Workflow Templates

It allows you to automate candidate retrieval and onboarding in your HR processes. How it works It monitors a Gmail address for new emails with a PDF attachment It expects the PDF to be a candidate’s CV, extracts the text using OCR, and then structures the data using ChatGPT Once the data is processed, it connects to Notion and adds (or updates) an entry in the specified database How to use Configure your Gmail account and provide your ChatGPT API key Provide an API key for the OCR service in a variable named OCR_SPACE_API_KEY Connect your Notion account Once everything is configured, the workflow will monitor your inbox for new emails. Just send an email with a PDF attachment to the configured address Requirements In addition to Gmail, ChatGPT, and Notion, the system uses a third-party OCR API (OCR SPACE). You’ll need to create an account and obtain an API key You must map the fields returned by ChatGPT to the Notion database, or use the same field names we are using Customising It should be easy to replace Notion with PostgreSQL or another database if needed

Yelp Business Scraper by URL via Bright Data API with Google Sheets Storage Overview This n8n workflow automates the process of scraping comprehensive business information from Yelp using individual business URLs. It integrates with Bright Data for professional web scraping and Google Sheets for centralized data storage, providing detailed business intelligence for market research, competitor analysis, and lead generation. Workflow Components 1. 📥 Form Trigger Type**: Form Trigger Purpose**: Initiates the workflow with user-submitted Yelp business URL Input Fields**: URL (Yelp business page URL) Function**: Captures target business URL to start the scraping process 2. 🔍 Trigger Bright Data Scrape Type**: HTTP Request (POST) Purpose**: Sends scraping request to Bright Data API for Yelp business data Endpoint**: https://api.brightdata.com/datasets/v3/trigger Parameters**: Dataset ID: gd_lgugwl0519h1p14rwk Include errors: true Limit multiple results: 5 Limit per input: 20 Function**: Initiates comprehensive business data extraction from Yelp 3. 📡 Monitor Snapshot Status Type**: HTTP Request (GET) Purpose**: Monitors the progress of the Yelp scraping job Endpoint**: https://api.brightdata.com/datasets/v3/progress/{snapshot_id} Function**: Checks if the business data scraping is complete 4. ⏳ Wait 30 Sec for Snapshot Type**: Wait Node Purpose**: Implements intelligent polling mechanism Duration**: 30 seconds Function**: Pauses workflow before rechecking scraping status to optimize API usage 5. 🔁 Retry Until Ready Type**: IF Condition Purpose**: Evaluates scraping completion status Condition**: status === "ready" Logic**: True: Proceeds to data retrieval False: Loops back to status monitoring with wait 6. 📥 Fetch Scraped Business Data Type**: HTTP Request (GET) Purpose**: Retrieves the final scraped business information Endpoint**: https://api.brightdata.com/datasets/v3/snapshot/{snapshot_id} Format**: JSON Function**: Downloads completed Yelp business data with comprehensive details 7. 📊 Store to Google Sheet Type**: Google Sheets Node Purpose**: Stores scraped business data for analysis and storage Operation**: Append rows Target**: "Yelp scraper data by URL" sheet Data Mapping**: Business Name, Overall Rating, Reviews Count Business URL, Images/Videos URLs Additional business metadata fields Workflow Flow Form Input → Trigger Scrape → Monitor Status → Wait 30s → Check Ready ↑ ↓ └─── Loop ─────┘ ↓ Fetch Data → Store to Sheet Configuration Requirements API Keys & Credentials Bright Data API Key**: Required for Yelp business scraping Google Sheets OAuth2**: For data storage and export access n8n Form Webhook**: For user input collection Setup Parameters Google Sheet ID**: Target spreadsheet identifier Dataset ID**: gd_lgugwl0519h1p14rwk (Yelp business scraper) Form Webhook ID**: User input form identifier Google Sheets Credential ID**: OAuth2 authentication Key Features Comprehensive Business Data Extraction Complete business profile information Customer ratings and review counts Contact details and business hours Photo and video content URLs Location and category information Intelligent Status Monitoring Real-time scraping progress tracking Automatic retry mechanisms with 30-second intervals Status validation before data retrieval Error handling and timeout management Centralized Data Storage Automatic Google Sheets export Organized business data format Historical scraping records Easy sharing and collaboration URL-Based Processing Direct Yelp business URL input Single business deep-dive analysis Flexible input through web form Real-time workflow triggering Use Cases Market Research Competitor business analysis Local market intelligence gathering Industry benchmark establishment Service offering comparison Lead Generation Business contact information extraction Potential client identification Market opportunity assessment Sales prospect development Business Intelligence Customer sentiment analysis through ratings Competitor performance monitoring Market positioning research Brand reputation tracking Location Analysis Geographic business distribution Local competition assessment Market saturation evaluation Expansion opportunity identification Data Output Fields | Field | Description | Example | |-------|-------------|---------| | Name | Business name | "Joe's Pizza Restaurant" | | Overall Rating | Average customer rating | "4.5" | | Reviews Count | Total number of reviews | "247" | | URL | Original Yelp business URL | "https://www.yelp.com/biz/joes-pizza..." | | Images/Videos URLs | Media content links | "https://s3-media1.fl.yelpcdn.com/..." | Technical Notes Polling Interval**: 30-second status checks for optimal API usage Result Limiting**: Maximum 20 businesses per input, 5 multiple results Data Format**: JSON with structured field mapping Error Handling**: Comprehensive error tracking in all API requests Retry Logic**: Automatic status rechecking until completion Form Input**: Single URL field with validation Storage Format**: Structured Google Sheets with predefined columns Setup Instructions Step 1: Import Workflow Copy the JSON workflow configuration Import into n8n: Workflows → Import from JSON Paste configuration and save Step 2: Configure Bright Data Set up credentials: Navigate to Credentials → Add Bright Data API Enter your Bright Data API key Test connection Update API key