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).
This n8n template builds a simple WhatsApp chabot acting as a Sales Agent. The Agent is backed by a product catalog vector store to better answer user's questions.
This template is intended to help introduce n8n users interested in building with WhatsApp.
How it works
This template is in 2 parts: creating the product catalog vector store and building the WhatsApp AI chatbot.
A product brochure is imported via HTTP request node and its text contents extracted.
The text contents are then uploaded to the in-memory vector store to build a knowledgebase for the chatbot.
A WhatsApp trigger is used to capture messages from customers where non-text messages are filtered out.
The customer's message is sent to the AI Agent which queries the product catalogue using the vector store tool.
The Agent's response is sent back to the user via the WhatsApp node.
How to use
Once you've setup and configured your WhatsApp account and credentials
First, populate the vector store by clicking the "Test Workflow" button.
Next, activate the workflow to enable the WhatsApp chatbot.
Message your designated WhatsApp number and you should receive a message from the AI sales agent.
Tweak datasource and behaviour as required.
Requirements
WhatsApp Business Account
OpenAI for LLM
Customising this workflow
Upgrade the vector store to Qdrant for persistance and production use-cases.
Handle different WhatsApp message types for a more rich and engaging experience for customers.
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.
This workflow automatically generates draft replies in Gmail.
It's designed for anyone who manages a high volume of emails or often face writer's block when crafting responses.
Since it doesn't send the generated message directly, you're still in charge of editing and approving emails before they go out.
How It Works:
Email Trigger: activates when new emails reach the Gmail inbox
Assessment: uses OpenAI gpt-4o and a JSON parser to determine if a response is necessary.
Reply Generation: crafts a reply with OpenAI GPT-4 Turbo
Draft Integration: after converting the text to html, it places the draft into the Gmail thread as a reply to the first message
Set Up Overview (~10 minutes):
OAuth Configuration (follow n8n instructions here):
Setup Google OAuth in Google Cloud console. Make sure to add Gmail API with the modify scope.
Add Google OAuth credentials in n8n. Make sure to add the n8n redirect URI to the Google Cloud Console consent screen settings.
OpenAI Configuration: add OpenAI API Key in the credentials
Tweaking the prompt: edit the system prompt in the "Generate email reply" node to suit your needs
Detailed Walkthrough
Check out this blog post where I go into more details on how I built this workflow.
Reach out to me here if you need help building automations for your business.
This n8n workflow demonstrates how you can summarise and automate post-meeting actions from video transcripts fed into an AI Agent.
Save time between meetings by allowing AI handle the chores of organising follow-up meetings and invites.
How it works
This workflow scans for the calendar for client or team meetings which were held online. * Attempts will be made to fetch any recorded transcripts which are then sent to the AI agent.
The AI agent summarises and identifies if any follow-on meetings are required.
If found, the Agent will use its Calendar Tool to to create the event for the time, date and place for the next meeting as well as add known attendees.
Requirements
Google Calendar and the ability to fetch Meeting Transcripts (There is a special OAuth permission for this action!)
OpenAI account for access to the LLM.
Customising the workflow
This example only books follow-on meetings but could be extended to generate reports or send emails.