What is weighted expected sales volume in SAP CRM-ANA - CRM Analytics?

SAP Term: weighted expected sales volume

• Component: CRM-ANA

• Component Name: CRM Analytics

• Description: The anticipated target to date sales in the target to date simulation influenced by a chosen factor. This involves a method for calculating the predicted sales volume for a specific time frame using weighted calculations. A factor, for example, a sum of money, is multiplied by a value, such as a percentage rate, to increase or decrease the results of the forecasted sales volume. The weighted expected sales volume is a worst-case scenario revenue figure.

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• Key Concepts: 
  Weighted expected sales volume is a metric used in CRM Analytics to measure the expected sales volume of a product or service. It is calculated by taking into account the current sales volume, the expected sales volume, and the weighting factor. The weighting factor is used to adjust the expected sales volume based on the current market conditions. 
  
  How to use it: 
  Weighted expected sales volume can be used to help businesses make decisions about their product or service offerings. It can be used to determine the optimal pricing strategy, identify potential new markets, and forecast future sales. Additionally, it can be used to compare different products or services and assess their potential profitability. 
  
  Tips & Tricks: 
  When calculating weighted expected sales volume, it is important to consider all relevant factors such as market conditions, customer preferences, and competitor offerings. Additionally, it is important to regularly update the weighting factor in order to ensure that the metric remains accurate and up-to-date. 
  
  Related Information: 
  Weighted expected sales volume is closely related to other metrics such as weighted average price and weighted average cost of goods sold. Additionally, it can be used in conjunction with other analytics tools such as predictive analytics and customer segmentation in order to gain a more comprehensive understanding of customer behavior and market trends.