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Track real-time stock prices with Yahoo Finance, ScrapegraphAI, and Google Sheets
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. How it works This automated workflow monitors stock prices by scraping real-time data from Yahoo Finance. It uses a scheduled trigger to run at specified intervals, extracts key stock metrics using AI-powered extraction, formats the data through a custom code node, and automatically saves the structured information to Google Sheets for tracking and analysis. Key Steps: Scheduled Trigger: Runs automatically at specified intervals to collect fresh stock data AI-Powered Scraping: Uses ScrapeGraphAI to intelligently extract stock information (symbol, current price, price change, change percentage, volume, and market cap) from Yahoo Finance Data Processing: Formats extracted data through a custom Code node for optimal spreadsheet compatibility and handles both single and multiple stock formats Automated Storage: Saves all stock data to Google Sheets with proper column mapping for easy filtering, analysis, and historical tracking Set up steps Setup Time: 5-10 minutes Configure Credentials: Set up your ScrapeGraphAI API key and Google Sheets OAuth2 credentials Customize Target: Update the website URL in the ScrapeGraphAI node to your desired stock symbol (currently set to AAPL) Configure Schedule: Set your preferred trigger frequency (daily, hourly, etc.) for stock price monitoring Map Spreadsheet: Connect to your Google Sheets document and configure column mapping for the stock data fields Pro Tips: Keep detailed configuration notes in the sticky notes within the workflow Test with a single stock first before scaling to multiple stocks Consider modifying the Code node to handle different stock symbols or add additional data fields Perfect for building a historical database of stock performance over time Can be extended to track multiple stocks by modifying the ScrapeGraphAI prompt
By vinci-king-01Monitor content trends across social media with AI, Slack and Google Sheets
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. How it works This workflow automatically monitors trending topics across multiple platforms and generates content strategy insights for marketing teams. Key Steps Daily Trigger - Runs automatically every 24 hours to capture fresh trends and viral content. Multi-Platform Scraping - Uses AI-powered scrapers to analyze trends from LinkedIn, Twitter, Instagram, Google Trends, BuzzSumo, and Reddit. Trend Analysis - Processes collected data to identify viral patterns, engagement metrics, and content opportunities. Content Strategy Generation - Creates actionable insights for content planning and social media strategy. Team Notifications - Sends comprehensive reports to Slack and updates content calendars in Google Sheets. Set up steps Setup time: 10-15 minutes Configure ScrapeGraphAI credentials - Add your ScrapeGraphAI API key for AI-powered trend scraping. Set up Slack connection - Connect your Slack workspace for team notifications. Configure Google Sheets - Set up a Google Sheets connection for content calendar updates. Customize target industries - Modify the configuration to focus on your specific industry verticals (AI, marketing, tech, etc.). Adjust monitoring frequency - Change the trigger timing based on your content planning needs. What you get Daily trend reports with viral content analysis and engagement metrics Content opportunity scores for different platforms and topics Automated content calendar updates with trending topics and suggested content Team notifications with key insights and actionable recommendations Competitive analysis of viral content patterns and successful strategies
By vinci-king-01Automate news article scraping with ScrapegraphAI and store in Google Sheets
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. News Article Scraping and Analysis with AI and Google Sheets Integration 🎯 Target Audience News aggregators and content curators Media monitoring professionals Market researchers tracking industry news PR professionals monitoring brand mentions Journalists and content creators Business analysts tracking competitor news Academic researchers collecting news data 🚀 Problem Statement Manual news monitoring is time-consuming and often misses important articles. This template solves the challenge of automatically collecting, structuring, and storing news articles from any website for comprehensive analysis and tracking. 🔧 How it Works This workflow automatically scrapes news articles from websites using AI-powered extraction and stores them in Google Sheets for analysis and tracking. Key Components Scheduled Trigger: Runs automatically at specified intervals to collect fresh content AI-Powered Scraping: Uses ScrapeGraphAI to intelligently extract article titles, URLs, and categories from any news website Data Processing: Formats extracted data for optimal spreadsheet compatibility Automated Storage: Saves all articles to Google Sheets with metadata for easy filtering and analysis 📊 Google Sheets Column Specifications The template creates the following columns in your Google Sheets: | Column | Data Type | Description | Example | |--------|-----------|-------------|---------| | title | String | Article headline and title | "'My friend died right in front of me' - Student describes moment air force jet crashed into