references: Replace BRIGHT_DATA_API_KEY in all HTTP request nodes Verify dataset access for gd_lgugwl0519h1p14rwk Step 3: Configure Google Sheets Create target spreadsheet: Create new Google Sheet named "Yelp Business Data" or similar Copy the Sheet ID from URL Set up OAuth2 credentials: Add Google Sheets OAuth2 credential in n8n Complete authentication process Update workflow references: Replace YOUR_GOOGLE_SHEET_ID with actual Sheet ID Update YOUR_GOOGLE_SHEETS_CREDENTIAL_ID with credential reference Step 4: Test and Activate Test with sample URL: Use a known Yelp business URL Monitor execution progress Verify data appears in Google Sheet Activate workflow: Toggle workflow to "Active" Share form URL with users Sample Business Data The workflow captures comprehensive business information including: Basic Information**: Name, category, location Performance Metrics**: Ratings, review counts, popularity Contact Details**: Phone, website, address Visual Content**: Photos, videos, gallery URLs Operational Data**: Hours, services, amenities Customer Feedback**: Review summaries, sentiment indicators Advanced Configuration Batch Processing Modify the input to accept multiple URLs: [ {"url": "https://www.yelp.com/biz/business-1"}, {"url": "https://www.yelp.com/biz/business-2"}, {"url": "https://www.yelp.com/biz/business-3"} ] Enhanced Data Fields Add more extraction fields by updating the dataset configuration: Business hours and schedule Menu items and pricing Customer photos and reviews Special offers and promotions Notification Integration Add alert mechanisms: Email notifications for completed scrapes Slack messages for team updates Webhook triggers for external systems Error Handling Common Issues Invalid URL**: Ensure URL is a valid Yelp business page Rate Limiting**: Bright Data API usage limits exceeded Authentication**: Google Sheets or Bright Data credential issues Data Format**: Unexpected response structure from Yelp Troubleshooting Steps Verify URLs: Ensure Yelp business URLs are correctly formatted Check Credentials: Validate all API keys and OAuth tokens Monitor Logs: Review n8n execution logs for detailed errors Test Connectivity: Verify network access to all external services Performance Specifications Processing Time**: 2-5 minutes per business URL Data Accuracy**: 95%+ for publicly available business information Success Rate**: 90%+ for valid Yelp business URLs Concurrent Processing**: Depends on Bright Data plan limits Storage Capacity**: Unlimited (Google Sheets based) **For any questions or support, please contact: info@incrementors.com or fill out this form: https://www.incrementors.com/contact-us/

HubSpot Contact Enrichment with Explorium Template Download the following json file and import it to a new n8n workflow: hubspot\_flow.json Overview This n8n workflow monitors your HubSpot instance for newly created contacts and automatically enriches them with additional contact information. When a contact is created, the workflow: Detects the new contact via HubSpot webhook trigger Retrieves recent contact details from HubSpot Matches the contact against Explorium's database using name, company, and email Enriches the contact with professional emails and phone numbers Updates the HubSpot contact record with discovered information This automation ensures your sales and marketing teams have complete contact information, improving outreach success rates and data quality. Key Features Real-time Webhook Trigger**: Instantly processes new contacts as they're created Intelligent Matching**: Uses multiple data points (name, company, email) for accurate matching Comprehensive Enrichment**: Adds both professional and work emails, plus phone numbers Batch Processing**: Efficiently handles multiple contacts to optimize API usage Smart Data Mapping**: Intelligently maps multiple emails and phone numbers Profile Enrichment**: Optional additional enrichment for deeper contact insights Error Resilience**: Continues processing other contacts if some fail to match Prerequisites Before setting up this workflow, ensure you have: n8n instance (self-hosted or cloud) HubSpot account with: Developer API access (for webhooks) Private App or OAuth2 app created Contact object permissions (read/write) Explorium API credentials (Bearer token) - Get explorium api key Understanding of HubSpot contact properties HubSpot Requirements Required Contact Properties The workflow uses these HubSpot contact properties: firstname - Contact's first name lastname - Contact's last name company - Associated company name email - Primary email (read and updated) work_email - Work email (updated by workflow) phone - Phone number (updated by workflow) API Access Setup Create a Private App in HubSpot: Navigate to Settings → Integrations → Private Apps Create new app with Contact read/write scopes Copy the Access Token Set up Webhooks (for Developer API): Create app in HubSpot Developers portal Configure webhook for contact.creation events Note the App ID and Developer API Key Custom Properties (Optional) Consider creating custom properties for: Multiple email addresses Mobile vs. office phone numbers Data enrichment timestamps Match confidence scores Installation & Setup Step 1: Import the Workflow Copy the workflow JSON from the template In n8n: Navigate to Workflows → Add Workflow → Import from File Paste the JSON and click Import Step 2: Configure HubSpot Developer API (Webhook) Click on the HubSpot Trigger node Under Credentials, click Create New Enter your HubSpot Developer credentials: App ID: From your HubSpot app Developer API Key: From your developer account Client Secret: From your app settings Save as "HubSpot Developer account" Step 3: Configure HubSpot App Token Click on the HubSpot Recently Created node Under Credentials, click Create New (App Token) Enter your Private App access token Save as "HubSpot App Token account" Apply the same credentials to the Update HubSpot node Step 4: Configure Explorium API Credentials Click on the Explorium Match Prospects node Under Credentials, click Create New (HTTP Header Auth) Configure the authentication: Name: Authorization Value: Bearer YOUR_EXPLORIUM_API_TOKEN Save as "Header Auth Connection" Apply to all Explorium nodes: Explorium Enrich Contacts Information Explorium Enrich Profiles Step 5: Configure Webhook Subscription In HubSpot Developers portal: Go to your app's webhook settings Add subscription for contact.creation events Set the target URL