Best Accuracy in Price Optimization by Using Demand Forecasting
The pricing systems normally establish the market sensitivity based on the data of a SKU/product from the recent past. The price elasticity that has been established through this data represents the market sensitivity of the product during the recent past. The total size of market (demand) that a company is able to capture in a specific time period also plays a very significant role in deciding the optimal prices. Sales teams must target to achieve these prices during the negotiations in sales transactions.
Thus the pricing systems available in the market assume that the market volume for the current or future period is the same as the past period, and compute the prices for the current or future period. This will result in inaccurate price computations. The optimal prices that are established through this approach do not account the increase or decrease in demand for the current or future period and result in inaccurate prices that beat the goal of arriving at price optimization.
If the demand for the future period increases, it will open a significant opportunity to produce higher revenues and margins by increasing prices. Thus the increase in demand must be captured through certain forecasting process before computing the optimal prices for the market segments. On the other hand, a decrease in demand must be accounted to successfully retain customers by proposing suitable prices during the period of low demand.
GDRi PRM system now augments its pricing system with an extensive demand forecasting system to predict the size of market demand for a future period. The pricing engine utilizes this information to more accurately compute the optimal prices for each customer segment in the market. The demand forecasting module is available as an integral part of the pricing system to better serve the GDRi customers.
Thus the pricing systems available in the market assume that the market volume for the current or future period is the same as the past period, and compute the prices for the current or future period. This will result in inaccurate price computations. The optimal prices that are established through this approach do not account the increase or decrease in demand for the current or future period and result in inaccurate prices that beat the goal of arriving at price optimization.
If the demand for the future period increases, it will open a significant opportunity to produce higher revenues and margins by increasing prices. Thus the increase in demand must be captured through certain forecasting process before computing the optimal prices for the market segments. On the other hand, a decrease in demand must be accounted to successfully retain customers by proposing suitable prices during the period of low demand.
GDRi PRM system now augments its pricing system with an extensive demand forecasting system to predict the size of market demand for a future period. The pricing engine utilizes this information to more accurately compute the optimal prices for each customer segment in the market. The demand forecasting module is available as an integral part of the pricing system to better serve the GDRi customers.
