AI-Powered SEO Cannibalization Monitor: Databox, Google Search Console & Slack

This workflow runs weekly and checks multiple client websites for potential SEO cannibalization issues using Google Search Console data from Databox.

It pulls page-level impressions and average position data, prepares the data, analyzes it with AI, and sends SEO risk reports to Slack.

Who’s it for

• SEO agencies managing multiple clients
• Client success or account managers who need weekly SEO visibility
• SEO leads who want a high-level view of client risks

How it works

• A weekly trigger starts the workflow.
• The first Code node contains the client list and Databox metric setup.
• The loop processes each client one by one.
• Databox pulls Google Search Console impressions and average position data.
• The data is merged, cleaned, and filtered to remove low-traffic pages.
• The first AI agent checks each client for possible SEO cannibalization.
• A Slack alert is sent with the client-level findings.
• After all clients are processed, a second AI agent creates a combined leadership summary.
• The final cross-client report is sent to Slack.

How to set up

1. Connect the Databox MCP Client Tool with your endpoint and authentication headers.
2. Add your clients in the first Code node, including:
   • Client name
   • Google Search Console data source ID
   • Impressions metric key
   • Average position metric key
3. Connect your OpenAI credentials.
4. Connect the Slack nodes to the right channels.
5. Adjust the weekly schedule if needed.

You can ask Databox Genie to provide the correct data source IDs and metric keys for each client, then format them in the same structure as the example Code node.

Requirements

• n8n 1.0+
• Databox MCP access
• Google Search Console data available in Databox
• OpenAI credentials
• Slack workspace

Output

The workflow sends two reports:

• Client-level report: highlights possible cannibalization issues for each client.
• Leadership report: summarizes SEO risks across all processed clients.