from the HubSpot Trigger node Activate the subscription Step 6: Activate the Workflow Save the workflow Toggle the Active switch to ON The webhook is now listening for new contacts Node Descriptions HubSpot Trigger: Webhook that fires when new contacts are created HubSpot Recently Created: Fetches details of recently created contacts Loop Over Items: Processes contacts in batches of 6 Explorium Match Prospects: Finds matching person in Explorium database Filter: Validates successful matches Extract Prospect IDs: Collects matched prospect identifiers Enrich Contacts Information: Fetches emails and phone numbers Enrich Profiles: Gets additional profile data (optional) Merge: Combines all enrichment results Split Out: Separates individual enriched records Update HubSpot: Updates contact with new information Data Mapping Logic The workflow maps Explorium data to HubSpot properties: | Explorium Data | HubSpot Property | Notes | | ------------------------------ | ------------------ | ----------------------------- | | professions_email | email | Primary professional email | | emails[].address | work_email | All email addresses joined | | phone_numbers[].phone_number | phone | All phones joined with commas | | mobile_phone | phone (fallback) | Used if no other phones found | Data Processing The workflow handles complex data scenarios: Multiple emails**: Joins all discovered emails with commas Phone numbers**: Combines all phone numbers into a single field Missing data**: Uses "null" as placeholder for empty fields Name parsing**: Cleans sample data and special characters Usage & Operation Automatic Processing Once activated: Every new contact triggers the webhook immediately Contact is enriched within seconds HubSpot record is updated automatically Process repeats for each new contact Manual Testing To test the workflow: Use the pinned test data in the HubSpot Trigger node, or Create a test contact in HubSpot Monitor the execution in n8n Verify the contact was updated in HubSpot Monitoring Performance Track workflow health: Go to Executions in n8n Filter by this workflow Monitor success rates Review any failed executions Check webhook delivery in HubSpot Troubleshooting Common Issues Webhook not triggering Verify webhook subscription is active in HubSpot Check the webhook URL is correct and accessible Ensure workflow is activated in n8n Test webhook delivery in HubSpot developers portal Contacts not matching Verify contact has firstname, lastname, and company Check for typos or abbreviations in company names Some individuals may not be in Explorium's database Email matching improves accuracy significantly Updates failing in HubSpot Check API token has contact write permissions Verify property names exist in HubSpot Ensure rate limits haven't been exceeded Check for validation rules on properties Missing enrichment data Not all prospects have all data types Phone numbers may be less available than emails Profile enrichment is optional and may not always return data Error Handling Built-in error resilience: Failed matches don't block other contacts Each batch processes independently Partial enrichment is possible All errors are logged for review Debugging Tips Check webhook logs: HubSpot shows delivery attempts Review executions: n8n logs show detailed error messages Test with pinned data: Use the sample data for isolated testing Verify API responses: Check Explorium API returns expected data Best Practices Data Quality Complete contact records: Ensure name and company are populated Standardize company names: Use official names, not abbreviations Include existing emails: Improves match accuracy Regular data hygiene: Clean up test and invalid contacts Performance Optimization Batch size: 6 is optimal for rate limits Webhook reliability: Monitor delivery success API quotas: Track usage in both platforms Execution history: Regularly clean old executions Compliance & Privacy GDPR compliance: Ensure lawful basis for enrichment Data minimization: Only enrich necessary fields Access controls: Limit who can modify enriched data Audit trail: Document enrichment for compliance Customization Options Additional Enrichment Extend with more Explorium data: Job titles and departments Social media profiles Professional experience Skills and interests Company information Enhanced Processing Add workflow logic for: Lead scoring based on enrichment Routing based on data quality Notifications for high-value matches Custom field mapping Integration Extensions Connect to other systems: Sync enriched data to CRM Trigger marketing automation Update data warehouse Send notifications to Slack API Considerations HubSpot Limits API calls**: Monitor daily limits Webhook payload**: Max 200 contacts per trigger Rate limits**: 100 requests per 10 seconds Property limits**: Max 1000 custom properties Explorium Limits Match API**: Batched for efficiency Enrichment calls**: Two parallel enrichments Rate limits**: Based on your plan Data freshness**: Real-time matching Architecture Considerations This workflow integrates with: HubSpot workflows and automation Marketing campaigns and sequences Sales engagement tools Reporting and analytics Other enrichment services Security Best Practices Webhook validation**: Verify requests are from HubSpot Token security**: Rotate API tokens regularly Access control**: Limit workflow modifications Data encryption**: All API calls use HTTPS Audit logging**: Track all enrichments Advanced Configuration Custom Field Mapping Modify the Update HubSpot node to map to custom properties: // Example custom mapping { "custom_mobile": "{{ $json.data.mobile_phone }}", "custom_linkedin": "{{ $json.data.linkedin_url }}", "enrichment_date": "{{ $now.toISO() }}" } Conditional Processing Add logic to process only certain contacts: Filter by contact source Check for specific properties Validate email domains Exclude test contacts Support Resources For assistance: n8n issues**: Check n8n documentation and forums HubSpot API**: Reference HubSpot developers documentation Explorium API**: Contact Explorium support Webhook issues**: Use HubSpot webhook testing tools

