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    • 3. 发明授权
    • High-precision customer-based targeting by individual usage statistics
    • 根据个人使用统计信息进行高精度的基于客户的定位
    • US08412566B2
    • 2013-04-02
    • US10616486
    • 2003-07-08
    • Jesse T. QuatseAnssi KarhinenEric G. Wasserman
    • Jesse T. QuatseAnssi KarhinenEric G. Wasserman
    • G06Q30/00
    • G06Q30/0254G06Q30/02G06Q30/0211
    • A system for distributing limited numbers of promotional offers to individual customers, the promotional offers being targeted to customers based on the customers' individual probabilities of accepting the offers in such a way that each customer can receive a limited number of offers that are estimated to be most likely to be acceptable by the customer. Customer-Based targeting analyzes each customer's past purchasing behavior relative to a master list of promotional offers made available to all customers. From that master list Customer-Based targeting selects a preset limit of promotional offers for each individual customer according to the likelihood that, given the opportunity to select any offers of the master list, each customer would prefer those few offers selected specifically for the customer. Various techniques are disclosed for providing an offer acceptance probability profile tailored for individual customers for use in the Customer-Based targeting technique. Product groupings and market segments are taken into account. Empirical Bayes techniques are applied to the estimation of the offer acceptance profile, and techniques suitable for handling sparse data are applied. Various marketing strategies are incorporated into the system. A graphical technique is provided for adjusting the offer acceptance profile that enables a user to override a system computation and manually set the relative offer acceptance probabilities for an individual user or class of users.
    • 一种向个人客户分发有限数量的促销优惠的系统,根据客户的个人接受要约的方式,将促销优惠定位到客户,使得每个客户可以收到有限数量的优惠,估计是 最有可能被客户所接受。 基于客户的定位分析每个客户过去的采购行为相对于所有客户提供的促销优惠的主列表。 从该主列表中,基于客户的定位根据可能性,为每个客户选择预定的促销优惠限制,因为有机会选择主列表的任何优惠,每个客户都希望选择专门为客户选择的几个优惠。 公开了各种技术来提供为个人客户定制的报价接受概率概况,以用于基于客户的目标技术。 产品分组和市场细分被考虑在内。 经验贝叶斯技术被应用于报价接受概况的估计,并适用于处理稀疏数据的技术。 各种营销策略纳入系统。 提供了一种图形技术,用于调整报价接受简档,使得用户能够覆盖系统计算,并手动设置单个用户或一类用户的相对报价接受概率。
    • 4. 发明申请
    • High-precision customer-based targeting by individual usage statistics
    • 根据个人使用统计信息进行高精度的基于客户的定位
    • US20050010472A1
    • 2005-01-13
    • US10616486
    • 2003-07-08
    • Jesse QuatseAnssi KarhinenEric Wasserman
    • Jesse QuatseAnssi KarhinenEric Wasserman
    • G06F17/60
    • G06Q30/0254G06Q30/02G06Q30/0211
    • A system for distributing limited numbers of promotional offers to individual customers, the promotional offers being targeted to customers based on the customers' individual probabilities of accepting the offers in such a way that each customer can receive a limited number of offers that are estimated to be most likely to be acceptable by the customer. Customer-Based targeting analyzes each customer's past purchasing behavior relative to a master list of promotional offers made available to all customers. From that master list Customer-Based targeting selects a preset limit of promotional offers for each individual customer according to the likelihood that, given the opportunity to select any offers of the master list, each customer would prefer those few offers selected specifically for the customer. Various techniques are disclosed for providing an offer acceptance probability profile tailored for individual customers for use in the Customer-Based targeting technique. Product groupings and market segments are taken into account. Empirical Bayes techniques are applied to the estimation of the offer acceptance profile, and techniques suitable for handling sparse data are applied. Various marketing strategies are incorporated into the system. A graphical technique is provided for adjusting the offer acceptance profile that enables a user to override a system computation and manually set the relative offer acceptance probabilities for an individual user or class of users.
    • 一种向个人客户分发有限数量的促销优惠的系统,根据客户的个人接受要约的方式,将促销优惠定位到客户,使得每个客户可以收到有限数量的优惠,估计是 最有可能被客户所接受。 基于客户的定位分析每个客户过去的采购行为相对于所有客户提供的促销优惠的主列表。 从该主列表中,基于客户的定位根据可能性,为每个客户选择预定的促销优惠限制,因为有机会选择主列表的任何优惠,每个客户都希望选择专门为客户选择的几个优惠。 公开了各种技术来提供为个人客户定制的报价接受概率概况,以用于基于客户的目标技术。 产品分组和市场细分被考虑在内。 经验贝叶斯技术被应用于报价接受概况的估计,并适用于处理稀疏数据的技术。 各种营销策略纳入系统。 提供了一种图形技术,用于调整报价接受简档,使得用户能够覆盖系统计算,并手动设置单个用户或一类用户的相对报价接受概率。