Enrich your company lists with OpenAI GPT-3 ↓
You’ll get valuable information such as:
Market (B2B or B2C)
Industry
Target Audience
Value Proposition
This will help you to:
add more personalization to your outreach
make informed decisions about which accounts to target
I've made the process easy with an n8n workflow.
Here is what it does:
Retrieve website URLs from Google Sheets
Extract the content for each website
Analyze it with GPT-3
Update Google Sheets with GPT-3 data
How it works:
The workflow starts by sending a request to a website to retrieve its HTML content.
It then parses the HTML extracting the relevant information
The extracted data is storted and converted into a CSV file.
The CSV file is attached to an email and sent to your specified address.
The data is simultaneously saved to both Google Sheets and Microsoft Excel for further analysis or use.
Set-up steps:
Change the website to scrape in the "Fetch website content" node
Configure Microsoft Azure credentials with Microsoft Graph permissions (required for the Save to Microsoft Excel 365 node)
Configure Google Cloud credentials with access to Google Drive, Google Sheets and Gmail APIs (the latter is required for the Send CSV via e-mail node).
Who is this for?
This workflow is for all sales reps and lead generation manager who need to prepare their prospecting activities, and find relevant information to personalize their outreach.
Use Case
This workflow allows you to do account research with the web using AI.
It has the potential to replace manual work done by sales rep when preparing their prospecting activities by searching complex information available online.
What this workflow does
The advanced AI module has 2 capabilities:
Research Google using SerpAPI
Visit and get website content using a sub-workflow
From an unstructured input like a domain or a company name.
It will return the following properties:
domain
company Linkedin Url
cheapest plan
has free trial
has entreprise plan
has API
market (B2B or B2C)
The strength of n8n here is that you can adapt this workflow to research whatever information you need.
You just have to precise it in the prompt and to precise the output format in the "Strutured Output Parser" module.
Detailed instructions + video guide can be found by following this link.
Task:
Create a simple API endpoint using the Webhook and Respond to Webhook nodes
Why:
You can prototype or replace a backend process with a single workflow
Main use cases:
Replace backend logic with a workflow
Want to learn the basics of n8n? Our comprehensive quick quickstart tutorial is here to guide you through the basics of n8n, step by step.
Designed with beginners in mind, this tutorial provides a hands-on approach to learning n8n's basic functionalities.
You still can use the app in a workflow even if we don’t have a node for that or the existing operation for that. With the HTTP Request node, it is possible to call any API point and use the incoming data in your workflow
Main use cases:
Connect with apps and services that n8n doesn’t have integration with
Web scraping
How it works
This workflow can be divided into three branches, each serving a distinct purpose:
1.Splitting into Items (HTTP Request - Get Mock Albums):
The workflow initiates with a manual trigger (On clicking 'execute').
It performs an HTTP request to retrieve mock albums data from "https://jsonplaceholder.typicode.com/albums."
The obtained data is split into items using the Item Lists node, facilitating easier management.
2.Data Scraping (HTTP Request - Get Wikipedia Page and HTML Extract):
Another branch of the workflow involves fetching a random Wikipedia page using an HTTP request to "https://en.wikipedia.org/wiki/Special:Random."
The HTML Extract node extracts the article title from the fetched Wikipedia page.
3.Handling Pagination (The final branch deals with handling pagination for a GitHub API request):
It sends an HTTP request to "https://api.github.com/users/that-one-tom/starred," with parameters like the page number and items per page dynamically set by the Set node.
The workflow uses conditions (If - Are we finished?) to check if there are more pages to retrieve and increments the page number accordingly (Set - Increment Page).
This process repeats until all pages are fetched, allowing for comprehensive data retrieval.
Temporary solution using the undocumented REST API for backups using Google drive.
Please note that there are issues with this workflow. It does not support versioning, so please know that it will create multiple copies of the workflows so if you run this daily it will make the folder grow quickly. Once I figure out how to version in Gdrive I'll update it here.
A robust n8n workflow designed to enhance Telegram bot functionality for user management and broadcasting. It facilitates automatic support ticket creation, efficient user data storage in Redis, and a sophisticated system for message forwarding and broadcasting.
How It Works
Telegram Bot Setup: Initiate the workflow with a Telegram bot configured for handling different chat types (private, supergroup, channel).
User Data Management: Formats and updates user data, storing it in a Redis database for efficient retrieval and management.
Support Ticket Creation: Automatically generates chat tickets for user messages and saves the corresponding topic IDs in Redis.
Message Forwarding: Forwards new messages to the appropriate chat thread, or creates a new thread if none exists.
Support Forum Management: Handles messages within a support forum, differentiating between various chat types and user statuses.
Broadcasting System: Implements a broadcasting mechanism that sends channel posts to all previous bot users, with a system to filter out blocked users.
Blocked User Management: Identifies and manages blocked users, preventing them from receiving broadcasted messages.
Versatile Channel Handling: Ensures that messages from verified channels are properly managed and broadcasted to relevant users.
Set Up Steps
Estimated Time**: Around 30 minutes.
Requirements**: A Telegram bot, a Redis database, and Telegram group/channel IDs are necessary.
Configuration**: Input the Telegram bot token and relevant group/channel IDs. Configure message handling and user data processing according to your needs.
Detailed Instructions**: Sticky notes within the workflow provide extensive setup information and guidance.
Live Demo Workflow
Bot: Telegram Bot Link (Click here)
Support Group: Telegram Group Link (Click here)
Broadcasting Channel: Telegram Channel Link (Click here)
Keywords: n8n workflow, Telegram bot, chat ticket system, Redis database, message broadcasting, user data management, support forum automation
This n8n workflow template lets teams easily generate a custom AI chat assistant based on the schema of any Notion database. Simply provide the Notion database URL, and the workflow downloads the schema and creates a tailored AI assistant designed to interact with that specific database structure.
Set Up
Watch this quick set up video 👇
Key Features
Instant Assistant Generation**: Enter a Notion database URL, and the workflow produces an AI assistant configured to the database schema.
Advanced Querying**: The assistant performs flexible queries, filtering records by multiple fields (e.g., tags, names). It can also search inside Notion pages to pull relevant content from specific blocks.
Schema Awareness**: Understands and interacts with various Notion column types like text, dates, and tags for accurate responses.
Reference Links**: Each query returns direct links to the exact Notion pages that inform the assistant’s response, promoting transparency and easy access.
Self-Validation**: The workflow has logic to check the generated assistant, and if any errors are detected, it reruns the agent to fix them.
Ideal for
Product Managers**: Easily access and query product data across Notion databases.
Support Teams**: Quickly search through knowledge bases for precise information to enhance support accuracy.
Operations Teams**: Streamline access to HR, finance, or logistics data for fast, efficient retrieval.
Data Teams**: Automate large dataset queries across multiple properties and records.
How It Works
This AI assistant leverages two HTTP request tools—one for querying the Notion database and another for retrieving data within individual pages. It’s powered by the Anthropic LLM (or can be swapped for GPT-4) and always provides reference links for added transparency.