by Yaron Been
Scrape Indeed Job Listings for Hiring Signals Using Bright Data and LLMs How the flow runs Fill the form with job position you're hunting for. Bright data's scraper will scrape Indeed based on your requirments. Workflow waits for the snapshot. Data returns as JSON. Jobs append to Google Sheets. Each row goes to an LLM to analyze if you're a good fit for the job (based on your prompts). The LLMswrites YES or NO next to each job opportunity, helping you find job posts that are relevant to you. What you need Google Sheets with our template. Bright Data dataset and API key. OpenAI key for GPT‑4o mini (or any other LLM). n8n with required nodes. Form fields To Fill Job Location** – city or region. Keyword** – role or skills. Country** – two‑letter code. Setup steps Copy the sheet template link. Import the JSON workflow. Add your credentials in nodes. Test the form manually. Add a schedule if desired. Bright Data filter example [ { "country": "US", "domain": "indeed.com", "keyword_search": "Growth Marketer", "location": "Miami", "date_posted": "Last 24 hours" } ] Tips -Choose Last 24 hours often. -Increase wait time for big snapshots. -Narrow keywords to save credits. **Need help? **Email me anytime: Yaron@nofluff.online YouTube: @YaronBeen LinkedIn: https://www.linkedin.com/in/yaronbeen/ Bright Data Docs: https://docs.brightdata.com/introduction
by Leonardo Grigorio
Youtube Video This n8n workflow is designed to assist YouTube content creators in identifying trending topics within a specific niche. By leveraging YouTube's search and data APIs, it gathers and analyzes video performance metrics from the past two days to provide insights into what content is gaining traction. Here's how the workflow operates: Trigger Setup: The workflow begins when a user sends a query through the chat_message_received node. If no niche is provided, the AI prompts the user to select or input one. AI Agent (Language Model): The central node utilizes a GPT-based AI agent to: Understand the user's niche or content preferences. Generate tailored search terms related to the niche. Process YouTube API responses and summarize trends using insights such as common themes, tags, and audience engagement metrics (views, likes, and comments). YouTube Search: The youtube_search node runs a secondary workflow to query YouTube for relevant videos published within the last two days. It retrieves basic video data such as video IDs, relevance scores, and publication dates. Video Details Retrieval: The workflow fetches additional details for each video: Video Snippet: Metadata like title, description, and tags. Video Statistics: Metrics such as views, likes, and comments. Content Details: Video duration, ensuring only content longer than 3 minutes and 30 seconds is analyzed. Data Processing: Video metadata is cleaned, sanitized, and stored in memory. Tags, titles, and descriptions are analyzed to identify patterns and trends across multiple videos. Output: The workflow compiles insights and presents them to the user, highlighting: The most common themes or patterns within the niche. URLs to trending videos and their respective channels. Engagement statistics, helping the user understand the popularity of the content. Key Notes for Setup: API Keys**: Ensure valid YouTube API credentials are configured in the get_videos, find_video_snippet, find_video_statistics, and find_video_data nodes. Memory Buffer**: The window_buffer_memory node ensures the AI agent retains context during analysis, enhancing the quality of the generated insights. Search Term Customization**: The AI agent dynamically creates search terms based on the user’s niche to improve search precision. Use Case: This workflow is ideal for YouTubers or marketers seeking data-driven inspiration for creating content that aligns with current trends, maximizing the potential to engage their audience. Example Output: For the niche "digital marketing": Trending Topic: Videos about "mental triggers" and "psychological marketing." Tags: "SEO," "Conversion Rates," "Social Proof." Engagement: Videos with over 200K views and high likes/comment ratios are leading trends. Video links: https://www.youtube.com/watch?v=video_id1 https://www.youtube.com/watch?v=video_id2
by darrell_tw
How it works Fetch all workflows from your n8n instance. Filter workflows that contain nodes with a modelId setting. Extract the node names, model IDs, model names, workflow names, and workflow URLs. Save the extracted information into a connected Google Sheet. Set up steps Connect your n8n API credentials. Connect your Google Sheets account. Replace "Your n8n domain" with your actual domain URL. Use this Google Sheet template to create a new sheet for results. Setup typically takes 5 minutes. Be cautious: if you have over 100 workflows, performance may be impacted. Notes Sticky notes inside the workflow provide extra guidance. This workflow clears old sheet data before writing new results. Make sure your n8n instance allows API access. Result Example Update: It didn't detect the AI model in tool originally. Now it's fixed! Update 20250429: Support 1.91.0 with open node directly! Optimize the url with node id.
