Agents & Automations

Video Guide I prepared a detailed guide that showed the whole process of building an AI bot, from the simplest version to the most complex in a template.Who is this for? This workflow is ideal for developers, chatbot enthusiasts, and businesses looking to build a dynamic Telegram bot with memory capabilities. The bot leverages OpenAI's assistant to interact with users and stores user data in Supabase for personalized conversations.What problem does this workflow solve? Many simple chatbots lack context awareness and user memory. This workflow solves that by integrating Supabase to keep track of user sessions (via telegram_id and openai_thread_id), allowing the bot to maintain continuity and context in conversations, leading to a more human-like and engaging experience.What this workflow does This Telegram bot template connects with OpenAI to answer user queries while storing and retrieving user information from a Supabase database. The memory component ensures that the bot can reference past interactions, making it suitable for use cases such as customer support, virtual assistants, or any application where context retention is crucial. 1. Receive New Message: The bot listens for incoming messages from users in Telegram. 2. Check User in Database: The workflow checks if the user is already in the Supabase database using the telegram_id. 3. Create New User (if necessary): If the user does not exist, a new record is created in Supabase with the telegram_id and a unique openai_thread_id. 4. Start or Continue Conversation with OpenAI: Based on the user’s context, the bot either creates a new thread or continues an existing one using the stored openai_thread_id. 5. Merge Data: User-specific data and conversation context are merged. 6. Send and Receive Messages: The message is sent to OpenAI, and the response is received and processed. 7. Reply to User: The bot sends OpenAI’s response back to the user in Telegram.Setup Create a Telegram Bot using the Botfather and obtain the bot token.Set up Supabase: Create a new project and generate a SUPABASE_URL and SUPABASE_KEY. Create a new table named telegram_users with the following SQL query:sql create table public.telegram_users ( id uuid not null default gen_random_uuid (), date_created timestamp with time zone not null default (now() at time zone 'utc'::text), telegram_id bigint null, openai_thread_id text null, constraint telegram_users_pkey primary key (id) ) tablespace pg_default; OpenAI Setup: Create an OpenAI assistant and obtain the OPENAI_API_KEY. Customize your assistant’s personality or use cases according to your requirements.Environment Configuration in n8n: Configure the Telegram, Supabase, and OpenAI nodes with the appropriate credentials. Set up triggers for receiving messages and handling conversation logic. Set up OpenAI assistant ID in "++OPENAI - Run assistant++" node.

💡🌐 Essential Multipage Website Scraper with Jina.ai Use responsibly and follow local rules and regulations. This N8N workflow enables automated multi-page website scraping using Jina.ai's powerful web scraping capabilities, with seamless integration to Google Drive for content storage. Main Features The workflow automatically scrapes multiple pages from a website's sitemap and saves each page's content as a separate Google Drive document. Key ComponentsInput Configuration - Starts with a sitemap URL (default: https://ai.pydantic.dev/sitemap.xml) - Processes the sitemap to extract individual page URLs - Includes filtering options to target specific topics or pages Scraping Process - Uses Jina.ai's web scraper to extract content from each URL - Converts webpage content into clean markdown format - Extracts page titles automatically for document naming Storage Integration - Creates individual Google Drive documents for each scraped page - Names documents using the format "URL - Page Title" - Saves content in markdown format for better readability Usage Instructions 1. Set your target website's sitemap URL in the "Set Website URL" node 2. Configure the "Filter By Topics or Pages" node to select specific content 3. Adjust the "Limit" node (default: 20 pages) to control batch size 4. Connect your Google Drive account 5. Run the workflow to begin automated scraping Additional Features - Built-in rate limiting through the Wait node to prevent overloading servers - Batch processing capability for handling large sitemaps The workflow requires no API key for Jina.ai, making it accessible for immediate use while maintaining responsible scraping practices.

