Predictive Analytics and Forecasting

Leverage AI to predict future trends and outcomes.

Predictive Analytics Overview

What Is Predictive Analytics?

AI-powered analysis that:
- Identifies patterns in historical data
- Forecasts future values
- Detects trends and seasonality
- Predicts outcomes

Availability

Predictive features available on Enterprise plan.

Accessing Predictive Analytics

Navigation

1. Go to Analytics in sidebar
2. Select Predictive Analytics
3. Or use conversational AI: "Forecast next month's revenue"

Forecast Types

Time Series Forecasting

Predict future values based on historical trends:
- Revenue forecasting
- User growth projection
- Demand prediction
- Inventory planning

Trend Analysis

Identify and project patterns:
- Growth rates
- Seasonal patterns
- Cyclical trends
- Anomaly detection

Creating Forecasts

Step 1: Select Data

1. Choose data source
2. Select metric to forecast
3. Set historical date range

Step 2: Configure Forecast

• Forecast Period: How far to predict
• Confidence Interval: 80%, 95%, 99%
• Seasonality: Auto-detect or manual

Step 3: Generate Forecast

1. Click Generate Forecast
2. AI analyzes patterns
3. Results displayed with confidence bands

Step 4: Review Results

Forecast shows:
- Predicted values
- Confidence intervals
- Historical comparison
- Key assumptions

Understanding Results

Forecast Visualization

• Line: Predicted values
• Shaded Area: Confidence interval
• Historical: Past actual values
• Trend Line: Overall direction

Confidence Intervals

• Narrow Band: High confidence
• Wide Band: More uncertainty
• Higher % = Wider: 99% wider than 80%

Accuracy Metrics

• MAE: Mean Absolute Error
• MAPE: Mean Absolute Percentage Error
• R-squared: Model fit quality

Conversational Forecasting

Ask Predictive Questions

```
"What will revenue be next quarter?"
"Forecast user growth for the next 6 months"
"Predict customer churn for December"
"When will we reach 10,000 users?"
```

Getting Better Results

• Provide sufficient historical data
• Specify time period clearly
• Mention seasonality if relevant
• Ask follow-up questions

Using Forecasts

Dashboard Widgets

Add forecast widgets:
- Forecast trend chart
- Projected KPI card
- Goal with forecast

Report Integration

Include forecasts in reports:
- Executive summaries
- Planning documents
- Budget projections

Decision Support

Use forecasts for:
- Resource planning
- Budget allocation
- Hiring decisions
- Inventory management

Best Practices

Data Requirements

• Minimum 12 months historical data
• Consistent data quality
• No major gaps
• Regular time intervals

Interpretation

• Consider confidence intervals
• Understand limitations
• Combine with domain knowledge
• Update regularly

Limitations

• Forecasts are probabilistic, not certain
• Cannot predict black swan events
• Quality depends on historical data
• Recent changes may not be reflected