公开(公告)号：US20150161658A1

公开(公告)日：2015-06-11

申请号：US14103589

申请日：2013-12-11

Applicant: Google Inc.

Inventor： Richard Little ,  William Patrick Kee ,  Bozhena Bidyuk ,  Chao Cai ,  David Earl Barney ,  Stefan Schnabl

IPC: G06Q30/02

CPC classification number: G06Q30/0242 ,  G06Q30/0243 ,  G06Q30/0246

Abstract: Systems and methods for creating a data-driven attribution model are described. A processor identifies visits to a website. The processor identifies a path for each visitor identifier associated with the visits. The processor determines, for each path type associated with the identified paths, a path-type conversion probability based on a number of visits corresponding to the path type that resulted in a conversion. The processor calculates, for each of a plurality of the path types, a counterfactual gain for each event based on a conversion probability of the given path type and a conversion probability of a path type that does not include the event for which the counterfactual gain is calculated. The processor determines, for each event, an attribution credit based on the calculated counterfactual gain of the event. The processor then stores the attribution credits of each of the events.

Abstract translation: 描述了用于创建数据驱动归因模型的系统和方法。 处理器识别对网站的访问。 处理器识别与访问相关联的每个访问者标识符的路径。 对于与所识别的路径相关联的每个路径类型，处理器基于与导致转换的路径类型相对应的访问次数来确定路径类型转换概率。 对于多个路径类型中的每一个，处理器基于给定路径类型的转换概率和不包括反事实增益的事件的路径类型的转换概率来计算每个事件的每个事件的反事实增益 计算。 处理器根据事件的反事实增益确定每个事件的归因信用。 然后处理器存储每个事件的归因信用。

公开(公告)号：US09858587B2

公开(公告)日：2018-01-02

申请号：US14103589

申请日：2013-12-11

Applicant: Google Inc.

Inventor： Richard Little ,  William Patrick Kee ,  Bozhena Bidyuk ,  Chao Cai ,  David Earl Barney ,  Stefan Schnabl

IPC: G06Q30/00 ,  G06Q30/02

CPC classification number: G06Q30/0242 ,  G06Q30/0243 ,  G06Q30/0246

Abstract: Systems and methods for creating a data-driven attribution model are described. A processor identifies visits to a website. The processor identifies a path for each visitor identifier associated with the visits. The processor determines, for each path type associated with the identified paths, a path-type conversion probability based on a number of visits corresponding to the path type that resulted in a conversion. The processor calculates, for each of a plurality of the path types, a counterfactual gain for each event based on a conversion probability of the given path type and a conversion probability of a path type that does not include the event for which the counterfactual gain is calculated. The processor determines, for each event, an attribution credit based on the calculated counterfactual gain of the event. The processor then stores the attribution credits of each of the events.