Who this is for? Indeed Data Scraper & Summarization with Airtable, Bright Data and Google Gemini is an automated workflow that extracts company profile information from Indeed using Bright Data Web Unlocker, transforms the data using Google Gemini's LLM, and forwards the transformed response with the summary to a specified webhook for downstream use. This workflow is tailored for: - Recruiters and HR teams who want quick summaries of companies listed on Indeed. - Market researchers and analysts needing structured insights into businesses. - Founders, investors, and consultants scouting potential competitors, partners, or clients. - No-code enthusiasts looking to automate data extraction and enrichment pipelines without manual scraping or parsing. What problem is this workflow solving? Manually gathering structured information about companies on Indeed is time-consuming and inconsistent. Pages vary in structure, and extracting clean, digestible summaries can require technical scraping expertise. This workflow automates: - Extracting company data from Indeed reliably using Bright Data Web Unlocker. - Cleaning and summarizing the extracted content using Google Gemini LLM. - Storing structured insights directly into Airtable for easy access and further workflows. It eliminates manual research, saves hours, and produces AI-enhanced, easily searchable records. What this workflow does - Triggers on-demand. - Pulls company page URLs from Airtable. - Scrapes content from each Indeed company profile using Bright Data Web Unlocker. - Sends the raw HTML to Google Gemini for extraction and summarization. - Sends the summarized data to other platforms via a Webhook notification mechanism. How to customize this workflow to your needs This workflow is built to be flexible - whether you're a company or a market researcher, entrepreneur, or data analyst. Here's how you can adapt it to fit your specific use case: - Extend the scraper: Modify Bright Data targets to pull job listings, salaries, or employee reviews via the Airtable data source. - Customize the summary prompt: Ask Gemini to extract different attributes such as hiring trends, practices, etc. - Routing the output to different destinations: Send summaries or transformed responses to Google Sheets, Airtable, or CRMs like HubSpot or Salesforce.

Discover how to increase your WooCommerce sales with AI-generated, high-converting product descriptions. Enhance SEO ranking, drive organic traffic, and boost revenue effortlessly.

Automatically generate and send newsletters using ChatGPT and Mailchimp. Create engaging content and reach your audience effortlessly. Here is a template to help you get started.

This n8n workflow demonstrates how we can use Multimodal LLMs to parse and extract from PDF documents in n8n. In this particular scenario, we're passing a candidate's CV/resume to an AI which filters out unqualified applications. However, this sneaky candidate has added in a hidden prompt to bypass our bot! Whatever will we do? No fret, using AI Vision is one approach to solve this problem... read on! How it works Our candidate's CV/Resume is a PDF downloaded via Google Drive for this demonstration. The PDF is then converted into an image PNG using a tool called Stirling PDF. Since the hidden prompt has a white font color, it is invisible in the converted image. The image is then forwarded to a Basic LLM node to process using our multimodal model - in this example, we'll use Google's Gemini 1.5 Pro. In the Basic LLM node, we'll need to set a User Message with the type of Binary. This allows us to directly send the image file in our request. The LLM is now immune to the hidden prompt and its response is as expected. Requirements - Google Gemini API Key. Alternatively, GPT-4 will also work for this use-case. - Stirling PDF or another service which can convert PDFs into images. Note for data privacy, this example uses a public API and it is recommended that you self-host and use a private instance of Stirling PDF instead. Customising the workflow Swap out the manual trigger for another trigger such as a webhook to integrate into your existing services. This example demonstrates a validation use-case, i.e., "does the candidate look qualified?". You can try additionally extracting data points such as years of experience, previous companies, etc.

Instantly Find & Fix What’s Holding Your Page Back You’ve put in the work. Your content is strong. Your design is polished. But… ❌ Your page isn’t ranking where it should. ❌ Your competitors are outranking you—even with weaker content. ❌ You have no idea what’s wrong—or how to fix it. The truth? SEO isn’t just about keywords. Your technical setup, content structure, and on-page elements must work together seamlessly. And if anything is off? Google won’t rank your page. --- Who Is This For? - SaaS Founders & Startups – Get higher rankings & organic traffic that converts. - Marketing Teams & Agencies – Audit & optimize pages in seconds. - E-commerce & Content Sites – Improve rankings for product pages, blogs, and landing pages. --- How It Works 1. Paste your URL 2. Get an instant audit + recommendations list 3. Implement changes & watch your rankings jump The workflow scrapes the URL you input, gets the HTML source code of the landing page, and sends it to OpenAI AI Agent. The Agent makes a deep analysis, audits the Technical + Content SEO of the page, and provides 10 Recommendations to improve your SEO. --- Setup Guide You will need OpenAI Credentials with an API Key to run the workflow. The workflow is using the OpenAI-o1 model to deliver the best results. It costs between $0.20/0.30 per run. You can adjust the prompt to your wish in the AI Agent parameters. Once the audit has been completed, it will send an email (don't forget to add your email address here). Below is an example of what you can expect.

