profile and writes a one-line personalized icebreaker that references something specific (a recent post, a job change, a company milestone), not a generic compliment.

  4. Casualized merge variables

    Generates short job title, city, and casual company name for natural-feeling merge tags. "Tom at Acme in Austin" reads human, "Tom at Acme Industries, LLC" reads like a bot.

  5. CSV export

    Outputs a single Instantly-ready CSV with email, firstName, companyName, personalization, city, and title_short. Drop it into Instantly and the campaign launches.

What it ships

100%

Verified emails on every row (unverified leads drop before export)

1-line

Per-lead AI icebreaker referencing something specific about the lead

1

Command from search URL to Instantly-ready CSV. No manual cleanup.

Stack

Claude CodePythonVayne APIAnyMailFinder APIAnthropic API

Want a clean outbound pipeline for your business?

Email JW