by simonscrapes
What this workflow does: This flow uses an AI node to generate Seed Keywords to focus SEO efforts on based on your ideal customer profile. You can use these keywords to form part of your SEO strategy. Outputs: List of 20 Seed Keywords Setup Fill the Set Ideal Customer Profile (ICP) Connect with your credentials Replace the Connect to your own database with your own database Pre-requisites / Dependencies You know your ideal customer profile (ICP) An AI API account (either OpenAI or Anthropic recommended) More templates and n8n workflows >>> @simonscrapes
by Federico De Ponte
🔁 Loop & Optimize Meta Tags with Google Gemini This workflow automates the shortening of meta titles and descriptions for SEO—directly from your Google Sheet, row by row, using Google Gemini. ✅ What it does Reads rows from a Google Sheet (meta_title, meta_description, row_index) Loops through each row and checks if content exists Sends the data to Google Gemini for length-optimized output Cleans and parses the response Updates the original sheet with the shortened results 🛠️ Setup Requirements Google Sheets (OAuth2 credentials connected in n8n) Google Gemini API key (configured in n8n credentials) Sheet must contain: row_index meta_title meta_description Output will be written into: meta_titleFixed meta_descriptionFixed
by David Olusola
🤖 AI-Powered Lead Enrichment with Explorium MCP & Telegram Who it's for Sales reps, agencies, and growth teams who want to turn basic company info into qualified leads with automated research . Perfect for B2B prospecting. What it does This workflow lets you send a company name or domain via Telegram, and instantly returns: ✅ Enriched company profile (industry, size, tech, pain points) ✅ A clean, structured JSON — ready for your CRM or sales tools How it works 💬 Send company info to your Telegram bot 🔎 Workflow pulls data from Explorium MCP + Tavily 🧠 AI analyzes model, tools, pain points & goals 📤 JSON response sent back via Telegram or logged to your database Requirements 🔐 OpenAI API (GPT-4) 🧠 Explorium MCP API 🌐 Tavily Web Search API 🤖 Telegram Bot API 🗃️ PostgreSQL (for memory/logging) How to set up Add API keys in n8n Connect Telegram bot to webhook Set up PostgreSQL for memory persistence Customize prompts (tone, niche, etc.) Test by sending a company name via Telegram Customization Options 🎯 Focus enrichment on specific industries or keywords 💬 Adjust the email sequence structure & style 🧩 Add extra data sources (e.g. Clearbit, Crunchbase) 🧾 Format JSON to match your CRM schema ⚙️ Add approval step before sending emails Highlights ✅ Uses multi-source enrichment ✅ Works 100% from Telegram ✅ Integrates into any sales pipeline
by Rex Lui
Easily generate QR codes from any URL! This workflow lets users submit a URL via a simple form and instantly receive a downloadable QR code image—perfect for quick sharing or promotions. Setup is fast and user-friendly, so you’ll be up and running in minutes! 🚀 How it works The end user submits a URL through a simple online form. The workflow automatically sends the submitted URL to a QR code generation API. The user receives a downloadable QR code image corresponding to their URL. ⚙️ Setup instruction Import Workflow: Click "Import from JSON" in your n8n environment and paste the provided workflow JSON. Click "Save" and activate the workflow. Double click the "On form submission" node to obtain the production URL. You may now use this URL to do QR code generation.
