Workflow Templates

Workflow Overview This workflow automates the process of scraping Trustpilot reviews, extracting key details, analyzing sentiment, and saving the results to Google Sheets. It uses OpenAI for sentiment analysis and HTML parsing for review extraction. How It Works 1. Scrape Trustpilot Reviews HTTP Request**: Fetches review pages from Trustpilot (https://it.trustpilot.com/review/{{company_id}}). Paginates through pages (up to max_page limit). HTML Parsing**: Extracts review URLs using CSS selectors Splits the URLs into individual review links. 2. Extract Review Details Information Extractor**: Uses DeepSeek to extract structured data from the review: Author: Name of the reviewer. Rating: Numeric rating (1-5). Date: Review date in YYYY-MM-DD format. Title: Review title. Text: Full review text. Total Reviews: Number of reviews by the user. Country: Reviewer’s country (2-letter code). 3. Sentiment Analysis Sentiment Analysis Node**: Uses OpenAI to classify the review text as Positive, Neutral, or Negative. Example output: { "category": "Positive", "confidence": 0.95 } 4. Save to Google Sheets Google Sheets Node**: Appends or updates the extracted data to a Google Sheet Set Up Steps 1. Configure Trustpilot Scraping Edit Fields1 Node**: Set company_id to the Trustpilot company name Set max_page to limit the number of pages scraped. 2. Configure Google Sheets Google Sheets Node**: Update the documentId with your Google Sheet ID Ensure the sheet has the required columns (Id, Data, Nome, etc.). 3. Configure OpenAI OpenAI Chat Model Node**: Add your OpenAI API key. Sentiment Analysis Node**: Ensure the categories match your desired sentiment labels (Positive, Neutral, Negative). Key Components Nodes**: HTTP Request/HTML: Scrape and parse Trustpilot reviews. Information Extractor: Extract structured review data using DeepSeek. Sentiment Analysis: Classify review sentiment. Google Sheets: Save and update review data. Credentials**: OpenAI API key. DeepSeek API key. Google Sheets OAuth2.

This workflow implements a Retrieval-Augmented Generation (RAG) system that: Stores vectorized documents in Qdrant, Retrieves relevant content based on user input, Generates AI answers using Google Gemini, Automatically cites the document sources (from Google Drive). Workflow Steps Create Qdrant Collection A REST API node creates a new collection in Qdrant with specified vector size (1536) and cosine similarity. Load Files from Google Drive The workflow lists all files in a Google Drive folder, downloads them as plain text, and loops through each. Text Preprocessing & Embedding Documents are split into chunks (500 characters, with 50-character overlap). Embeddings are created using OpenAI embeddings (text-embedding-3-small assumed). Metadata (file name and ID) is attached to each chunk. Store in Qdrant All vectors, along with metadata, are inserted into the Qdrant collection. Chat Input & Retrieval When a chat message is received, the question is embedded and matched against Qdrant. Top 5 relevant document chunks are retrieved. A Gemini model is used to generate the answer based on those sources. Source Aggregation & Response File IDs and names are deduplicated. The AI response is combined with a list of cited documents (filenames). Final output: AI Response Sources: ["Document1", "Document2"] Main Advantages End-to-end Automation**: From document ingestion to chat response generation, fully automated with no manual steps. Scalable Knowledge Base**: Easy to expand by simply adding files to the Google Drive folder. Traceable Responses**: Each answer includes its source files, increasing transparency and trustworthiness. Modular Design**: Each step (embedding, storage, retrieval, response) is isolated and reusable. Multi-provider AI**: Combines OpenAI (for embeddings) and Google Gemini (for chat), optimizing performance and flexibility. Secure & Customizable**: Uses API credentials and configurable chunk size, collection name, etc. How It Works Document Processing & Vectorization The workflow retrieves documents from a specified Google Drive folder. Each file is downloaded, split into chunks (using a recursive text splitter), and converted into embeddings via OpenAI. The embeddings, along with metadata (file ID and name), are