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Create data-driven SEO content briefs with AI analysis of SERP data using Bright Data

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Create data-driven SEO content briefs with AI analysis of SERP data using Bright Data preview
Open on n8n.io

Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

This workflow is your all in one AI Content Strategist , designed to generate comprehensive, data driven content briefs by analyzing top ranking competitors. It operates through a simple chat inter...

Best for

  • Market Research automation workflows
  • AI RAG automation workflows
  • advanced n8n builders looking for reusable templates

Tools used

@n8n/n8n-nodes-langchain.chattrigger, n8n-nodes-base.code, @brightdata/n8n-nodes-brightdata.brightdata, n8n-nodes-base.splitinbatches, n8n-nodes-base.limit, n8n-nodes-base.aggregate, @n8n/n8n-nodes-langchain.lmchatopenrouter, @n8n/n8n-nodes-langchain.chat

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by phil.

Original n8n.io source

1.1 Workflow description

Title
Create data-driven SEO content briefs with AI analysis of SERP data using Bright Data
Workflow name
Create data-driven SEO content briefs with AI analysis of SERP data using Bright Data

This workflow is your all-in-one AI Content Strategist, designed to generate comprehensive, data-driven content briefs by analyzing top-ranking competitors.

It operates through a simple chat interface.

You provide a target keyword, and the workflow automates the entire research process. First, it scrapes the top 10 Google search results using the powerful Bright Data SERP API.

Then, for each of those results, it performs a deep dive, using the Bright Data Web Unblocker to reliably extract the full content from each page, bypassing any anti-bot measures.

Finally, all the gathered data—titles, headings, word counts, and page summaries—is synthesized by a Large Language Model (LLM) to produce a strategic content plan.

This plan identifies search intent, core topics, and crucial content gaps, giving you a clear roadmap to outrank the competition. This template is indispensable for SEO specialists, content marketers, and digital agencies looking to scale their content production with strategies that are proven to work.


Why Use This AI Content Strategist Workflow ?

  • Data-Driven Insights: Base your content strategy on what is actually ranking on Google, not guesswork.
  • Automated Competitive Analysis: Instantly understand the structure, length, and key themes of the top-performing articles for any keyword.
  • Strategic Gap Detection: The AI analysis highlights poorly covered topics and missed opportunities, allowing you to create content that provides unique value.
  • Massive Time Savings: Condenses hours of manual research into a fully automated process that runs in minutes.

How It Works

  1. Chat Interaction Begins: The workflow is initiated via a chat UI. The user enters a target keyword to start the analysis.
  2. Google SERP Scraping (Bright Data): The "Google SERP" node uses Bright Data's SERP API to fetch the top 10 organic results, providing the URLs for the next stage.
  3. Individual Page Scraping (Bright Data): The workflow loops through each URL. The "Access and extract data" node uses the Bright Data Web Unblocker to ensure successful and complete HTML scraping of every competitor's page.
  4. Content Extraction & Aggregation: A series of Code nodes clean the raw HTML and extract structured data (title, meta description, headings, word count). The Aggregate node then compiles the data from all 10 pages into a single dataset.
  5. AI Synthesis (OpenRouter): The "Analysis" node sends the entire compiled dataset to an LLM via OpenRouter. The AI performs a holistic analysis to identify search intent, must-cover topics, and differentiation opportunities.
  6. Strategic Brief Generation: The "Format Output" node takes the AI's structured JSON analysis and transforms it into a clean, human-readable Markdown report, which is then delivered back to the user in the chat interface.

🔑 Prerequisites

To use this workflow, you will need active accounts with both Bright Data (for web scraping) and OpenRouter (for AI model access).

Setting Up Your Credentials:

  1. Bright Data Account:

    • Sign up for a free trial account on their website.
    • Inside your Bright Data dashboard, you will need to activate both the SERP API and the Web Unblocker products to create the necessary Zones.
    • In n8n, navigate to the Credentials section, add a new "Brightdata API" credential, and enter your API key.
    • In the workflow, select your newly created credential in both the "Google SERP" node and the "Access and extract data from a specific URL" node.
  2. OpenRouter Account:

    • Sign up for an account at OpenRouter.ai.
    • Navigate to your account settings to find your API Key.
    • In n8n, go to Credentials, add a new "OpenRouter API" credential, and paste your key.
    • In the workflow, select this credential in all three "OpenRouter Chat Model" nodes.

