HumationHuman + Automation
Back to Catalog

Automate Glassdoor job search with Bright Data scraping & Google Sheets storage

Bright DataBright Data
3872 views
2/3/2026
SFTPCloud StorageGoogle DriveAutomationFile Export
Official Page

🔍 Glassdoor Job Finder: Bright Data Scraping + Keyword-Based Automation

A comprehensive n8n automation that scrapes Glassdoor job listings using Bright Data's web scraping service based on user-defined keywords, location, and country parameters, then automatically stores the results in Google Sheets.

📋 Overview

This workflow provides an automated job search solution that extracts job listings from Glassdoor using form-based inputs and stores organized results in Google Sheets. Perfect for recruiters, job seekers, market research, and competitive analysis.

Workflow Description: Automates Glassdoor job searches using Bright Data's web scraping capabilities. Users submit keywords, location, and country via form trigger. The workflow scrapes job listings, extracts company details, ratings, and locations, then automatically stores organized results in Google Sheets for easy analysis and tracking.

✨ Key Features

  • 🎯 Form-Based Input: Simple web form for job type, location, and country
  • 🔍 Glassdoor Integration: Uses Bright Data's Glassdoor dataset for accurate job data
  • 📊 Smart Data Processing: Automatically extracts key job information
  • 📈 Google Sheets Storage: Organized data storage with automatic updates
  • 🔄 Status Monitoring: Built-in progress tracking and retry logic
  • ⚡ Fast & Reliable: Professional scraping with error handling
  • 🎯 Keyword Flexibility: Search any job type with location filters
  • 📝 Structured Output: Clean, organized job listing data

🎯 What This Workflow Does

Input

  • Job Keywords: Job title or role (e.g., "Software Engineer", "Marketing Manager")
  • Location: City or region for job search
  • Country: Target country for job listings

Processing

  1. Form Submission
  2. Data Scraping via Bright Data
  3. Status Monitoring
  4. Data Extraction
  5. Data Processing
  6. Sheet Update

Output Data Points

| Field | Description | Example | |-------|-------------|---------| | Job Title | Position title from listing | Senior Software Engineer | | Company Name | Employer name | Google Inc. | | Location | Job location | San Francisco, CA | | Rating | Company rating score | 4.5 | | Job Link | Direct URL to listing | https://glassdoor.com/job/... |

🚀 Setup Instructions

Prerequisites

  • n8n instance (self-hosted or cloud)
  • Google account with Sheets access
  • Bright Data account with Glassdoor scraping dataset access
  • 5–10 minutes for setup

Step 1: Import the Workflow

  1. Copy the JSON workflow code from the provided file
  2. In n8n: Workflows → + Add workflow → Import from JSON
  3. Paste JSON and click Import

Step 2: Configure Bright Data

  1. Set up Bright Data credentials in n8n
  2. Ensure access to dataset: gd_lpfbbndm1xnopbrcr0
  3. Update API tokens in:
    • "Scrape Job Data" node
    • "Check Delivery Status of Snap ID" node
    • "Getting Job Lists" node

Step 3: Configure Google Sheets Integration

  1. Create a new Google Sheet (e.g., "Glassdoor Job Tracker")
  2. Set up Google Sheets OAuth2 credentials in n8n
  3. Prepare columns:
    • Column A: Job Title
    • Column B: Company Name
    • Column C: Location
    • Column D: Rating
    • Column E: Job Link

Step 4: Update Workflow Settings

  1. Update "Update Job List" node with your Sheet ID and credentials
  2. Test the form trigger and webhook URL

Step 5: Test & Activate

  1. Submit test data (e.g., "Software Engineer" in "New York")
  2. Activate the workflow
  3. Verify Google Sheet updates and field extraction

📖 Usage Guide

Submitting Job Searches

  1. Navigate to your workflow's webhook URL
  2. Fill in:
    • Search Job Type
    • Location
    • Country
  3. Submit the form

Reading the Results

  • Real-time job listing data
  • Company ratings and reviews
  • Direct job posting links
  • Location-specific results
  • Processing timestamps

