Turn Your Inbox into CRM Intelligence — Export Email Data to Salesforce, HubSpot, and Pipedrive

#tutorial #python #devops #productivity

Your CRM is only as good as the data in it. Most sales teams lose deals because contacts go stale, emails aren't logged, and relationship context lives in individual inboxes instead of the CRM.

Manually copy-pasting email data into Salesforce, HubSpot, or Pipedrive doesn't scale. Native email sync features from CRM vendors are expensive add-ons. Building custom integrations against Gmail API or Microsoft Graph takes weeks.

Nylas CLI extracts structured email and contact data from any provider (Gmail, Outlook, Exchange, Yahoo, iCloud, IMAP) and exports it in formats every CRM can ingest — CSV for bulk import, JSON for API sync, or direct API calls.

Install and authenticate

brew install nylas/nylas-cli/nylas
nylas auth login

Full setup: Getting Started with Nylas CLI

Extract contacts from your inbox

Every email contains contact data. Pull it out:

# Get all unique senders from recent emails
nylas email list --json --limit 500 | \
  jq -r '.[].from[0] | "\(.email),\(.name // "")"' | \
  sort -u > contacts.csv

# Get contacts with email frequency (who emails you most)
nylas email list --json --limit 1000 | \
  jq -r '.[].from[0].email' | sort | uniq -c | sort -rn > contact-frequency.csv

For advanced contact enrichment from email signatures: Parse Email Signatures for Contact Enrichment

Group emails by company domain

Identify which organizations email you most:

# Extract corporate domains (filter out freemail)
nylas email list --json --limit 500 | \
  jq -r '.[].from[0].email' | \
  awk -F@ '{print $2}' | \
  grep -vE 'gmail|yahoo|hotmail|outlook\.com' | \
  sort | uniq -c | sort -rn | head -20

Full guide: Group Inbox by Corporate Email Domain

Export to Salesforce

CSV import (bulk)

# Generate Salesforce-compatible Lead CSV
nylas email list --json --limit 500 | \
  jq -r '.[].from[0] | [.name // "", .email, (.email | split("@")[1])] | @csv' \
  > salesforce-leads.csv

# Add headers
sed -i '1i\Name,Email,Company' salesforce-leads.csv

Upload via Salesforce Data Import Wizard or Data Loader.

API sync (real-time)

import subprocess
import json
import requests

# Fetch recent contacts from email
result = subprocess.run(
    ["nylas", "email", "list", "--json", "--limit", "100"],
    capture_output=True, text=True
)
emails = json.loads(result.stdout)

# Upsert to Salesforce
for email in emails:
    sender = email["from"][0]
    requests.post(
        "https://your-instance.salesforce.com/services/data/v58.0/sobjects/Lead/",
        headers={"Authorization": f"Bearer {SF_TOKEN}"},
        json={
            "Email": sender["email"],
            "LastName": sender.get("name", "Unknown"),
            "Company": sender["email"].split("@")[1]
        }
    )

Full guide: Export Email Data to Salesforce

Export to HubSpot

# Upsert contacts to HubSpot
for email in emails:
    sender = email["from"][0]
    requests.post(
        "https://api.hubapi.com/crm/v3/objects/contacts",
        headers={"Authorization": f"Bearer {HUBSPOT_TOKEN}"},
        json={
            "properties": {
                "email": sender["email"],
                "firstname": sender.get("name", "").split()[0] if sender.get("name") else "",
                "lastname": sender.get("name", "").split()[-1] if sender.get("name") else "",
                "company": sender["email"].split("@")[1]
            }
        }
    )

Full guide: Export Email Data to HubSpot

Export to Pipedrive

Full guide: Export Email Data to Pipedrive

Export to Zoho CRM

Full guide: Export Email Data to Zoho CRM

Export to Dynamics 365

Full guide: Export Email Data to Dynamics 365

Build org charts from CC patterns

Who CCs whom reveals reporting lines. A manager is usually CC'd on reports from their team:

# Extract CC relationships
nylas email list --json --limit 500 | \
  jq -r '.[] | select(.cc != null) | 
    .from[0].email as $from | 
    .cc[].email as $cc | 
    "\($from) -> \($cc)"' | \
  sort | uniq -c | sort -rn

Full guide: Reconstruct Org Charts from Email CC Patterns

Score relationship strength

Not all contacts are equal. Measure relationship strength by email frequency, response time, and recency:

# Emails per contact in the last 30 days
nylas email list --after "30 days ago" --json --limit 1000 | \
  jq -r '.[].from[0].email' | sort | uniq -c | sort -rn

Full guide: Visualize Communication Patterns Between Organizations

Automate outbound with mail merge

Once your CRM data is enriched, send personalized outreach:

# Bulk send from CSV
while IFS=, read -r email name company; do
  nylas email send \
    --to "$email" \
    --subject "Quick question about $company" \
    --body "Hi $name, I noticed we've been exchanging emails..." \
    --yes
  sleep 2
done < outreach-list.csv

Full guide: CLI Mail Merge

For draft-based workflows with review steps: Automate Email Draft Creation

Build a fuzzy email autocomplete

Speed up email composition with contact autocomplete:

# Generate a contact frequency list for autocomplete
nylas email list --json --limit 2000 | \
  jq -r '.[].from[0] | "\(.name // "") <\(.email)>"' | \
  sort | uniq -c | sort -rn > ~/.email-contacts

Full guide: Build Shell-Integrated Email Autocomplete

Graph analysis with Neo4j

For advanced relationship mapping, import email data into a graph database:

# Export sender-recipient pairs for Neo4j import
nylas email list --json --limit 1000 | \
  jq -r '.[] | .from[0].email + "," + (.to[0].email // "unknown")' \
  > email-edges.csv