Amazon affiliate marketing automation
Who this is for This workflow is for Amazon affiliate marketers and social media managers who want to quickly turn product links into engaging Facebook posts with AI-generated captions and images — fully automated. --- What this workflow does This workflow starts every time a new Product Link is added to a connected Google Sheet. It then: Extracts the ASIN from the product link. Fetches product details from Amazon using RapidAPI. Generates a short, scroll-stopping Facebook caption with OpenRouter AI. Creates a product image prompt and sends it to Google Gemini for high-quality image generation. Uploads the creative directly to Facebook via the Facebook Graph API. Marks the Google Sheet row as “Done ✅” after posting. The Facebook post includes: Product image (AI-enhanced) Short, benefit-focused caption with emojis Affiliate link --- Setup To set this template up, follow the sticky notes inside the workflow and: Google Sheets → Connect your sheet and ensure the columns “Product Link” & “Facebook Upload” exist. RapidAPI → Add your API key in the “Amazon Product Details” node. OpenRouter → Add credentials for caption generation. Google Gemini → Add your API key for image generation. Facebook Graph API → Connect your Facebook account for posting. --- How to customize this workflow to your needs Change the Facebook caption prompt to match your tone or branding. Adjust the AI image generation prompt to fit your preferred photography style. Modify the Google Sheet update logic if you want to track additional info (e.g., posting date, engagement stats). Switch Facebook posting to Instagram or another platform by replacing the final API call.
By Rakin JakariaBrand visibility & sentiment analysis across AI search tools (OpenAI, Perplexity, ChatGPT)
This n8n template demonstrates how to audit your brand’s visibility across multiple AI systems and automatically log the results to Google Sheets. It sends the same prompt to OpenAI, Perplexity, and (optionally) a ChatGPT web actor, then runs sentiment and brand-hierarchy analysis on the responses. Use cases are many: benchmark how often (and how positively) your brand appears in AI answers, compare responses across models, and build a repeatable “AI visibility” report for marketing and comms teams. 💡 Good to know You’ll bring your own API keys for OpenAI and Perplexity. Usage costs depend on your providers’ pricing. The optional APIfy actor automates the ChatGPT web UI and may violate terms of service. Use strictly at your own risk. ⁉ How it works A Manual Trigger starts the workflow (you can replace it with any trigger). Input prompts are read from a Google Sheet (or you can use the included “manual input” node). The prompt is sent to three tools: -- OpenAI (via API) to check baseline LLM knowledge. -- Perplexity (API) to retrieve an answer with citations. -- Optionally, an APIfy actor that scrapes a ChatGPT response (web interface). Responses are normalized and mapped (including citations where available). An LLM-powered sentiment pass classifies each response into: -- Basic Polarity: Positive, Neutral, or Negative -- Emotion Category: Joy, Sadness, Anger, Fear, Disgust, or Surprise -- Brand Hierarchy: ordered list such as Nike>Adidas>Puma The consolidated record (Prompt, LLM, Response, Brand mentioned flag, Brand Hierarchy, Basic Polarity, Emotion Category, Source 1–3/4) is appended to your “Output many models” Google Sheet. A simplified branch shows how to take a single response and push it to a separate sheet. 🗺️ How to use Connect your Google Sheets OAuth and create two tabs: -- Input: a single “Prompt” column -- Output: columns for Prompt, LLM, Response, Brand mentioned, Brand Hierarchy, Basic Polarity, Emotion Category, Source 1, Source 2, Source 3, Source 4 Add your OpenAI and Perplexity credentials. (Optional) Add an APIfy credential (Query Auth with token) if you want the ChatGPT web actor path. Run the Manual Trigger to process prompts in batches and write results to Sheets. Adjust the included “Limit for testing” node or remove it to process more rows. ⚒️ Requirements OpenAI API access (e.g., GPT-4.1-mini / GPT-5 as configured in the template) Perplexity API access (model: sonar) Google Sheets account with OAuth connected in n8n (Optional) APIfy account/token for the ChatGPT web actor 🎨 Customising this workflow Swap the Manual Trigger for a webhook or schedule to run audits automatically. Extend the sentiment analyzer instructions to include brand-specific rules or compliance checks. Track more sources (e.g., additional models or vertical search tools) by duplicating the request→map→append pattern. Add scoring (e.g., “visibility score” per prompt) and charts by pointing the output sheet into Looker Studio or a BI tool.