school" | | url | URL | Direct link to the article | "https://www.bbc.com/news/articles/cglzw8y5wy5o" | | category | String | Article category or section | "Asia" | 🛠️ Setup Instructions Estimated setup time: 10-15 minutes Prerequisites n8n instance with community nodes enabled ScrapeGraphAI API account and credentials Google Sheets account with API access Step-by-Step Configuration Install Community Nodes bash Install ScrapeGraphAI community node npm install n8n-nodes-scrapegraphai Configure ScrapeGraphAI Credentials Navigate to Credentials in your n8n instance Add new ScrapeGraphAI API credentials Enter your API key from ScrapeGraphAI dashboard Test the connection to ensure it's working Set up Google Sheets Connection Add Google Sheets OAuth2 credentials Grant necessary permissions for spreadsheet access Select or create a target spreadsheet for data storage Configure the sheet name (default: "Sheet1") Customize News Source Parameters Update the websiteUrl parameter in the ScrapeGraphAI node Modify the target news website URL as needed Adjust the user prompt to extract additional fields if required Test with a small website first before scaling to larger news sites Configure Schedule Trigger Set your preferred execution frequency (daily, hourly, etc.) Choose appropriate time zones for your business hours Consider the news website's update frequency when setting intervals Test and Validate Run the workflow manually to verify all connections Check Google Sheets for proper data formatting Validate that all required fields are being captured 🔄 Workflow Customization Options Modify News Sources Change the website URL to target different news sources Add multiple news websites for comprehensive coverage Implement filters for specific topics or categories Extend Data Collection Modify the user prompt to extract additional fields (author, date, summary) Add sentiment analysis for article content Integrate with other data sources for comprehensive analysis Output Customization Change Google Sheets operation from "append" to "upsert" for deduplication Add data validation and cleaning steps Implement error handling and retry logic 📈 Use Cases Media Monitoring: Track mentions of your brand, competitors, or industry keywords Content Curation: Automatically collect articles for newsletters or content aggregation Market Research: Monitor industry trends and competitor activities News Aggregation: Build custom news feeds for specific topics or sources Academic Research: Collect news data for research projects and analysis Crisis Management: Monitor breaking news and emerging stories �� Important Notes Respect the target website's terms of service and robots.txt Consider implementing delays between requests for large datasets Regularly review and update your scraping parameters Monitor API usage to manage costs effectively Keep your credentials secure and rotate them regularly 🔧 Troubleshooting Common Issues: ScrapeGraphAI connection errors: Verify API key and account status Google Sheets permission errors: Check OAuth2 scope and permissions Data formatting issues: Review the Code node's JavaScript logic Rate limiting: Adjust schedule frequency and implement delays Pro Tips: Keep detailed configuration notes in the sticky notes within the workflow Test with a small website first before scaling to larger news sites Consider adding filters in the Code node to exclude certain article types or categories Monitor execution logs for any issues and adjust parameters accordingly Support Resources: ScrapeGraphAI documentation and API reference n8n community forums for workflow assistance Google Sheets API documentation for advanced configurations
By vinci-king-01Instagram influencer content monitor with ScrapeGraphAI analysis and ROI tracking
Influencer Content Monitor with ScrapeGraphAI Analysis and ROI Tracking 🎯 Target Audience Marketing managers and brand managers Influencer marketing agencies Social media managers Digital marketing teams Brand partnerships coordinators Marketing analysts and strategists Campaign managers ROI and performance analysts 🚀 Problem Statement Manual monitoring of influencer campaigns is time-consuming and often misses critical performance insights, brand mentions, and ROI calculations. This template solves the challenge of automatically tracking influencer content, analyzing engagement metrics, detecting brand mentions, and calculating campaign ROI using AI-powered analysis and automated workflows. 🔧 How it Works This workflow automatically monitors influencer profiles and content using ScrapeGraphAI for intelligent analysis, tracks brand mentions and sponsored content, calculates performance metrics, and provides comprehensive ROI analysis for marketing campaigns. Key Components Daily Schedule Trigger - Runs automatically every day at 9:00 AM to monitor influencer campaigns ScrapeGraphAI - Influencer Profiles - Uses AI to extract profile data and recent posts from Instagram Content Analyzer - Analyzes post content for engagement rates and quality scoring Brand Mention Detector - Identifies brand mentions and sponsored content indicators Campaign Performance Tracker - Tracks campaign metrics and KPIs Marketing ROI Calculator - Calculates return on investment for campaigns 📊 Data Analysis Specifications The template analyzes and tracks the following metrics: | Metric Category | Data Points | Description | Example | |----------------|-------------|-------------|---------| | Profile