Phil | Inforeole

🇫🇷 Contactez nous pour automatiser vos processus

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - When chat message received

Type / Role
@n8n/n8n-nodes-langchain.chatTrigger - chatTrigger
Config choices
Version 1.3

Block 2 - extract url

Type / Role
n8n-nodes-base.code - code
Config choices
Version 2

Block 3 - Google SERP

Type / Role
@brightdata/n8n-nodes-brightdata.brightData - brightData
Config choices
Version 1

Block 4 - Loop Over Items

Type / Role
n8n-nodes-base.splitInBatches - splitInBatches
Config choices
Version 3

Block 5 - Limit

Type / Role
n8n-nodes-base.limit - limit
Config choices
Version 1

Block 6 - Aggregate

Type / Role
n8n-nodes-base.aggregate - aggregate
Config choices
Version 1

Block 7 - OpenRouter Chat Model1

Type / Role
@n8n/n8n-nodes-langchain.lmChatOpenRouter - lmChatOpenRouter
Config choices
Version 1

Block 8 - Respond to Chat

Type / Role
@n8n/n8n-nodes-langchain.chat - chat
Config choices
Version 1

Block 9 - Respond to Chat1

Type / Role
@n8n/n8n-nodes-langchain.chat - chat
Config choices
Version 1

Block 10 - Respond to Chat2

Type / Role
@n8n/n8n-nodes-langchain.chat - chat
Config choices
Version 1

Block 11 - Respond to Chat3

Type / Role
@n8n/n8n-nodes-langchain.chat - chat
Config choices
Version 1

Block 12 - Respond to Chat4

Type / Role
@n8n/n8n-nodes-langchain.chat - chat
Config choices
Version 1

Block 13 - OpenRouter Chat Model2

Type / Role
@n8n/n8n-nodes-langchain.lmChatOpenRouter - lmChatOpenRouter
Config choices
Version 1

Block 14 - Respond to Chat5

Type / Role
@n8n/n8n-nodes-langchain.chat - chat
Config choices
Version 1

Block 15 - Access and extract data from a specific URL

Type / Role
@brightdata/n8n-nodes-brightdata.brightData - brightData
Config choices
Version 1

Block 16 - OpenRouter Chat Model

Type / Role
@n8n/n8n-nodes-langchain.lmChatOpenRouter - lmChatOpenRouter
Config choices
Version 1

Block 17 - Structured Output Parser

Type / Role
@n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices
Version 1.3

Block 18 - analyse site

Type / Role
@n8n/n8n-nodes-langchain.chainLlm - chainLlm
Config choices
Version 1.7

Block 19 - extract html1

Type / Role
n8n-nodes-base.code - code
Config choices
Version 2

Block 20 - clean html

Type / Role
n8n-nodes-base.code - code
Config choices
Version 2

Block 21 - url

Type / Role
n8n-nodes-base.set - set
Config choices
Version 3.4

Block 22 - Merge1

Type / Role
n8n-nodes-base.merge - merge
Config choices
Version 3.2

Block 23 - Structured Output Parser1

Type / Role
@n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices
Version 1.3

Block 24 - Analysis

Type / Role
@n8n/n8n-nodes-langchain.chainLlm - chainLlm
Config choices
Version 1.7

Showing the first 24 of 27 workflow blocks. Download the JSON for the full node graph.

3. Summary Table

Workflow Create data-driven SEO content briefs with AI analysis of SERP data using Bright Data
Complexity advanced
Nodes 27
Categories Market Research, AI RAG
Author phil
Published 30 Aug 2025

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/8053/8053.json as the source template for this automation.

  2. 2. Import the template into n8n

    Open n8n, import the downloaded JSON, and review each node before activating the workflow.

  3. 3. Configure credentials and variables

    Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.

  4. 4. Test with sample data

    Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.

  5. 5. Activate and monitor

    Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Frequently asked questions

What does Create data-driven SEO content briefs with AI analysis of SERP data using Bright Data do?

This workflow is your all in one AI Content Strategist , designed to generate comprehensive, data driven content briefs by analyzing top ranking competitors. It operates through a simple chat inter...

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Market Research, AI RAG use case.