Case Study - 5+ hrs/week saved with an automated email-to-CRM pipeline.

Bonafide.fm's team was manually reading podcast nomination emails and creating CRM contacts one by one. We built an AI pipeline that scans the inbox, classifies threads, extracts nominees, enriches them, and creates Folk CRM contacts automatically.

Client
Bonafide.fm
Year
Service
Email Automation, AI Classification, CRM Integration, Lead Enrichment

Overview

Bonafide.fm receives 10 to 20 podcast guest nominations via email every week. The team was manually reading each thread, extracting nominee details, and creating CRM contacts one by one — a repetitive process that consumed 5+ hours every week and introduced gaps whenever threads were skimmed or overlooked.

The system runs daily, scanning the inbox for any email thread containing nomination-related language. An AI classifier reads each thread and determines whether it contains actual nominee names or is just a scheduling conversation, a LinkedIn post coordination, or general back-and-forth. Only threads with real nominations pass through.

A second AI layer extracts every nominee's name, LinkedIn URL, email address, and company from both the plain text and the HTML body of the email — catching hyperlinks hidden behind names. Each nominee is enriched through Apollo to pull in job title, company size, and verified contact info. If Apollo doesn't return a match, the system falls back to Clay for enrichment.

The enriched contact is created in Folk CRM with all details populated, the source contact is linked, and the original email gets labeled so it's never processed twice.

What we did

  • n8n Workflows
  • OpenAI
  • Apollo.io
  • Clay
  • Folk CRM
  • Email Processing
Hours saved per week
5+
Nominations missed
0
Auto-enriched CRM contacts
100%

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