Automated CFO Revenue Forecasting Workflow

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This n8n workflow streamlines the process of financial revenue forecasting by automating data retrieval from Stripe, summarizing sales, generating predictive insights with OpenAI’s GPT-4, and storing/reporting results. It runs daily to ensure real-time updates, making it ideal for CFOs and financial teams seeking accurate forecasts and trends.

The workflow begins with a Schedule Trigger node that initiates the process daily at 6 AM. It then fetches all successful Stripe transactions, summarizes daily revenue, and formats this data into a natural language prompt for OpenAI’s GPT-4. The AI analyzes recent sales trends, forecasts revenues for the upcoming three months, and outputs insights.

The forecast data is parsed and stored in a Supabase database for historical tracking. Simultaneously, the results are logged into Google Sheets for easy visualization. Optional integration with Pinecone allows long-term data embedding and retrieval, enabling enhanced AI memory. This complete automation provides CFOs with timely, data-driven financial forecasts, crucial for strategic planning.

Practical uses include financial planning, sales trend analysis, and quarterly revenue predictions, ensuring CFOs and financial teams stay ahead with minimal manual effort.

Node Count

11 – 20 Nodes

Nodes Used

@n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.embeddingsOpenAi, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.outputParserStructured, @n8n/n8n-nodes-langchain.vectorStorePinecone, code, googleSheets, scheduleTrigger, set, stickyNote, stripe, supabase

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