stored in a Qdrant vector database under the collection negozio-emporio-verde. Query Handling & Response Generation When a user submits a chat message, the workflow: Embeds the query using OpenAI. Retrieves the top 5 relevant document chunks from Qdrant. Uses Google Gemini to generate a response based on the retrieved context. Aggregates and deduplicates the source file names from the retrieved chunks. The final output includes both the AI-generated response and a list of source documents (e.g., Sources: ["FAQ.pdf", "Policy.txt"]). Set Up Steps Configure Qdrant Collection Replace QDRANTURL and COLLECTION in the "Create collection" HTTP node to initialize the Qdrant collection with: Vector size: 1536 (OpenAI embedding dimension). Distance metric: Cosine. Ensure the "Clear collection" node is configured to reset the collection if needed. Google Drive & OpenAI Integration Link the Google Drive node to the target folder (Test Negozio in this example). Verify OpenAI and Google Gemini API credentials are correctly set in their respective nodes. Metadata & Output Customization Adjust the "Aggregate" and "Response" nodes if additional metadata fields are needed. Modify the "Output" node to format the response (e.g., changing Sources: {{...}} to match your preferred style). Testing Trigger the workflow manually to test document ingestion. Use the chat interface to verify responses include accurate source attribution. Note: Replace placeholder values (e.g., QDRANTURL) with actual endpoints before deployment. Need help customizing? Contact me for consulting and support or add me on Linkedin.

This n8n template demonstrates walks you through a fully automated process to generate faceless videos - from script creation to final download - using AI-generated voice, images, and smart video editing. Use cases are many: This tool is perfect for YouTube and Shorts creators who want to publish daily content without showing their face, TikTok and Reels marketers automating voice-over-driven videos, and solopreneurs scaling up their content without hiring a team. It’s also ideal for agencies producing batches of faceless video ads, automation enthusiasts building smart media workflows in n8n, and anyone who’s rich in ideas but tired of spending hours editing. How It Works Phase 1: Provide Topic Input A short topic and idea should be entered into the Idea part in Node Fields - Set Idea inside the workflow in n8n. Trigger the process manually by clicking Test Workflow or Execute Workflow. Phase 2: Script Generation Your idea is passed to Google Gemini's chat model. The model returns a concise, 60-second faceless video script. The script is then reformatted into a structured layout optimized for voice generation and visual synchronization. Phase 3: Audio Generation The formatted script is passed to ElevenLabs, which turns the text into a high-quality voiceover audio. The generated audio is uploaded to Google Drive and made publicly accessible. At the same time, the audio is sent to OpenAI Whisper via a POST request to generate a transcription of the voiceover. Phase 4: Timestamps Generation The tool merges the original script and the OpenAI Whisper-generated transcription. The merged data is passed to Google Gemini's chat model to generate image prompts with precise timestamps. The output is parsed and cleaned using a structured parser to ensure it's in ready-to-use JSON format for image generation. Phase 5: Images Generation The full list of timestamped prompts is is split into individual entries. Each prompt is sent to Leonardo's API that turns text descriptions into visuals. A delay of 30 seconds is added to give the image generation engine enough time to complete rendering. Once completed, the workflow retrieves all final images for the next stage. Phase 6: Images To Video Conversion All generated images are sent to Leonardo's API, which stitches them together based on the structured prompts and timing. A 5-minute wait allows time for rendering. After the wait, the workflow retrieves the generated small videos and makes them downloadable. Then, the tool aggregates all downloaded videos into a single unified structure, preparing them for the final editing. Phase 7: Video Editing and Downloading The raw video, along with timestamps