🔧 Customization Options

  • More Data Points: Add job descriptions, salary, company size, etc.
  • Search Parameters: Add filters for salary, experience, remote work
  • Data Processing: Add validation, deduplication, formatting

🚨 Troubleshooting

  • Bright Data connection failed: Check API credentials and dataset access
  • No job data extracted: Validate search terms and location format
  • Google Sheets permission denied: Re-authenticate and check sharing
  • Form submission failed: Check webhook URL and form config
  • Workflow execution failed: Check logs, add retry logic

Advanced Troubleshooting

  • Check execution logs in n8n
  • Test individual nodes
  • Verify data formats
  • Monitor rate limits
  • Add error handling

📊 Use Cases & Examples

  • Recruitment Pipeline: Track job postings, build talent database
  • Market Research: Analyze job trends, hiring patterns
  • Career Development: Monitor opportunities, salary trends
  • Competitive Intelligence: Track competitor hiring activity

⚙️ Advanced Configuration

  • Batch Processing: Accept multiple keywords, loop logic, delays
  • Search History: Track trends, compare results over time
  • External Tools: Integrate with CRM, Slack, databases, BI tools

📈 Performance & Limits

  • Single search: 2–5 minutes
  • Data accuracy: 95%+
  • Success rate: 90%+
  • Concurrent searches: 1–3 (depends on plan)
  • Daily capacity: 50–200 searches
  • Memory: ~50MB per execution
  • API calls: 3 Bright Data + 1 Google Sheets per search

🤝 Support & Community

  • n8n Community Forum: community.n8n.io
  • Documentation: docs.n8n.io
  • Bright Data Support: Via your dashboard
  • GitHub Issues: Report bugs and features

Contributing: Share improvements, report issues, create variations, document best practices.

Need Help? Check the full documentation or visit the n8n Community for support and workflow examples.

n8n Form Trigger to Google Sheets

This n8n workflow simplifies data collection by allowing users to submit information via an n8n form, then stores that data directly into a Google Sheet. It also includes a conditional logic step and a wait step, though their specific configurations are not detailed in the provided JSON.

What it does

  1. Triggers on Form Submission: The workflow starts when a user submits data through an n8n-generated form.
  2. Conditional Logic (If): It then processes the submitted data through an 'If' node, allowing for conditional routing based on the data's content.
  3. Waits for a Duration: Following the conditional check, the workflow introduces a 'Wait' period, pausing execution for a specified duration.
  4. Makes an HTTP Request: After the wait, it performs an HTTP request, which could be used to interact with an external API or service.
  5. Stores Data in Google Sheets: Finally, the collected data (or processed data from previous steps) is written to a Google Sheet.

Prerequisites/Requirements

  • n8n Instance: A running n8n instance to host and execute the workflow.
  • Google Sheets Account: A Google account with access to Google Sheets for storing the data.
  • Google Sheets Credential in n8n: You will need to set up a Google Sheets credential (OAuth2 or Service Account) in your n8n instance.

Setup/Usage

  1. Import the workflow: Download the provided JSON and import it into your n8n instance.
  2. Configure the Form Trigger:
    • Open the "On form submission" node.
    • Define the fields you want in your form.
    • Activate the workflow to generate the public URL for your form.
  3. Configure Google Sheets Node:
    • Open the "Google Sheets" node.
    • Select your Google Sheets credential.
    • Specify the Spreadsheet ID and Sheet Name where you want to store the data.
    • Map the incoming data from the form to the columns in your Google Sheet.
  4. Configure the If Node:
    • Open the "If" node.
    • Define the conditions based on the data submitted through the form. This will determine which path the workflow takes.
  5. Configure the Wait Node:
    • Open the "Wait" node.
    • Specify the duration for which the workflow should pause.
  6. Configure the HTTP Request Node:
    • Open the "HTTP Request" node.
    • Set up the URL, method (GET, POST, etc.), headers, and body for the API call you intend to make.
  7. Activate the Workflow: Once configured, activate the workflow. Any submissions to the n8n form will now trigger the workflow, process the data, and store it in your Google Sheet.

