Getting Started with SalesForecaster
This guide walks you through your first forecast — from uploading data to interpreting predictions. You'll be generating AI-powered forecasts in under five minutes.
Prerequisites
Before you begin, make sure you have:
- A SalesForecaster account (sign up here)
- A CSV or Excel file with historical sales data (minimum 12 months recommended)
Step 1: Upload Your Data
Navigate to Data > Upload in your dashboard. Drag and drop your file or click to browse.
SalesForecaster supports:
- CSV files with headers
- Excel (.xlsx) workbooks
- JSON arrays of objects
Your data should include at minimum a date column and a sales/revenue column. Additional columns like product category, region, or customer segment will be automatically detected and used as features.
date,revenue,region,product_line,deals_closed
2024-01-01,125000,North America,Enterprise,12
2024-01-08,118000,North America,Enterprise,10
2024-01-15,142000,EMEA,Mid-Market,15
Step 2: Configure Your Dataset
After upload, SalesForecaster automatically detects column types and suggests configurations:
- Target variable — The column you want to forecast (e.g.,
revenue) - Date column — Your time dimension
- Frequency — Daily, weekly, monthly, or quarterly
- Categorical features — Dimensions for segmented forecasts
Review the suggestions and adjust if needed, then click Save Dataset.
Step 3: Launch AI Research
This is where the magic happens. Navigate to Research > New Session and select your dataset.
The AI research agents will:
- Analyze your data patterns and seasonality
- Search for relevant external factors (market trends, economic indicators, industry events)
- Build a knowledge graph connecting discovered factors to your revenue drivers
- Generate a research report with recommendations
This typically takes 2-5 minutes depending on your industry complexity.
Step 4: Train Your Model
Go to Models > Train and select your dataset along with the research session results.
Choose from:
| Model Type | Best For | Training Time |
|---|---|---|
| Quick Forecast | Fast initial predictions | ~30 seconds |
| Standard Ensemble | Balanced accuracy & speed | ~2 minutes |
| Deep Ensemble | Maximum accuracy | ~5 minutes |
We recommend starting with Standard Ensemble for your first forecast.
Step 5: Generate Forecasts
Once training completes, navigate to Forecasts and click New Forecast.
Select your trained model, set the forecast horizon (how far ahead to predict), and click Generate.
Your forecast includes:
- Point predictions with confidence intervals
- Feature importance showing what drives each prediction
- Anomaly alerts for unusual patterns
- Scenario comparisons against baseline
Next Steps
- Explore Scenario Simulation to model what-if scenarios
- Set up Scheduled Forecasts for automatic weekly updates
- Connect your CRM via API Integration for real-time data ingestion
Have questions? Visit our Help Center or contact us.