How to Build an n8n SEO Automation Workflow: From Keyword Research to Published Post

Every guide on n8n SEO automation covers the same 10 individual tasks. None of them show you how those tasks connect into a single pipeline that starts with a keyword list and ends with a published WordPress post — meta title, meta description, schema markup, featured image, and all. This guide does exactly that.

Why Individual n8n SEO Workflows Are Not Enough

Most n8n SEO automation content shows you how to pull Ahrefs data into a Google Sheet, or how to generate a content brief using GPT-4, or how to auto-publish to WordPress. Each workflow is documented in isolation. That is where the real problem lives.

When you run disconnected workflows, you reintroduce manual handoffs at every stage. Your rank tracking fires at 7 AM and delivers a Slack message. Someone reads the Slack message and copies the keywords into another tool. A brief gets generated and saved to Notion. A writer opens Notion, reads the brief, opens ChatGPT, generates a draft, copies it to WordPress, adds meta fields manually. The automation covered 20% of the work and left 80% on the table.

For a deeper publishing setup, read our n8n WordPress automation workflow guide, where we explain how to auto-create SEO-ready WordPress drafts with meta data, schema considerations, featured images, categories, tags, and review steps.

The pipeline in this guide covers 100% of the journey from keyword data to live published post. Every stage passes its output directly to the next stage. No Slack messages. No copy-paste. No manual handoffs.

The Writimate pipeline that this article documents runs this workflow for our own content. This article itself was produced by that pipeline and edited by our team before publication. Build time for first draft: 7 minutes.

The Complete Pipeline: 7 Stages End-to-End

Before building individual nodes, understand the complete architecture. Every stage has one job and one output that feeds the next stage. No stage does more than one thing.

Total pipeline execution time from trigger to published post: 90–150 seconds. That is the gap between this architecture and the 4-hour manual workflow it replaces.

Stage 1: The Schedule Trigger

Open a new workflow in n8n. Add a Schedule Trigger node as your first node. This is the only node that does not receive input from another node — it fires on a time condition and wakes the entire pipeline.

Recommended Trigger Configuration

Connect the Schedule Trigger to your first HTTP Request node. The trigger passes an empty object {} to the next node — that is intentional and correct. The Ahrefs node pulls its own data and does not need input from the trigger beyond the start signal.

Stage 2: Pulling Keywords from the Ahrefs API

Add an HTTP Request node. This is where most n8n SEO guides stop — they show you how to call Ahrefs and dump the response to a Google Sheet. That is not a pipeline. That is a data export. The difference in this stage is that the output flows directly into the filter node, not into a sheet for someone to review later.

Authentication Setup

Navigate to n8n credentials and create a new HTTP Header Auth credential. Set the header name to Authorization and the value to Bearer YOUR_AHREFS_API_KEY. Name it "Ahrefs API" and save. You will reference this credential in every Ahrefs HTTP Request node.

Keyword Ideas Endpoint Configuration

// Node: HTTP Request
// Method: GET
// URL: https://apiv3.ahrefs.com/v3/keywords-explorer/overview

{
  "keywords": "n8n automation,SEO automation,AI content pipeline",
  "country": "us",
  "limit": 50
}

The Ahrefs Keywords Explorer endpoint returns keyword metrics that help the filter stage decide whether a keyword enters your publishing queue.

Stage 3: Keyword Filtering and Queue Management

Raw Ahrefs output is noise until filtered. This stage is where most people building n8n SEO pipelines make their most consequential mistake: they filter only by keyword difficulty and miss three other signals that determine whether a keyword is worth producing content for.

The Four-Signal Filter

const keywords = $input.all().map(item => item.json);

const filtered = keywords.filter(kw => {
  if (kw.volume < 200) return false;
  if (kw.difficulty > 45) return false;
  if (kw.clicks_per_search < 0.4) return false;
  if (kw.cpc === 0) return false;

  return true;
});

const scored = filtered.map(kw => ({
  ...kw,
  opportunity_score: (kw.volume / Math.max(kw.difficulty, 1)).toFixed(1)
}));

scored.sort((a, b) => b.opportunity_score - a.opportunity_score);

return scored.slice(0, 5).map(kw => ({ json: kw }));

Writing to the Content Queue

Connect the Code node to a Google Sheets node. This writes each filtered keyword as a new row in your content queue sheet. The queue sheet becomes your audit trail for every keyword that enters the publishing pipeline.

