Posting to multiple social media platforms daily is exhausting. Creating fresh content for each one? Even worse.

This tutorial shows you how to build an AI-powered social media automation system that generates platform-specific content, schedules posts, and runs without your constant attention.

What We’re Building

[Content Source] → [AI: Generate Platform Variants] → [Schedule Posts]
        ↓                                                    ↓
   Blog Post                                    ┌────────────┼────────────┐
   or Idea                                      ↓            ↓            ↓
                                           [Twitter]   [LinkedIn]   [Instagram]

The system will:

  • Take a single piece of content (blog post, idea, news)
  • Generate tailored versions for each platform
  • Respect character limits, tone, and formatting conventions
  • Schedule posts at optimal times
  • Track performance

Prerequisites

  • n8n (self-hosted or cloud)
  • Anthropic API key (Claude)
  • Social media accounts with API access
  • RSS feed or content source (optional)

Step 1: Content Source Setup

You need content to post. Here are three options:

Option A: Blog RSS Feed

When you publish a blog post, automatically create social content.

RSS Feed Trigger node:

Feed URL: https://yourblog.com/rss
Poll Interval: Every hour

Option B: Notion Database

Use a Notion database as your content calendar.

Notion Trigger node:

Database: Content Ideas
Trigger: When "Status" changes to "Ready to Post"

Option C: Manual Input

For ad-hoc content needs.

Webhook node:

Method: POST
Path: /generate-social
Expected body: { "topic": "...", "key_points": [...] }

Step 2: Content Extraction

Extract what you need from the source content.

From Blog Posts

Use Claude to summarize:

System: You are a content strategist extracting key information from blog posts.

User: Extract the following from this blog post:
- Main topic (1 line)
- 3 key takeaways
- Target audience
- Call to action (if any)
- Quotable lines (2-3 short phrases)

Blog content:
{{$json.content}}

Return as JSON.

Sample Output

{
  "main_topic": "How to reduce customer churn with automation",
  "key_takeaways": [
    "Early warning systems detect at-risk customers",
    "Automated re-engagement can save 30% of churning users",
    "Personal touch still matters for high-value accounts"
  ],
  "target_audience": "SaaS founders and customer success teams",
  "cta": "Download the churn prevention checklist",
  "quotable": [
    "The best retention strategy is invisible to the customer",
    "Automation doesn't replace relationships—it enables them"
  ]
}

Step 3: Platform-Specific Generation

This is where AI shines. Each platform needs different content.

Twitter/X Thread Generation

Claude prompt:

You are a Twitter content strategist. Create a thread from this content.

Content summary:
{{$json.main_topic}}

Key points:
{{$json.key_takeaways}}

Quotable lines:
{{$json.quotable}}

Requirements:
- 4-6 tweets in the thread
- First tweet must hook attention (no "Thread:" or "🧵")
- Each tweet under 280 characters
- Use line breaks for readability
- Natural, conversational tone
- End with a soft CTA (not "follow for more")
- 1-2 relevant hashtags on last tweet only

Return as JSON array of tweet strings.

Sample output:

[
  "Most SaaS companies only react to churn after it happens.\n\nBut by then, it's too late.\n\nHere's how the best teams prevent churn before customers even think about leaving:",
  "1/ Early warning systems\n\nTrack the signals that predict churn:\n- Login frequency drops\n- Feature usage declines\n- Support tickets spike\n\nCatch these patterns early = time to act.",
  "2/ Automated re-engagement\n\nWhen someone goes quiet, don't wait.\n\nTrigger personalized outreach:\n- \"We noticed you haven't used X feature\"\n- \"Here's a quick win you might have missed\"\n\nThis alone saves 30% of at-risk accounts.",
  "3/ The human touch still matters\n\nFor high-value accounts, automation is the alert system.\n\nA real person makes the call.\n\n\"Automation doesn't replace relationships—it enables them.\"",
  "The best retention strategy is invisible to the customer.\n\nThey just feel... supported.\n\nWant the playbook? Link in bio.\n\n#SaaS #CustomerSuccess"
]

LinkedIn Post Generation

Claude prompt:

You are a LinkedIn content strategist. Create a professional post from this content.