by explorium
Salesforce Lead Enrichment with Explorium Template Download the following json file and import it to a new n8n workflow: salesforce\_Workflow.json Overview This n8n workflow monitors your Salesforce instance for new leads and automatically enriches them with missing contact information. When a lead is created, the workflow: Detects the new lead via Salesforce trigger Matches the lead against Explorium's database using name and company Enriches the lead with professional email addresses and phone numbers Updates the Salesforce lead record with the discovered contact information This automation ensures your sales team always has the most up-to-date contact information for new leads, improving reach rates and accelerating the sales process. Key Features Real-time Processing**: Triggers automatically when new leads are created in Salesforce Intelligent Matching**: Uses lead name and company to find the correct person in Explorium's database Contact Enrichment**: Adds professional emails, mobile phones, and office phone numbers Batch Processing**: Efficiently handles multiple leads to optimize API usage Error Handling**: Continues processing other leads even if some fail to match Selective Updates**: Only updates leads that successfully match in Explorium Prerequisites Before setting up this workflow, ensure you have: n8n instance (self-hosted or cloud) Salesforce account with: OAuth2 API access enabled Lead object permissions (read/write) API usage limits available Explorium API credentials (Bearer token) - Get explorium api key Basic understanding of Salesforce lead management Salesforce Requirements Required Lead Fields The workflow expects these standard Salesforce lead fields: FirstName - Lead's first name LastName - Lead's last name Company - Company name Email - Will be populated/updated by the workflow Phone - Will be populated/updated by the workflow MobilePhone - Will be populated/updated by the workflow API Permissions Your Salesforce integration user needs: Read access to Lead object Write access to Lead object fields (Email, Phone, MobilePhone) API enabled on the user profile Sufficient API calls remaining in your org limits 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 Salesforce OAuth2 Credentials Click on the Salesforce Trigger node Under Credentials, click Create New Follow the OAuth2 flow: Client ID: From your Salesforce Connected App Client Secret: From your Salesforce Connected App Callback URL: Copy from n8n and add to your Connected App Authorize the connection Save the credentials as "Salesforce account connection" Note: Use the same credentials for all Salesforce nodes in the workflow. Step 3: Configure Explorium API Credentials Click on the Match\_prospect node Under Credentials, click Create New (HTTP Header Auth) Configure the header: Name: Authorization Value: Bearer YOUR_EXPLORIUM_API_TOKEN Save as "Header Auth account" Apply the same credentials to the Explorium Enrich Contacts Information node Step 4: Verify Node Settings Salesforce Trigger: Trigger On: Lead Created Poll Time: Every minute (adjust based on your needs) Salesforce Get Leads: Operation: Get All Condition: CreatedDate = TODAY (fetches today's leads) Limit: 20 (adjust based on volume) Loop Over Items: Batch Size: 6 (optimal for API rate limits) Step 5: Activate the Workflow Save the workflow Toggle the Active switch to ON The workflow will now monitor for new leads every minute Detailed Node Descriptions Salesforce Trigger: Polls Salesforce every minute for new leads Get Today's Leads: Retrieves all leads created today to ensure none are missed Loop Over Items: Processes leads in batches of 6 for efficiency Match Prospect: Searches Explorium for matching person using name + company Filter: Checks if a valid match was found Extract Prospect IDs: Collects all matched prospect IDs Enrich Contacts: Fetches detailed contact information from Explorium Merge: Combines original lead data with enrichment results Split Out: Separates individual enriched records Update Lead: Updates Salesforce with new contact information Data Mapping The workflow maps Explorium data to Salesforce fields as follows: | Explorium Field | Salesforce Field | Fallback Logic | | ------------------- | ---------------- | --------------------------------- | | emails[0].address | Email | Falls back to professions_email | | mobile_phone | MobilePhone | Falls back to phone_numbers[1] | | phone_numbers[0] | Phone | Falls back to mobile_phone | Usage & Monitoring Automatic Operation Once activated, the workflow runs automatically: Checks for new leads every minute Processes any leads created since the last check Updates leads with discovered contact information Continues running until deactivated Manual Testing To test the workflow manually: Create a test lead in Salesforce Click "Execute Workflow" in n8n Monitor the execution to see each step Verify the lead was updated in Salesforce Monitoring Executions Track workflow performance: Go to Executions in n8n Filter by this workflow Review successful and failed executions Check logs for any errors or issues Troubleshooting Common Issues No leads are being processed Verify the workflow is activated Check Salesforce API limits haven't been exceeded Ensure new leads have FirstName, LastName, and Company populated Confirm OAuth connection is still valid Leads not matching in Explorium Verify company names are accurate (not abbreviations) Check that first and last names are properly formatted Some individuals may not be in Explorium's database Try testing with known companies/contacts Contact information not updating Check Salesforce field-level security Verify the integration user has edit permissions Ensure Email, Phone, and