Stock market daily digest with Bright Data scraping & Gemini AI email reports

Add Google Sheets rows for new Memberful subscriptions activated

Every time a new subscription is activated in your Memberful, Make will automatically add a Google Sheets row. Here's the [sheet](https://docs.google.com/spreadsheets/d/1Z00W95GxHFJIKmHxI5NahaYItzzO3Rzw8ET71jIW3zc/edit?usp=sharing) used in this scenario.

Send automated emails and add rows in Google Sheets using ChatGPT completions

Automatically send personalized emails and add new rows in Google Sheets with ChatGPT. Triggered by new rows, this workflow enhances communication and data management.

Add a new row to a Google Sheets spreadsheet from a new Delighted response

Every time a new response is collected in Delighted, a new row containing response details will be added to a Google Sheets spreadsheet. The template is using [this sample](https://docs.google.com/spreadsheets/d/1KD60ql1wRRYhhlHyD3lC6aOzPAVcC0jrQBMZdkn9u_w/edit?usp=sharing) Google Sheets spreadsheet as the destination for the Delighted responses. You should make a copy of it before configuring the template. The template is processing the "Thumbs" survey type. More about Delighted survey types

🎓 Optimize Speed-Critical Workflows Using Parallel Processing (Fan-Out/Fan-In)

How it works This template is a hands-on tutorial for one of the most advanced and powerful patterns in n8n: asynchronous parallel processing, also known as the Fan-Out/Fan-In model. When should you use this? Use this pattern when speed is your top priority and you have multiple independent, long-running tasks. Instead of running them one after another (which is slow), this workflow runs them all at the same time and waits for them all to finish. We use a Construction Project analogy to explain

Add tracks from Spotify playlists to Google Sheets for easy management

Effortlessly manage your Spotify playlists by adding tracks to Google Sheets. Automatically filter and organize playlist tracks for streamlined music management.

Automate web research & analysis with Oxylabs & GPT for comprehensive reports

Fully automate deep research from start to finish: scrape Google Search results, select relevant sources, scrape & analyze each source in parallel, and generate a comprehensive research report. Who is this for? This workflow is for anyone who needs to research topics quickly and thoroughly: content creators, marketers, product managers, researchers, journalists, students, or anyone seeking deep insights without spending hours browsing websites. If you find yourself opening dozens of b

Personalise outreach emails using customer data and AI

This n8n template uses existing emails from customers as context to customise and "finetune" outreach emails to them using AI. By now, it should be common knowledge that we can leverage AI to generate unique emails but in a way, they can remain generic as the AI lacks the customer context to be truly personalised. One way to solve this is by pulling in a source of customer data - and what better way then by using existing email correspondence. How it works Customers to target are pulled from Hu

Build a RAG system with automatic citations using Qdrant, Gemini & OpenAI

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 1. Create Qdrant Collection A REST API node creates a new collection in Qdrant with specified vector size (1536) and cosine similarity. 2. Load Files from Google Drive The workflow lists all files in a Googl