Content summary:
{{$json.main_topic}}

Key points:
{{$json.key_takeaways}}

Target audience:
{{$json.target_audience}}

Requirements:
- 150-300 words
- Strong opening hook (first line matters most)
- Use line breaks every 1-2 sentences
- Professional but not corporate
- Include a question to drive comments
- End with clear CTA
- No hashtags in the main text
- Add 3-5 relevant hashtags at the very end

Return the post as a single string.

Sample output:

Customer churn doesn't happen suddenly.

It's a slow fade that most companies miss until it's too late.

Here's what I've learned watching SaaS teams tackle retention:

The best ones don't react to churn. They predict it.

They track subtle signals:
→ Login frequency dropping
→ Feature usage declining
→ Support tickets increasing

When they spot these patterns, automated outreach kicks in.

Not generic "we miss you" emails.

Personalized messages that add value:
"We noticed you haven't tried our new reporting feature—here's a 2-minute setup guide."

This approach saves 30% of at-risk accounts.

But here's the thing: automation isn't the whole answer.

For your highest-value customers, automation is the early warning system.

A real human makes the call.

The best retention strategy is invisible to customers. They just feel supported.

What's your team's approach to catching churn early?

---

#CustomerSuccess #SaaS #Retention #CustomerExperience #B2B

Instagram Caption Generation

Claude prompt:

You are an Instagram content strategist. Create a caption for a carousel post.

Content summary:
{{$json.main_topic}}

Key points:
{{$json.key_takeaways}}

Requirements:
- Hook in first line (this shows before "more")
- Conversational, approachable tone
- Use emojis sparingly (2-3 max)
- 100-200 words
- End with CTA to save/share
- Add relevant hashtags (8-10) after a line break

Also suggest carousel slide topics (4-6 slides).

Step 4: Scheduling Logic

Don’t post everything at once. Space it out strategically.

Optimal Posting Times

Add a Code node to calculate posting times:

const now = new Date();

// Platform optimal times (adjust for your audience)
const postingSchedule = {
  twitter: {
    daysFromNow: 0,
    hour: 9, // 9am
    timezone: 'America/New_York'
  },
  linkedin: {
    daysFromNow: 0,
    hour: 8, // 8am (business hours)
    timezone: 'America/New_York'
  },
  instagram: {
    daysFromNow: 1, // Post next day
    hour: 12, // Noon
    timezone: 'America/New_York'
  }
};

const schedulePost = (platform) => {
  const schedule = postingSchedule[platform];
  const postDate = new Date(now);
  postDate.setDate(postDate.getDate() + schedule.daysFromNow);
  postDate.setHours(schedule.hour, 0, 0, 0);
  return postDate.toISOString();
};

return {
  twitter_time: schedulePost('twitter'),
  linkedin_time: schedulePost('linkedin'),
  instagram_time: schedulePost('instagram')
};

Using Buffer/Later for Scheduling

If you use a scheduling tool like Buffer:

HTTP Request node:

Method: POST
URL: https://api.bufferapp.com/1/updates/create.json

Body:
{
  "profile_ids": ["{{$json.twitter_profile_id}}"],
  "text": "{{$json.twitter_thread[0]}}",
  "scheduled_at": "{{$json.twitter_time}}"
}

Direct API Posting (Twitter Example)

Twitter node:

Operation: Create Tweet
Text: {{$json.twitter_thread[0]}}

For threads, use a loop:

// Post thread with delays
const tweets = $json.twitter_thread;
let previousTweetId = null;

for (const tweet of tweets) {
  const response = await $http.post('https://api.twitter.com/2/tweets', {
    text: tweet,
    reply: previousTweetId ? { in_reply_to_tweet_id: previousTweetId } : undefined
  });
  previousTweetId = response.data.id;

  // Wait 30 seconds between tweets
  await new Promise(resolve => setTimeout(resolve, 30000));
}

Step 5: Content Approval Flow (Optional)

For teams that need review before posting:

[Generate Content] → [Save to Notion] → [Slack Alert: "Content ready for review"]
                                                       ↓
                                              [Human Reviews]
                                                       ↓
                                        [Notion Status → "Approved"]
                                                       ↓
                                              [Trigger: Post Content]

Slack Approval Message

📝 *New Social Content Ready for Review*

*Source:* {{$json.blog_title}}

*Twitter Thread:*
{{$json.twitter_thread[0]}}
[+ {{$json.twitter_thread.length - 1}} more tweets]

*LinkedIn:*
{{$json.linkedin_post.substring(0, 200)}}...