Data | Username, Followers, Following, Posts Count, Bio, Verification Status | Basic influencer profile information | "@influencer", "100K followers", "Verified" | | Post Analysis | Post URL, Caption, Likes, Comments, Date, Hashtags, Mentions | Individual post performance data | "5,000 likes", "150 comments" | | Engagement Metrics | Engagement Rate, Content Quality Score, Performance Tier | Calculated performance indicators | "3.2% engagement rate", "High performance" | | Brand Detection | Brand Mentions, Sponsored Content, Mention Count | Brand collaboration tracking | "Nike mentioned", "Sponsored post detected" | | Campaign Performance | Total Reach, Total Engagement, Average Engagement, Performance Score | Overall campaign effectiveness | "50K total reach", "85.5 performance score" | | ROI Analysis | Total Investment, Estimated Value, ROI Percentage, Cost per Engagement | Financial performance metrics | "$2,500 investment", "125% ROI" | 🛠️ Setup Instructions Estimated setup time: 20-25 minutes Prerequisites n8n instance with community nodes enabled ScrapeGraphAI API account and credentials Instagram accounts to monitor (influencer usernames) Campaign budget and cost data for ROI calculations Step-by-Step Configuration Install Community Nodes bash Install required community nodes npm install n8n-nodes-scrapegraphai Configure ScrapeGraphAI Credentials Navigate to Credentials in your n8n instance Add new ScrapeGraphAI API credentials Enter your API key from ScrapeGraphAI dashboard Test the connection to ensure it's working Set up Schedule Trigger Configure the daily schedule (default: 9:00 AM UTC) Adjust timezone to match your business hours Set appropriate frequency for your monitoring needs Configure Influencer Monitoring Update the websiteUrl parameter with target influencer usernames Customize the user prompt to extract specific profile data Set up monitoring for multiple influencers if needed Configure brand keywords for mention detection Customize Brand Detection Update brand keywords in the Brand Mention Detector node Add sponsored content indicators (ad, sponsored, etc.) Configure brand mention sensitivity levels Set up competitor brand monitoring Configure ROI Calculations Update cost estimates in the Marketing ROI Calculator Set value per engagement and reach metrics Configure campaign management costs Adjust ROI calculation parameters Test and Validate Run the workflow manually with test data Verify all analysis steps complete successfully Check data accuracy and calculation precision Validate ROI calculations with actual campaign data 🔄 Workflow Customization Options Modify Monitoring Parameters Adjust monitoring frequency (hourly, daily, weekly) Add more social media platforms (TikTok, YouTube, etc.) Customize engagement rate calculations Modify content quality scoring algorithms Extend Brand Detection Add more sophisticated brand mention detection Implement sentiment analysis for brand mentions Include competitor brand monitoring Add automated alert systems for brand mentions Customize Performance Tracking Modify performance tier thresholds Add more detailed engagement metrics Implement trend analysis and forecasting Include audience demographic analysis Output Customization Add integration with marketing dashboards Implement automated reporting systems Create alert systems for performance drops Add campaign comparison features 📈 Use Cases Influencer Campaign Monitoring: Track performance of influencer partnerships Brand Mention Detection: Monitor brand mentions across influencer content ROI Analysis: Calculate return on investment for marketing campaigns Competitive Intelligence: Monitor competitor brand mentions Performance Optimization: Identify top-performing content and influencers Campaign Reporting: Generate automated reports for stakeholders 🚨 Important Notes Respect Instagram's terms of service and rate limits Implement appropriate delays between requests to avoid rate limiting Regularly review and update brand keywords and detection parameters Monitor API usage to manage costs effectively Keep your credentials secure and rotate them regularly Consider data privacy and compliance requirements Ensure accurate cost data for ROI calculations 🔧 Troubleshooting Common Issues: ScrapeGraphAI connection errors: Verify API key and account status Instagram access issues: Check account accessibility and rate limits Brand detection false positives: Adjust keyword sensitivity ROI calculation errors: Verify cost and value parameters Schedule trigger failures: Check timezone and cron expression Data parsing errors: Review the Code node's JavaScript logic Support Resources: ScrapeGraphAI documentation and API reference n8n community forums for workflow assistance Instagram API documentation and best practices Influencer marketing analytics best practices ROI calculation methodologies and standards
By vinci-king-01Track stock prices with ScrapeGraphAI, Yahoo Finance & Google Sheets