or subtitles, is sent to Shotstack, a video editing tool that supports advanced edits. A delay of 1 minute allows Shotstack to process the edit. Then, the tool checks whether the edited video is finished by Shotstack and ready to be downloaded. Once completed, you can download the final polished video to your local storage for later use. How To Use Download the workflow package. Import the package into your n8n interface. Set up necessary credentials for tools access and usability: For Google Gemini access, please connect to its API in the following nodes: Node Google Gemini Chat Model 1 Node Google Gemini Chat Model 2 For Google Drive access, please ensure connection in the following nodes: Node Upload Audio to Drive Node Make Audio File Public For ElevenLabs access, please connect to its API in the following node: Node Generate Voice For OpenAI Whisper access, please connect to its API in the following node: Node Transcribe Audio with OpenAI Whisper For Leonardo access, please allow connection to its API in the following nodes: Node Generate Images Node Generate Videos/Scenes For Shortstack access, please connect to its API in the following nodes: Node Edit with Shotstack Node Render Final Video with Shotstack Input your video idea or short description as a string in Node Fields - Set Idea in n8n. Run the workflow by clicking Execute Workflow or Test Workflow. Wait the process to run and finish. View the result in Node Download Final Video and download it in your local storage for later use. Requirements Basic setup in Google Cloud Console (OAuth or API Key method enabled) with enabled access to Google Drive. Google Gemini API** access with permission to use chat-based large language models. ElevenLabs API** access for generating high-quality voiceovers from scripts. OpenAI Whisper API** access to transcribe voiceovers into clean text. Leonardo API** access for both image and video generation tasks. Shotstack API** access for editing and rendering the final video with enhanced visuals and timing. How To Customize You can input your requested video topic or description directly in Node Fields – Set Idea. By default, the script length is set to around 60 seconds in Node 60 Second Script Writer. You can easily change this in the prompt to create shorter or longer videos based on your needs. While the default setup uses Google Gemini for script and prompt generation, you can replace it with OpenAI ChatGPT, Claude, or any other compatible chat-based model you prefer. The voiceover is currently created using ElevenLabs, but you’re free to substitute it with other text-to-speech engines like Google Cloud Text-to-Speech, HeyGen, etc. We're using OpenAI Whisper to transcribe the voiceover into text. You can switch to alternatives such as AssemblyAI, Deepgram, or other compatible providers depending on your preference. This workflow uses Leonardo for both image and video generation. You can swap it out for other compatible providers based on availability or style preference. Video editing is handled by Shotstack by default. You can plug in alternatives like Runway, FFmpeg, or other API-based editors depending on your editing needs or desired effects. If you’d like this workflow customized to fit your tools and platforms availability, or if you’re looking to build a tailored AI Agent for your own business - please feel free to reach out to Agent Circle. We’re always here to support and help you to bring automation ideas to life. Need Help? Join our community on different platforms for support, inspiration and tips from others. Website: https://www.agentcircle.ai/ Etsy: https://www.etsy.com/shop/AgentCircle Gumroad: http://agentcircle.gumroad.com/ Discord Global: https://discord.gg/d8SkCzKwnP FB Page Global: https://www.facebook.com/agentcircle/ FB Group Global: https://www.facebook.com/groups/aiagentcircle/ X: https://x.com/agent_circle YouTube: https://www.youtube.com/@agentcircle LinkedIn: https://www.linkedin.com/company/agentcircle

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: Configure your connections Connect your Google Sheets account Add your Airtop API key (obtain from the Airtop dashboard) 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 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!