Related Templates

Track competitor SEO keywords with Decodo + GPT-4.1-mini + Google Sheets

This workflow automates competitor keyword research using OpenAI LLM and Decodo for intelligent web scraping. Who this is for SEO specialists, content strategists, and growth marketers who want to automate keyword research and competitive intelligence. Marketing analysts managing multiple clients or websites who need consistent SEO tracking without manual data pulls. Agencies or automation engineers using Google Sheets as an SEO data dashboard for keyword monitoring and reporting. What problem this workflow solves Tracking competitor keywords manually is slow and inconsistent. Most SEO tools provide limited API access or lack contextual keyword analysis. This workflow solves that by: Automatically scraping any competitor’s webpage with Decodo. Using OpenAI GPT-4.1-mini to interpret keyword intent, density, and semantic focus. Storing structured keyword insights directly in Google Sheets for ongoing tracking and trend analysis. What this workflow does Trigger — Manually start the workflow or schedule it to run periodically. Input Setup — Define the website URL and target country (e.g., https://dev.to, france). Data Scraping (Decodo) — Fetch competitor web content and metadata. Keyword Analysis (OpenAI GPT-4.1-mini) Extract primary and secondary keywords. Identify focus topics and semantic entities. Generate a keyword density summary and SEO strength score. Recommend optimization and internal linking opportunities. Data Structuring — Clean and convert GPT output into JSON format. Data Storage (Google Sheets) — Append structured keyword data to a Google Sheet for long-term tracking. Setup Prerequisites If you are new to Decode, please signup on this link visit.decodo.com n8n account with workflow editor access Decodo API credentials OpenAI API key Google Sheets account connected via OAuth2 Make sure to install the Decodo Community node. Create a Google Sheet Add columns for: primarykeywords, seostrengthscore, keyworddensity_summary, etc. Share with your n8n Google account. Connect Credentials Add credentials for: Decodo API credentials - You need to register, login and obtain the Basic Authentication Token via Decodo Dashboard OpenAI API (for GPT-4o-mini) Google Sheets OAuth2 Configure Input Fields Edit the “Set Input Fields” node to set your target site and region. Run the Workflow Click Execute Workflow in n8n. View structured results in your connected Google Sheet. How to customize this workflow Track Multiple Competitors → Use a Google Sheet or CSV list of URLs; loop through them using the Split In Batches node. Add Language Detection → Add a Gemini or GPT node before keyword analysis to detect content language and adjust prompts. Enhance the SEO Report → Expand the GPT prompt to include backlink insights, metadata optimization, or readability checks. Integrate Visualization → Connect your Google Sheet to Looker Studio for SEO performance dashboards. Schedule Auto-Runs → Use the Cron Node to run weekly or monthly for competitor keyword refreshes. Summary This workflow automates competitor keyword research using: Decodo for intelligent web scraping OpenAI GPT-4.1-mini for keyword and SEO analysis Google Sheets for live tracking and reporting It’s a complete AI-powered SEO intelligence pipeline ideal for teams that want actionable insights on keyword gaps, optimization opportunities, and content focus trends, without relying on expensive SEO SaaS tools.

