Predictive Tool for Defining Target Group
    2.
    发明申请
    Predictive Tool for Defining Target Group 审中-公开
    用于定义目标群体的预测工具

    公开(公告)号:US20150348073A1

    公开(公告)日:2015-12-03

    申请号:US14326207

    申请日:2014-07-08

    IPC分类号: G06Q30/02

    CPC分类号: G06Q30/0204 G06Q30/0201

    摘要: Embodiments relate to methods and apparatuses creating and analyzing target groups, for example as relied upon in conducting marketing campaigns. Certain embodiments allow predictive definition of a target group based upon an underlying complex mathematical model, which may reference large data volumes regarding individual targets in an underlying database. An interface affords simplified visualizations of the target group, for example circles of varying diameter representing target group size. Adjustable graphic elements (e.g., sliders) in dashboard views may allow predictive definition of the target group based upon inputs such as marketing cost, target group size, and/or expected revenue, etc. Once defined and stored, target groups may be explored in an interactive manner through application of filter criteria, thereby promoting familiarity with target group characteristics. Embodiments allow users who are not modeling experts, to nevertheless interact efficiently with large data volumes in order to intuitively define and/or explore a target group.

    摘要翻译: 实施例涉及创建和分析目标群体的方法和装置,例如在进行营销活动时依赖的。 某些实施例允许基于潜在的复杂数学模型对目标组进行预测定义,所述基础复杂数学模型可以参考关于底层数据库中的各个目标的大数据量。 界面提供目标组的简化可视化,例如表示目标组大小的不同直径的圆。 仪表板视图中的可调节图形元素(例如,滑块)可以允许基于诸如营销成本,目标组大小和/或预期收入等输入来对目标组进行预测性定义。一旦定义和存储,可以在 通过应用过滤标准的互动方式,从而提高对目标群体特征的熟悉程度。 实施例允许不是建模专家的用户尽可能高效地与大数据量交互,以便直观地定义和/或探索目标组。

    Interactive Tool for Exploring Target Group
    4.
    发明申请
    Interactive Tool for Exploring Target Group 审中-公开
    用于探索目标群体的互动工具

    公开(公告)号:US20150348124A1

    公开(公告)日:2015-12-03

    申请号:US14326227

    申请日:2014-07-08

    IPC分类号: G06Q30/02

    CPC分类号: G06Q30/0269

    摘要: Embodiments relate to methods and apparatuses creating and analyzing target groups, for example as relied upon in conducting marketing campaigns. Certain embodiments allow predictive definition of a target group based upon an underlying complex mathematical model, which may reference large data volumes regarding individual targets in an underlying database. An interface affords simplified visualizations of the target group, for example circles of varying diameter representing target group size. Adjustable graphic elements (e.g., sliders) in dashboard views may allow predictive definition of the target group based upon inputs such as marketing cost, target group size, and/or expected revenue, etc. Once defined and stored, target groups may be explored in an interactive manner through application of filter criteria, thereby promoting familiarity with target group characteristics. Embodiments allow users who are not modeling experts, to nevertheless interact efficiently with large data volumes in order to intuitively define and/or explore a target group.

    摘要翻译: 实施例涉及创建和分析目标群体的方法和装置,例如在进行营销活动时依赖的。 某些实施例允许基于潜在的复杂数学模型对目标组进行预测定义,所述基础复杂数学模型可以参考关于底层数据库中的各个目标的大数据量。 界面提供目标组的简化可视化,例如表示目标组大小的不同直径的圆。 仪表板视图中的可调节图形元素(例如,滑块)可以允许基于诸如营销成本,目标组大小和/或预期收入等输入来对目标组进行预测性定义。一旦定义和存储,可以在 通过应用过滤标准的互动方式,从而提高对目标群体特征的熟悉程度。 实施例允许不是建模专家的用户尽可能高效地与大数据量交互,以便直观地定义和/或探索目标组。

    Assessment of users feedback data to evaluate a software object

    公开(公告)号:US09613367B2

    公开(公告)日:2017-04-04

    申请号:US13913516

    申请日:2013-06-10

    IPC分类号: G06Q30/02

    CPC分类号: G06Q30/0282

    摘要: In one embodiment, feedback data of a software object is received through a sequence of cascaded GUIs. The cascaded GUIs include an interaction portion to receive the feedback data from users at a plurality of feedback levels. Further, user role weightings of the users, account weightings of enterprises associated with the users and a time weighting corresponding to a life-cycle phase of the software object are retrieved. Furthermore, average rating of the software object corresponding to each feedback level is determined as a function of the user role weightings, the account weightings, the time weighting, the feedback data corresponding to a feedback level and a number of users submitted the feedback data. The determined average ratings and rating distribution corresponding to each feedback level are graphically displayed on the interaction portion associated with a next feedback level.