Drive-to-Store is a multi-channel marketing strategy that includes both the web and the physical context, with the aim of increasing the number of customers and sales in physical stores. This strategy guides potential customers from the online world to the physical point of sale through the provision of a coupon that can be spent in the store or on an e-commerce site. The basic idea is to have a landing page with a form and a series of unique coupons to assign to leads as a "reward" for filling out the form. This workflow is ideal for businesses looking to automate lead generation and management, especially when integrating with CRM systems like SuiteCRM and using Google Sheets for data tracking. How It Works Form Submission: The workflow starts with the On form submission node, which triggers when a user submits a form on a landing page. The form collects the user's name, surname, email, and phone number. Form Data Processing: The Form Fields node extracts and sets the form data (name, surname, email, and phone) for use in subsequent steps. Duplicate Lead Check: The Duplicate Lead? node checks if the submitted email already exists in a Google Sheets document. If the email is found, the workflow responds with a "duplicate lead" message (Respond KO node) and stops further processing. Coupon Retrieval: If the email is not a duplicate, the Get Coupon node retrieves a coupon code from the Google Sheets document based on the lead's email. Lead Creation in SuiteCRM: The Create Lead SuiteCRM node creates a new lead in SuiteCRM using the form data and the retrieved coupon code. The lead includes: First name, last name, email, phone number, and coupon code. Google Sheets Update: The Update Sheet node updates the Google Sheets document with the newly created lead's details, including: Name, surname, email, phone, coupon code, lead ID, and the current date and time. Response to Webhook: The Respond OK node sends a success response back to the webhook, indicating that the lead was created successfully. Set Up Steps Configure Form Trigger: Set up the On form submission node to collect user data (name, surname, email, and phone) via a web form. Set Up Google Sheets Integration: Configure the Duplicate Lead?, Get Coupon, and Update Sheet nodes to interact with the Google Sheets document. Ensure the document contains columns for email, coupon, lead ID, and other relevant fields. Set Up SuiteCRM Authentication: Configure the Token SuiteCRM node with the appropriate client credentials (client ID and client secret) to obtain an access token from SuiteCRM. Set Up Lead Creation in SuiteCRM: Configure the Create Lead SuiteCRM node to send a POST request to SuiteCRM's API to create a new lead. Include the form data and coupon code in the request body. Set Up Webhook Responses: Configure the Respond OK and Respond KO nodes to send appropriate JSON responses back to the webhook based on whether the lead was created or if it was a duplicate. Test the Workflow: Submit a test form to ensure the workflow correctly checks for duplicates, retrieves a coupon, creates a lead in SuiteCRM, and updates the Google Sheets document. Activate the Workflow: Once tested, activate the workflow to automate the process of handling form submissions and lead creation. Key Features Duplicate Lead Check**: Prevents duplicate leads by checking if the email already exists in the Google Sheets document. Coupon Assignment**: Retrieves a coupon code from Google Sheets and assigns it to the new lead. SuiteCRM Integration**: Automatically creates a new lead in SuiteCRM with the form data and coupon code. Data Logging**: Logs all lead details in a Google Sheets document for tracking and analysis. Webhook Responses**: Provides immediate feedback on whether the lead was created successfully or if it was a duplicate.

