COMPETING SIMULATOR IN MULTI-CHANNEL RETAILING ENVIRONMENT AMONG MULTIPLE RETAILERS
    1.
    发明申请
    COMPETING SIMULATOR IN MULTI-CHANNEL RETAILING ENVIRONMENT AMONG MULTIPLE RETAILERS 有权
    在多个零售商的多渠道零售环境中竞争模拟器

    公开(公告)号:US20120046991A1

    公开(公告)日:2012-02-23

    申请号:US12859028

    申请日:2010-08-18

    IPC分类号: G06Q10/00 G06N3/02

    CPC分类号: G06Q30/0201 G06Q30/02

    摘要: A system, method and computer program product for providing the ability for retailers to devise a current channel strategy (e.g., adaptive price setting) that considers competitors in a dynamic competing environment, and that enables computing a competitive advantage of a channel. To estimate a price for selling a product j in a commerce channel comprises: a) receiving, at a processor device, real market data including sales and price history data of a product j sold by one or more retailers over one or alternate sales channels t; generating, by the processor device, a competitive advantage parameter value based on the sales and price history data; and, computing, utilizing the competitive advantage parameter value, an optimum price for a particular product to be marketed in one of the one or alternate sales channel.

    摘要翻译: 一种系统,方法和计算机程序产品,用于为零售商提供在动态竞争环境中考虑竞争对手的当前渠道策略(例如,自适应价格设置)的能力,并且能够计算渠道的竞争优势。 估计在商业通道中销售产品j的价格包括:a)在处理器设备处接收包括由一个或多个零售商通过一个或多个销售渠道销售的产品j的销售和价格历史数据的真实市场数据 ; 由所述处理器设备基于所述销售和价格历史数据生成竞争优势参数值; 以及利用竞争优势参数值计算在一个或另一个销售渠道之一上销售的特定产品的最优价格。

    Competing simulator in multi-channel retailing environment among multiple retailers
    2.
    发明授权
    Competing simulator in multi-channel retailing environment among multiple retailers 有权
    多渠道零售环境中的竞争模拟器

    公开(公告)号:US08386298B2

    公开(公告)日:2013-02-26

    申请号:US12859028

    申请日:2010-08-18

    IPC分类号: G06Q10/00 G06Q30/00

    CPC分类号: G06Q30/0201 G06Q30/02

    摘要: A system, method and computer program product for providing the ability for retailers to devise a current channel strategy (e.g., adaptive price setting) that considers competitors in a dynamic competing environment, and that enables computing a competitive advantage of a channel. To estimate a price for selling a product j in a commerce channel comprises: a) receiving, at a processor device, real market data including sales and price history data of a product j sold by one or more retailers over one or alternate sales channels t; generating, by the processor device, a competitive advantage parameter value based on the sales and price history data; and, computing, utilizing the competitive advantage parameter value, an optimum price for a particular product to be marketed in one of the one or alternate sales channel.

    摘要翻译: 一种系统,方法和计算机程序产品,用于为零售商提供在动态竞争环境中考虑竞争对手的当前渠道策略(例如,自适应价格设置)的能力,并且能够计算渠道的竞争优势。 估计在商业通道中销售产品j的价格包括:a)在处理器设备处接收包括由一个或多个零售商通过一个或多个销售渠道销售的产品j的销售和价格历史数据的真实市场数据 ; 由所述处理器设备基于所述销售和价格历史数据生成竞争优势参数值; 以及利用竞争优势参数值计算在一个或另一个销售渠道之一上销售的特定产品的最优价格。

    Maximizing retailer profit and customer satisfaction using multi-channel optimization
    3.
    发明授权
    Maximizing retailer profit and customer satisfaction using multi-channel optimization 失效
    通过多渠道优化最大化零售商利润和客户满意度

    公开(公告)号:US08660882B2

    公开(公告)日:2014-02-25

    申请号:US12837758

    申请日:2010-07-16

    IPC分类号: G06Q30/00 G06Q10/00

    摘要: A data integration module is operable to integrate a plurality of data sources, a customer preference module builds a model representing preference to different channels in merchandise category for each customer segment. A customer satisfaction module creates a model representing customer satisfaction metrics. A joint multi-channel optimization module is operable to use an optimization model that utilizes the customer preference model and the customer satisfaction model and maximize retailer's profit and customer satisfaction.

