公开(公告)号：US08396742B1

公开(公告)日：2013-03-12

申请号：US12329391

申请日：2008-12-05

申请人： Matthias Blume ,  Raul Navarro-Cantu ,  Craig Macdonald ,  Dema Zlotin ,  Russ Mann

发明人： Matthias Blume ,  Raul Navarro-Cantu ,  Craig Macdonald ,  Dema Zlotin ,  Russ Mann

IPC分类号： G06Q30/00

CPC分类号： G06Q30/0256 ,  G06Q30/0246

摘要： The invention is a computer-implementable methodology for quantitatively assessing the impact of paid search advertising on the total visits (paid and organic search-based visits) from search engines and utilizing this assessment to improve search engine marketing performance. The methodology relies on the computation of a synergy score for each search engine keyword of interest or coefficients in a synergy equation. Once computed, the score can be used to repeatedly compute the total return on advertising spend (ROAS) and other performance metrics on a go-forward basis without the time lag inherent in computing the synergy score itself. The invention includes specific computer-implementable methods for improving search engine marketing performance based on the total (paid plus organic) performance metrics.

摘要翻译： 本发明是一种计算机可实现的方法，用于定量评估付费搜索广告对来自搜索引擎的总访问（有偿和有机搜索访问）的影响，并利用此评估来提高搜索引擎营销绩效。 该方法依赖于在协同方程中对感兴趣的每个搜索引擎关键词或系数的协同评分的计算。 一旦计算，该分数可用于重复计算广告支出（ROAS）的总收益和其他性能指标，而无需计算协同评分本身所固有的时间滞后。 本发明包括基于总计（付费加有机）性能指标来改进搜索引擎营销绩效的特定计算机可实现的方法。