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    • 2. 发明授权
    • System, method, and computer program product for increasing inventory turnover using targeted consumer offers
    • 系统,方法和计算机程序产品,用于使用目标消费者提供来增加库存周转
    • US08335720B2
    • 2012-12-18
    • US11501914
    • 2006-08-10
    • David JuangRajendra R. Rane
    • David JuangRajendra R. Rane
    • G06Q30/00
    • G06Q30/0254G06Q30/02G06Q30/0202G06Q30/0205G06Q30/0255G06Q30/0259G06Q30/0269
    • Consumer, merchant, and transactional data from a closed loop network and external sources may be leveraged to increase demand of a merchant's inventory during normally low-demand periods. Extensive data mining is used to determine the excess merchant inventory and demand patterns at different times and different locations for merchants and groups of merchants. Similar data mining is used to analyze cardmember demand patterns to identify the cardmember preferences regarding when and where they which to purchase goods and/or services. Cardmembers may also be grouped based on their demand patterns. Using pricing as a lever, cardholders with specific preferences are targeted to shift the demand from peak periods and locations to non-peak periods and locations, and to increase the non-peak demand by location as well as time period. Higher precision may be obtained using product level transaction data from point-of-sale terminals used by merchants wherever applicable.
    • 可以利用来自闭环网络和外部来源的消费者,商家和交易数据,以在正常低需求期间增加商家库存的需求。 广泛的数据挖掘用于确定商家和商人群体在不同时间和不同地点的商户库存和需求模式。 类似的数据挖掘用于分析成人需求模式,以便识别在何时何地购买商品和/或服务的卡会员偏好。 卡片成员也可以根据需求模式进行分组。 使用定价作为杠杆,具有特定偏好的持卡人的目标是将需求从高峰期和地点转移到非高峰期和地点,并通过地点和时间段增加非高峰需求。 使用商品使用的销售点终端的产品级交易数据可以获得更高的精度。
    • 8. 发明授权
    • System and method for matching merchants based on consumer spend behavior
    • 基于消费者支出行为来匹配商家的系统和方法
    • US08255268B2
    • 2012-08-28
    • US12690810
    • 2010-01-20
    • Rajendra R. RaneMelissa Schwartz
    • Rajendra R. RaneMelissa Schwartz
    • G06F17/00
    • G06Q30/02G06Q30/0202
    • The present invention improves upon existing systems and methods by providing a passive profile creation method. The data accessible to a financial processor, such as spend level data, is leveraged using sophisticated data clustering and/or data appending techniques. Associations are established among entities (e.g., consumers), among merchants, and between entities and merchants. In one embodiment, a system and method for passively collecting spend level data for a transaction of a first entity, aggregating the collected spend level data for a plurality of entities; and clustering the first entity with a subset of the plurality of entities, based on aggregated spend level data of the first entity is provided.
    • 本发明通过提供被动简档创建方法来改进现有的系统和方法。 使用复杂的数据集群和/或数据附加技术,可以利用金融处理器访问的数据(如支出级数据)。 在实体(例如,消费者)之间,商家之间以及实体和商家之间建立关联。 在一个实施例中,一种用于被动地收集用于第一实体的交易的消费水平数据的系统和方法,聚集多个实体的所收集的消费水平数据; 并且提供基于所述第一实体的汇总支出水平数据来将所述第一实体与所述多个实体的子集进行聚类。
    • 9. 发明申请
    • SYSTEM AND METHOD FOR MATCHING MERCHANTS BASED ON CONSUMER SPEND BEHAVIOR
    • 基于消费者行为行为匹配商品的系统和方法
    • US20110178849A1
    • 2011-07-21
    • US12690810
    • 2010-01-20
    • Rajendra R. RaneMelissa Schwartz
    • Rajendra R. RaneMelissa Schwartz
    • G06Q10/00G06N5/02
    • G06Q30/02G06Q30/0202
    • The present invention improves upon existing systems and methods by providing a passive profile creation method. The data accessible to a financial processor, such as spend level data, is leveraged using sophisticated data clustering and/or data appending techniques. Associations are established among entities (e.g., consumers), among merchants, and between entities and merchants. In one embodiment, a system and method for passively collecting spend level data for a transaction of a first entity, aggregating the collected spend level data for a plurality of entities; and clustering the first entity with a subset of the plurality of entities, based on aggregated spend level data of the first entity is provided.
    • 本发明通过提供被动简档创建方法来改进现有的系统和方法。 使用复杂的数据集群和/或数据附加技术,可以利用金融处理器访问的数据(如支出级数据)。 在实体(例如,消费者)之间,商家之间以及实体和商家之间建立关联。 在一个实施例中,一种用于被动地收集用于第一实体的交易的消费水平数据的系统和方法,聚集多个实体的所收集的消费水平数据; 并且提供基于所述第一实体的汇总支出水平数据来将所述第一实体与所述多个实体的子集进行聚类。