What Is FutureMargin?
FutureMargin is a cloud based demand planning software for modern e-commerce retailers. FutureMargin predicts expected product sales for e-commerce stores to optimize inventory stock levels. Retailers use FutureMargin to automate and simplify stock replenishment process, avoid stock-outs and detect over-stocks.
FutureMargin offers demand forecasting and inventory optimization tools for enterprise retail chains and large e-commerce stores.
Automatic sale forecasting helps retailers create optimal purchase orders, increase fill-rate, analyze overstock and speed up replenishment. FutureMargin further includes tools to optimally redistribute stock among groups of warehouses and stores.
Sale forecasting is performed using machine learning algorithms which are tuned for specific needs of each retailer.
FutureMargin Features
Demand planning
All necessary multi-location and multi-channel data needed for replenishment decisions can easily by viewed: stock quantities on hold, forecast sales, existing purchase orders, unfulfilled orders and recommended replenishment tips.
Create purchase orders easily
Generate purchase orders quicker
With FutureMargin purchase order editing capabilities, you can quickly generate purchase orders for your locations based on actionable stock quantity recommended tips.
Analyze purchase order line item demand
For each line item, you can visually inspect the historical order data and sale forecasts, add recommended quantity to a purchase order and optionally adjust the line item quantity based on other external events.
Generate optimal purchase orders
For each purchase order, you can analyze the total line item quantity and cost with respect to individual item coverages. For example, you can replenish to cover expected demand for shorter or larger time interval based on your current available budget.
Parameters of FutureMargin forecasting engine
Daily forecasts
Demand forecasts on the variant level are computed automatically daily or on demand, when your latest store data is synchronised.
Forecast periods
Multiple future time windows are computed and you can select appropriate time interval forecast based on your selected brand, collection or product.
Machine learning
Sale forecasts are computed automatically using store data using machine learning. Forecast models minimizing prediction errors are automatically learned.
Seasonality estimation
Seasonality is automatically estimated from historical data and product variant hierarchies using unsupervised machine learning.
Discount detection
Previous short-term sale spikes due to pricing discounts are automatically handled. This feature requires synchronising daily channel specific variant pricing information.
Multi-channel and currency support
FutureMargin supports integrating data from multiple channels (countries or platforms) to enable precise channel specific price discount handling.
Pricing
