2026-02-18 Marketing Backend Tasks

Describing three concrete workstreams:

1. distribution surface area
2. CRM + list infrastructure
3. publishing pipeline

Below is a structured, executable breakdown.

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1. Free Submission & Distribution Backlog

See ref/sharing-locations

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2. CRM + Mailing List Infrastructure

You are correct: this is an asset.

If you have ~15,000 DataHub contacts, even 1% engaged = 150 high-quality leads.

A. Immediate Tasks

• Audit where data lives:
  • Brevo
  • CSV exports
  • Old Mailchimp?
  • Spreadsheets?
• Export everything to a master CSV.
• Deduplicate.
• Tag by:
  • Source (DataHub, Datopian, client, event, inbound, etc.)
  • Date acquired
  • Engagement level (if known)

This can be partially automated with AI-assisted tagging.

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B. Lightweight CRM Options

You want database-first, flexible, AI-compatible.

Candidates:

• HubSpot (free tier surprisingly strong)
• Pipedrive
• Airtable (more DB-like)
• Close
• Brevo (if extending)

Given your AI workflows and technical stack, Airtable or HubSpot are probably the cleanest starting points.

Long term: you may build your own thin CRM layer, but do not block on that.

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C. Segmentation Strategy

At minimum:

• Cold archive
• Warm past leads
• Active clients
• Strategic contacts
• High-value partners

Goal: enable targeted reactivation campaigns.

Assign an owner. This must not be “everyone’s job.”

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3. Post / Launch Pipeline System

You need a repeatable pipeline:

A. Standard Flow

1. Publish core content (site / GitHub)
2. Announcement post (Twitter/X, LinkedIn)
3. Submit to directories
4. Post to 3–5 relevant communities
5. Email segmented list
6. Add to “evergreen mention” backlog

Document this in LAUNCH_CHECKLIST.md.