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

Setup steps (~ 5-10 minutes) ScrapeOps Account: Register for a free API key at ScrapeOps. Configure the ScrapeOps Scraper node with your API key. OpenAI Account: Add your OpenAI credentials to the Message a model node. 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.