Instantly access NFT metadata, collections, traits, contracts, and ownership details from OpenSea! This workflow integrates GPT-4o-mini AI, OpenSea API, and n8n automation to provide structured NFT data for traders, collectors, and investors. How It Works Receives user queries via Telegram, webhooks, or another connected interface. Determines the correct API tool based on the request (e.g., user profile, NFT metadata, contract details). Retrieves data from OpenSea API (requires API key). Processes the information using an AI-powered NFT insights engine. Returns structured insights in an easy-to-read format for quick decision-making. What You Can Do with This Agent 🔹 Retrieve OpenSea User Profiles → Get user bio, links, and profile info. 🔹 Fetch NFT Collection Details → Get collection metadata, traits, fees, and contract info. 🔹 Analyze NFT Metadata → Retrieve ownership, rarity, and trait-based pricing. 🔹 Monitor NFTs Owned by a Wallet → Track all NFTs under a specific account. 🔹 Retrieve Smart Contract Data → Get blockchain contract details for an NFT collection. 🔹 Identify Valuable Traits → Fetch NFT trait insights and rarity scores. Example Queries You Can Use ✅ "Get OpenSea profile for 0xA5f49655E6814d9262fb656d92f17D7874d5Ac7E." ✅ "Retrieve details for the 'Azuki' NFT collection." ✅ "Fetch metadata for NFT #5678 from 'Bored Ape Yacht Club'." ✅ "Show all NFTs owned by 0x123... on Ethereum." ✅ "Get contract details for NFT collection 'CloneX'." Available API Tools & Endpoints 1️⃣ Get OpenSea Account Profile → /api/v2/accounts/{address_or_username} (Retrieve user bio, links, and image) 2️⃣ Get NFT Collection Details → /api/v2/collections/{collection_slug} (Get collection-wide metadata) 3️⃣ Get NFT Metadata → /api/v2/chain/{chain}/contract/{address}/nfts/{identifier} (Retrieve individual NFT details) 4️⃣ Get NFTs Owned by Account → /api/v2/chain/{chain}/account/{address}/nfts (List all NFTs owned by a wallet) 5️⃣ Get NFTs by Collection → /api/v2/collection/{collection_slug}/nfts (Retrieve all NFTs from a specific collection) 6️⃣ Get NFTs by Contract → /api/v2/chain/{chain}/contract/{address}/nfts (Retrieve all NFTs under a contract) 7️⃣ Get Payment Token Details → /api/v2/chain/{chain}/payment_token/{address} (Fetch info on payment tokens used in NFT transactions) 8️⃣ Get NFT Traits → /api/v2/traits/{collection_slug} (Retrieve collection-wide trait data) Set Up Steps Get an OpenSea API Key Sign up at OpenSea API and request an API key. Configure API Credentials in n8n Add your OpenSea API key under HTTP Header Authentication. Connect the Workflow to Telegram, Slack, or Database (Optional) Use n8n integrations to send alerts to Telegram, Slack, or save results to Google Sheets, Notion, etc. Deploy and Test Send a query (e.g., "Azuki latest sales") and receive instant NFT market insights! Unlock powerful NFT analytics with AI-powered OpenSea insights—start now!

