At the core of AMP2's demand forecasting/price optimization capability resides a price elasticity based dynamic demand model designed to compute sales forecasts at a SKU level from price and promotion information. There are four major components of AMP2's demand forecasting/price optimization facility:

Trend and Seasonality
For every product, the mathematical model takes into account information on sales trends as well as seasonality coefficients to assess the underlying foundations on which increased sales are to be built.

Parameterisation
During the model building phase (parameterisation), other related statistics are gathered to provide valuable information on the quality of the models' parameters. These statistics include an error margin for the demand equation, the correlation coefficient and the confidence interval.

Simulation
Preparing accurate sales simulations for each product involves taking into account wide-ranging influences, such as own and competitor price changes, price cross effects between own products or between own and competitor products and promotional events.

Optimization
The optimization module has been designed to accommodate a variety of objective functions and maximize performance over several periods subject to price constraints, performance targets and operation constraints. This versatility allows various optimization scenarios to be tackled, such as pricing reviews, promotions and competition attack.