MobilePhone fields are writeable Check for validation rules blocking updates Authentication errors Salesforce: Re-authorize OAuth connection Explorium: Verify Bearer token is valid and not expired Check API quotas haven't been exceeded Error Handling The workflow includes built-in error handling: Failed matches don't stop other leads from processing Each batch is processed independently Failed executions are logged for review Partial successes are possible (some leads updated, others skipped) Best Practices Data Quality Ensure complete lead data: FirstName, LastName, and Company should be populated Use full company names: "Microsoft Corporation" matches better than "MSFT" Standardize data entry: Consistent formatting improves match rates Performance Optimization Adjust batch size: Lower if hitting API limits, higher for efficiency Modify polling frequency: Every minute for high volume, less frequent for lower volume Set appropriate limits: Balance between processing speed and API usage Compliance & Privacy Data permissions: Ensure you have rights to enrich lead data GDPR compliance: Consider privacy regulations in your region Data retention: Follow your organization's data policies Audit trail: Monitor who has access to enriched data Customization Options Extend the Enrichment Add more Explorium enrichment by: Adding firmographic data (company size, revenue) Including technographic information Appending social media profiles Adding job title and department verification Modify Trigger Conditions Change when enrichment occurs: Trigger on lead updates (not just creation) Add specific lead source filters Process only leads from certain campaigns Include lead score thresholds Add Notifications Enhance with alerts: Email sales reps when leads are enriched Send Slack notifications for high-value matches Create tasks for leads that couldn't be enriched Log enrichment metrics to dashboards API Considerations Salesforce Limits API calls: Each execution uses \~4 Salesforce API calls Polling frequency: Consider your daily API limit Batch processing: Reduces API usage vs. individual processing Explorium Limits Match API: One call per batch of leads Enrichment API: One call per batch of matched prospects Rate limits: Respect your plan's requests per minute Integration Architecture This workflow can be part of a larger lead management system: Lead Capture → This Workflow → Lead Scoring → Assignment Can trigger additional workflows based on enrichment results Compatible with existing Salesforce automation (Process Builder, Flows) Works alongside other enrichment tools Security Considerations Credentials**: Stored securely in n8n's credential system Data transmission**: Uses HTTPS for all API calls Access control**: Limit who can modify the workflow Audit logging**: All executions are logged with details Support Resources For assistance with: n8n issues**: Consult n8n documentation or community forum Salesforce integration**: Reference Salesforce API documentation Explorium API**: Contact Explorium support for API questions Workflow logic**: Review execution logs for debugging
by Cyril Nicko Gaspar
Amazon Price Monitoring Workflow This workflow enables you to monitor the prices of Amazon product listings directly from a Google Sheet, using data provided by Bright Data’s Amazon Scraper API. It automates the retrieval of price data for specified products and is ideal for market research, competitor analysis, or personal price tracking. ✅ Requirements Before using this template, ensure you have the following: A Bright Data account and access to the Amazon Scraper API. An active API key from Bright Data. A Google Sheet set up with the required columns. N8N account (self-host or cloud version) ⸻ ⚙️ Setup 1. Create a Google Sheet with the following columns: Product URL ZIP Code (used for regional price variations) ASIN (Amazon Standard Identification Number) 2. Extract ASIN Automatically using the following formula in the ASIN column: =REGEXEXTRACT(A2, "/(?:dp|gp/product|product)/([A-Z0-9]{10})") Replace A2 with the appropriate cell reference 3. Obtain an API Key: Sign in to your Bright Data account. Go to the API section to generate an API key. Create a Bearer Authentication Credential using this key in your automation tool. 4. Configure the Workflow: Use a node (e.g., “Google Sheets”) to read data from your sheet. Use an HTTP Request node to send a query to Bright Data’s Amazon API with the ASIN and ZIP code. Parse the returned JSON response to extract product price and other relevant data. Optionally write the output (e.g., current price, timestamp) back into the sheet or another data store. ⸻ Workflow Functionality The workflow is triggered periodically (or manually) and reads product details from your Google Sheet. For each row, it extracts the Product URL and ZIP code and sends a request to the Bright Data API. The API returns product price information, which is then logged or updated back into the sheet using ASIN. You can also map the product URL to the product URL, but ensure that the URL has no parameters. If the URL has appended parameters, refer to the input field from the Bright Data snapshot result. ⸻ 💡 Use Cases E-commerce sellers monitoring competitors’ prices. Consumers tracking price drops on wishlist items. Market researchers collecting pricing data across ZIP codes. Affiliate marketers ensuring accurate product pricing on their platforms. ⸻ 🛠️ Customization Add columns for additional product data such as rating, seller, or stock availability. Schedule the workflow to run hourly, daily, or weekly depending on your needs. Implement email or Slack alerts for significant price changes. Filter by product category or brand to narrow your tracking focus.
