公开(公告)号：US20130138507A1

公开(公告)日：2013-05-30

申请号：US13308527

申请日：2011-11-30

Applicant: Amit Kumar ,  Gursharan Singh ,  Andrew Pariser ,  Santiago Akle ,  Ilana Segall

Inventor： Amit Kumar ,  Gursharan Singh ,  Andrew Pariser ,  Santiago Akle ,  Ilana Segall

IPC: G06Q30/02

CPC classification number: G06Q30/0251

Abstract: Systems and methods for facilitating a predictive advertising campaign are disclosed herein, in one embodiment an advertising analytics server is programmed with a predictive advertising engine and an advertisement personalization engine. The advertising analytics server is communicatively coupled to one or more e-commerce sites, search engines, Web browsers or other Web sites. The advertising analytics server and its constituent components are capable of implementing predictive advertising models and rules that automatically generate advertisements on behalf of e-commerce sites by analyzing data (analytics) from the e-commerce sites or individual consumers. Advertisements are optimally generated for e-commerce businesses based on statistical models that predict consumer behavior, preferences, and likelihood of purchases. Using these models, e-commerce businesses are able to advertise their products and services, bid on key words and target a variety of consumers in a personalized, targeted and cost effective manner, resulting in increased revenue and efficient allocation of marketing resources.

Abstract translation: 本文公开了用于促进预测性广告活动的系统和方法，在一个实施例中，广告分析服务器用预测广告引擎和广告个性化引擎进行编程。 广告分析服务器通信地耦合到一个或多个电子商务站点，搜索引擎，Web浏览器或其他网站。 广告分析服务器及其组成部分能够通过分析电子商务网站或个人消费者的数据（分析）来实现代表电子商务网站自动生成广告的预测广告模型和规则。 根据预测消费者行为，偏好和购买可能性的统计模型，为电子商务企业优化广告。 使用这些模型，电子商务企业能够通过个性化，有针对性和成本有效的方式宣传其产品和服务，对关键词进行投标，并针对各种消费者，从而增加收入并有效地分配营销资源。