Upload your time series data to start forecasting demand. We support CSV and XLSX files.
Data Format
Your data should be in a time series format with at least two columns: one for the date and another for the sales quantity. The date column should be in a standard date format (e.g., YYYY-MM-DD), and the sales quantity column should contain numerical values representing the sales for each corresponding date.
Required Columns:
- date - Date of the record
- actual_demand - Sales quantity
- item_name - Product name
Example Format:
2023-01-01,Winter Coat,150
2023-02-01,Winter Coat,120
2023-03-01,Winter Coat,80
Predictive Model
Our app uses a sophisticated time series forecasting model that is specifically designed to handle high seasonality in data. The model analyzes historical sales patterns, identifies seasonal trends, and generates accurate demand forecasts for future periods. It automatically adjusts for seasonal fluctuations, ensuring reliable predictions even for products with significant seasonal variations.