by Davide
This workflow is designed to automate the generation and updating of SEO meta titles and descriptions for WooCommerce products using n8n. It leverages Google Sheets for data input, a FREE language model (Gemini 2.0 Flash Exp. via OpenRouter) for generating SEO-optimized meta tags, and WooCommerce for updating product details. How It Works: Trigger: The workflow can be triggered manually or on a schedule. The manual trigger allows for testing, while the schedule trigger can be set to run at regular intervals (e.g., every few minutes) to process new products. Data Retrieval: The workflow starts by retrieving product IDs from a Google Sheets document. It looks for products that do not yet have meta titles or descriptions. Using the retrieved product ID, the workflow fetches the corresponding product details from WooCommerce, including the product name, description, short description, and categories. Meta Tag Generation: The product details are passed to a language model (Gemini 2.0 Flash Exp) via OpenRouter. The model generates SEO-optimized meta titles and descriptions based on the provided content. The generated meta tags are structured and validated to ensure they meet SEO best practices, such as character limits and keyword inclusion. Update WooCommerce: The generated meta title and description are then updated in the WooCommerce product metadata using the Yoast SEO fields. Update Google Sheets: Finally, the workflow updates the Google Sheets document with the newly generated meta tags, along with the product URL, title, and the timestamp of the update. Set Up Steps: Google Sheets Setup: Create a copy of the provided Google Sheets template and insert WooCommerce product IDs in column "B". Ensure the Google Sheets document has columns for METATITLE, METADESCRIPTION, URL, TITLE POST, and DATA (timestamp). n8n Workflow Configuration: Google Sheets Node: Configure the "Get product ID" node to connect to your Google Sheets document. Use OAuth2 for authentication. WooCommerce Node: Set up the WooCommerce nodes to connect to your WooCommerce store using the WooCommerce API credentials. OpenRouter Node: Configure the "Gemini 2.0 Flash Exp" node with your OpenRouter API credentials to access the language model. Structured Output Parser: Ensure the output parser is set to handle the structured data format for meta titles and descriptions. Workflow Execution: Trigger the workflow manually to test the process or set up a schedule trigger to automate the workflow at regular intervals. Monitor the workflow execution to ensure that meta tags are generated and updated correctly in both WooCommerce and Google Sheets. Validation: After the workflow runs, verify that the meta titles and descriptions in WooCommerce are correctly updated and that the Google Sheets document reflects the changes. This workflow streamlines the process of optimizing WooCommerce product pages for SEO, saving time and ensuring consistency in meta tag generation. Need help customizing? Contact me for consulting and support or add me on Linkedin.