SEO Blog Generator with GPT-4o, Perplexity, and Telegram Integration This workflow helps you automatically generate SEO-optimized blog posts using Perplexity.ai, OpenAI GPT-4o, and optionally Telegram for interaction. 🚀 Features - 🧠 Topic research via Perplexity sub-workflow - ✍️ AI-written blog post generated with GPT-4o - 📊 Structured output with metadata: title, slug, meta description - 📩 Integration with Telegram to trigger workflows or receive outputs (optional) ⚙️ Requirements - ✅ OpenAI API Key (GPT-4o or GPT-3.5) - ✅ Perplexity API Key (with access to /chat/completions) - ✅ (Optional) Telegram Bot Token and webhook setup 🛠 Setup InstructionsCredentials: - Add your OpenAI credentials (openAiApi) - Add your Perplexity credentials under httpHeaderAuth - Optional: Setup Telegram credentials under telegramApi Inputs: - Use the Form Trigger or Telegram input node to send a Research Query Subworkflow: - Make sure to import and activate the subworkflow Perplexity_Searcher to fetch recent search results Customization: - Edit prompt texts inside the Blog Content Generator and Metadata Generator to change writing style or target industry - Add or remove output nodes like Google Sheets, Notion, etc. 📦 Output Format The final blog post includes: - ✅ Blog content (1500-2000 words) - ✅ Metadata: title, slug, and meta description - ✅ Extracted summary in JSON - ✅ Delivered to Telegram (if connected) Need help? Reach out on the n8n community forum.

Automatically respond to Telegram updates by analyzing images with ChatGPT. Download files and send replies directly through Telegram for instant communication.

This workflow automates the process of creating a complete SEO-optimized blog post, including generating content, titles, images, and meta tags, and publishing it on WordPress. It leverages AI models (like DeepSeek and OpenRouter) for content generation and SEO optimization, and integrates with Google Sheets, WordPress, and OpenAI for image generation. This is a powerful tool for automating the creation and optimization of blog posts, saving time and ensuring high-quality, SEO-friendly content. It integrates multiple tools and AI models to deliver a seamless content creation experience. Below is a breakdown of the workflow: 1. How It Works The workflow is designed to streamline the creation of SEO-friendly blog posts. Here's how it works: - Trigger: The workflow starts with a Manual Trigger node, which initiates the process when the user clicks "Test workflow." - Fetch Context: The Google Sheets node retrieves the blog post context (e.g., topic, keywords) from a predefined Google Sheet. - Generate Content: - The Generate Article node uses an AI model (DeepSeek) to create an SEO-friendly blog post based on the fetched context. - The Generate Title node creates a compelling, keyword-rich title for the blog post. - Publish to WordPress: - The Add Draft to WP node creates a draft post in WordPress with the generated content and title. - Generate and Upload Image: - The Generate Image node uses OpenAI to create a realistic, blog-appropriate image. - The Upload Image node uploads the image to WordPress media. - The Set Image node associates the uploaded image as the featured image for the blog post. - SEO Optimization: - The SEO Expert node analyzes the blog post and generates optimized meta titles and descriptions using an AI model (OpenRouter). - The Set Metatag node updates the WordPress post with the generated meta tags. - Update Google Sheets: - The Update Sheet and Finish Work nodes update the Google Sheet with the post's details, including the URL, title, and metadata. 2. Set Up Steps To set up and use this workflow in n8n, follow these steps: - Google Sheets Setup: Create a Google Sheet with columns for ID POST, PROMPT, TITLE, URL, METATITLE, and METADESCRIPTION. Link the Google Sheet to the Get Context node by providing the Document ID and Sheet Name. - WordPress Integration: Set up WordPress credentials in n8n for the Add Draft to WP, Upload Image, and Set Image nodes. Ensure the WordPress site is accessible via its REST API. - AI Model Configuration: Configure the DeepSeek and OpenRouter credentials in n8n for the Generate Article, Generate Title, and SEO Expert nodes. Ensure the AI models are correctly set up to generate content and meta tags. - Image Generation: Set up OpenAI credentials for the Generate Image node to create blog post images. - Meta Tag Optimization: The SEO Expert node uses OpenRouter to generate meta titles and descriptions. Ensure the node is configured to analyze the blog post content and produce SEO-friendly tags. - Workflow Execution: Click the "Test workflow" button to trigger the workflow. The workflow will: - Fetch the blog post context from Google Sheets. - Generate the article, title, and image. - Publish the draft to WordPress. - Upload and set the featured image. - Generate and apply meta tags. - Update the Google Sheet with the post details. - Optional Customization: Modify the workflow to include additional SEO optimizations, such as internal linking, keyword density analysis, or social media sharing. Need help customizing? Contact me for consulting and support or add me on LinkedIn.

