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Automate niche research with Wikipedia, GPT-4o-mini, and Google Sheets

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Important notice

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

1. Workflow Overview

This n8n template automates the process of researching niche topics. It searches for a topic on Wikipedia, scrapes the relevant page using ScrapeOps , extracts the history or background section, an...

Best for

  • Market Research automation workflows
  • AI Summarization automation workflows
  • intermediate n8n builders looking for reusable templates

Tools used

n8n-nodes-base.manualtrigger, n8n-nodes-base.set, n8n-nodes-base.httprequest, @scrapeops/n8n-nodes-scrapeops.scrapeops, n8n-nodes-base.googlesheets, @n8n/n8n-nodes-langchain.openai, n8n-nodes-base.stickynote, n8n-nodes-base.code

Source and attribution

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

Original n8n.io source

1.1 Workflow description

Title
Automate niche research with Wikipedia, GPT-4o-mini, and Google Sheets
Workflow name
Automate niche research with Wikipedia, GPT-4o-mini, and Google Sheets

Overview

This n8n template automates the process of researching niche topics. It searches for a topic on Wikipedia, scrapes the relevant page using ScrapeOps, extracts the history or background section, and uses AI to generate a concise summary and timeline. The results are automatically saved to Google Sheets for easy content planning.

Who is this for?

  • Content Creators: Quickly gather background info for videos or articles.
  • Marketers: Research niche markets and product histories.
  • Educators/Students: Generate timelines and summaries for study topics.
  • Researchers: Automate the initial data gathering phase.

What problems it solves

  • Time Consumption: Manually reading and summarizing Wikipedia pages takes time.
  • Blocking: Scraping Wikipedia directly can sometimes lead to IP blocks; ScrapeOps handles this.
  • Unstructured Data: Raw HTML is hard to use; this workflow converts it into a clean, structured format (JSON/CSV).

How it works

  1. Define Topic: You set a keyword in the workflow.
  2. Locate Page: The workflow queries the Wikipedia API to find the correct page URL.
  3. Smart Scraping: It uses the ScrapeOps Proxy API to fetch the page content reliably.
  4. Extraction: A code node intelligently parses the HTML to find "History", "Origins", or "Background" sections.
  5. AI Processing: GPT-4o-mini summarizes the text and extracts key dates for a timeline.
  6. Storage: The structured data is appended to a Google Sheet.

Setup steps (~ 5-10 minutes)

  1. ScrapeOps Account:
    • Register for a free API key at ScrapeOps.
    • Configure the ScrapeOps Scraper node with your API key.
  2. OpenAI Account:
    • Add your OpenAI credentials to the Message a model node.
  3. Google Sheets:
    • Create a Google Sheet. You can duplicate this Template Sheet (copy the headers).
    • Connect your Google account to the Append row in sheet node and select your new sheet.

Pre-conditions

  • An active ScrapeOps account.
  • An OpenAI API key (or another LLM credential).
  • A Google account for Sheets access.

Disclaimer

This template uses ScrapeOps as a community node. You are responsible for complying with Wikipedia's Terms of Use, robots directives, and applicable laws in your jurisdiction. Scraping targets may change at any time; adjust render/scroll/wait settings and parsers as needed. Use responsibly for legitimate business purposes.

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 clicking "Execute Workflow"

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

Block 2 - Set Topic

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

Block 3 - Wikipedia Search API

Type / Role
n8n-nodes-base.httpRequest - httpRequest
Config choices
Version 4.1

Block 4 - ScrapeOps Scraper

Type / Role
@scrapeops/n8n-nodes-scrapeops.ScrapeOps - ScrapeOps
Config choices
Version 1

Block 5 - Append row in sheet

Type / Role
n8n-nodes-base.googleSheets - googleSheets
Config choices
Version 4.7

Block 6 - Message a model

Type / Role
@n8n/n8n-nodes-langchain.openAi - openAi
Config choices
Version 1.8

Block 7 - Sticky Note

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

Block 8 - Sticky Note1

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

Block 9 - Sticky Note2

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

Block 10 - Sticky Note3

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

Block 11 - Sticky Note4

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

Block 12 - Extract History Section

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

Block 13 - Format AI Output

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

Block 14 - Construct Page URL

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

3. Summary Table

Workflow Automate niche research with Wikipedia, GPT-4o-mini, and Google Sheets
Complexity intermediate
Nodes 14
Categories Market Research, AI Summarization
Author Ian Kerins
Published 04 Dec 2025

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/11482/11482.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.

Download workflow JSON Original n8n.io source Market Research workflows AI Summarization workflows

Frequently asked questions

What does Automate niche research with Wikipedia, GPT-4o-mini, and Google Sheets do?

This n8n template automates the process of researching niche topics. It searches for a topic on Wikipedia, scrapes the relevant page using ScrapeOps , extracts the history or background section, an...

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 Summarization use case.