Automated Competitor Price Monitoring & Analysis
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Automate the collection and analysis of competitor pricing data with this n8n workflow. Gain critical insights into market trends and optimize your pricing strategy effortlessly.
About This Workflow
The Competitor Price Scraper workflow is designed to provide businesses with a powerful tool for staying ahead in competitive markets. It leverages n8n's automation capabilities to continuously monitor and analyze competitor pricing. The workflow begins with a webhook trigger, allowing you to initiate price scraping on demand. Data is then processed, vectorized using OpenAI embeddings, and stored in Supabase for efficient retrieval. An Anthropic chat model powers an agent that interprets this data, providing actionable insights. Finally, results are logged to a Google Sheet and alerts are sent via Slack for immediate awareness of significant price changes or errors. This workflow streamlines the complex task of competitive intelligence, enabling data-driven decision-making.
Key Features
- Automated Data Collection: Continuously scrape competitor pricing data without manual intervention.
- Intelligent Data Processing: Utilizes advanced text splitting and embedding techniques for effective data analysis.
- Vectorized Data Storage: Leverages Supabase for efficient storage and retrieval of price data and insights.
- AI-Powered Analysis: Employs a RAG agent for contextual understanding and interpretation of competitor pricing.
- Integrated Alerting & Logging: Notifies stakeholders via Slack and logs results to Google Sheets for comprehensive tracking.
How To Use
- Trigger Setup: Configure the 'Webhook Trigger' to receive incoming requests to start the scraping process.
- Data Preparation: The 'Text Splitter' node breaks down incoming data into manageable chunks.
- Vectorization: The 'Embeddings' node (using OpenAI) converts text data into numerical vectors.
- Data Storage: Use 'Supabase Insert' to store these vectors in a Supabase vector store indexed as 'competitor_price_scraper'.
- Data Retrieval: The 'Supabase Query' node retrieves relevant price data based on similarity searches.
- Contextualization: The 'Vector Tool' node makes retrieved data available as a tool for the agent.
- Memory Management: 'Window Memory' helps the agent maintain conversation context.
- AI Agent Configuration: Configure the 'Chat Model' (Anthropic) and 'RAG Agent' to process scraped data and perform analysis. Ensure the 'RAG Agent' prompt is set up to handle competitor pricing tasks.
- Logging: Connect the 'Append Sheet' node to your Google Sheet to log the status and results of the scraping process.
- Error Handling: Configure the 'Slack Alert' node to receive notifications in case of workflow failures.
Apps Used
Workflow JSON
{
"id": "84fefd89-51e2-40f8-a9e7-8ed4819a70f7",
"name": "Automated Competitor Price Monitoring & Analysis",
"nodes": 10,
"category": "Operations",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: 84fefd89-51e2...
About the Author
SaaS_Connector
Integration Guru
Connecting CRM, Notion, and Slack to automate your life.
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