How We Automated a Full Content Marketing Engine with Ghost, Make, AI & Social Media
Managing consistent content marketing is hard.
It takes time, coordination, and a lot of manual steps from drafting blog posts to distributing them across channels and optimizing them for SEO.
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In this case study, we show how we automated the entire content pipeline from AI-generated drafts to SEO-indexing using Ghost, Make, AI, and webhooks.
The Problem
Our client, a growing SaaS company, had a content strategy but lacked consistency. The bottlenecks:
- Blog articles weren’t published on time
- Social posts were written manually (or forgotten)
- SEO indexing was delayed
- The team spent more time on logistics than strategy
They needed a content machine not a content checklist.
The Solution: A Modular, Automated Content Engine
We designed a system using:
- Ghost CMS — for blazing-fast publishing & SEO control with Ghost 6
- Make (Integromat) — for automating each step
- OpenAI & Claude — for article drafts, meta descriptions, social captions
- Webhooks + APIs — to push content live to social media & indexers
- IndexNow — to instantly notify search engines like Bing & Yandex
Step-by-Step Automation Workflow
1. AI-Powered Draft Generation
- A marketer inputs a topic into Airtable or Notion
- A Make scenario triggers OpenAI to generate:
- Blog draft in Markdown
- Meta title & description
- SEO-optimized slug
- Twitter/LinkedIn post copy
2. Publishing via Ghost API
- Draft is posted to Ghost in “Draft” mode
- Content editor reviews and hits “Publish” manually or via webhook
3. Social Distribution (Automated)
- Once the post goes live, Make detects the webhook
- Automatically posts to:
- LinkedIn Company Page
- Optional: Buffer / Later integrations for scheduling
4. Search Engine Notification via IndexNow
- Post URL and metadata are instantly pushed to IndexNow API
- Search engines are notified immediately no crawling delay
5. Analytics & Archiving
- Make writes the post data back to Airtable for tracking
- CTR, shares, and index status are monitored automatically
Results After 30 Days
| KPI | Before | After |
|---|---|---|
| Avg. Time to Publish an Article | 6–8 hours | 45 minutes |
| Articles Published / Month | 4 | 16 |
| Social Shares per Article | <5 | 30+ |
| Indexing Time | 2–3 days (avg.) | Instant (via IndexNow) |
| SEO Click-Through Rate | 1.8% | 4.5% |
The team now has a repeatable content engine with built-in scale, quality control, and visibility.
Why This Works
- Ghost is clean, fast, and SEO-native
- Make lets us connect tools and trigger flows without code
- AI speeds up ideation without replacing human judgment
- IndexNow puts SEO visibility on autopilot
- Social webhooks eliminate repetitive marketing actions
This system is lean, modular, and works with small or large content teams.
Scaling Content Automation: Lessons Learned
Building a modular content engine was not just about connecting Ghost, Make and AI. It also forced us to rethink how marketing teams actually operate. Automation works best when paired with a disciplined workflow, because technology alone does not fix broken processes.
One of the most important lessons we learned is the value of structured inputs. If the raw material is inconsistent, the automation chain will amplify that inconsistency. For example, a blog outline without a clear SEO focus keyword can result in scattered social posts and diluted search performance. By enforcing a standard input format in Airtable, we created guardrails that keep every piece of content aligned with strategy.
Another key takeaway is the balance between automation and human oversight. While AI can generate first drafts of SEO titles or LinkedIn captions, human editors remain critical for tone of voice, brand alignment and compliance checks. Automating 80% of the work still requires 20% of thoughtful review. This hybrid model is where teams gain the most efficiency without sacrificing quality.
Scaling also required monitoring. We implemented dashboards that show not just which posts went live, but also which automations fired, which social posts succeeded and which failed. Visibility builds trust in the system and allows for quick troubleshooting when something breaks in the chain. Without this monitoring layer, teams may lose confidence in automation and fall back to manual work.
Finally, we realized that automation changes team culture. Writers began thinking in terms of modular assets rather than finished blog posts. A single article was now an input for a web post, a LinkedIn update, a Twitter thread and a newsletter section. This mindset shift unlocked more creativity, because contributors saw how their work would ripple across channels.
In short: automation is not just a technical upgrade, it is an organizational shift. When companies combine tools like Ghost, Make and AI with clear processes and accountability, they move from “managing content” to running a true marketing engine that scales.
Want to Automate Your Content Engine?
If you’re tired of bottlenecks in your publishing process and want to scale with fewer steps, we’ll help you build a content workflow that works on autopilot.