AI-Powered Stock Tracker with Yahoo Finance & Google Sheets ⚠️ COMMUNITY TEMPLATE DISCLAIMER: This is a community-contributed template that uses ScrapeGraphAI (a community node). Please ensure you have the ScrapeGraphAI community node installed in your n8n instance before using this template. This automated workflow monitors stock prices by scraping real-time data from Yahoo Finance. It uses a scheduled trigger to run at specified intervals, extracts key stock metrics using AI-powered extraction, formats the data through a custom code node, and automatically saves the structured information to Google Sheets for tracking and analysis. Pre-conditions/Requirements Prerequisites n8n instance (self-hosted or cloud) ScrapeGraphAI community node installed Google Sheets API access Yahoo Finance access (no API key required) Required Credentials ScrapeGraphAI API Key - For web scraping capabilities Google Sheets OAuth2 - For spreadsheet integration Google Sheets Setup Create a Google Sheets document with the following column structure: | Column A | Column B | Column C | Column D | Column E | Column F | Column G | |----------|----------|----------|----------|----------|----------|----------| | symbol | currentprice | change | changepercent | volume | market_cap | timestamp | | AAPL | 225.50 | +2.15 | +0.96% | 45,234,567 | 3.45T | 2024-01-15 14:30:00 | How it works This automated workflow monitors stock prices by scraping real-time data from Yahoo Finance. It uses a scheduled trigger to run at specified intervals, extracts key stock metrics using AI-powered extraction, formats the data through a custom code node, and automatically saves the structured information to Google Sheets for tracking and analysis. Key Steps: Scheduled Trigger: Runs automatically at specified intervals to collect fresh stock data AI-Powered Scraping: Uses ScrapeGraphAI to intelligently extract stock information (symbol, current price, price change, change percentage, volume, and market cap) from Yahoo Finance Data Processing: Formats extracted data through a custom Code node for optimal spreadsheet compatibility and handles both single and multiple stock formats Automated Storage: Saves all stock data to Google Sheets with proper column mapping for easy filtering, analysis, and historical tracking Set up steps Setup Time: 5-10 minutes Configure Credentials: Set up your ScrapeGraphAI API key and Google Sheets OAuth2 credentials Customize Target: Update the website URL in the ScrapeGraphAI node to your desired stock symbol (currently set to AAPL) Configure Schedule: Set your preferred trigger frequency (daily, hourly, etc.) for stock price monitoring Map Spreadsheet: Connect to your Google Sheets document and configure column mapping for the stock data fields Node Descriptions Core Workflow Nodes: Schedule Trigger - Initiates the workflow at specified intervals Yahoo Finance Stock Scraper - Extracts real-time stock data using ScrapeGraphAI Stock Data Formatter - Processes and formats extracted data for spreadsheet compatibility Google Sheets Stock Logger - Saves formatted stock data to your spreadsheet Data Flow: Trigger → Scraper → Formatter → Logger Customization Examples Track Multiple Stocks javascript // In the ScrapeGraphAI node, modify the URL to track different stocks: const stockSymbols = ['AAPL', 'GOOGL', 'MSFT', 'TSLA']; const baseUrl = 'https://finance.yahoo.com/quote/'; Add Additional Data Fields javascript // In the Code node, extend the data structure: const extendedData = { ...stockData, peratio: extractedData.peratio, dividendyield: extractedData.dividendyield, dayrange: extractedData.dayrange }; Custom Scheduling javascript // Modify the Schedule Trigger for different frequencies: // Daily at 9:30 AM (market open): "0 30 9 *" // Every 15 minutes during market hours: "0 /15 9-16 * 1-5" // Weekly on Monday: "0 0 9 1" Data Output Format The workflow outputs structured JSON data with the following fields: json { "symbol": "AAPL", "current_price": "225.50", "change": "+2.15", "change_percent": "+0.96%", "volume": "45,234,567", "market_cap": "3.45T", "timestamp": "2024-01-15T14:30:00Z" } Troubleshooting Common Issues ScrapeGraphAI Rate Limits - Implement delays between requests Yahoo Finance Structure Changes - Update scraping prompts Google Sheets Permission Errors - Verify OAuth2 credentials and document permissions Performance Tips Use appropriate trigger intervals (avoid excessive scraping) Implement error handling for network issues Consider data validation before saving to sheets Pro Tips: Keep detailed configuration notes in the sticky notes within the workflow Test with a single stock first before scaling to multiple stocks Consider modifying the Code node to handle different stock symbols or add additional data fields Perfect for building a historical database of stock performance over time Can be extended to track multiple stocks by modifying the ScrapeGraphAI prompt
By vinci-king-01Auto-send Zillow real estate listings to Telegram using ScrapeGraphAI
How it works This workflow automatically scrapes real estate listings from Zillow and sends them to a Telegram channel. Key Steps Scheduled Trigger - Runs the workflow at specified intervals to find new listings. AI-Powered Scraping - Uses ScrapeGraphAI to extract property information from Zillow. Data Formatting - Processes and structures the scraped data for Telegram messages. Telegram Integration - Sends formatted listing details to your specified Telegram channel. Set up steps Setup time: 5-10 minutes Configure ScrapeGraphAI credentials - Add your ScrapeGraphAI API key. Set up Telegram connection - Connect your Telegram account and specify the target channel. Customize the Zillow URL - Update the URL to target specific locations or search criteria. Adjust schedule - Modify the trigger timing based on how frequently you want to check for new listings.
