Send Zendesk tickets to Pipedrive contacts and assign tasks
This workflow automatically sends Zendesk tickets to Pipedrive contacts and makes them task assignees. The automation is triggered every 5 minutes, with Zendesk checking and collecting new tickets which are then individually assigned to a Pipedrive contact. Prerequisites Pipedrive account and Pipedrive credentials Zendesk account and Zendesk credentials Note: The Pipedrive and the Zendesk accounts need to be created by the same person / with the same email. How it works Cron node triggers the workflow every 5 minutes. Zendesk node collects all the tickets received after the last execution timestamp. Set node passes only the requester`s email and ID further to the Merge node. Merge by key node merges both inputs together, the tickets and their contact emails. Pipedrive node then searches for the requester. HTTP Request node gets owner information of Pipedrive contact. Set nodes keep only the requester owner's email and the agent`s email and id. Merge by key node merges the information and adds the contact owner to ticket data. Zendesk node changes the assignee to the Pipedrive contact owner or adds a note if the requester is not found. The Function Item node sets the new last execution timestamp.
By n8n TeamAutomate droplet snapshots on DigitalOcean
This workflow automates the management of DigitalOcean Droplet snapshots by listing all droplets, filtering based on the number of snapshots, and deleting excess snapshots before creating new ones. It ensures your droplet snapshots stay organized and within a manageable limit, preventing unnecessary storage costs due to an excess of snapshots. Who is this for? This workflow is perfect for users managing DigitalOcean Droplets and looking to automate the process of snapshot creation and cleanup to save on storage costs and maintain efficient resource management. It’s useful for DevOps teams, cloud administrators, or any developer leveraging DigitalOcean for their infrastructure. What problem is this workflow solving? When managing multiple DigitalOcean Droplets, snapshots can quickly accumulate, taking up space and increasing storage costs. Manually deleting and creating snapshots can be time-consuming and inefficient. This automation solves this problem by automating the snapshot management process, ensuring that no more than a defined number of snapshots are kept per droplet. What this workflow does Runs every 48 hours: The workflow is triggered by a cron node that runs every 48 hours, ensuring timely snapshot management. List all droplets: The workflow retrieves all droplets in the DigitalOcean account. Retrieve snapshots: For each droplet, the workflow retrieves a list of existing snapshots. Filter snapshots: If the number of snapshots exceeds 4, the workflow filters for snapshots that need to be deleted. Delete snapshots: Excess snapshots are automatically deleted based on the filter criteria. Create new snapshot: After cleaning up, the workflow creates a new snapshot for each droplet, ensuring that backups are always up-to-date. Setup DigitalOcean API Key: You’ll need to configure the HTTP Request nodes with your DigitalOcean API key. This key is required for authenticating requests to list droplets, retrieve snapshots, delete snapshots, and create new ones. Snapshot Threshold: By default, the workflow is set to keep no more than 4 snapshots per droplet. This can be adjusted by modifying the filter node conditions. Set Execution Frequency: The cron node is set to run every 48 hours, but you can adjust the timing to suit your needs. How to customize this workflow Adjust Snapshot Limit: Change the value in the filter node if you want to keep more or fewer snapshots. Modify Run Frequency: The workflow runs every 48 hours by default. You can change the frequency in the cron node to run more or less often. Enhance with Notifications: You can add a notification node (e.g., Slack or email) to alert you when snapshots are deleted or created. Workflow Summary This workflow automates the management of DigitalOcean Droplet snapshots by keeping the number of snapshots under a defined limit, deleting the oldest ones, and ensuring new snapshots are created at regular intervals.
