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Forecast Analysis Chatbot

Business Need​

Enable business users to interactively analyze forecasting model predictions through natural language queries, generating visualizations and comparative analyses to sanity-check predictions and diagnose forecast behavior.

Solution Overview​

This solution leverages a Custom Chatbot with feature group integration to deliver conversational forecast analytics:

Step 1: Feature Group Preparation

  • Data Sources: Combines input feature group (historical data) and output feature group (forecast predictions) from a forecasting batch prediction
  • Data Structure: Merged feature group contains both actual historical values and predicted future values for all forecast entities
  • Time Alignment: Historical data and forecasts aligned by timestamp to enable side-by-side comparison
  • Refresh Schedule: Feature group updates daily as new forecasts are generated

Step 2: Chatbot Configuration

The Custom Chatbot is configured with forecasting domain knowledge:

  • Connected to the merged historical + forecast feature group
  • Configured with time series analysis capabilities
  • Understands forecasting terminology (YoY growth, seasonality, trend, forecast horizon)
  • Equipped with Python visualization libraries for automatic chart generation
💡Pro Tip

Include metadata in the feature group such as forecast confidence intervals, model version, and training date. Users can then ask questions like "Show me predictions where the model had low confidence" to focus review efforts.

Step 3: Interactive Analysis

Users interact with the chatbot through natural language queries:

  • Trend Analysis: "Show me next quarter's forecast compared to last year same period"
  • Visual Comparison: "Plot actual vs. forecast for top 10 products"
  • Statistical Queries: "What's the average YoY growth rate in the forecast?"
  • Anomaly Detection: "Which forecasts deviate significantly from historical patterns?"

The chatbot generates appropriate visualizations automatically:

  • Time series plots comparing actual vs. forecast
  • YoY growth comparison charts
  • Histograms showing forecast distribution
  • Heatmaps for multi-dimensional forecasts

How It's Used in Practice​

This solution provides self-service forecast analysis to business stakeholders:

Daily Forecast Review Workflow:

  • Demand planners access the chatbot through ChatLLM UI
  • Ask exploratory questions about the latest forecast batch
  • Generate visualizations to spot check predictions
  • Identify anomalies or unusual patterns requiring investigation
  • Export charts and analysis for stakeholder presentations

Users spend 60% less time in BI tools building manual reports, with the chatbot generating analysis on-demand within seconds.

✨Key Outcomes

Key achievements:

📊 Self-service forecast analysis​

Business users explore predictions without requiring data analyst support

⚡ Seconds to generate visualizations​

What took 15-30 minutes in BI tools now takes 10-20 seconds

🔍 Improved forecast validation​

Interactive analysis catches questionable predictions before they impact decisions

📈 Increased forecast model trust​

Transparency and easy validation builds confidence in using model predictions

Additional Information​