By vinci-king-01Social media sentiment analysis dashboard with custom AI for Twitter, Reddit & LinkedIn
Social Media Sentiment Analysis Dashboard with AI and Real-time Monitoring 🎯 Target Audience Social media managers and community managers Marketing teams monitoring brand reputation PR professionals tracking public sentiment Customer service teams identifying trending issues Business analysts measuring social media ROI Brand managers protecting brand reputation Product managers gathering user feedback 🚀 Problem Statement Manual social media monitoring is overwhelming and often misses critical sentiment shifts or trending topics. This template solves the challenge of automatically collecting, analyzing, and visualizing social media sentiment data across multiple platforms to provide actionable insights for brand management and customer engagement. 🔧 How it Works This workflow automatically monitors social media platforms using AI-powered sentiment analysis, processes mentions and conversations, and provides real-time insights through a comprehensive dashboard. Key Components Scheduled Trigger - Runs the workflow at specified intervals to maintain real-time monitoring AI-Powered Sentiment Analysis - Uses advanced NLP to analyze sentiment, emotions, and topics Multi-Platform Integration - Monitors Twitter, Reddit, and other social platforms Real-time Alerting - Sends notifications for critical sentiment changes or viral content Dashboard Integration - Stores all data in Google Sheets for comprehensive analysis and reporting 📊 Google Sheets Column Specifications The template creates the following columns in your Google Sheets: | Column | Data Type | Description | Example | |--------|-----------|-------------|---------| | timestamp | DateTime | When the mention was recorded | "2024-01-15T10:30:00Z" | | platform | String | Social media platform | "Twitter" | | username | String | User who posted the content | "@john_doe" | | content | String | Full text of the post/comment | "Love the new product features!" | | sentiment_score | Number | Sentiment score (-1 to 1) | 0.85 | | sentiment_label | String | Sentiment classification | "Positive" | | emotion | String | Primary emotion detected | "Joy" | | topics | Array | Key topics identified | ["product", "features"] | | engagement | Number | Likes, shares, comments | 1250 | | reach_estimate | Number | Estimated reach | 50000 | | influence_score | Number | User influence metric | 0.75 | | alert_priority | String | Alert priority level | "High" | 🛠️ Setup Instructions Estimated setup time: 20-25 minutes Prerequisites n8n instance with community nodes enabled ScrapeGraphAI API account and credentials Google Sheets account with API access Slack workspace for notifications (optional) Social media API access (Twitter, Reddit, etc.) Step-by-Step Configuration Install Community Nodes bash Install required community nodes npm install n8n-nodes-scrapegraphai npm install n8n-nodes-slack Configure ScrapeGraphAI Credentials Navigate to Credentials in your n8n instance Add new ScrapeGraphAI API credentials Enter your API key from ScrapeGraphAI dashboard Test the connection to ensure it's working Set up Google Sheets Connection Add Google Sheets OAuth2 credentials Grant necessary permissions for spreadsheet access Create a new spreadsheet for sentiment analysis data Configure the sheet name (default: "Sentiment Analysis") Configure Social Media Monitoring Update the websiteUrl parameters in ScrapeGraphAI nodes Add URLs for social media platforms you want to monitor Customize the user prompt to extract specific sentiment data Set up keywords, hashtags, and brand mentions to track Set up Notification Channels Configure Slack webhook or API credentials Set up email service credentials for alerts Define sentiment thresholds for different alert levels Test notification delivery Configure Schedule Trigger Set monitoring frequency (every 15 minutes, hourly, etc.) Choose appropriate time zones for your business hours Consider social media platform rate limits Test and Validate Run the workflow manually to verify all connections Check Google Sheets for proper data formatting Test sentiment analysis with sample content 🔄 Workflow Customization Options Modify Monitoring Targets Add or remove social media platforms Change keywords, hashtags, or brand mentions Adjust monitoring frequency based on platform activity Extend Sentiment Analysis Add more sophisticated emotion detection Implement topic clustering and trend analysis Include influencer identification and scoring Customize Alert System Set different thresholds for different sentiment levels Create tiered alert systems (info, warning, critical) Add sentiment trend analysis and predictions Output Customization Add data visualization and reporting features Implement sentiment trend charts and graphs Create executive dashboards with key metrics Add competitor sentiment comparison 📈 Use Cases Brand Reputation Management: Monitor and respond to brand mentions Crisis Management: Detect and respond to negative sentiment quickly Customer Feedback Analysis: Understand customer satisfaction and pain points Product Launch Monitoring: Track sentiment around new product releases Competitor