Ranjan DailataBy Ranjan Dailata
161

Generate song lyrics and music from text prompts using OpenAI and Fal.ai Minimax

Spark your creativity instantly in any chat—turn a simple prompt like "heartbreak ballad" into original, full-length lyrics and a professional AI-generated music track, all without leaving your conversation. 📋 What This Template Does This chat-triggered workflow harnesses AI to generate detailed, genre-matched song lyrics (at least 600 characters) from user messages, then queues them for music synthesis via Fal.ai's minimax-music model. It polls asynchronously until the track is ready, delivering lyrics and audio URL back in chat. Crafts original, structured lyrics with verses, choruses, and bridges using OpenAI Submits to Fal.ai for melody, instrumentation, and vocals aligned to the style Handles long-running generations with smart looping and status checks Returns complete song package (lyrics + audio link) for seamless sharing 🔧 Prerequisites n8n account (self-hosted or cloud with chat integration enabled) OpenAI account with API access for GPT models Fal.ai account for AI music generation 🔑 Required Credentials OpenAI API Setup Go to platform.openai.com → API keys (sidebar) Click "Create new secret key" → Name it (e.g., "n8n Songwriter") Copy the key and add to n8n as "OpenAI API" credential type Test by sending a simple chat completion request Fal.ai HTTP Header Auth Setup Sign up at fal.ai → Dashboard → API Keys Generate a new API key → Copy it In n8n, create "HTTP Header Auth" credential: Name="Fal.ai", Header Name="Authorization", Header Value="Key [Your API Key]" Test with a simple GET to their queue endpoint (e.g., /status) ⚙️ Configuration Steps Import the workflow JSON into your n8n instance Assign OpenAI API credentials to the "OpenAI Chat Model" node Assign Fal.ai HTTP Header Auth to the "Generate Music Track", "Check Generation Status", and "Fetch Final Result" nodes Activate the workflow—chat trigger will appear in your n8n chat interface Test by messaging: "Create an upbeat pop song about road trips" 🎯 Use Cases Content Creators: YouTubers generating custom jingles for videos on the fly, streamlining production from idea to audio export Educators: Music teachers using chat prompts to create era-specific folk tunes for classroom discussions, fostering interactive learning Gift Personalization: Friends crafting anniversary R&B tracks from shared memories via quick chats, delivering emotional audio surprises Artist Brainstorming: Songwriters prototyping hip-hop beats in real-time during sessions, accelerating collaboration and iteration ⚠️ Troubleshooting Invalid JSON from AI Agent: Ensure the system prompt stresses valid JSON; test the agent standalone with a sample query Music Generation Fails (401/403): Verify Fal.ai API key has minimax-music access; check usage quotas in dashboard Status Polling Loops Indefinitely: Bump wait time to 45-60s for complex tracks; inspect fal.ai queue logs for bottlenecks Lyrics Under 600 Characters: Tweak agent prompt to enforce fuller structures like [V1][C][V2][B][C]; verify output length in executions