By Darryn BalancoCreate an offline DIGIPIN microservice API for precise location mapping in India
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. What is DIGIPIN? DIGIPIN (Digital Pincode) is a 10-character alphanumeric code introduced by India Post. It maps any 3x3 meter square in India to a unique digital address. This helps precisely locate homes, shops, or landmarks, especially in areas where physical addresses are inconsistent or missing. What this workflow does This workflow creates a fully offline DIGIPIN microservice using only JavaScript - no external APIs are used. You get two HTTP endpoints: GET /generate-digipin?lat={latitude}&lon={longitude} → returns a DIGIPIN GET /decode-digipin?digipin={code} → returns the latitude and longitude You can plug this into any system to: Convert GPS coordinates to a DIGIPIN Convert a DIGIPIN back to coordinates How it works An HTTP Webhook node receives the request A JS Function node either encodes or decodes based on input The result is returned as a JSON response All the logic is handled inside the workflow - no API keys, no external calls. Why use this Fast and lightweight Easily extendable: you can connect this to forms, CRMs, apps, or spreadsheets Ideal for field agents, address validation, logistics, or rural operations
By Srinivasan KBBoost posts/statuses from a specific FediVerse account on your Mastodon profile
Template Overview This template is designed for individuals and businesses who want to maintain a consistent presence on the Fediverse while also posting on Threads or managing multiple Fediverse profiles. By automating the process of resharing statuses or posts, this workflow saves time and ensures regular engagement across accounts. --- Use Case The template addresses the challenge of managing activity across Fediverse accounts by automatically boosting or resharing posts from a specific account to your own. It is especially helpful for users who want to consolidate engagement without manually reposting content across multiple platforms or profiles. --- How It Works The workflow runs on a scheduled trigger and retrieves recent posts from a specified Fediverse account, such as your Threads.net account. It uses a JavaScript filter to identify posts from the current day and then automatically boosts or reshares them to your selected Mastodon profile. --- Preconditions You need a Mastodon account with developer access. Identify a Threads.net or other Fediverse account which you want to boost. Basic familiarity with APIs and setting up credentials in n8n. --- Setup Steps Step 1: Create a Developer Application on Mastodon Log in to your Mastodon account and navigate to Preferences > Development > New Application. Fill out the required information and create your application. Set Scopes to atleast read, profile, write:statuses. Click Submit. Note down the access token generated for this application. Step 2: Get the Account ID Use the following command to retrieve the account ID for the profile you want to boost: bash curl -s "https://mastodon.social/api/v1/accounts/lookup?acct=<ACCOUNTNAME>" Alternatively, paste the URL into a GET node on n8n. From the returned JSON, copy the "id" field value (e.g., {"id":"110564198672505618", ...}). Step 3: Update the "Get Statuses" Node Replace <ACCOUNTID> in the URL field with the ID you retrieved in Step 2: https://mastodon.social/api/v1/accounts/<ACCOUNTID>/statuses Step 4: Configure the "Boost Statuses" Node Authentication type will already be set to Header Auth. Grab the access token from Step 1. In the Credential for Header Auth field, create a new credential. Click the pencil icon in the top-left corner to name your credential. In the Name field, enter Authorization. In the Value field, enter Bearer <YOURMASTODONACCESS_TOKEN>. (Note: there is a space after "Bearer.") Save the credential, and it should automatically be selected as your Header Auth. Step 5: Test the Workflow Run the workflow to ensure everything is set up correctly. Adjust filters or parameters as needed for your specific use case. --- Customization Guidance Replace mastodon.social with your own Mastodon domain if you're using a self-hosted instance. Adjust the JavaScript filter logic to meet your specific needs (e.g., filtering by hashtags or keywords). For enhanced security, store the access token as an n8n credential. Embedding it directly in the URL is ++not recommended++. --- Notes This workflow is designed to work with any Mastodon domain. Ensure your Mastodon account has appropriate permissions for boosting posts. By following these steps, you can automate your Fediverse engagement and focus on creating meaningful content while the workflow handles the rest!