Analysis: Monitor competitor sentiment and engagement Influencer Identification: Find and engage with influential users 🚨 Important Notes Respect social media platforms' terms of service and rate limits Implement appropriate delays between requests to avoid rate limiting Regularly review and update your monitoring keywords and parameters Monitor API usage to manage costs effectively Keep your credentials secure and rotate them regularly Consider privacy implications and data protection regulations 🔧 Troubleshooting Common Issues: ScrapeGraphAI connection errors: Verify API key and account status Google Sheets permission errors: Check OAuth2 scope and permissions Sentiment analysis errors: Review the Code node's JavaScript logic Rate limiting: Adjust monitoring frequency and implement delays Alert delivery failures: Check notification service credentials Support Resources: ScrapeGraphAI documentation and API reference n8n community forums for workflow assistance Google Sheets API documentation for advanced configurations Social media platform API documentation Sentiment analysis best practices and guidelines
By vinci-king-01Automate deep research with ScrapeGraphAI, GPT-4 & Google Sheets
Deep Research Agent with AI Analysis and Multi-Source Data Collection 🎯 Target Audience Market researchers and analysts Business intelligence teams Academic researchers and students Content creators and journalists Product managers conducting market research Consultants performing competitive analysis Data scientists gathering research data Marketing teams analyzing industry trends 🚀 Problem Statement Manual research processes are time-consuming, inconsistent, and often miss critical information from multiple sources. This template solves the challenge of automating comprehensive research across web, news, and academic sources while providing AI-powered analysis and actionable insights. 🔧 How it Works This workflow automatically conducts deep research on any topic using AI-powered web scraping, collects data from multiple source types, and provides comprehensive analysis with actionable insights. Key Components Webhook Trigger - Receives research requests and initiates the automated research process Research Configuration Processor - Validates and processes research parameters, generates search queries Multi-Source AI Scraping - Uses ScrapeGraphAI to collect data from web, news, and academic sources Data Processing Engine - Combines and structures data from all sources for analysis AI Research Analyst - Uses GPT-4 to provide comprehensive analysis and insights Data Storage - Stores all research findings in Google Sheets for historical tracking Response System - Returns structured research results via webhook response 📊 Google Sheets Column Specifications The template creates the following columns in your Google Sheets: | Column | Data Type | Description | Example | |--------|-----------|-------------|---------| | sessionId | String | Unique research session identifier | "research_1703123456789" | | query | String | Research query that was executed | "artificial intelligence trends" | | timestamp | DateTime | When the research was conducted | "2024-01-15T10:30:00Z" | | analysis | Text | AI-generated comprehensive analysis | "Executive Summary: AI trends show..." | | totalSources | Number | Total number of sources analyzed | 15 | 🛠️ Setup Instructions Estimated setup time: 20-25 minutes Prerequisites n8n instance with community nodes enabled ScrapeGraphAI API account and credentials OpenAI API account and credentials Google Sheets account with API access Step-by-Step Configuration Install Community Nodes bash Install required community nodes npm install n8n-nodes-scrapegraphai Configure ScrapeGraphAI Credentials Navigate to Credentials in your n8n instance Add new ScrapeGraphAI API credentials Enter your API key from ScrapeGraphAI dashboard Test the connection to ensure it's working Set up OpenAI Credentials Add OpenAI API credentials Enter your API key from OpenAI dashboard Ensure you have access to GPT-4 model Test the connection to verify API access Set up Google Sheets Connection Add Google Sheets OAuth2 credentials Grant necessary permissions for spreadsheet access Create a new spreadsheet for research data Configure the sheet name (default: "Research_Data") Configure Research Parameters Update the webhook endpoint URL Customize default research parameters in the configuration processor Set appropriate search query generation logic Configure research depth levels (basic, detailed, comprehensive) Test the Workflow Send a test webhook request with research parameters Verify data collection from all source types Check Google Sheets for proper data storage Validate AI analysis output quality 🔄 Workflow Customization Options Modify Research Sources Add or remove source types (web, news, academic) Customize search queries for specific industries Adjust source credibility scoring algorithms Implement custom data extraction patterns Extend Analysis Capabilities Add industry-specific analysis frameworks Implement comparative analysis between sources Create custom insight generation rules Add sentiment analysis for news sources Customize Data Storage Add more detailed metadata