Daniel NkenchoBy Daniel Nkencho
601

Automate invoice processing with OCR, GPT-4 & Salesforce opportunity creation

PDF Invoice Extractor (AI) End-to-end pipeline: Watch Drive ➜ Download PDF ➜ OCR text ➜ AI normalize to JSON ➜ Upsert Buyer (Account) ➜ Create Opportunity ➜ Map Products ➜ Create OLI via Composite API ➜ Archive to OneDrive. --- Node by node (what it does & key setup) 1) Google Drive Trigger Purpose: Fire when a new file appears in a specific Google Drive folder. Key settings: Event: fileCreated Folder ID: google drive folder id Polling: everyMinute Creds: googleDriveOAuth2Api Output: Metadata { id, name, ... } for the new file. --- 2) Download File From Google Purpose: Get the file binary for processing and archiving. Key settings: Operation: download File ID: ={{ $json.id }} Creds: googleDriveOAuth2Api Output: Binary (default key: data) and original metadata. --- 3) Extract from File Purpose: Extract text from PDF (OCR as needed) for AI parsing. Key settings: Operation: pdf OCR: enable for scanned PDFs (in options) Output: JSON with OCR text at {{ $json.text }}. --- 4) Message a model (AI JSON Extractor) Purpose: Convert OCR text into strict normalized JSON array (invoice schema). Key settings: Node: @n8n/n8n-nodes-langchain.openAi Model: gpt-4.1 (or gpt-4.1-mini) Message role: system (the strict prompt; references {{ $json.text }}) jsonOutput: true Creds: openAiApi Output (per item): $.message.content → the parsed JSON (ensure it’s an array). --- 5) Create or update an account (Salesforce) Purpose: Upsert Buyer as Account using an external ID. Key settings: Resource: account Operation: upsert External Id Field: taxid_c External Id Value: ={{ $json.message.content.buyer.tax_id }} Name: ={{ $json.message.content.buyer.name }} Creds: salesforceOAuth2Api Output: Account record (captures Id) for downstream Opportunity. --- 6) Create an opportunity (Salesforce) Purpose: Create Opportunity linked to the Buyer (Account). Key settings: Resource: opportunity Name: ={{ $('Message a model').item.json.message.content.invoice.code }} Close Date: ={{ $('Message a model').item.json.message.content.invoice.issue_date }} Stage: Closed Won Amount: ={{ $('Message a model').item.json.message.content.summary.grand_total }} AccountId: ={{ $json.id }} (from Upsert Account output) Creds: salesforceOAuth2Api Output: Opportunity Id for OLI creation. --- 7) Build SOQL (Code / JS) Purpose: Collect unique product codes from AI JSON and build a SOQL query for PricebookEntry by Pricebook2Id. Key settings: pricebook2Id (hardcoded in script): e.g., 01sxxxxxxxxxxxxxxx Source lines: $('Message a model').first().json.message.content.products Output: { soql, codes } --- 8) Query PricebookEntries (Salesforce) Purpose: Fetch PricebookEntry.Id for each Product2.ProductCode. Key settings: Resource: search Query: ={{ $json.soql }} Creds: salesforceOAuth2Api Output: Items with Id, Product2.ProductCode (used for mapping). --- 9) Code in JavaScript (Build OLI payloads) Purpose: Join lines with PBE results and Opportunity Id ➜ build OpportunityLineItem payloads. Inputs: OpportunityId: ={{ $('Create an opportunity').first().json.id }} Lines: ={{ $('Message a model').first().json.message.content.products }} PBE rows: from previous node items Output: { body: { allOrNone:false, records:[{ OpportunityLineItem... }] } } Notes: Converts discount_total ➜ per-unit if needed (currently commented for standard pricing). Throws on missing PBE mapping or empty lines. --- 10) Create Opportunity Line Items (HTTP Request) Purpose: Bulk create OLIs via Salesforce Composite API. Key settings: Method: POST URL: https://<your-instance>.my.salesforce.com/services/data/v65.0/composite/sobjects Auth: salesforceOAuth2Api (predefined credential) Body (JSON): ={{ $json.body }} Output: Composite API results (per-record statuses). --- 11) Update File to One Drive Purpose: Archive the original PDF in OneDrive. Key settings: Operation: upload File Name: ={{ $json.name }} Parent Folder ID: onedrive folder id Binary Data: true (from the Download node) Creds: microsoftOneDriveOAuth2Api Output: Uploaded file metadata. --- Data flow (wiring) Google Drive Trigger → Download File From Google Download File From Google → Extract from File → Update File to One Drive Extract from File → Message a model Message a model → Create or update an account Create or update an account → Create an opportunity Create an opportunity → Build SOQL Build SOQL → Query PricebookEntries Query PricebookEntries → Code in JavaScript Code in JavaScript → Create Opportunity Line Items --- Quick setup checklist 🔐 Credentials: Connect Google Drive, OneDrive, Salesforce, OpenAI. 📂 IDs: Drive Folder ID (watch) OneDrive Parent Folder ID (archive) Salesforce Pricebook2Id (in the JS SOQL builder) 🧠 AI Prompt: Use the strict system prompt; jsonOutput = true. 🧾 Field mappings: Buyer tax id/name → Account upsert fields Invoice code/date/amount → Opportunity fields Product name must equal your Product2.ProductCode in SF. ✅ Test: Drop a sample PDF → verify: AI returns array JSON only Account/Opportunity created OLI records created PDF archived to OneDrive --- Notes & best practices If PDFs are scans, enable OCR in Extract from File. If AI returns non-JSON, keep “Return only a JSON array” as the last line of the prompt and keep jsonOutput enabled. Consider adding validation on parsing.warnings to gate Salesforce writes. For discounts/taxes in OLI: Standard OLI fields don’t support per-line discount amounts directly; model them in UnitPrice or custom fields. Replace the Composite API URL with your org’s domain or use the Salesforce node’s Bulk Upsert for simplicity.

Le NguyenBy Le Nguyen
942