Explorium Prospects Search Chatbot Template Download the following json file and import it to a new n8n workflow: mcp\_to\_prospects\_to\_csv.json Overview This n8n workflow creates a chatbot that understands natural language requests for finding business prospects and automatically: Interprets your query using AI (Claude Sonnet 3.7) Converts it to proper Explorium API filters Validates the API request structure Fetches prospect data from Explorium Exports results as a downloadable CSV file Perfect for sales teams, recruiters, and business development professionals who need to quickly find and export targeted prospect lists without learning complex API syntax. Key Features Natural Language Interface**: Simply describe who you're looking for in plain English Smart Query Translation**: AI converts your request to valid API parameters Built-in Validation**: Ensures API calls meet Explorium's requirements Error Recovery**: Automatically retries with corrections if validation fails Pagination Support**: Handles large result sets automatically CSV Export**: Clean, formatted output ready for CRM import Conversation Memory**: Maintains context for follow-up queries Example Queries The chatbot understands queries like: "Find marketing directors at SaaS companies in New York with 50-200 employees" "Get me CTOs from fintech startups in California" "Show me sales managers at healthcare companies with revenue over $10M" "Find engineers at Microsoft with 3-5 years experience" "Get customer service leads from e-commerce companies in Europe" Prerequisites Before setting up this workflow, ensure you have: n8n instance with chat interface enabled Anthropic API key for Claude Explorium API credentials (Bearer token) - Get explorium api key Basic understanding of n8n chat workflows Supported Filters The chatbot can search using these criteria: Company Filters Size**: 1-10, 11-50, 51-200, 201-500, 501-1000, 1001-5000, 5001-10000, 10001+ employees Revenue**: Ranges from $0-500K up to $10T+ Age**: 0-3, 3-6, 6-10, 10-20, 20+ years Location**: Countries, regions, cities Industry**: Google categories, NAICS codes, LinkedIn categories Name**: Specific company names Prospect Filters Job Level**: CXO, VP, Director, Manager, Senior, Entry, etc. Department**: Sales, Marketing, Engineering, Finance, HR, etc. Experience**: Total months and current role duration Location**: Country and region codes Contact Info**: Filter by email/phone availability Installation & Setup Step 1: Import the Workflow Copy the workflow JSON from the template In n8n: Workflows → Add Workflow → Import from File Paste the JSON and click Import Step 2: Configure Anthropic Credentials Click on the Anthropic Chat Model1 node Under Credentials, click Create New Add your Anthropic API key Name: "Anthropic API" Save credentials Step 3: Configure Explorium Credentials You'll need to set up Explorium credentials in two places: For MCP Client: Click on the MCP Client node Under Credentials, create new Header Auth Add your authentication header (usually Authorization: Bearer YOUR_TOKEN) Save credentials For API Calls: Click on the Prospects API Call node Use the same Header Auth credentials created above Verify the API endpoint is correct Step 4: Activate the Workflow Save the workflow Click the Active toggle to enable it The chat interface will now be available Step 5: Access the Chat Interface Click on the When chat message received node Copy the webhook URL Access this URL in your browser to start chatting How It Works Workflow Architecture Chat Trigger: Receives natural language queries from users Memory Buffer: Maintains conversation context AI Agent: Interprets queries and generates API parameters Validation: Checks API structure against Explorium requirements API Call: Fetches prospect data with pagination Data Processing: Formats results for CSV export File Conversion: Creates downloadable CSV file Processing Flow User Query → AI Interpretation → Validation → API Call → CSV Export ↑ ↓ └──── Error Correction Loop ←──────┘ Validation Rules The workflow validates: Filter keys are allowed by Explorium API Values match expected formats (e.g., valid country codes) Range filters have proper gte/lte values No duplicate values in arrays Required structure is maintained Usage Guide Basic Conversation Flow Start with your query: "Find me VPs of Sales at software companies in the US" Bot processes and responds: Generates API filters Validates the structure Fetches data Returns CSV download link Refine if needed: "Can you also include directors and filter for companies with 100+ employees?" Query Tips Be specific**: Include job titles, departments, company details Use standard terms**: "CTO" instead of "Chief Technology Officer" Specify locations**: Use country names or standard codes Include size/revenue**: Helps narrow results effectively Advanced Queries Combine multiple criteria: "Find engineering managers and senior engineers at B2B SaaS companies in New York and California with 50-500 employees and revenue over $5M who have been in their role for at least 1 year" Output Format The CSV file includes: Prospect ID Name (first, last, full) Location (country, region, city) LinkedIn profile Experience summary Skills and interests Company details Job information Business ID Troubleshooting Common Issues "Validation failed" errors Check that your query uses supported filter values Ensure location names are spelled correctly Verify company sizes/revenues match allowed ranges No results returned Broaden your search criteria Check if the company exists in Explorium's database Verify filter combinations aren't too restrictive Chat not responding Ensure workflow is activated Check all credentials are properly configured Verify webhook URL is accessible Large result sets timing out Try adding more specific filters Limit results by location or company size Use the size parameter (max 10,000) Error Messages The bot provides clear feedback: Invalid filters**: Shows which filters aren't supported Value errors**: Lists correct options for each field API failures**: Explains connection or authentication issues Performance Optimization Best Practices Start broad, then narrow: Begin with basic criteria and add filters Use business IDs: When targeting specific companies Limit by contact info: Add has_email: true for actionable leads Batch by location: Process regions separately for large searches API Limits Maximum 10,000 results per search Pagination handles up to 100 records per page Rate limits apply based on your Explorium subscription Customization Options Modify AI Behavior Edit the AI Agent system message to: Change response format Add custom filters Adjust interpretation logic Include additional instructions Extend Functionality Add nodes to: Send results via email Import directly to CRM Schedule recurring searches Create custom reports Integration Ideas Connect to Slack for team queries Add to CRM workflows Create lead scoring systems Build automated outreach campaigns Security Considerations API credentials are stored securely in n8n Chat sessions are isolated No prospect data is stored permanently CSV files are generated on-demand Support Resources For issues with: n8n platform**: Check n8n documentation Explorium API**: Contact Explorium support Anthropic/Claude**: Refer to Anthropic docs Workflow logic**: Review node configurations