    摘要翻译: 数据集成模块可操作以集成多个数据源,客户偏好模块为每个客户分段构建表示对商品类别中的不同渠道的偏好的模型。 客户满意度模块创建一个表示客户满意度指标的模型。 联合多渠道优化模块可操作地使用利用客户偏好模型和客户满意度模型并最大限度地提高零售商利润和客户满意度的优化模型。

    JOINT MULTI-CHANNEL CONFIGURATION OPTIMIZATION FOR RETAIL INDUSTRY
    7.
    发明申请
    JOINT MULTI-CHANNEL CONFIGURATION OPTIMIZATION FOR RETAIL INDUSTRY 失效
    联合多渠道配置优化零售业

    公开(公告)号:US20120016716A1

    公开(公告)日:2012-01-19

    申请号:US12837758

    申请日:2010-07-16

    IPC分类号: G06Q10/00

    摘要: A data integration module is operable to integrate a plurality of data sources, a customer preference module builds a model representing preference to different channels in merchandise category for each customer segment. A customer satisfaction module creates a model representing customer satisfaction metrics. A joint multi-channel optimization module is operable to use an optimization model that utilizes the customer preference model and the customer satisfaction model and maximize retailer's profit and customer satisfaction.

    摘要翻译: 数据集成模块可操作以集成多个数据源,客户偏好模块为每个客户分段构建表示对商品类别中的不同渠道的偏好的模型。 客户满意度模块创建一个表示客户满意度指标的模型。 联合多渠道优化模块可操作地使用利用客户偏好模型和客户满意度模型的最优化模型,并最大化零售商的利润和客户满意度。

    METHOD AND APPARATUS FOR END-TO-END RETAIL STORE SITE OPTIMIZATION
    9.
    发明申请
    METHOD AND APPARATUS FOR END-TO-END RETAIL STORE SITE OPTIMIZATION 失效
    端到端零售店现场优化的方法与装置

    公开(公告)号:US20090187464A1

    公开(公告)日:2009-07-23

    申请号:US12017673

    申请日:2008-01-22

    IPC分类号: G06F17/00

    CPC分类号: G06Q10/04 G06Q30/0205

    摘要: A method and apparatus for end-to-end retail store one-stop site configuration integrates multiple data sources, identifying key customers, forecasting merchandise demand. Site configuration is formulated as a mathematical optimization problem with both in-store and external data as input to the problem whose solution provides proper suggestions for retail store transformation.

    摘要翻译: 端到端零售店一站式配置的方法和装置集成了多个数据源,识别关键客户,预测商品需求。 现场配置被形容为一个数学优化问题,可以将店内和外部数据作为输入问题的输入,解决方案为零售店转型提供了适当的建议。

    Method and apparatus for customer segmentation using adaptive spectral clustering
    10.
    发明授权
    Method and apparatus for customer segmentation using adaptive spectral clustering 失效
    使用自适应光谱聚类的客户分割的方法和装置

    公开(公告)号:US08260646B2

    公开(公告)日:2012-09-04

    申请号:US12539256

    申请日:2009-08-11

    IPC分类号: G06Q10/00

    摘要: A method and system for customer segmentation using adaptive spectral clustering may include determining initial segmentation labels, determining new customer behavior data, formulating a single objective minimization function that integrates the initial segmentation labels with the new customer behavior data, and determining best fit to both the initial segmentation labels and the new customer behavior data simultaneously by minimizing the single objective minimization function.

    摘要翻译: 用于使用自适应光谱聚类的客户分割的方法和系统可以包括确定初始分割标签,确定新的客户行为数据,制定将初始分割标签与新的客户行为数据集成的单个目标最小化函数,以及确定最佳匹配 通过最小化单个目标最小化函数同时初始分割标签和新的客户行为数据。