By Suleman HasibWooCommerce 🛒 Product Review Sentiment Analysis and AI Report 🤖 for Improvement
This workflow automates the end-to-end analysis of WooCommerce product reviews, transforming raw customer feedback into actionable product and customer-care insights, and delivering them in a structured, visual, and shareable format. This workflow analyzes product review sentiment from WooCommerce using AI. It starts by retrieving reviews for a specified product via the WooCommerce. Each review then undergoes sentiment analysis using LangChain's Sentiment Analysis. The workflow aggregates sentiment data, creates a pie chart visualization via QuickChart, and compiles a comprehensive report using an AI Agent. The report includes executive summaries, quantitative data, qualitative analysis, product diagnostics, and operational recommendations. Finally, the AI-generated report is converted to HTML and emailed to a designated recipient for review by customer and product teams. --- Key Advantages ✅ Full Automation of Review Analysis Eliminates manual work by automating data collection, sentiment analysis, reporting, visualization, and delivery in a single workflow. ✅ Scalable and Reliable Batch processing ensures the workflow can handle dozens or hundreds of reviews without performance issues. ✅ Action-Oriented Insights (Not Just Sentiment) Instead of stopping at sentiment scores, the workflow produces: Root-cause hypotheses Concrete improvement actions Prioritized recommendations (P0 / P1 / P2) Measurable KPIs ✅ Combines Quantitative and Qualitative Analysis Merges hard metrics (averages, distributions, outliers) with qualitative insights (themes, risks, opportunities), giving a 360° view of customer feedback. ✅ Visual + Narrative Output Stakeholders receive both: Visual sentiment charts for quick understanding Structured written reports for strategic decision-making ✅ Ready for Product & Customer Care Teams The output format is tailored for non-technical teams: Clear language Masked personal data (GDPR-friendly) Immediate usability in meetings, emails, or documentation ✅ Easily Extensible The workflow can be extended to: Run on a schedule Analyze multiple products Store results in a database or CRM Trigger alerts for negative sentiment spikes Ideal Use Cases Continuous monitoring of product sentiment Supporting product roadmap decisions Identifying customer pain points early Improving customer support response strategies Reporting customer voice to stakeholders automatically --- How it works Manual Trigger & Configuration The workflow starts manually and sets the target WooCommerce product ID and store URL. Data Retrieval from WooCommerce Fetches all reviews for the selected product via the WooCommerce REST API. Retrieves product details (name, description, categories) to enrich the analysis context. Batch Processing of Reviews Reviews are processed in batches to ensure scalability and reliability, even with a large number of reviews. AI-Powered Sentiment Analysis Each review is analyzed using an OpenAI-based sentiment analysis model. For every review, the workflow extracts: Sentiment category (Positive / Negative / Neutral) Strength (intensity) Confidence (reliability of the classification) Data Normalization & Aggregation Review text is cleaned and structured. Sentiment data is aggregated to compute overall distributions and metrics. Visual Sentiment Distribution A pie chart is dynamically generated via QuickChart to visually represent sentiment distribution. Advanced AI Insight Generation A specialized AI agent (“Product Insights Analyst”) transforms the raw and aggregated data into a professional, structured report, including: Executive summary Quantitative statistics Qualitative themes Product diagnosis Operational recommendations Product backlog ideas Next steps HTML Conversion & Delivery The report is converted into clean HTML. The final output is automatically sent via email to stakeholders (e.g. product or customer care teams). --- Set up steps Configure credentials: Set up WooCommerce API credentials in the HTTP Request node. Add OpenAI API credentials for both sentiment analysis and reporting. Configure Gmail OAuth2 credentials for sending the final email report. Set parameters: In the "Product ID" node, replace PRODUCTID and YOURWEBSITE with actual product ID and WooCommerce site URL. Update the recipient email address in the "Send a message" node. Optional adjustments: Modify the pie chart design in the "QuichChart" node if needed. Adjust the report structure or language in the "Product Insights Analyst" system prompt. Run the workflow: Click "Execute workflow" on the manual trigger to start the process. Monitor execution in n8n to ensure all nodes process correctly. Once configured, the workflow will automatically analyze product reviews, generate insights, and deliver a formatted report via email. --- 👉 Subscribe to my new YouTube channel. Here I’ll share videos and Shorts with practical tutorials and FREE templates for n8n. [](https://youtube.com/@n3witalia) --- Need help customizing? Contact me for consulting and support or add me on Linkedin.
By Davide