This n8n workflow assists property managers and surveyors by reducing the time and effort it takes to complete property inventory surveys. In such surveys, articles and goods within a property may need to be captured and reported as a matter of record. This can take a sizable amount of time if the property or number of items is big enough. Our solution is to delegate this task to a capable AI Agent who can identify and fill out the details of each item automatically. How it works An AirTable Base is used to capture just the image of an item within the property. Our workflow monitoring this AirTable Base sends the photo to an AI image recognition model to describe the item for the purpose of identification. Our AI agent uses this description and the help of Google's reverse image search in an attempt to find an online product page for the item. If found, the product page is scraped for the item's specifications which are then used to fill out the rest of the details of the item in our Airtable. Requirements - Airtable for capturing photos and product information - OpenAI account for image recognition service and AI for agent - SerpAPI account for Google reverse image search - Firecrawl.dev account for web scraping Customizing this workflow Try building an internal inventory database to query and integrate into the workflow. This could save on costs by avoiding fetching new each time for common items.

🧠 Problem This Solves Manually sharing Medium articles to LinkedIn daily can be repetitive and time-consuming. This automation: - Fetches the latest Medium articles based on a tag (e.g., android) - Posts them on LinkedIn twice daily - Uses Airtable to prevent duplicates - Sends a confirmation to Telegram once posted Stay consistently active on LinkedIn without lifting a finger. 👥 Who This Template Is For Developers who write or follow Medium content Tech creators or founders looking to grow an audience Community or page managers needing regular curated posts Busy professionals who want hands-free LinkedIn engagement ⚙️ Workflow Breakdown This automation runs at 9:00 AM and 7:00 PM daily and performs these steps: - Fetch articles from MediumAPI.com by tag - Check Airtable to prevent reposting the same article - Post on LinkedIn if it’s new - Store the article ID in Airtable - Send a Telegram message after successful posting 🧾 Step-by-Step Setup Instructions ✅ 1. Airtable Configuration Create a base with: Table Name: PostedArticles Column: ArticleID (Single line text – to track posted articles) 🔗 2. MediumAPI Setup Go to https://mediumapi.com Sign up and generate your API key from the dashboard Use this API endpoint in an HTTP node: GET https://mediumapi.com/api/tag/YOUR_TAG/latest Headers: Authorization: Bearer YOUR_API_KEY Replace YOUR_TAG with a topic like android, ai, webdev, etc. 💬 3. Telegram Bot Setup Go to @BotFather and create a new bot Save the bot token Use @userinfobot to get your Telegram chat ID Add a Telegram node in n8n with the token + chat ID 🔗 4. LinkedIn Setup Create a LinkedIn Developer App Connect it via OAuth2 in n8n Choose to post on your profile or company page 🧱 5. n8n Workflow Structure Node Type Description: - Cron: Triggers the flow twice a day - HTTP Request: Fetches articles from MediumAPI.com - Airtable Search: Checks if article ID already exists - IF Node: Skips duplicates - LinkedIn Post: Publishes to your LinkedIn profile/page - Airtable Create: Stores posted article ID - Telegram Node: Sends success notification 🛠️ Customization Tips - Change the tag in the API URL to match your niche - Add hashtags or personal comments to the LinkedIn message - Schedule different posting times in the Cron node - Filter Medium posts based on length or title keywords (optional)