by Sira Ekabut
This workflow automates AI-based image generation using the Fal.ai Flux API. Define custom prompts, image parameters, and effortlessly generate, monitor, and save the output directly to Google Drive. Streamline your creative automation with ease and precision. Who is this for? This template is for content creators, developers, automation experts, and creative professionals looking to integrate AI-based image generation into their workflows. It’s ideal for generating custom visuals with the Fal.ai Flux API and automating storage in Google Drive. What problem is this workflow solving? Manually generating AI-based images, checking their status, and saving results can be tedious. This workflow automates the entire process — from requesting image generation, monitoring its progress, downloading the result, and saving it directly to a Google Drive folder. What this workflow does Sets Custom Image Parameters: Allows you to define the prompt, resolution, guidance scale, and steps for AI image generation. Sends a Request to Fal.ai: Initiates the image generation process using the Fal.ai Flux API. Monitors Image Status: Checks for completion and waits if needed. Downloads the Generated Image: Fetches the completed image once ready. Saves to Google Drive: Automatically uploads the generated image to a specified Google Drive folder. Setup 1. Prerequisites: • Fal.ai API Key: Obtain it from the Fal.ai platform and set it as the Authorization header in HTTP Header Auth credentials. • Google Drive OAuth Credentials: Connect your Google Drive account in n8n. 2. Configuration: • Update the “Edit Fields” node with your desired image parameters: • Prompt: Describe the image (e.g., “Thai young woman net idol 25 yrs old, walking on the street”). • Width/Height: Define image resolution (default: 1024x768). • Steps: Number of inference steps (e.g., 30). • Guidance Scale: Controls image adherence to the prompt (e.g., 3.5). • Set your Google Drive folder ID in the “Google Drive” node to save the image. 3. Run the Workflow: • Trigger the workflow manually to generate the image. • The workflow waits, checks status, and saves the final output seamlessly. Customization • Modify Image Parameters: Adjust the prompt, resolution, steps, and guidance scale in the “Edit Fields” node. • Change Storage Location: Update the Google Drive node with a different folder ID. • Add Notifications: Integrate an email or messaging node to alert you when the image is ready. • Additional Outputs: Expand the workflow to send the generated image to Slack, Dropbox, or other platforms. This workflow streamlines AI-based image generation and storage, offering flexibility and customization for creative automation.
by Ranjan Dailata
Who this is for? This workflow enables automated, scalable collection of high-quality, AI-ready data from websites using Bright Data’s Web Unlocker, with a focus on preparing that data for LLM training. Leveraging LLM Chains and AI agents, the system formats and extracts key information, then stores the structured embeddings in a Pinecone vector database. This workflow is tailored for: ML Engineers & Researchers building or fine-tuning domain-specific LLMs. AI Startups needing clean, structured content for product training. Data Teams preparing knowledge bases for enterprise-grade AI apps. LLM-as-a-Service Providers sourcing dynamic web content across niches. What problem is this workflow solving? Training a large language model (LLM) requires vast amounts of clean, relevant, and structured data. Manual collection is slow, error-prone, and lacks scalability. This workflow: Automatically extracts web data from specified URLs. Bypasses anti-bot measures using Bright Data’s Web Unlocker. Formats, cleans, and transforms raw content using LLM agents. Stores semantically searchable vectors in Pinecone. Makes datasets AI-ready for fine-tuning, RAG, or domain-specific training. What this workflow does This workflow automates the process of collecting, cleaning, and vectorizing web content to create structured, high-quality datasets that are ready to be used for LLM (Large Language Model) training or retrieval-augmented generation (RAG). Web Crawling with Bright Data Web Unlocker. AI Information Extraction and Data Formatting. AI Data Formatting to produce a JSON structured data. Persistence in Pinecone Vector DB. Handle Webhook notification of structured data. Setup Sign up at Bright Data. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. In n8n, configure the Header Auth account under Credentials (Generic Auth Type: Header Authentication). The Value field should be set with the Bearer XXXXXXXXXXXXXX. The XXXXXXXXXXXXXX should be replaced by the Web Unlocker Token. A Google Gemini API key (or access through Vertex AI or proxy). Update the LinkedIn URL by navigating to the Set LinkedIn URL node. Update the Set Fields - URL and Webhook URL node with the URL for web data extraction and the Webhook notification URL. How to customize this workflow to your needs Set Your Target URLs. Target sites that are high-quality, domain-specific, and relevant to your LLM's purpose. Adjust Bright Data Web Unlocker Settings. Geo-location, Headers / User-Agent strings, Retry rules and proxies. Modify the Information Extraction Logic. Change prompts to extract specific attributes. Use structured templates or few-shot examples in prompts. Swap the Embedding Model. Use OpenAI, Hugging Face or other your own hosted embedding model API. Customize Pinecone Metadata Fields. Store extra fields in Pinecone for better filtering & semantic querying. Add Data Validation or Deduplication. Skip duplicates or low-quality content.