Social Media Auto-Publisher & Content Scheduler
Automated content pipeline that repurposes one long-form piece into 8 platform-specific posts, schedules them, and reports engagement — saving 20 hours of agency work per week.
The Problem
A digital marketing agency managing 8 clients was spending 20+ hours per week manually repurposing blog posts and videos into social media content for each client. The process was: read the long-form content, rewrite for each platform tone, resize creatives, schedule manually, and pull weekly reports. With 8 clients posting to 5–6 platforms each, it was unsustainable.
Our Solution
An n8n automation pipeline triggered when a new piece of long-form content is added to Notion. GPT-4o repurposes it into 8 variants: a LinkedIn thought-leadership post, 3 tweet-thread posts, a Facebook post, a concise Instagram caption, a short-form WhatsApp status, and a newsletter snippet — each matched to the client's tone-of-voice document. The posts are scheduled at optimal times via the respective platform APIs and engagement data flows into a Notion reporting dashboard weekly.
Our Approach
Tone-of-Voice Capture
For each client, built a tone-of-voice document (10 examples + style guide) that feeds the GPT-4o system prompt for consistent brand voice.
Content Ingestion
Notion database trigger in n8n: when a "Ready to Publish" blog post is added, the workflow fires automatically.
GPT-4o Repurposing
A single GPT-4o call with a structured output schema returns all 8 variants in one shot, each formatted for its platform.
Multi-Platform Scheduling
Meta Graph API for Facebook/Instagram, LinkedIn API for LinkedIn, Twitter v2 API for X, WhatsApp Business API for status updates.
Analytics Loop
Weekly n8n workflow pulls engagement metrics from each platform and writes to the client's Notion dashboard.
The Results
| Metric | Before | After |
|---|---|---|
| Content Production Time | 2.5 hrs/piece | 8 minutes |
| Posts per Client/Week | 5–8 posts | 25–35 posts |
| Agency Capacity | 8 clients max | 20+ clients (same team) |
| Brand Consistency | Inconsistent | Tone-matched per client |
Tech Stack
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