tracking Implement research versioning and history Create multiple sheet tabs for different research types Add data export capabilities Output Customization Create custom response formats Add research summary generation Implement citation and source tracking Create executive dashboard integration 📈 Use Cases Market Research: Comprehensive industry and competitor analysis Academic Research: Literature reviews and citation gathering Content Creation: Research for articles, reports, and presentations Business Intelligence: Strategic decision-making support Product Development: Market validation and trend analysis Investment Research: Due diligence and market analysis 🚨 Important Notes Respect website terms of service and robots.txt files Implement appropriate delays between requests to avoid rate limiting Monitor API usage to manage costs effectively Keep your credentials secure and rotate them regularly Consider data privacy and compliance requirements Validate research findings from multiple sources 🔧 Troubleshooting Common Issues: ScrapeGraphAI connection errors: Verify API key and account status OpenAI API errors: Check API key and model access permissions Google Sheets permission errors: Check OAuth2 scope and permissions Research data quality issues: Review search query generation logic Rate limiting: Adjust request frequency and implement delays Webhook response errors: Check response format and content Support Resources: ScrapeGraphAI documentation and API reference OpenAI API documentation and model specifications n8n community forums for workflow assistance Google Sheets API documentation for advanced configurations
By vinci-king-01AI-powered content gap analysis using ScrapeGraphAI and strategic planning
Content Gap Analyzer with AI-Powered Competitor Intelligence Overview This comprehensive workflow automatically analyzes competitor content strategies and identifies content gaps in your market. Using advanced AI-powered scraping and analysis, it provides actionable insights for content planning, SEO optimization, and competitive advantage. Key Features 🔍 AI-Powered Content Analysis Scrapes and analyzes competitor websites using ScrapeGraphAI Extracts comprehensive content metadata (titles, keywords, engagement metrics) Identifies trending topics and content formats Analyzes your existing content library for comparison 📊 Advanced Gap Identification Identifies topic gaps where competitors are active but you're not Discovers keyword opportunities with low competition Analyzes content format gaps (videos, guides, case studies) Calculates opportunity scores based on engagement and competition 🎯 SEO Strategy Mapping Maps primary, secondary, and long-tail keywords for each opportunity Analyzes search intent (informational, commercial, transactional) Identifies keyword clusters for pillar content strategies Provides SEO difficulty assessments 📅 Strategic Content Planning Generates detailed content plans with specifications Creates 6-month editorial calendars with production timelines Provides resource planning and workload analysis Includes success metrics and performance tracking 🤝 Team Collaboration Exports complete editorial calendar to Google Sheets Enables real-time team collaboration and progress tracking Includes writer assignments and milestone management Provides performance analytics and ROI tracking Workflow Steps Weekly Content Analysis Trigger - Automated weekly execution Competitor Content Scraping - AI-powered analysis of multiple competitors Your Content Library Analysis - Comprehensive audit of existing content Data Processing & Merging - Normalizes and combines competitor data Advanced Gap Identification - Identifies opportunities using scoring algorithms SEO Keyword Mapping - Strategic keyword planning and clustering Content Planning & Roadmap - Detailed content specifications and timelines Editorial Calendar Generation - Production schedules and team assignments Google Sheets Integration - Team collaboration and tracking platform Benefits Competitive Intelligence: Stay ahead of competitor content strategies Data-Driven Decisions: Make content decisions based on real market data SEO Optimization: Target high-opportunity keywords with low competition Resource Efficiency: Optimize content production based on opportunity scores Team Productivity: Streamlined editorial calendar and workflow management Performance Tracking: Monitor content success and ROI Use Cases Content Marketing Teams: Strategic content planning and competitive analysis SEO Specialists: Keyword research and content gap identification Digital Marketing Agencies: Client content strategy development E-commerce Businesses: Product content and educational material planning B2B Companies: Thought leadership and industry content strategies Technical Requirements ScrapeGraphAI Integration: For competitor content analysis Google Sheets API: For editorial calendar storage Weekly Automation: Scheduled execution for continuous monitoring Data Processing: Advanced algorithms for opportunity scoring This workflow transforms competitive intelligence into actionable content strategies, helping you identify and capitalize on content opportunities that your competitors are missing.