By AOE Agent LabGet updates when a response is created in SurveyMonkey
Companion workflow for SurveyMonkey node docs
By amudhanEdit & deliver images with DALL-E 2, Google Drive & Telegram messaging
🎨 AI Image Editor with Form Upload + Telegram Delivery 🚀 Who’s it for? 👥 This workflow is built for content creators, social media managers, designers, and agencies who need fast, AI-powered image editing without the hassle. Whether you're batch-editing for clients or spicing up personal projects, this tool gets it done — effortlessly. What it does 🛠️ A seamless pipeline that: 📥 Accepts uploads + prompts via a clean form ☁️ Saves images to Google Drive automatically 🧠 Edits images with OpenAI’s image API 📁 Converts results to downloadable PNGs 📬 Delivers the final image instantly via Telegram Perfect for AI-enhanced workflows that need speed, structure, and simplicity. How it works ⚙️ User Uploads: Fill a form with an image + editing prompt Cloud Save: Auto-upload to your Google Drive folder AI Editing: OpenAI processes the image with your prompt Convert & Format: Image saved as PNG Telegram Delivery: Final result sent straight to your chat 💬 You’ll need ✅ 🔑 OpenAI API key 📂 Google Drive OAuth2 setup 🤖 Telegram bot token & chat ID ⚙️ n8n instance (self-hosted or cloud) Setup in 4 Easy Steps 🛠️ Connect APIs Add OpenAI, Google Drive, and Telegram credentials to n8n Store keys securely (avoid hardcoding!) Configure Settings Set Google Drive folder ID Add Telegram chat ID Tweak image size (default: 1024×1024) Deploy the Form Add a Webhook Trigger node Test with a sample image Share the form link with users 🎯 Fine-Tune Variables In the Set node, customize: 📐 Image size 📁 Folder path 📲 Delivery options ⏱️ Timeout duration Want to customize more? 🎛️ 🖼️ Image Settings Change size (e.g. 512x512 or 2048x2048) Update the model (when new versions drop) 📂 Storage Auto-organize files by date/category Add dynamic file names using n8n expressions 📤 Delivery Swap Telegram with Slack, email, Discord Add multiple delivery channels Include image prompt or metadata in messages 📝 Form Upgrades Add fields for advanced editing Validate file types (e.g. PNG/JPEG only) Show a progress bar for long edits ⚡ Advanced Features Add error handling or retry flows Support batch editing Include approvals or watermarking before delivery ⚠️ Notes & Best Practices ✅ Check OpenAI credit balance 🖼️ Test with different image sizes/types ⏱️ Adjust timeout settings for larger files 🔐 Always secure your API keys
By David OlusolaAutomate support ticket classification & routing from HubSpot to Jira with GPT
Who is this for? This n8n workflow template is designed for customer support, CX, and ops teams that manage customer messages through HubSpot and use Jira for internal task management. It is especially useful for SaaS companies aiming to automate ticket triage, sentiment detection, and team assignment using AI agents. --- 🧩 What problem is this workflow solving? Customer service teams often struggle with manual message classification, delayed reactions to churn signals, and inefficiencies in routing support issues to the right internal teams. This workflow uses LLMs and automated profiling to: Detect churn risk or intent in customer messages Summarize issues Classify tickets into categories (e.g. fulfillment, technical, invoicing) Automatically create Jira tickets based on enriched insights --- 🤖 What this workflow does This AI-powered workflow processes HubSpot support tickets and routes them to Jira based on sentiment and topic. Here’s the full breakdown: Triggers: Either manually or on a schedule (via cron). Fetch HubSpot tickets: Retrieves new messages and their metadata. Run Orchestration Agent: Uses Sentinel Agent to detect emotional tone, churn risk, and purchase intent. Calls Profiler Agent to enrich customer profiles from HubSpot. Summarizes the message using OpenAI. Classifies the ticket using a custom classifier (technical, fulfillment, etc.). Generate a Jira ticket: Title and description are generated using GPT. The assignee and project are predefined. AI agents can be expanded (e.g. add Guide or Facilitator agents). --- ⚙️ Setup To use this template, you’ll need: HubSpot account with OAuth2 credentials in n8n Jira Software Cloud account and project ID OpenAI credentials for GPT-based nodes Optional: Create sub-workflows for additional AI agents Steps: Clone the workflow in your n8n instance. Replace placeholder credentials for HubSpot, OpenAI, and Jira. Adjust Jira project/issue type IDs to match your setup. Test the workflow using the manual trigger or scheduled trigger node. --- 🛠️ How to customize this workflow to your needs Edit category logic In the “Category Classifier” node, modify categories and prompt structure to match your internal team structures (e.g., billing, account management, tech support). Refine AI prompts Customize the agent prompt definitions in: Sentinel_agent Profiler_agent Orchestrator to better align with your brand tone or service goals. Update Jira integration You can route tickets to different projects or team leads by adjusting the “Create an issue in Jira” node based on classification output. Add escalation paths Insert Slack, email, or webhook notifications for specific risk levels or customer segments. --- This workflow empowers your team with real-time message triage, automated decision-making, and AI-enhanced customer insight, turning every inbound ticket into a data-driven action item. ---
By PollupAI