This workflow automatically transcribes audio files, translates the content between languages, and generates natural-sounding speech from the translated text - all in one seamless process. Who's it for Content creators, educators, and businesses needing to make their audio content accessible across language barriers. Perfect for translating podcasts, voice messages, lectures, or any audio content while preserving the spoken format. How it works The workflow receives an audio file through a webhook, transcribes it using OpenAI's Whisper, translates and structures the text with GPT-4, generates new audio in the target language, and stores it in S3 for easy access. The entire process takes seconds and returns both the transcribed/translated text and a URL to the translated audio file. How to set up Configure OpenAI credentials - Add your OpenAI API key for Whisper transcription and GPT-4 translation Set up AWS S3 - Create a bucket with public read permissions for audio storage Update configuration - Replace 'YOUR-BUCKET-NAME' with your actual S3 bucket name Activate webhook - Deploy and copy your webhook URL for receiving audio files Send a POST request with: Binary audio file (as 'audiofile') Languages parameter (e.g., "English, Spanish") Requirements OpenAI API account with access to Whisper and GPT-4 AWS account with S3 bucket configured Basic understanding of webhooks and API requests How to customize Add language detection** - Automatically detect source language if not specified Customize voice settings** - Adjust speech speed, pitch, or select different voices Add file validation** - Implement size limits and format checks Enhance security** - Add webhook authentication and rate limiting Extend functionality** - Add subtitle generation or multiple output formats

🐦 Twitter Profile Scraper via Bright Data API with Google Sheets Output A comprehensive n8n automation that scrapes Twitter profile data using Bright Data's Twitter dataset and stores comprehensive tweet analytics, user metrics, and engagement data directly into Google Sheets. 📋 Overview This workflow provides an automated Twitter data collection solution that extracts profile information and tweet data from specified Twitter accounts within custom date ranges. Perfect for social media analytics, competitor research, brand monitoring, and content strategy analysis. ✨ Key Features 🔗 Form-Based Input: Easy-to-use form for Twitter URL and date range selection 🐦 Twitter Integration: Uses Bright Data's Twitter dataset for accurate data extraction 📊 Comprehensive Data: Captures tweets, engagement metrics, and profile information 📈 Google Sheets Storage: Automatically stores all data in organized spreadsheet format 🔄 Progress Monitoring: Real-time status tracking with automatic retry mechanisms ⚡ Fast & Reliable: Professional scraping with built-in error handling 📅 Date Range Control: Flexible time period selection for targeted data collection 🎯 Customizable Fields: Advanced data field selection and mapping 🎯 What This Workflow Does Input Twitter Profile URL**: Target Twitter account for data scraping Date Range**: Start and end dates for tweet collection period Custom Fields**: Configurable data points to extract Processing Form Trigger: Collects Twitter URL and date range from user input API Request: Sends scraping request to Bright Data with specified parameters Progress Monitoring: Continuously checks scraping job status until completion Data Retrieval: Downloads complete dataset when scraping is finished Data Processing: Formats and structures extracted information Sheet Integration: Automatically populates Google Sheets with organized data Output Data Points | Field | Description | Example | |-------|-------------|---------| | user_posted | Username who posted the tweet | @elonmusk | | name | Display name of the user | Elon Musk | | description | Tweet content/text | "Exciting updates coming soon..." | | date_posted | When the tweet was posted | 2025-01-15T10:30:00Z | | likes | Number of likes on the tweet | 1,234 | | reposts | Number of retweets | 567 | | replies | Number of replies | 89 | | views | Total view count | 12,345 | | followers | User's follower count | 50M | | following | Users they follow | 123 | | is_verified | Verification status | true/false | | hashtags | Hashtags used in tweet | #AI #Technology | | photos | Image URLs in tweet | image1.jpg, image2.jpg | | videos | Video content URLs | video1.mp4 | | user_id | Unique user identifier | 12345678 | | timestamp | Data extraction timestamp | 2025-01-15T11:00:00Z | 🚀 Setup Instructions Prerequisites n8n instance (self-hosted or cloud) Bright Data account with Twitter dataset access Google account with Sheets access Valid Twitter profile URLs to scrape 10-15 minutes for setup Step 1: Import the Workflow Copy the JSON workflow code from the provided file In n8n: Workflows → + Add workflow → Import from JSON Paste JSON and click Import Step 2: Configure Bright Data Set up Bright Data credentials: In n8n: Credentials → + Add credential → HTTP Header Auth Enter your Bright Data API credentials Test the connection Configure dataset: Ensure you have access to Twitter dataset (gd_lwxkxvnf1cynvib9co) Verify dataset permissions in Bright Data dashboard Step 3: Configure Google Sheets Integration Create a Google Sheet: Go to Google Sheets Create a new spreadsheet named "Twitter Data" or similar Copy the Sheet ID from URL: https://docs.google.com/spreadsheets/d/SHEET_ID_HERE/edit Set up Google Sheets credentials: In n8n: Credentials → + Add credential → Google Sheets OAuth2 API Complete OAuth setup and test connection Prepare your data sheet with columns: Use the column headers from the data points table above The workflow will automatically populate these fields Step 4: Update Workflow Settings Update Bright Data nodes: Open "🚀 Trigger Twitter Scraping" node Replace BRIGHT_DATA_API_KEY