Stage 4: Automated Content Brief Generation

This is where generic n8n content pipelines fail. They send a keyword directly to GPT-4 and ask it to write an article. The output is usually generic because the AI has no information about the specific SERP, competitor content gaps, or the angle that would make the article useful.

The brief generation stage fixes this by doing SERP research programmatically and feeding that intelligence into the AI before any content is written.

SERP Research Node

Add an HTTP Request node that calls your SERP data provider to pull the top 10 results for the target keyword. Extract their titles, meta descriptions, and URLs. This data goes into the brief prompt.

Brief Generation AI Agent

You are an expert SEO content strategist.
Output only valid JSON.

Target keyword: {{ $json.keyword }}
Monthly search volume: {{ $json.volume }}
Keyword difficulty: {{ $json.difficulty }}

Produce a JSON brief with:
- target_keyword
- secondary_keywords
- search_intent
- recommended_title
- recommended_h1
- meta_description
- word_count_target
- h2_sections
- must_include_topics
- avoid_topics
- content_angle
- internal_link_target
- faq_questions

Stage 5: AI Draft Generation

With a structured brief available, the draft generation node has everything it needs to produce a strong first draft. This stage uses a separate AI node from the brief generator so you can use one model for strategic analysis and another model for long-form writing.

Write a {{ $json.brief.word_count_target }}-word article using this brief.

Title: {{ $json.brief.recommended_h1 }}
Target keyword: {{ $json.brief.target_keyword }}
Secondary keywords: {{ $json.brief.secondary_keywords }}
Angle: {{ $json.brief.content_angle }}

Requirements:
- Include target keyword in first 100 words
- Use clean HTML
- Use h2 and h3 heading hierarchy
- No markdown
- Add FAQ section at the end

Draft Post-Processing

Add a Code node after the draft generator to extract the meta description, clean the content, validate word count, and prepare the final fields WordPress needs.

Stage 6: WordPress Auto-Publishing via REST API

This is the stage many guides cover too quickly. A useful automation should not only create a post. It should send the title, slug, content, status, SEO meta title, meta description, focus keyword, categories, tags, and featured image.

WordPress REST API Authentication

In WordPress admin, go to Users → Your Profile → Application Passwords. Generate a new application password named "n8n Pipeline". Copy it immediately because WordPress shows it only once.

The Complete Publish Node Configuration

{
  "title": "{{ $json.title }}",
  "content": "{{ $json.content }}",
  "slug": "{{ $json.slug }}",
  "status": "draft",
  "meta": {
    "_yoast_wpseo_title": "{{ $json.title }}",
    "_yoast_wpseo_metadesc": "{{ $json.meta_description }}",
    "_yoast_wpseo_focuskw": "{{ $json.focus_keyword }}"
  },
  "categories": [12],
  "tags": [45, 67]
}

Featured Image Auto-Generation and Upload

Add two nodes after the publish node. The first generates a featured image based on the article title. The second uploads it to the WordPress Media Library and attaches it to the post.

Stage 7: Quality Gates and Error Handling

A pipeline without error handling is a liability. When it works, it is invisible. When it fails, it may publish a half-formed post, skip a title, or waste API credits in repeated calls.

The Four Quality Gates

Prerequisites and Full Cost Breakdown

What You Need Before Building

• n8n instance — self-hosted or n8n Cloud.
• Ahrefs account — for keyword research API access.
• OpenAI API key — for AI draft generation.
• Anthropic API key — optional, for brief generation.
• SERP data provider — for competitor result analysis.
• WordPress site — with REST API enabled.
• Google account — for Google Sheets queue management.

Frequently Asked Questions