Details

Parameters of our sale forecasting approach

Improve stock coverage

Improve SKU availability

Set Minimum Stock Level Quantities and easily see, which variants have stock quantities which will likely drop below a threshold soon.

Reduce stock-outs

Avoid over-stocks

Analyze expected stock level in future time window for variants and products and quickly identify over-stocked items. Launch promotions to get rid of unneeded stock.

Browse and filter variant groups

See where action is necessary

Sort variants and products by forecast sales, by expected stock levels in future time periods, by final replenishment tip or by any quantity to easily identify items, which need top attention.

Daily forecasts

Daily forecasts

Demand forecasts on the variant level are computed automatically daily or on demand, when your latest store data is synchronised.

Multiple forecast periods

Forecast periods

Multiple future time windows are computed and you can select appropriate time interval forecast based on your selected brand, collection or product.

Minimum and maximum cover replenishment

Min/max replenishment

Minimum/maximum coverage mode guarantees minimal required stock availability and also minimizes number of necessary repeated purchase orders.

easonality estimation

Seasonality estimation

Seasonality is automatically estimated from historical data and product variant hierarchies using unsupervised machine learning.

Discount handling

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 multi-currency support

Multi-channel and currency support

FutureMargin supports integrating data from multiple channels (countries or platforms) for a precise channel specific price discount handling.

Data cleaning

Data cleaning

Historical data are automatically preprocessed and cleaned by removing outliers.

New product forecasting

New product forecasts

Seasonality for new products is estimated statistically using available product history and learned seasonality patterns among other products.

Actionable replenishment tip

Actionable replenishment tips

Actionable replenishment tip is always available for each variant. Replenishment recommendation combines current stock, forecast, unfulfilled quantity, open purchase orders and minimum stock quantities.

Technology

Leverage cloud computing and your data to improve your supply chain efficiency

AI

Our system uses unsupervised learning to continuously learn patterns in your data, detects seasonality trends and provides you daily forecasts to shorten time required for manual computations. Automatic forecasts help you see which products need attention to avoid stock-outs and to reduce unneeded inventory.

Scalability

Our team combines extensive experience in high performance and cloud computing. FutureMargin can handle hundreds of thousands of SKUs and automatically provides up-to-date forecasts for all of your products. Our hardware infrastructure handles all extensive automatic modeling and forecasting.

Integration

Built for retailers with large number of SKUs, we provide an easy to use JSON API which you can quickly integrate to automatically perform data exchange and to download predictions for your inventory management software. FutureMargin also provides alternative CSV, FTP or custom integration options for any scenario.

Please get in touch to get a free demo.