with your actual API token Verify dataset ID is correct Update Google Sheets node: Open "📊 Store Twitter Data in Google Sheet" node Replace YOUR_GOOGLE_SHEET_ID with your Sheet ID Select your Google Sheets credential Choose the correct sheet/tab name Step 5: Test & Activate Add test data: Use the form trigger to input a Twitter profile URL Set a small date range for testing (e.g., last 7 days) Test the workflow: Submit the form to trigger the workflow Monitor progress in n8n execution logs Verify data appears in Google Sheet Check all expected columns are populated 📖 Usage Guide Running the Workflow Access the workflow form trigger URL (available when workflow is active) Enter the Twitter profile URL you want to scrape Set the start and end dates for tweet collection Submit the form to initiate scraping Monitor progress - the workflow will automatically check status every minute Once complete, data will appear in your Google Sheet Understanding the Data Your Google Sheet will show: Real-time tweet data** for the specified date range User engagement metrics** (likes, replies, retweets, views) Profile information** (followers, following, verification status) Content details** (hashtags, media URLs, quoted tweets) Timestamps** for each tweet and data extraction Customizing Date Ranges Recent data**: Use last 7-30 days for current activity analysis Historical analysis**: Select specific months or quarters for trend analysis Event tracking**: Focus on specific date ranges around events or campaigns Comparative studies**: Use consistent time periods across different profiles 🔧 Customization Options Modifying Data Fields Edit the custom_output_fields array in the "🚀 Trigger Twitter Scraping" node to add or remove data points: "custom_output_fields": [ "id", "user_posted", "name", "description", "date_posted", "likes", "reposts", "replies", "views", "hashtags", "followers", "is_verified" ] Changing Google Sheet Structure Modify the column mapping in the "📊 Store Twitter Data in Google Sheet" node to match your preferred sheet layout and add custom formulas or calculations. Adding Multiple Recipients To process multiple Twitter profiles: Modify the form to accept multiple URLs Add a loop node to process each URL separately Implement delays between requests to respect rate limits 🚨 Troubleshooting Common Issues & Solutions "Bright Data connection failed" Cause: Invalid API credentials or dataset access Solution: Verify credentials in Bright Data dashboard, check dataset permissions "No data extracted" Cause: Invalid Twitter URLs or private/protected accounts Solution: Verify URLs are valid public Twitter profiles, test with different accounts "Google Sheets permission denied" Cause: Incorrect credentials or sheet permissions Solution: Re-authenticate Google Sheets, check sheet sharing settings "Workflow timeout" Cause: Large date ranges or high-volume accounts Solution: Use smaller date ranges, implement pagination for high-volume accounts "Progress monitoring stuck" Cause: Scraping job failed or API issues Solution: Check Bright Data dashboard for job status, restart workflow if needed Advanced Troubleshooting Check execution logs in n8n for detailed error messages Test individual nodes by running them separately Verify data formats and ensure consistent field mapping Monitor rate limits if scraping multiple profiles consecutively Add error handling and implement retry logic for robust operation 📊 Use Cases & Examples 1. Social Media Analytics Goal: Track engagement metrics and content performance Monitor tweet engagement rates over time Analyze hashtag effectiveness and reach Track follower growth and audience interaction Generate weekly/monthly performance reports 2. Competitor Research Goal: Monitor competitor social media activity Track competitor posting frequency and timing Analyze competitor content themes and strategies Monitor competitor engagement and audience response Identify trending topics and hashtags in your industry 3. Brand Monitoring Goal: Track brand mentions and sentiment analysis Monitor specific Twitter accounts for brand mentions Track hashtag campaigns and user-generated content Analyze sentiment trends and audience feedback Identify influencers and brand advocates 4. Content Strategy Development Goal: Analyze successful content patterns Identify high-performing tweet formats and topics Track optimal posting times and frequencies Analyze hashtag performance and reach Study audience engagement patterns 5. Market Research Goal: Collect social media data for market analysis Gather consumer opinions and feedback Track industry trends and discussions Monitor product launches and market reactions Support product development with social insights ⚙ Advanced Configuration Batch Processing Multiple Profiles To monitor multiple Twitter accounts efficiently: Create a master sheet with profile URLs and date ranges Add a loop node to process each profile separately Implement delays between requests to respect rate limits Use separate sheets or tabs for different profiles Adding Data Analysis Enhance the workflow with analytical capabilities: Create additional sheets for processed data and insights Add formulas to calculate engagement rates and trends Implement data visualization with charts and graphs Generate automated reports and summaries Integration with Business Tools Connect the workflow to your existing systems: CRM Integration**: Update customer records with social media data Slack Notifications**: Send alerts when data collection is complete Database Storage**: Store data in PostgreSQL/MySQL for advanced analysis BI Tools**: Connect to Tableau/Power BI for comprehensive visualization 📈 Performance & Limits Expected Performance Single profile**: 30 seconds to 5 minutes (depending on date range) Data accuracy**: 95%+ for public Twitter profiles Success rate**: 90%+ for accessible accounts Daily capacity**: 10-50 profiles (depends on rate limits and data volume) Resource Usage Memory**: ~200MB per execution Storage**: Minimal (data stored in Google Sheets) API calls**: 1 Bright Data call + multiple Google Sheets calls per profile Bandwidth**: ~5-10MB per profile scraped Execution time**: 2-10 minutes for typical date ranges Scaling Considerations Rate limiting**: Add delays for high-volume scraping Error handling**: Implement retry logic for failed requests Data validation**: Add checks for malformed or missing data Monitoring**: Track success/failure rates