[View in Notion]({{$json.notion_url}}) | [Approve] | [Edit]

Step 6: Performance Tracking

Track what works to improve over time.

Collect Metrics

Set up a scheduled workflow to pull engagement data:

[Every 24 hours] → [Get Recent Posts] → [Fetch Engagement] → [Store in Database]

Metrics to Track

const metrics = {
  twitter: {
    impressions: response.impressions,
    engagements: response.likes + response.retweets + response.replies,
    engagement_rate: (engagements / impressions * 100).toFixed(2)
  },
  linkedin: {
    impressions: response.impressions,
    engagements: response.reactions + response.comments + response.shares,
    engagement_rate: (engagements / impressions * 100).toFixed(2)
  }
};

Weekly Performance Summary

📊 *Social Media Weekly Report*

*Top Performing Content:*
1. "How to reduce churn..." - 5.2% engagement
2. "The automation myth..." - 4.8% engagement
3. "Three mistakes founders make..." - 3.1% engagement

*Platform Breakdown:*
- Twitter: 12 posts, avg 3.2% engagement
- LinkedIn: 5 posts, avg 4.5% engagement
- Instagram: 3 posts, avg 2.8% engagement

*Insights:*
- Question-ending posts perform 40% better
- Tuesday/Wednesday posts outperform others
- Educational content > promotional content

Complete Workflow Overview

1. Trigger: New Blog Post (RSS) or Webhook
     ↓
2. Claude: Extract Key Content
     ↓
3. Branch: For Each Platform
   ├── Claude: Generate Twitter Thread
   ├── Claude: Generate LinkedIn Post
   └── Claude: Generate Instagram Caption
     ↓
4. Code: Calculate Posting Schedule
     ↓
5. Branch: Needs Approval?
   ├── Yes → Save to Notion → Slack Alert → Wait for Approval
   └── No → Continue
     ↓
6. Schedule/Post to Each Platform
     ↓
7. Log to Database for Tracking

Advanced Features

Content Variations

Generate multiple versions and A/B test:

Generate 3 variations of this tweet hook:
{{content}}

Make each hook use a different technique:
1. Question
2. Surprising statistic
3. Contrarian take

Return as JSON array.

Add news/trends to stay relevant:

[Daily: Fetch Industry News] → [AI: Identify Relevant Trends] → [Generate Timely Content]

User Engagement Responses

Auto-draft replies to comments:

[New Comment/Reply] → [Analyze Sentiment] → [Generate Response Draft] → [Queue for Review]

Content Repurposing Chain

One piece of content, multiple formats:

[Blog Post] → [Twitter Thread] → [LinkedIn Article] → [YouTube Script] → [Podcast Talking Points]

Maintaining Brand Voice

Create a Brand Voice Document

Give Claude context about your voice:

Brand Voice Guidelines:

Tone: Professional but approachable. We're experts, not lecturers.

We say:
- "Here's what works..." (not "You should...")
- "I've seen teams..." (not "Studies show...")
- Direct statements (not hedging language)

We don't:
- Use buzzwords (synergy, leverage, disrupt)
- Over-promise ("10x your results!")
- Talk down to readers

Examples of our voice:
[Include 3-5 examples of posts that nail your voice]

Include in Every Prompt

Add brand guidelines to your system prompts:

System: You write social media content for [Brand].

{{brand_voice_guidelines}}

Generate content that matches this voice exactly.

Troubleshooting

”AI content sounds generic”

  • Add more specific examples to your prompts
  • Include your brand voice guidelines
  • Use few-shot prompting (show examples of good posts)

“Scheduling conflicts”

  • Add buffer time between posts
  • Check platform rate limits
  • Stagger multi-platform posts by 30+ minutes

”Engagement is low”

  • Test different posting times
  • Analyze top performers for patterns
  • Add more hooks and questions
  • Reduce promotional content ratio

”Twitter thread formatting breaks”

  • Verify character counts before posting
  • Handle emoji character counting correctly
  • Test with edge cases (links, mentions)

What’s Next

Once your basic system works:

  1. Add more sources: Podcast episodes, YouTube videos, customer testimonials
  2. Build a content library: Store evergreen content for reposting
  3. Create platform-specific series: Twitter threads, LinkedIn carousels
  4. Integrate analytics deeply: Auto-adjust strategy based on performance

Want help building a custom social media automation system? Book a free consultation and we’ll design one for your specific needs.

Sources