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    • 3. 发明授权
    • System, method and program product for predicting best/worst time to buy
    • 用于预测最佳/最差时间购买的系统,方法和程序产品
    • US08762219B2
    • 2014-06-24
    • US13232444
    • 2011-09-14
    • Michael SwinsonParam Pash Kaur DhillonXingchu Liu
    • Michael SwinsonParam Pash Kaur DhillonXingchu Liu
    • G06Q30/00G06Q30/02G06Q30/06
    • G06Q30/02G06Q30/0613
    • In response to a user request for information on the best/worst days in an upcoming time period to buy a commodity, a vehicle data system may determine anticipated daily discounts applicable to the commodity. An example commodity may be a vehicle of a specific configuration. In one embodiment, characteristics of month, day of week, and day of month may be gathered and fed into a Best Day to Buy model to determine, for each day of the time period, a projected daily discount relative to a set price for the commodity. Additional input variables such as incentives and seasonal discounts may be included. From the computed daily discounts, the vehicle data system may determine the best day and/or the worst day to buy and report same to the user.
    • 响应于用户要求在即将到来的时间段内购买商品的最佳/最差天数的信息,车辆数据系统可以确定适用于商品的预期每日折扣。 示例商品可以是具体配置的载体。 在一个实施例中,可以收集月份,星期几和月份的特征,并且将其馈送到“最佳购买日”模型中,以确定每个时间段的每一天相对于 商品。 可能包括其他输入变量,如激励和季节性折扣。 从计算出的每日折扣中,车辆数据系统可以确定最佳的一天和/或最差的一天,以向用户购买和报告相同的日期。
    • 4. 发明申请
    • SYSTEM, METHOD AND PROGRAM PRODUCT FOR PREDICTING BEST/WORST TIME TO BUY
    • 用于预测最佳/最差时间购买的系统,方法和程序产品
    • US20120066092A1
    • 2012-03-15
    • US13232444
    • 2011-09-14
    • Michael SwinsonParam Pash Kaur DhillonXingchu Liu
    • Michael SwinsonParam Pash Kaur DhillonXingchu Liu
    • G06Q30/00
    • G06Q30/02G06Q30/0613
    • In response to a user request for information on the best/worst days in an upcoming time period to buy a commodity, a vehicle data system may determine anticipated daily discounts applicable to the commodity. An example commodity may be a vehicle of a specific configuration. In one embodiment, characteristics of month, day of week, and day of month may be gathered and fed into a Best Day to Buy model to determine, for each day of the time period, a projected daily discount relative to a set price for the commodity. Additional input variables such as incentives and seasonal discounts may be included. From the computed daily discounts, the vehicle data system may determine the best day and/or the worst day to buy and report same to the user.
    • 响应于用户要求在即将到来的时间段内购买商品的最佳/最差天数的信息,车辆数据系统可以确定适用于商品的预期每日折扣。 示例商品可以是具体配置的载体。 在一个实施例中,可以收集月份,星期几和月份的特征,并且将其馈送到“最佳购买日”模型中,以确定每个时间段的每一天相对于 商品。 可能包括其他输入变量,如激励和季节性折扣。 从计算出的每日折扣中,车辆数据系统可以确定最佳的一天和/或最差的一天,以向用户购买和报告相同的日期。