Workflow Description: Automated Content Publishing for WordPress This n8n workflow automates the entire process of content generation, image selection, and scheduled publishing to a self-hosted WordPress website. It is designed for bloggers, marketers, and businesses who want to streamline their content creation and posting workflow. 🌟 Features ✅ AI-Powered Content Generation Uses ChatGPT to generate engaging, market-ready blog articles Dynamically incorporates high-search volume keywords ✅ Automated Image Selection Searches for relevant stock images from Pexels Embeds images directly into posts (Optional)* Supports *Featured Image from URL (FIFU) plugin** for WordPress ✅ Scheduled & Randomized Posting Automatically schedules posts at predefined intervals Supports randomized delay (0-6 hours) for natural publishing ✅ WordPress API Integration Uses WordPress REST API to directly publish posts Configures featured images, categories, and metadata Supports SEO-friendly meta fields ✅ Flexible & Customizable Works with any WordPress website (self-hosted) Can be modified for other CMS platforms 🔧 How It Works 1️⃣ Trigger & Scheduling Automatically runs at preset times or on-demand Supports cron-like scheduling 2️⃣ AI Content Generation Uses a well-crafted prompt to generate high-quality blog posts Extracts relevant keywords for both SEO and image selection 3️⃣ Image Fetching from Pexels Searches and retrieves high-quality images Embeds image credits and ensures proper formatting 4️⃣ WordPress API Integration Sends post title, content, image, and metadata via HTTP Request Can include custom fields, categories, and tags 5️⃣ Randomized Delay Before Publishing Ensures natural posting behavior Avoids bulk publishing issues 📌 Requirements Self-hosted WordPress website* with *REST API enabled** FIFU Plugin* (optional) for *external featured images** n8n Self-Hosted or Cloud Instance** 🚀 Who Is This For? ✅ Bloggers who want to automate content publishing ✅ Marketing teams looking to scale content production ✅ Business owners who want to boost online presence ✅ SEO professionals who need consistent, optimized content 💡 Ready to Automate? 👉 Click here to get this workflow! (Replace with Purchase URL)

CallForge - AI Gong Sales Call Processing Workflow Automate your Gong.io sales call analysis with AI-driven insights, real-time tracking, and structured CRM integration. Who is This For? This workflow is designed for: ✅ Sales teams looking to automate sales call processing. ✅ Revenue operations (RevOps) professionals managing high volumes of call data. ✅ AI-driven sales intelligence teams using Gong.io for data-driven insights. What Problem Does This Workflow Solve? Manually managing and analyzing large volumes of Gong call data is time-consuming and error-prone. With CallForge, you can: ✔ Automate call processing to scale AI-driven insights. ✔ Integrate with Notion to track and organize sales call data efficiently. ✔ Get real-time Slack updates to stay informed on call processing progress. ✔ Handle API failures gracefully, allowing easy reruns if a rate limit is hit. ✔ Ensure AI-ready analysis, feeding structured call data into an AI-powered system. What This Workflow Does 1. Triggers on New Gong Calls Captures new Gong calls and retrieves metadata, call summaries, and participant details. 2. Compares Calls Against Notion Database Checks whether the call has already been processed and stored in Notion. Prevents duplicate entries** from being added. 3. Creates a Parent Notion Record for AI Processing Stores call details such as date, title, URL, company name, sales rep, and opportunity details in Notion. Links calls to Salesforce Opportunity (SF Opp) data. Assigns sales representatives and customer information to each call. 4. Loops Through Calls for Processing Ensures resilience* by allowing failed runs to *restart where they left off**. Processes calls one at a time to prevent Notion rate limits. 5. Sends Call Data to an AI Processor Extracts structured call details and sends them to an AI-powered analysis workflow. Allows multiple AI agents to process and extract structured data from calls. 6. Provides Real-Time Slack Alerts Posts a progress update in Slack when the queue starts processing. Sends real-time call progress notifications. Sends a completion alert once all calls are processed. How to Set Up This Workflow 1. Connect Your APIs 🔹 Gong API Credentials – Ensure you have valid Gong API credentials in n8n. 🔹 Notion Database – Provide access to a Notion database for storing call insights. 🔹 Slack Integration – Configure a Slack channel for progress alerts. 🔹 AI Processing Workflow – Connect an AI-powered call processing workflow for final analysis. CallForge - 01 - Filter Gong Calls Synced to Salesforce by Opportunity Stage CallForge - 02 - Prep Gong Calls with Sheets & Notion for AI Summarization CallForge - 03 - Gong Transcript Processor and Salesforce Enricher CallForge - 04 - AI Workflow for Gong.io Sales Calls CallForge - 05 - Gong.io Call Analysis with Azure AI & CRM Sync CallForge - 06 - Automate Sales Insights with Gong.io, Notion & AI CallForge - 07 - AI Marketing Data Processing with Gong & Notion CallForge - 08 - AI Product Insights from Sales Calls with Notion How to Customize This Workflow 💡 Modify Call Storage – Swap Notion for a different CRM or database (e.g., HubSpot, Airtable, Salesforce). 💡 Change AI Processing – Integrate a custom AI model for analyzing sales conversations. 💡 Customize Slack Notifications – Adjust Slack messages or send alerts via email instead. 💡 Expand with More Integrations – Connect with Salesforce, Pipedrive, or HubSpot for further enrichment. Why Use CallForge? 🚀 Automate Gong call tracking for seamless sales intelligence. 📊 Improve sales operations with structured, AI-powered insights. ⚡ Get real-time updates and keep your team informed instantly. Start optimizing your Gong call processing today!

Trigger on new Typeform form submission Write data to Google Sheet Check severity of problem If very severe post message to Slack If not so severe just send an email Assumptions Google Sheet Sheet in Spreadsheet called "Problems". Columns Names: Name Email Severity Problem Example Sheet: https://docs.google.com/spreadsheets/d/17fzSFl1BZ1njldTfp5lvh8HtS0-pNXH66b7qGZIiGRU Typeform Typeform formular with questions named exactly like the columns of the Google Sheet.

This workflow will trigger daily at 6am to retrieve your day's calendar events from Google Calendar and send them as a summary message to Slack. I've used a low-code method to filter the dates as I can't code much in JSON :) Contact me on https://twitter.com/sami_abid if you have any questions!

