公开(公告)号：US08386285B2

公开(公告)日：2013-02-26

申请号：US13115748

申请日：2011-05-25

申请人： Yiwei Chen ,  Ramesh Natarajan

发明人： Yiwei Chen ,  Ramesh Natarajan

IPC分类号： G06Q40/00

CPC分类号： G06Q30/02 ,  G06Q10/087

摘要： System, method and computer program product for demand modeling and prediction in retail categories. The method uses time-series data comprising of unit prices and unit sales for a designated choice set of related products, with the time-series data obtained over a given sequence of sales reporting periods, and over a collection of stores in a market geography. Other relevant data sets from participating retail entities that include additional product attribute data such as market and consumer factors that affect retail demand are further used. A demand model for improved accuracy is achieved by individual sub-modeling method steps of: estimating a model for price movements and price dynamics from the time series data of unit-prices in the aggregated sales data; estimating a model for market share of each product in the retail category using the aggregated sales data and integrated additional product attribute data; and, estimating generating a model for an overall market demand in the retail category from the aggregated sales data.

摘要翻译： 零售类需求建模与预测的系统，方法和计算机程序产品。 该方法使用包括相关产品的指定选择集合的单位价格和单位销售的时间序列数据，以及在给定的销售报告期间获得的时间序列数据，以及在市场地理学中的商店集合。 进一步使用参与零售实体的其他相关数据集，其中包括影响零售需求的其他产品属性数据，如市场和消费者因素。 通过个别子建模方法步骤实现提高准确度的需求模型：从聚合销售数据中单位价格的时间序列数据估计价格变动和价格动态模型; 使用聚合销售数据和集成的附加产品属性数据估计零售类别中每个产品的市场份额的模型; 并且从聚合的销售数据估计为零售类别的整体市场需求生成模型。

公开(公告)号：US20120303411A1

公开(公告)日：2012-11-29

申请号：US13115748

申请日：2011-05-25

申请人： Yiwei Chen ,  Ramesh Natarajan

发明人： Yiwei Chen ,  Ramesh Natarajan

IPC分类号： G06Q10/00

CPC分类号： G06Q30/02 ,  G06Q10/087

摘要： System, method and computer program product for demand modeling and prediction in retail categories. The method uses time-series data comprising of unit prices and unit sales for a designated choice set of related products, with the time-series data obtained over a given sequence of sales reporting periods, and over a collection of stores in a market geography. Other relevant data sets from participating retail entities that include additional product attribute data such as market and consumer factors that affect retail demand are further used. A demand model for improved accuracy is achieved by individual sub-modeling method steps of: estimating a model for price movements and price dynamics from the time series data of unit-prices in the aggregated sales data; estimating a model for market share of each product in the retail category using the aggregated sales data and integrated additional product attribute data; and, estimating generating a model for an overall market demand in the retail category from the aggregated sales data.

摘要翻译： 零售类需求建模与预测的系统，方法和计算机程序产品。 该方法使用包括相关产品的指定选择集合的单位价格和单位销售的时间序列数据，以及在给定的销售报告期间获得的时间序列数据，以及在市场地理学中的商店集合。 进一步使用参与零售实体的其他相关数据集，其中包括影响零售需求的其他产品属性数据，如市场和消费者因素。 通过个别子建模方法步骤实现提高准确度的需求模型：从聚合销售数据中单位价格的时间序列数据估计价格变动和价格动态模型; 使用聚合销售数据和集成的附加产品属性数据估计零售类别中每个产品的市场份额的模型; 并且从聚合的销售数据估计为零售类别的整体市场需求生成模型。