over time Cost optimization**: Monitor API usage to control costs 🤝 Support & Community Getting Help n8n Community Forum**: community.n8n.io Documentation**: docs.n8n.io Bright Data Support**: Contact through your dashboard GitHub Issues**: Report bugs and feature requests Contributing Share improvements with the community Report issues and suggest enhancements Create variations for specific use cases Document best practices and lessons learned 📋 Quick Setup Checklist Before You Start ☐ n8n instance running (self-hosted or cloud) ☐ Bright Data account with Twitter dataset access ☐ Google account with Sheets access ☐ Valid Twitter profile URLs ready for scraping ☐ 10-15 minutes available for setup Setup Steps ☐ Import Workflow - Copy JSON and import to n8n ☐ Configure Bright Data - Set up API credentials and test ☐ Create Google Sheet - New sheet with proper column structure ☐ Set up Google Sheets credentials - OAuth setup and test ☐ Update workflow settings - Replace API keys and sheet IDs ☐ Test with sample data - Add 1 Twitter URL and small date range ☐ Verify data flow - Check data appears in Google Sheet correctly ☐ Activate workflow - Enable form trigger for production use Ready to Use! 🎉 Your workflow URL: Access form trigger when workflow is active 🎯 Happy Twitter Scraping! This workflow provides a solid foundation for automated Twitter data collection. Customize it to fit your specific social media analytics and research needs. For any questions or support, please contact: info@incrementors.com or fill out this form: https://www.incrementors.com/contact-us/

Overview This workflow watches for new rows in a Google Sheet (e.g., where you manually log customer reviews) and uses a Code node to perform a simple sentiment analysis, then updates the same row with the detected sentiment. Use Case: Quickly gauge customer satisfaction, identify positive/negative trends, and prioritize follow-ups based on sentiment. How It Works This workflow operates in four main steps: Google Sheets Trigger (New Row): The workflow starts with a Google Sheets Trigger node configured to monitor a specific Google Sheet for new rows. This triggers the workflow whenever a new review is added. Code Node (Sentiment Analysis): A Code node receives the new row data (containing the review text). Inside this node, JavaScript code performs a basic sentiment analysis by checking for keywords (e.g., "great", "excellent" for positive; "bad", "problem" for negative). It assigns "Positive", "Negative", or "Neutral" sentiment. Update Google Sheet Row: A Google Sheets node is configured to update the same row that triggered the workflow. It adds the sentiment result (and potentially other analysis data) to a new column in that row. Setup Steps To get this workflow up and running, follow these instructions: Step 1: Create Google Sheets Credentials in n8n In your n8n instance, click on Credentials in the left sidebar. Click New Credential. Search for and select "Google Sheets OAuth2 API" and follow the authentication steps with your Google account. Save it. Make note of the Credential Name (e.g., "My Google Sheets Account"). Step 2: Prepare Your Google Sheet (or better Make a copy of the one provided in the template) Create a new Google Sheet in your Google Drive (e.g., Customer Reviews). In the first row, add these column headers: Timestamp Customer Name Review Text Sentiment (This column will be updated by the workflow) Review ID (Optional, for tracking) Copy the Sheet ID from the URL (e.g., https://docs.google.com/spreadsheets/d/YOUR_GOOGLE_SHEET_ID_HERE/edit). Copy the GID of the specific sheet tab (e.g., https://docs.google.com/spreadsheets/d/YOUR_GOOGLE_SHEET_ID_HERE/edit#gid=YOUR_GID_HERE). This is the sheetName value. Step 3: Import the Workflow JSON Step 4: Activate and Test the Workflow Click the "Activate" toggle button in the top right corner of the n8n workflow editor. Go to your Google Sheet and manually add a new row with a "Review Text" (e.g., "This product is great, I love it!"). Leave the "Sentiment" column empty. The workflow should trigger automatically (it polls every minute by default), analyze the sentiment, and update the "Sentiment" column in your Google Sheet. You can also manually "Execute Workflow" to test immediately.

This n8n workflow automatically retrieves recent Reuters news articles related to a user-specified keyword, summarizes the main findings using Google Gemini, formats the output into styled HTML, and sends a clean email report to a specified address. 🚀 What It Does Collects news data from Bright Data's Reuters dataset. Sorts and filters top 10 most recent news articles by publication_date. Sends structured news data to Gemini Flash for summarization. Converts Gemini's response (in Markdown) into styled HTML. Delivers a concise news briefing via email, including clickable source links and topic highlights. 🛠️ Step-by-Step Setup User Form: Accepts a keyword from the user via an n8n form trigger. Bright Data API: Posts a discover_new request to Bright Data's Reuters dataset using the keyword. Snapshot Polling: Waits and checks for dataset readiness using the snapshot ID. Data Retrieval: Downloads the news data once the snapshot is complete. Parsing: Filters and sorts the latest 10 articles using a Python Code node. AI Analysis: Google Gemini summarizes the filtered content into one briefing. Markdown → HTML: Converts AI response into styled HTML using Markdown + Code node. Email Delivery: Sends the briefing as an email to a predefined recipient. 🧠 How It Works Polling Control: Uses Wait and If nodes to handle Bright Data snapshot readiness. Date Sorting: Publication dates (ISO 8601 format) are parsed and used for sorting. AI Summarization: Gemini condenses multiple articles into one cohesive summary. Formatting: Clean HTML with readable styles is generated dynamically before sending. 📨 Final Output The email includes: A brief summary of the most important developments Date range of the collected news Topics covered 🔐 Credentials Used Bright Data API (replace YOUR_API_KEY in the HTTP nodes) Google Gemini (Flash) API Email SMTP (configured in Email Send node) ⚠️ Notes You must replace all YOUR_API_KEY placeholders in Bright Data request headers with your actual Bright Data API key. You can customize the keyword prompt and output style freely. I would recommend to keep the sort = relevance option for best chronological results - sorting by date is handled later.

