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Component: CA-DDF-RT
Component Name: Demand Data Foundation for Retail
Description: A product whose increase or decrease in sales causes the sales of another product drag product to change as well - either in the same direction or the opposite direction. The change in sales of the driver product can have different causes. For example, if the driver product is put on promotion or newly added to an assortment, its sales increase. In a product cannibalization scenario, this increase causes the sales of another, non-promoted product to decrease negative drag product. Example: A specific brand of mineral water is put on promotion and its sales increase, while the sales of the competitor's brand of mineral water decrease. In a product affinity scenario, this increase causes the sales of another product positive drag product to increase as well. Example: If hamburger patties are put on promotion, the sales of hamburger rolls increase as well.
Key Concepts: A driver product is a component of the SAP Demand Data Foundation for Retail (CA-DDF-RT). It is a software solution that enables retailers to collect, store, and analyze customer data in order to better understand customer behavior and preferences. This data can then be used to create targeted marketing campaigns and optimize product offerings. How to use it: The driver product can be used to collect customer data from various sources, such as point-of-sale systems, loyalty programs, and online surveys. This data can then be analyzed to identify trends and patterns in customer behavior. The insights gained from this analysis can be used to create targeted marketing campaigns and optimize product offerings. Tips & Tricks: When using the driver product, it is important to ensure that the data collected is accurate and up-to-date. Additionally, it is important to ensure that the data is stored securely and that appropriate privacy measures are taken. Related Information: The driver product is part of the SAP Demand Data Foundation for Retail (CA-DDF-RT). This solution also includes other components such as the demand forecasting engine, the demand planning engine, and the demand optimization engine. These components work together to provide retailers with a comprehensive view of customer behavior and preferences.