Abandoned Cart Email Automation
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Automates the process of sending personalized emails to customers who have abandoned their shopping carts.
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About This Workflow
This workflow triggers when a webhook receives abandoned cart data. It then splits the text, generates embeddings using Cohere, and stores them in Supabase for efficient retrieval. A RAG agent utilizes OpenAI's chat model and a vector tool to craft personalized email content based on the retrieved context and conversation history. Finally, the generated email status is logged to Google Sheets, and any errors are reported to Slack.
Key Features
- Webhook Trigger: Initiates the workflow with incoming abandoned cart data.
- Text Splitting: Prepares text data for embedding.
- Cohere Embeddings: Creates vector representations of text for semantic search.
- Supabase Vector Store: Efficiently stores and retrieves vectorized data.
- OpenAI Chat Model: Powers the conversational AI for generating email content.
- RAG Agent: Implements Retrieval Augmented Generation for context-aware responses.
- Google Sheets Logging: Records workflow execution status.
- Slack Alerts: Notifies of any errors during execution.
How To Use
- Webhook Trigger (
Webhook Trigger): Configure this node to receive POST requests containing abandoned cart data. Ensure the path is set toabandoned-cart-email. - Text Splitter (
Text Splitter): This node automatically splits the incoming text data into manageable chunks. - Embeddings (
Embeddings): Connect the output of the Text Splitter to this node. Configure it to useembed-english-v3.0with your Cohere API credentials (COHERE_API). - Supabase Insert (
Supabase Insert): Connect the embeddings to this node. Set theindexNametoabandoned_cart_emailand use your Supabase credentials (SUPABASE_API). This stores the embeddings and associated data. - Supabase Query (
Supabase Query): This node is used internally by the RAG Agent to retrieve relevant context from Supabase. It also uses your Supabase credentials and theabandoned_cart_emailindex. - Vector Tool (
Vector Tool): This node prepares the retrieved data from Supabase to be used as context for the RAG Agent. - Window Memory (
Window Memory): This node maintains the conversation history for the RAG Agent. - Chat Model (
Chat Model): Connect this node to your OpenAI API credentials (OPENAI_API). It will be used by the RAG Agent for generating responses. - RAG Agent (
RAG Agent): This is the core AI node. Configure itstextparameter to `Process the following data for task 'Abandoned Cart Email':
{{ $json }}and set thesystemMessagetoYou are an assistant for Abandoned Cart Email. 10. **Append Sheet (Append Sheet):** Connect the RAG Agentto this node. Configure it to append the generated email status to your Google Sheet. EnsureSHEET_IDandLogsheet name are correctly set. TheStatuscolumn should map to={{$json["RAG Agent"].text}}. 11. **Slack Alert (Slack Alert):** Connect the onErroroutput of theRAG Agent to this node. Configure it with your Slack credentials (SLACK_API) and a channel (e.g., #alerts`) to receive error notifications.
Apps Used
Workflow JSON
{
"id": "58e9fbcd-5c78-4b91-8634-d61360e14a3d",
"name": "Abandoned Cart Email Automation",
"nodes": 0,
"category": "Marketing",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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ID: 58e9fbcd-5c78...
About the Author
Crypto_Watcher
Web3 Developer
Automated trading bots and blockchain monitoring workflows.
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