CallForge - AI-Powered Marketing Insights Extraction from Sales Calls Automate marketing intelligence gathering from AI-analyzed sales calls and store insights in Notion. 🎯 Who is This For? This workflow is designed for: ✅ Marketing teams looking to extract trends and insights from sales conversations. ✅ Product managers who need direct customer feedback from sales calls. ✅ Revenue operations (RevOps) teams optimizing AI-driven call analysis. It streamlines AI-powered marketing intelligence, identifying customer pain points, competitor mentions, and recurring trends—all automatically stored in Notion. 🔍 What Problem Does This Workflow Solve? Manually reviewing sales call transcripts for marketing insights is time-consuming and inconsistent. With CallForge, you can: ✔ Extract key marketing insights from AI-analyzed sales calls. ✔ Track recurring discussion topics across multiple conversations. ✔ Generate actionable marketing recommendations for strategy and content. ✔ Store structured insights in Notion for seamless access. This automation eliminates manual work and ensures marketing teams get data-driven insights from real customer conversations. 📌 Key Features & Workflow Steps 🎙️ AI-Driven Marketing Insights Processing This workflow processes AI-generated sales call insights and organizes them in Notion databases: Triggers when AI sales call data is received. Identifies marketing-related data (trends, customer pain points, competitor mentions). Extracts key marketing insights, categorizing product discussions and recurring topics. Logs trends across multiple calls, ensuring marketing teams spot recurring themes. Processes actionable insights, capturing marketing strategy recommendations. Stores all findings in Notion, enabling structured, searchable insights. 📊 Notion Database Integration Marketing Insights** → Logs key trends and product mentions from sales calls. Recurring Topics** → Tracks frequently discussed themes across calls. Actionable Recommendations** → Stores AI-generated recommendations for marketing teams. 🛠 How to Set Up This Workflow 1. Prepare Your AI Call Analysis Data Ensure AI-generated sales call insights are available. Compatible with Gong, Fireflies.ai, Otter.ai, and other AI transcription tools. 2. Connect Your Notion Database Set up Notion databases for: 🔹 Marketing Insights (logs trends and product mentions) 🔹 Recurring Topics (tracks frequently discussed customer concerns) 🔹 Actionable Recommendations (stores marketing strategy insights) 3. Configure n8n API Integrations Connect your Notion API key** in n8n under “Notion API Credentials.” Set up webhook triggers** to receive AI-generated sales insights. Test the workflow** using a sample AI sales call analysis. 🔧 How to Customize This Workflow 💡 Modify Notion Data Structure – Adjust fields to match marketing strategy needs. 💡 Refine AI Data Processing Rules – Customize what insights are extracted and logged. 💡 Integrate with Slack or Email – Notify teams when key marketing trends emerge. 💡 Expand CRM Integration – Sync insights with HubSpot, Salesforce, or Pipedrive. CallForge - 01 - Filter Gong Calls Synced to Salesforce by Opportunity Stage CallForge - 02 - Prep Gong Calls with Sheets & Notion for AI Summarization CallForge - 03 - Gong Transcript Processor and Salesforce Enricher CallForge - 04 - AI Workflow for Gong.io Sales Calls CallForge - 05 - Gong.io Call Analysis with Azure AI & CRM Sync CallForge - 06 - Automate Sales Insights with Gong.io, Notion & AI CallForge - 07 - AI Marketing Data Processing with Gong & Notion CallForge - 08 - AI Product Insights from Sales Calls with Notion ⚙️ Key Nodes Used in This Workflow 🔹 If Nodes – Detect if marketing insights, recurring topics, or recommendations exist in AI data. 🔹 Notion Nodes – Create and update entries in Notion databases. 🔹 Split Out & Aggregate Nodes – Process multiple insights and consolidate AI-generated data. 🔹 Wait Nodes – Ensure smooth sequencing of API calls and database updates. 🚀 Why Use This Workflow? ✔ Eliminates manual sales call review for marketing teams. ✔ Provides structured, AI-driven insights for marketing and product strategy. ✔ Tracks competitor mentions and customer pain points automatically. ✔ Improves content marketing and campaign planning with real customer insights. ✔ Scalable for teams using n8n Cloud or self-hosted deployments. This workflow empowers marketing teams by transforming sales call data into actionable intelligence, streamlining strategy, content planning, and competitor analysis. 🚀

This telegram bot is designed to send one random recipe a day. This specific bot has filtered out only vegan recipes, so you can choose your diet type and send only recipes for a specific diet. What credentials you need: Set up a telegram bot. Airtable for listing who has joined your bot. This is needed to send one random recipe a day. Recipe (or other) API. This one uses Spoonacular. I hope you enjoy your bot!