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Search & enrich: Smart keyword analysis with Decodo + OpenAI GPT-4.1-mini

Ranjan DailataRanjan Dailata
292 views
2/3/2026
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Disclaimer

Please note - This workflow is only available on n8n self-hosted as it's making use of the community node for the Decodo Web Scraping

Search & Enrich: Smart Keyword Analysis with Decodo + OpenAI GPT-4.1-mini

This workflow automates intelligent keyword and topic extraction from Google Search results, combining Decodo’s advanced scraping engine with OpenAI GPT-4.1-mini’s semantic analysis capabilities. The result is a fully automated keyword enrichment pipeline that gathers, analyzes, and stores SEO-relevant insights.

Who this is for

This workflow is ideal for:

  • SEO professionals who want to extract high-value keywords from competitors.
  • Digital marketers aiming to automate topic discovery and keyword clustering.
  • Content strategists building data-driven content calendars.
  • AI automation engineers designing scalable web intelligence and enrichment pipelines.
  • Growth teams performing market and search intent research with minimal effort.

What problem this workflow solves

Manual keyword research is time-consuming and often incomplete. Traditional keyword tools only provide surface-level data and fail to uncover contextual topics or semantic relationships hidden in search results.

This workflow solves that by:

  • Automatically scraping live Google Search results for any keyword.
  • Extracting meaningful topics, related terms, and entities using AI.
  • Enriching your keyword list with semantic intelligence to improve SEO and content planning.
  • Storing structured results directly in n8n Data Tables for trend tracking or export.

What this workflow does

Here’s a breakdown of the flow:

  1. Set the Input Fields – Define your search query and target geo (e.g., “Pizza” in “India”).
  2. Decodo Google Search – Fetches organic search results using Decodo’s web scraping API.
  3. Return Organic Results – Extracts the list of organic results and passes them downstream.
  4. Loop Over Each Result – Iterates through every search result description.
  5. Extract Keywords and Topics – Uses OpenAI GPT-4.1-mini to identify relevant keywords, entities, and thematic topics from each snippet.
  6. Data Enrichment Logic – Checks whether each result already exists in the n8n Data Table (based on URL).
  7. Insert or Skip – If a record doesn’t exist, inserts the extracted data into the table.
  8. Store Results – Saves both enriched search data and Decodo’s original response to disk.

End Result: A structured and deduplicated dataset containing URLs, keywords, and key topics — ready for SEO tracking or further analytics.

Setup

Pre-requisite

If you are new to Decode, please signup on this link visit.decodo.com

Please make sure to install the n8n custom node for Decodo.

Decodo Custom n8n Install Decodo Custom n8n node

Import and Configure the Workflow

  1. Open n8n and import the JSON template.

  2. Add your credentials:

    • Decodo API Key under Decodo Credentials account.
    • OpenAI API Key under OpenAI Account.

Define Input Parameters

  • Modify the Set node to define:

    • search_query: your keyword or topic (e.g., “AI tools for marketing”)
    • geo: the target region (e.g., “United States”)

Configure Output

  • The workflow writes two outputs:

    1. Enriched keyword data → Stored in n8n Data Table (DecodoGoogleSearchResults).
    2. Raw Decodo response → Saved locally in JSON format.

Execute

Click Execute Workflow or schedule it for recurring keyword enrichment (e.g., weekly trend tracking).

How to customize this workflow

  • Change AI Model — Replace gpt-4.1-mini with gemini-1.5-pro or claude-3-opus for testing different reasoning strengths.
  • Expand the Schema — Add extra fields like keyword difficulty, page type, or author info.
  • Add Sentiment Analysis — Chain a second AI node to assess tone (positive, neutral, or promotional).
  • Export to Sheets or DB — Replace the Data Table node with Google Sheets, Notion, Airtable, or MySQL connectors.
  • Multi-Language Research — Pass a locale parameter in the Decodo node to gather insights in specific languages.
  • Automate Alerts — Add a Slack or Email node to notify your team when high-value topics appear.

Summary

Search & Enrich is a low-code AI-powered keyword intelligence engine that automates research and enrichment for SEO, content, and digital marketing.

By combining Decodo’s real-time SERP scraping with OpenAI’s contextual understanding, the workflow transforms raw search results into structured, actionable keyword insights. It eliminates repetitive research work, enhances content strategy, and keeps your keyword database continuously enriched — all within n8n.

n8n Workflow: Smart Keyword Analysis with Decodr & OpenAI GPT-4.1 Mini

This n8n workflow provides a robust solution for enhancing keyword analysis by leveraging AI to extract and enrich information from raw text data. It streamlines the process of taking unstructured text, processing it through a language model, and then extracting structured insights, making it ideal for SEO, content analysis, or market research.

What it does

This workflow automates the following steps:

  1. Manual Trigger: Initiates the workflow upon manual execution, allowing for on-demand analysis.
  2. Define Input Data: A "Data table" node is used to define the initial input data, likely containing the raw text or keywords to be analyzed.
  3. Prepare Data for Processing: A "Code" node processes the input data, preparing it for the language model. This might involve formatting, cleaning, or structuring the text.
  4. Loop Over Items: The "Loop Over Items (Split in Batches)" node processes each item of data individually, ensuring that the AI model receives manageable chunks of information.
  5. Conditional Processing: An "If" node introduces conditional logic, allowing the workflow to branch based on certain criteria of the processed data.
  6. AI Chat Model Interaction: An "OpenAI Chat Model" node sends the prepared text to an OpenAI GPT-4.1 Mini model for analysis, generating enriched or transformed text.
  7. Information Extraction: An "Information Extractor" node (likely Decodr, based on the directory name) is used to extract structured information (e.g., entities, sentiment, categories) from the AI-generated text.
  8. Edit Fields: An "Edit Fields (Set)" node allows for further manipulation or standardization of the extracted data.
  9. Function Node: A "Function" node provides custom JavaScript logic for advanced data transformation or manipulation.
  10. Read/Write Files from Disk: A "Read/Write Files from Disk" node is included, suggesting the capability to save or load processed data from local storage.

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n Instance: A running instance of n8n.
  • OpenAI API Key: For the "OpenAI Chat Model" node to interact with GPT-4.1 Mini.
  • Decodr (or similar service): Although not explicitly shown as a separate node, the directory name suggests integration with Decodr for information extraction. Ensure you have the necessary access or credentials if this is an external service.
  • Basic JavaScript knowledge: For configuring the "Code" and "Function" nodes.

Setup/Usage

  1. Import the workflow: Import the provided JSON into your n8n instance.
  2. Configure Credentials:
    • Set up your OpenAI API Key credentials within n8n.
    • If Decodr is an external service, configure any necessary API keys or authentication.
  3. Define Input Data: Populate the "Data table" node with your initial keyword data or text for analysis.
  4. Customize Code Nodes: Adjust the JavaScript in the "Code" and "Function" nodes to match your specific data processing and transformation needs.
  5. Configure AI Prompts: Customize the prompts and parameters in the "OpenAI Chat Model" and "Information Extractor" nodes to guide the AI in generating the desired insights.
  6. Adjust Conditional Logic: Modify the "If" node's conditions to control the flow of data based on your requirements.
  7. Activate and Execute: Save the workflow and execute it manually using the "Manual Trigger" node to start the analysis.

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