How I automated 80% of SEO work with N8N and LLMs

SEO at scale is a nightmare. When you're managing thousands of pages across dozens of tools, manual optimization becomes impossible. So I built a system that does 80% of the work automatically.

The Problem

At Picsart, we had:

50,000+ live pages
40+ languages
Constantly changing search trends
A team of... me

Traditional SEO workflows don't scale. You can't manually optimize thousands of pages, track ranking changes, and respond to algorithm updates. Something had to change.

The Solution: N8N + LLMs

I built an automated pipeline using N8N (open-source workflow automation) and various LLMs to handle:

1. Content Optimization

The system automatically:

Analyzes top-ranking competitors for each keyword
Identifies content gaps
Generates optimization suggestions
Updates meta descriptions and titles

2. Keyword Research at Scale

Instead of manually researching keywords, the system:

Monitors search trends via APIs
Clusters related keywords
Prioritizes based on traffic potential and competition
Suggests new tool ideas based on search demand

3. Technical SEO Monitoring

Automated checks for:

Broken links
Page speed issues
Indexing problems
Schema markup validation

The Stack

N8N: Workflow orchestration
OpenAI GPT-4: Content analysis and generation
Google Search Console API: Performance data
Ahrefs API: Competitor analysis
Custom Python scripts: Data processing

Results

After 6 months:

3X organic traffic growth
90% reduction in manual SEO tasks
2-day response time to algorithm updates (down from weeks)
500+ new keyword rankings in top 10

Key Learnings

LLMs are great for first drafts, not final copy. Always have human review for important pages.
Start with the most repetitive tasks. The biggest ROI comes from automating what you do most often.
Build in quality checks. Automated doesn't mean unmonitored. Set up alerts for anomalies.
Document everything. When you automate, you need to understand what's happening to debug issues.

What's Next

I'm now working on predictive models that can anticipate algorithm changes based on Google's public statements and industry patterns. Early results are promising.

Want to learn more about AI-powered SEO? Reach out on LinkedIn or check out my other posts on AI productivity.