About The ICP Company Scoring Automation Sorting through lists of potential leads manually to determine who's truly worth your sales team's time isn't just tedious, it's incredibly inefficient. Without proper qualification, your team might spend hours pursuing prospects who aren't the right fit for your product, while ideal customers slip through the cracks. How to Automate Identifying Your Ideal Customers With this automation, you'll learn how to automatically score and prioritize leads using data extracted directly from LinkedIn profiles via Airtop's integration with n8n. By the end, you'll have a fully automated workflow that analyzes prospects and calculates an Ideal Customer Profile (ICP) score, helping your sales team focus on high-potential opportunities. What You'll Need - A free Airtop API key - A copy of this Google Sheets Understanding the Process This automation transforms how you qualify and prioritize leads by extracting real-time, accurate information directly from LinkedIn profiles. Unlike static databases that quickly become outdated, this workflow taps into the most current professional information available. The workflow in this template: - Uses Airtop to extract comprehensive LinkedIn profile data - Analyzes the data to calculate an ICP score based on AI interest, technical depth, and seniority - Updates your Google Sheet with the enriched data and the ICP Company score Company ICP Scoring Workflow Our company-focused workflow analyzes company LinkedIn profiles with a comprehensive set of criteria: - Company Identity Extraction - Company Scale Assessment - Business Classification - Technical Sophistication Assessment - Investment Profile To then calculate the ICP Scoring, it will focus on: - AI Implementation Level: Low-5 pts, Medium-10 pts, High-25 pts - Technical Sophistication: Basic-5 pts, Intermediate-15 pts, Advanced-25 pts, Expert-35 pts - Employee Count: 0-9 employees-5 pts, 10-150 employees-25 pts, 150+ employees-30 pts - Automation Agency Status: True-20 pts, False-0 pts - Geography: US/Europe Based-10 pts, Other-0 pts Setting Up Your Automation We've created ready-to-use templates for both person and company ICP scoring. Here's how to get started: 1. Configure your connections 2. Connect your Google Sheets account 3. Add your Airtop API key (obtain from the Airtop dashboard) 4. Set up your Google Sheet - Ensure your Google Sheet has the necessary columns for input data and result fields - Ensure that columns Linkedin_URL_Company and ICP_Score_Company exist at least 5. Configure the Airtop module - Set up the Airtop module to use the appropriate LinkedIn extraction prompt - Use our provided prompt that extracts company profile data Customization Options While our templates work out of the box, you might want to customize them for your specific needs: - Modify the ICP scoring criteria: Adjust the point values or add additional criteria specific to your business - Add notification triggers: Set up Slack or email notifications for high-value leads that exceed a certain ICP threshold - Implement batch processing: Modify the workflow to process leads in batches to optimize performance - Add conditional logic: Create different scoring models for different industries or product lines - Integrate with your CRM: Integrate this automation with your preferred CRM to get the details added automatically for you Real-World Applications Here's how businesses are using this automation: - AI Sales Platform: A B2B AI company could implement this workflow to process their trade show lead list of contacts. Within hours, they can identify the top 50 prospects based on ICP score. - SaaS Analytics Tool: A SaaS company could implement LinkedIn enrichment to identify which companies fit best. The automation processes weekly leads and categorizes them into high, medium, and low priority tiers, allowing their sales team to focus on the most promising opportunities first. Best Practices To get the most out of this automation: - Review and refine your ICP criteria quarterly: What constitutes an ideal customer may evolve as your product and market develop. - Create tiered follow-up processes: Develop different outreach strategies based on ICP score ranges. - Perform regular data validation: Periodically check the accuracy of the automated scoring against your actual sales results. What's Next? Now that you've automated your ICP scoring with LinkedIn data, you might be interested in: - Setting up automated outreach sequences based on ICP score thresholds - Creating custom reporting dashboards to track conversion rates by ICP segment - Expanding your scoring model to include additional data sources - Implementing lead assignment automation based on ICP scores Happy automating!

This is an example of how we can build a Slack bot in a few easy steps. Before you can start, you need to do a few things: - Create a copy of this workflow. - Create a Slack bot. - Create a slash command on Slack and paste the webhook URL to the Slack command. Note: Make sure to configure this webhook using a HTTPS wrapper and don't use the default http://localhost:5678 as that will not be recognized by your Slack webhook. Once the data has been sent to your webhook, the next step will be passing it via an AI Agent to process data based on the queries we pass to our agent. To have some sort of a memory, be sure to set the Slack token to the memory node. This way you can refer to other chats from the history. The final message is relayed back to Slack as a new message. Since we cannot wait longer than 3000 ms for Slack's response, we will create a new message with reference to the input we passed. We can advance this using the tools or data sources for it to be more custom-tailored for your company. Usage: To use the Slack bot, go to Slack and click on your set slash command (e.g., /Bob) and send your desired message. This will send the message to your endpoint and return the processed results as the message. If you would like help setting this up, feel free to reach out to [email protected].

