Deep Web Scraper and Logger

Overview

Manually tracking and archiving sublinks related to keywords across webpages is tedious and error-prone. This automation scrapes the parent page, identifies relevant sublinks using AI, fetches their content, saves all text files to Google Drive, and logs every step in Google Sheets for structured, searchable records.

The Impact

Automate sublink discovery. AI-driven extraction finds and follows relevant links without manual input.
Archive content systematically. Save both parent and subpage text files directly to Google Drive.
Maintain searchable logs. Record parameters and results in Google Sheets for easy review and auditing.
Iterate with precision. Loop through sublinks up to a defined depth, enabling deep chain scraping.

Who This Is For

Media Archivists Automate batch scraping and archiving of article-linked content.
Competitive Intelligence Analysts Track and save related industry pages for change analysis.
QA and Operations Teams Bulk verify website sublink validity and status codes.
Data Researchers Extract structured web data across linked pages efficiently.

How It Works

Scrape Parent Page
Fetch HTML content from the initial URL for analysis.

Identify Relevant Sublinks
Use an LLM to extract the first keyword-related sublink from the HTML.

Scrape Sublink Content
Fetch and save content from the identified subpage if valid.

Store Files and Logs
Save text files to Google Drive and append records to Google Sheets.

Iterate and Update
Repeat sublink search and scraping up to the specified depth, updating the current URL each cycle.

What You'll Need

Before using this template, make sure you have:

Google Sheets OAuth credentials for creating and updating sheets.
Google Drive OAuth credentials for creating and saving text files.
A Google Spreadsheet with an accessible Spreadsheet ID and a designated sheet/tab name.
Target URL of the parent webpage to start scraping from.
(Optional) Keywords to filter relevant sublinks.
A positive integer defining the depth of sublink search iterations.

How to Use

Step 1. Prepare Your Spreadsheet

Create a Google Sheet with a header row for parameters and rows for sublink records.

Step 2. Set Credentials

Configure Google Sheets and Drive OAuth credentials in the workflow nodes.

Step 3. Configure Parameters

Input the parent URL, optional keywords, search depth, Spreadsheet ID, and sheet/tab name.

Step 4. Run the Workflow

Start the automation to scrape, analyze, save files, and log results iteratively.

Step 5. Verify Results

Check Google Drive for saved files and Google Sheets for structured scraping records.

FAQs

How does the workflow decide which sublink to scrape?

It uses an LLM to analyze the parent page HTML and extract the first sublink matching the associated keywords. If no keywords are provided, it returns unrelated sublinks.

What happens if no valid sublink is found?

The workflow skips subpage scraping for that iteration and continues until the specified search depth is reached or no further sublinks are found.

How are scraping results recorded?

Initial parameters and each sublink’s URL and HTTP status code are appended as rows in the specified Google Sheet for easy tracking and auditing.

Can this workflow handle multiple levels of sublinks?

Yes, it iterates sublink discovery and scraping up to the SearchDepth parameter, updating the URL each cycle to chain through sublinks.

Where are the scraped contents saved?

Text content from both the parent page and subpages is saved as files in Google Drive using OAuth credentials configured in the workflow.

Updated on: Sep 18, 2026

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