By vinci-king-01Enterprise knowledge search with GPT-4 Turbo, Google Drive & Academic APIs
Enterprise Knowledge Search with GPT-4 Turbo, Google Drive & Academic APIs This workflow provides an enterprise-grade RAG (Retrieval-Augmented Generation) system that intelligently searches multiple sources and generates AI-powered responses using GPT-4 Turbo. How it works This workflow provides an enterprise-grade RAG (Retrieval-Augmented Generation) system that intelligently searches multiple sources and generates AI-powered responses using GPT-4 Turbo. Key Steps Form Input - Collects user queries with customizable search scope, response style, and language preferences Intelligent Search - Routes queries to appropriate sources (web, academic papers, news, internal documents) Data Aggregation - Unifies and processes information from multiple sources with quality scoring AI Processing - Uses GPT-4 Turbo to generate context-aware, source-grounded responses Response Enhancement - Formats outputs in various styles (comprehensive, concise, technical, etc.) Multi-Channel Delivery - Delivers results via webhook, email, Slack, and optional PDF generation Data Sources & AI Models Search Sources Web Search: Google, Bing, DuckDuckGo integration Academic Papers: arXiv, PubMed, Google Scholar via Crossref API News Articles: News API, RSS feeds, real-time news Technical Documentation: GitHub, Stack Overflow, documentation sites Internal Knowledge: Google Drive, Confluence, Notion integration AI Models GPT-4 Turbo: Primary language model for response generation Embedding Models: For semantic search and similarity matching Custom Prompts: Specialized prompts for different response styles Set up steps Setup time: 15-20 minutes Configure API credentials - Set up OpenAI API, News API, Google Drive, and other service credentials Set up search sources - Configure academic databases, news APIs, and internal knowledge sources Connect analytics - Link Google Sheets for usage tracking and performance monitoring Configure notifications - Set up Slack channels and email templates for automated alerts Test the workflow - Run sample queries to verify all components are working correctly Keep detailed configuration notes in sticky notes inside your workflow
By vinci-king-01Automated dynamic pricing with AI competitor monitoring & revenue optimization
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. How it works This workflow automatically monitors competitor prices, analyzes market demand, and optimizes product pricing in real-time for maximum profitability using advanced AI algorithms. Key Steps Hourly Trigger - Runs automatically every hour for real-time price optimization and competitive response. Multi-Platform Competitor Monitoring - Uses AI-powered scrapers to track prices from Amazon, Best Buy, Walmart, and Target. Market Demand Analysis - Analyzes Google Trends data to understand search volume trends and seasonal patterns. Customer Sentiment Analysis - Reviews customer feedback to assess price sensitivity and value perception. AI Pricing Optimization - Calculates optimal prices using weighted factors including competitor positioning, demand indicators, and inventory levels. Automated Price Updates - Directly updates e-commerce platform prices when significant opportunities are identified. Comprehensive Analytics - Logs all pricing decisions and revenue projections to Google Sheets for performance tracking. Set up steps Setup time: 15-20 minutes Configure ScrapeGraphAI credentials - Add your ScrapeGraphAI API key for AI-powered competitor and market analysis. Set up e-commerce API connection - Connect your e-commerce platform API for automated price updates. Configure Google Sheets - Set up Google Sheets connections for pricing history and revenue analytics logging. Set up Slack notifications - Connect your Slack workspace for real-time pricing alerts and team updates. Customize product catalog - Modify the product configuration with your actual products, costs, and pricing constraints. Adjust monitoring frequency - Change the trigger timing based on your business needs (hourly, daily, etc.). Configure competitor platforms - Update competitor URLs and selectors for your target market. What you get Real-time price optimization with 15-25% potential revenue increase through intelligent pricing Competitive intelligence with automated monitoring of major e-commerce platforms Market demand insights with seasonal and trend-based pricing adjustments Customer sentiment analysis to understand price sensitivity and value perception Automated price updates when significant opportunities are identified (>2% change, >70% confidence) Comprehensive analytics with pricing history, revenue projections, and performance tracking Team notifications with detailed market analysis and pricing recommendations Margin protection with intelligent constraints to maintain profitability
By vinci-king-01Discover & analyze SEO backlinks with ScrapeGraphAI and Google Sheets
How it works This workflow automatically discovers and analyzes backlinks for any website, providing comprehensive SEO insights and competitive intelligence using AI-powered analysis. Key Steps Website Input - Accepts target URLs via webhook or manual input for backlink analysis. Backlink Discovery - Scrapes and crawls the web to find all backlinks pointing to the target website. AI-Powered Analysis - Uses GPT-4 to analyze backlink quality, relevance, and SEO impact. Data Processing & Categorization - Cleans, validates, and automatically categorizes backlinks by type, authority, and relevance. Database Storage - Saves processed backlink data to PostgreSQL database for ongoing analysis and reporting. API Response - Returns structured summary with backlink counts, domain authority scores, and SEO insights. Set up steps Setup time: 8-12 minutes Configure OpenAI credentials - Add your OpenAI API key for AI-powered backlink analysis. Set up PostgreSQL database - Connect your PostgreSQL database and create the required table structure. Configure webhook endpoint - The workflow provides a /analyze-backlinks endpoint for URL submissions. Customize analysis parameters - Modify the AI prompt to include your preferred SEO metrics and analysis criteria. Test the workflow - Submit a sample website URL to verify the backlink discovery and analysis process. Set up database table - Ensure your PostgreSQL database has a backlinks table with appropriate columns. Features Comprehensive backlink discovery: Finds all backlinks pointing to target websites AI-powered analysis: GPT-4 analyzes backlink quality, relevance, and SEO impact Automatic categorization: Backlinks categorized by type (dofollow/nofollow), authority level, and relevance Data validation: Cleans and validates backlink data with error handling Database storage: PostgreSQL integration for data persistence and historical tracking API responses: Clean JSON responses with backlink summaries and SEO insights Competitive intelligence: Analyzes competitor backlink profiles and identifies link building opportunities Authority scoring: Calculates domain authority and page authority metrics for each backlink
By vinci-king-01