This is a simple webpage scraper that specifically grabs today's newest 4K Bluray Preorders as listed on the Blu-ray.com website. This is a scheduled workflow that can run every day and will post a formatted summary message of links to a Discord channel of your choice. Minimal setup required: Just create a webhook for the channel you want posted to in Discord and provide that in the final step. The timezone format step is set to East Coast (NYC) by default, feel free to change. No API keys or any special configuration needed (beyond your Discord webhook) Feel free to customize the formatting of the message that gets posted 👍 How it works: First format todays date to match the formatting used on the website Grab the HTML for the preorders page at www.blu-ray.com Filter only the hyperlinks for each Bluray on the page Then further filter only those with an html header matching today's date Format how you want the message to be sent to your Discord channel (in this case a simple list of Hyperlinks for each Title) Send to Discord! Disclaimer: This should be only for personal use.** The links go back to the blu-ray.com website, which is a good thing! Don't abuse this by slamming their site with some crazy level of automation frequency. Support the blu-ray.com website by using their affiliate links whenever you do want to preorder a title ;) This is one of my first shared templates, so it may not be super optimal or perfect but it works for my needs and hopefully you'll find some use out of it! Discord currently has a 2000 character limit on webhook messages. Some of the messages may get truncated as a result.

This workflow combines customers' details with their payment data and passes the input to Pipedrive as a note to the organization. Prerequisites Stripe account and Stripe credentials Pipedrive account and Pipedrive credentials How it works Cron node triggers the workflow every day at 8 a.m. HTTP Request node searches for payments in Stripe. The Item Lists node creates separate items from a list of payment data. Merge node takes in the payment data as an input 1. Stripe node gets all the customers data. Set node renames customer-related data fields and keeps only needed fields. Merge node takes in the customer data as an input 2. Merge node combines the payment data with the customers one. Pipedrive node searches for the organization and creates a note with payment data.

This n8n template allows you to automatically create shortened URLs using the TinyURL API by simply sending a webhook request. It's a quick and efficient way to integrate URL shortening into your automated workflows, ideal for sharing long links in social media, emails, or other applications. 🔧 How it works Receive Link Webhook: This node acts as the entry point for the workflow. It listens for incoming POST requests and expects a JSON body containing the url to be shortened and your api_key for TinyURL. Create TinyURL: This node sends a POST request to the TinyURL API, passing the long URL and your API key. It can also accept optional parameters like domain, alias, and description to customize the shortened link. Respond with Shortened URL: This node sends the response from the TinyURL API (which includes the new shortened URL) back to the service that initiated the webhook. 👤 Who is it for? This workflow is ideal for: Content Managers & Marketers: Quickly shorten links for campaigns, social media posts, or tracking. Developers: Automate the process of link shortening within applications or scripts. Automation Enthusiasts: Integrate a URL shortener into various n8n workflows (e.g., after generating a report, before sending a notification). Anyone needing on-demand short links: A flexible solution for ad-hoc link shortening. 📑 Data Structure When you trigger the webhook, send a POST request with a JSON body structured as follows: { "api_key": "YOUR_TINYURL_API_KEY", "url": "https://www.verylongwebsite.com/path/to/specific/page?param1=value1&param2=value2", "domain": "tinyurl.com", // Optional: defaults to tinyurl.com "alias": "myCustomAlias", // Optional: desired custom alias for the link "description": "My project link" // Optional: description for the link } The workflow will return the JSON response directly from the TinyURL API, which will include the short_url and other details about the newly created link. ⚙️ Setup Instructions Obtain TinyURL API Key: Before importing, make sure you have an API key from TinyURL. You can typically get this by signing up for an account on their website. Import Workflow: In your n8n editor, click "Import from JSON" and paste the provided workflow JSON. Configure Webhook Path: Double-click the Receive Link Webhook node. In the 'Path' field, set a unique and descriptive path (e.g., /shorten-link). Activate Workflow: Save and activate the workflow. 📝 Tips Dynamic Inputs: The workflow is set up to dynamically use the url, api_key, alias, and description from the incoming webhook data. This makes it highly flexible. Error Handling: You can add an Error Trigger node to catch any issues (e.g., invalid API key, malformed URL) during the TinyURL creation process. Configure it to send notifications or log errors for easy troubleshooting. Post-Shortening Actions: After generating the shortened URL, you can insert additional nodes before the Respond with Shortened URL node to perform other actions. For example, you could: Save to a Database: Store the original and shortened URLs in a database like Airtable, Google Sheets, or a PostgreSQL database. Send a Message: Automatically send the shortened URL via Slack, Discord, email, or SMS. Update a Record: Update a CRM record or project management task with the new shortened link. Custom Domains: If you have a custom domain configured with your TinyURL account, you can change the domain parameter in the Create TinyURL node to use it.

Automate Instagram DMs with OpenAI GPT and ManyChat How It Works: Once connected, GPT will automatically initiate conversations with messages from new recipients in Intagram. Who Is This For? This workflow is ideal for marketers, business owners content creators who want to automatically respond to Instagram direct messages using OpenAI GPT. By integrating ManyChat, you can manage conversations, nurture leads, and provide instant replies at scale. What This Workflow Does Captures** incoming Instagram DMs through ManyChat’s integration. Processes** messages with GPT to generate a relevant response. Delivers** instant replies back to Instagram users, creating efficient, AI-driven communication. Setup Import the Template: Copy the n8n workflow into your workspace. OpenAI Credentials: Add your OpenAI API key in n8n so GPT can generate responses. ManyChat Account: Create (or log in to) your ManyChat account. Connect Instagram: Link your Instagram profile as a channel in ManyChat. ManyChat Custom Field: Create a custom field for storing user input or conversation context. Configure Default Reply: In ManyChat, set up the default Instagram reply flow to point to your n8n webhook. Add External Request: Create an external request step in ManyChat to send messages to n8n. Test the Flow: Send yourself a DM on Instagram to confirm the workflow triggers and GPT responds correctly. Instructions and links: Notion instruction Register in ManyChat