Chat with local LLMs using n8n and Ollama This n8n workflow allows you to seamlessly interact with your self-hosted Large Language Models (LLMs) through a user-friendly chat interface. By connecting to Ollama, a powerful tool for managing local LLMs, you can send prompts and receive AI-generated responses directly within n8n. Use cases - Private AI Interactions Ideal for scenarios where data privacy and confidentiality are important. - Cost-Effective LLM Usage Avoid ongoing cloud API costs by running models on your own hardware. - Experimentation & Learning A great way to explore and experiment with different LLMs in a local, controlled environment. - Prototyping & Development Build and test AI-powered applications without relying on external services. How it works 1. When chat message received: Captures the user's input from the chat interface. 2. Chat LLM Chain: Sends the input to the Ollama server and receives the AI-generated response. 3. Delivers the LLM's response back to the chat interface.Set up steps Make sure Ollama is installed and running on your machine before executing this workflow. Edit the Ollama address if different from the default.

Case Study I'm too lazy to record every transaction for my expense tracking. Since all my expenses are digital, I just extract the transactions from bank PDF statements and screenshots into CSV to import into my budgeting software. What this workflow does Upload your PDF or screenshots into Google Drive. It then passes the PDF/image to Vertex Gemini to do some A.I. image recognition. It then sends the transactions as CSV and stores it into another Google Drive folder. Setup Set up 2 Google Drive folders: 1 for uploading and 1 for the output. Input your Google Drive credentials. Input your Vertex Gemini credentials. How to adjust it to your needs You can upload other types of documents for information extraction. You can extract any text data from any image or PDF. You can adjust the A.I. prompt to do different things.

Use Case Automate chat interactions in Bitrix24 with a customizable bot that can handle various events and respond to user messages.What This Workflow Does - Processes incoming webhook requests from Bitrix24 - Handles authentication and token validation - Routes different event types (messages, joins, installations) - Provides automated responses and bot registration - Manages secure communication between Bitrix24 and external servicesSetup Instructions - Configure Bitrix24 webhook endpoints - Set up authentication credentials - Customize bot responses and behavior - Deploy and test the workflow

Enhance Security Operations with the Venafi Slack CertBot! Our Venafi Slack CertBot is strategically designed to facilitate immediate security operations directly from Slack. This tool allows end users to request Certificate Signing Requests that are automatically approved or passed to the SecOps team for manual approval depending on the Virustotal analysis of the requested domain. Not only does this help centralize requests, but it helps an organization maintain the security certifications by allowing automated processes to log and analyze requests in real time. Workflow Highlights: - Interactive Modals: Utilizes Slack modals to gather user inputs for scan configurations and report generation, providing a user-friendly interface for complex operations. - Dynamic Workflow Execution: Integrates seamlessly with Venafi to execute CSR generation, and if any issues are found, AI can generate a custom report that is then passed to a Slack teams channel for manual approval with the press of a single button. Operational Flow: 1. Parse Webhook Data: Captures and parses incoming data from Slack to understand user commands accurately. 2. Execute Actions: Depending on the user's selection, the workflow triggers other actions within the flow like automatic Virustotal Scanning. 3. Respond to Slack: Ensures that every interaction is acknowledged, maintaining a smooth user experience by managing modal popups and sending appropriate responses. Setup Instructions: - Verify that Slack and Qualys API integrations are correctly configured for seamless interaction. - Customize the modal interfaces to align with your organization's operational protocols and security policies. - Test the workflow to ensure that it responds accurately to Slack commands and that the integration with Qualys is functioning as expected. Need Assistance? Explore Venafi's Documentation or get help from the n8n Community for more detailed guidance on setup and customization. Deploy this bot within your Slack environment to significantly enhance the efficiency and responsiveness of your security operations, enabling proactive management of CSRs.

