Autonomous Traffic Spike Reporting: Databox, AI & Slack
Autonomous Traffic Spike Reporting: Databox, AI & Slack This workflow gives PPC agencies and performance teams a daily traffic and performance check across multiple clients using Databox data. It pulls yesterday’s and day-before-yesterday’s data for key metrics, compares changes, analyzes the results with AI, and sends both client-level and cross-client reports to Slack. Who’s it for PPC agencies managing multiple client accounts Performance marketing teams tracking daily traffic changes Account managers who need fast visibility into client performance Operations leads who want a daily cross-client summary How it works A daily trigger starts the workflow. The first Code node stores the client list and Databox metric setup. The loop processes each client one by one. Databox pulls yesterday and day-before-yesterday data for: Sessions New users Ad cost Clicks The workflow merges and formats the metric data. AI checks for traffic spikes, drops, and unusual performance changes. A client-level Slack report is sent for each client. After all clients are processed, a second AI agent creates a leadership summary across all clients. The final cross-client report is sent to Slack. How to set up Connect the Databox MCP Client Tool with your endpoint and authentication headers. Add your clients in the first Code node, including: Client name Databox data source IDs Metric keys for sessions, new users, ad cost, and clicks Connect your OpenAI credentials. Connect the Slack nodes to the right channels. Adjust the daily 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 Metrics available in Databox for each client OpenAI credentials Slack workspace Output The workflow sends two reports: Client-level report:** highlights daily traffic spikes, drops, and metric changes for each client. Leadership report:** summarizes performance changes and priority risks across all processed clients. An n8n automation workflow template by n8n Lab.
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