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    • 1. 发明申请
    • SYSTEM AND METHOD FOR GENERATING AUTOMATED SELF-OPTIMIZING TARGETED E-MAILS
    • 用于生成自动优化目标电子邮件的系统和方法
    • US20090248523A1
    • 2009-10-01
    • US12416388
    • 2009-04-01
    • Geoffrey J. HueterSteven C. QuandtNoble H. HueterChristopher J. Bryant
    • Geoffrey J. HueterSteven C. QuandtNoble H. HueterChristopher J. Bryant
    • G06Q30/00
    • G06Q30/0631G06N99/005G06Q10/00G06Q30/00G06Q30/0185G06Q30/0201G06Q30/0202G06Q30/0255G06Q30/0269H04L51/12
    • A system and method is disclosed for generating targeted e-mails based on individual subject behavior and interests, as determined by an application's website browsing behavior, online and offline purchases, ratings, and other implicit and explicit indications of subject preferences and interests. The subject's behavior data is collected directly from the subject's client browser or from the application's own information and used to generate profiles of the subjects that will be sent e-mails and the objects that will be recommended. Targeted content is generated by matching subject and object profiles in combination with any subject segmentation filters that the application provides. The e-mail targeting is optimized by measuring subject response to targeted e-mails and adjusting recommendation strategies used to generate subsequent recommendations. The system has application in personalization, behavioral targeting, Internet retailing, affiliate marketing, and online advertising, to name but a few applications.
    • 公开了一种系统和方法,用于基于个人主体行为和兴趣来生成针对性的电子邮件,如由应用程序的网站浏览行为,在线和离线购买,评级以及其他隐含和明确的主题偏好和兴趣的指示所确定的。 受试者的行为数据直接从受试者的客户端浏览器或应用程序自己的信息中收集,并用于生成将发送电子邮件的主题和将被推荐的对象的配置文件。 通过将主题和对象简档与应用程序提供的任何主题分段过滤器相结合来生成目标内容。 通过测量对目标电子邮件的主题响应并调整用于生成后续建议的推荐策略,优化电子邮件定位。 该系统在个性化,行为定位,互联网零售,联盟营销和在线广告方面都有应用,仅举几例。
    • 3. 发明申请
    • SYSTEM AND METHOD FOR COMBINING AND OPTIMIZING BUSINESS STRATEGIES
    • 用于组合和优化业务战略的系统和方法
    • US20090248495A1
    • 2009-10-01
    • US12416083
    • 2009-03-31
    • Geoffrey J. HueterSteven C. QuandtChristopher J. Bryant
    • Geoffrey J. HueterSteven C. QuandtChristopher J. Bryant
    • G06Q30/00G06Q10/00
    • G06Q30/0631G06N20/00G06Q10/00G06Q30/00G06Q30/0185G06Q30/0201G06Q30/0202G06Q30/0204G06Q30/0255G06Q30/0269H04L51/12
    • A system and method is disclosed for tracking subject behavior and making object recommendations to drive the subject to a desired outcome. The system consists of several components: a data collection module that captures subject behavior and provides behavioral context for the recommendations; a profiling module that extracts characteristics of subjects and objects from the behavior data; and a recommendation module, which uses the profiles and the behavior context to generate personalized content, including product recommendations, content recommendations, and advertisements. The recommendation module consists of several sub-modules: a behavioral recommendation module, which matches profiles or uses other unconstrained methods for matching objects to subjects; a business rule module, which filters and modifies recommendations by applying application-specific business logic to defined attributes of the objects; and a promotion engine, which modifies the scores from the recommendation module to bias the recommendations towards certain objects based on additional business goals, such as exposing new objects, selling out old products, or satisfying promotional business agreements with partners. The system continuously samples and assesses the performance of a variety of candidate recommendation strategies and optimizes the selection of the rules and profiling methods to maximize or minimize the value of some objective function that characterizes the system. The system has application to Internet retailing, behavioral targeting, recommendation systems, personalization, business rules, and business optimization.
    • 公开了一种系统和方法,用于跟踪对象行为并提出对象建议以将受试者驱动到期望的结果。 该系统由几个组件组成:数据收集模块,用于捕获主题行为并提供建议的行为背景; 分析模块,从行为数据中提取主体和对象的特征; 以及推荐模块,其使用简档和行为上下文来生成个性化内容,包括产品建议,内容推荐和广告。 推荐模块由几个子模块组成:一个行为推荐模块,其匹配配置文件或使用其他无约束方法将对象与对象相匹配; 业务规则模块,其通过将特定于应用程序的业务逻辑应用于对象的定义属性来过滤和修改建议; 以及促销引擎,其改进来自推荐模块的分数,以基于额外的业务目标(诸如暴露新对象,销售旧产品或与合作伙伴达成促销商务协议)来将建议偏向某些对象。 系统不断地对各种候选推荐策略进行抽样和评估,并优化了规则和分析方法的选择,以最大化或最小化系统特征的一些目标函数的价值。 该系统应用于互联网零售,行为定位,推荐系统,个性化,业务规则和业务优化。