Scrape Competitor Reviews & Generate Ad Creatives with Bright Data and OpenAIHow the Flow Runs 1. Fill the Form Enter the Amazon product URL to analyze competitor reviews. 2. Trigger Bright Data Scraper Bright Data scrapes Amazon reviews based on the provided URL. 3. Wait for Snapshot Completion Periodically checks Bright Data until the scraping is complete. 4. Retrieve JSON Data Collects the scraped review data in JSON format. 5. Save Reviews to Google Sheets Automatically appends the scraped reviews to your Google Sheets. 6. Aggregate Reviews Consolidates all reviews into a single summary for simpler analysis. 7. Analyze Reviews with OpenAI LLM Sends the aggregated reviews to OpenAI (GPT-4o mini) to summarize competitors’ main weaknesses clearly. 8. Generate Creative Ad Image OpenAI generates a visually appealing 1080x1080 ad image addressing these identified pain points. 9. Send Ad Creative via Gmail Automatically emails the creative and review summary to your media buying team for immediate use in Meta ads. What You Need - Google Sheets: Template - Bright Data: Dataset and API key - OpenAI API Key: For GPT-4o mini or your preferred LLM - Automation Tool: Ensure it supports HTTP Requests, Wait, Conditional (If), Google Sheets integration, Form Trigger, OpenAI integration, and Gmail integration. Form Fields to Fill - Amazon Product URL: Enter the competitor’s product URL from Amazon. Setup Steps 1. Copy the provided Google Sheet template. 2. Import the JSON workflow into your automation tool. 3. Update credentials for Bright Data, Google Sheets, Gmail, and OpenAI. 4. Test manually by submitting the form and verifying functionality. 5. Optional: Set a schedule for regular workflow execution. Tips - Frequently update URLs to ensure fresh insights. - Allow more wait time for extensive data scrapes. - Focus on targeted products to optimize cost-efficiency. Need Help? Email: [email protected]

Automate Multi-Platform Social Media Content Creation with AIWho is this for? Social Media Managers and Digital Marketers seeking to streamline content production across 7+ platforms (X/Twitter, Instagram, LinkedIn, Facebook, TikTok, Threads, YouTube Shorts) using AI-powered automation. What problem does this solve? Creating platform-optimized content at scale while maintaining brand consistency across multiple channels, reducing manual work by 80% through AI generation and automated publishing. What this workflow doesAI Content Generation: - Uses GPT-4/Gemini to create platform-specific posts - Automatically generates hashtags, CTAs, and emoji placement - Supports image/video suggestions and image creation using OpenAI or Pollinations.ai - Uses SERP API to search for relevant contentApproval Workflow: - Sends formatted HTML emails for human review - Implements double-approval system with Gmail integrationCross-Platform Publishing: - One-click deployment to: - Instagram/Facebook (via Graph API) - X/Twitter (Official API) - LinkedIn (Sales Navigator integration)SetupCredentials: - OpenAI API key - Google Gemini API - Social media platform tokens (X, LinkedIn, Facebook) - ImgBB for image hosting - Gmail - SERP API - TelegramConfiguration: - Update all "your-unique-id" placeholders in API nodes - Set email recipients in Gmail nodes - Customize AI promptsCustomization: - Adjust character limits per platform - Modify approval thresholds - Add/remove social platforms as neededHow to customize - Content Style: Edit prompt templates in the "Social Media Content Factory" agent node - Approval Process: Modify email templates - Analytics: Connect to Google Sheets for performance tracking - Image Generation: Switch between Pollinations.ai/DALL-E/Midjourney

This workflow automatically generates draft replies in Gmail. It's designed for anyone who manages a high volume of emails or often faces writer's block when crafting responses. Since it doesn't send the generated message directly, you're still in charge of editing and approving emails before they go out. How It Works: - Email Trigger: activates when new emails reach the Gmail inbox - Assessment: uses OpenAI GPT-4 and a JSON parser to determine if a response is necessary - Reply Generation: crafts a reply with OpenAI GPT-4 Turbo - Draft Integration: after converting the text to HTML, it places the draft into the Gmail thread as a reply to the first message Set Up Overview (~10 minutes): 1. OAuth Configuration: - Setup Google OAuth in Google Cloud console. - Make sure to add Gmail API with the modify scope. - Add Google OAuth credentials in n8n. - Make sure to add the n8n redirect URI to the Google Cloud Console consent screen settings. 2. OpenAI Configuration: - Add OpenAI API Key in the credentials. 3. Tweaking the prompt: - Edit the system prompt in the "Generate email reply" node to suit your needs. Reach out to me here if you need help building automations for your business.