Methods and systems for compiling marketing information for a client

Abstract

Methods are provided for exploiting the secondary traffic generated by social networking sites. Traffic on a commercial website is constantly monitored by a web analytics tool that collects traffic measurements of hits, button presses, enquiries, purchases etc., as well as the referrer URL of a site, such as a social networking site, through which the commercial website is accessed. The collected measurements are forwarded to a referred traffic analysis system. Concurrently, the referred traffic analysis system crawls the Internet and collects a large number of social networking sites, analyses their content by extracting insight terms and phrases from them. The collected traffic measurements are correlated with the collected insights from the social networking sites, and the top insights that reoccur frequently enough to appear to be a driver for the measurements observed, are presented to the client. A corresponding system is also provided.

What is claimed is: 
     
         1 . A method of compiling marketing information for a client, comprising:
 (a) crawling blog posts that contain at least one link to a client website;   (b) extracting an insight related to a topic from the crawled blog posts resulting in an extracted insight;   (c) using a web analytics tool to measure traffic referred to the client website by referring blog posts and to collect the traffic measurements of traffic referred to the client website by the referring blog posts, the referring blog posts including the crawled blog posts; and   (d) associating the traffic measurements with the extracted insight.   
     
     
         2 . The method of  claim 1 , wherein the step (c) comprises:
 collecting one or more events recorded in the client website.   
     
     
         3 . The method of  claim 2 , wherein the step (c) comprises:
 recording one or more of the following events:   visits to the client website;   number of orders of products from the client website;   number of orders of products from the client website divided into a category; and   number of downloads from the client website.   
     
     
         4 . The method of  claim 1 , further comprising:
 aggregating the traffic measurements associated with the extracted insight across the crawled blog posts.   
     
     
         5 . The method of  claim 4 , wherein the aggregating comprises:
 multiplying each traffic measurement by a weighting factor associated with respective referring blog posts to obtain a product, and summing the products.   
     
     
         6 . The method of  claim 1 , wherein the step (c) comprises:
 collecting the traffic measurements referred from a subset of the crawled blog posts.   
     
     
         7 . The method of  claim 6 , wherein the collecting comprises:
 collecting the traffic measurements referred from the subset of crawled blog posts, which are most influential blog posts.   
     
     
         8 . The method of  claim 1 , wherein the step (c) comprises:
 collecting the traffic measurements referred from at least one additional blog post of the referring blog posts, the at least one additional blog post has not been crawled, the method further including:   crawling the at least one additional blog post and extracting the insight from the at least one additional blog post.   
     
     
         9 . The method of  claim 1 , further comprising:
 (e) determining frequently reoccurring insights, which reoccur frequently enough to appear to be a driver for the measurements of traffic; and   (f) presenting a plurality of said frequently reoccurring insights and associated traffic measurements to the client.   
     
     
         10 . The method of  claim 9 , wherein the determining comprises:
 determining the highest number of insights associated with one or more selected traffic measurements.   
     
     
         11 . The method of  claim 9 , wherein the plurality of said frequently reoccurring insights includes a number (K) of most frequently occurring insights, and K is between 5 and 20. 
     
     
         12 . A non-transitory computer readable medium having computer readable instructions stored thereon for execution by a processor, to perform steps of a method for compiling marketing information for a client, comprising:
 (a) crawling blog posts that contain at least one link to a client website;   (b) extracting an insight related to a topic from the crawled blog posts;   (c) measuring traffic referred to the client website by referring blog posts and collecting the traffic measurements of traffic referred to the client website by the referring blog posts, the referring blog posts including the crawled blog posts;   (d) associating the traffic measurements with the extracted insight.   
     
     
         13 . A referred traffic analysis system for compiling marketing information for a client, the system comprising a processor and a computer readable medium comprising a computer readable instruction stored thereon for execution by the processor, forming:
 a crawler module to crawl blog posts that contain at least one link to a client website, resulting in crawled blog posts;   a collector module to extract an insight related to a topic from the crawled blog posts resulting in an extracted insight;   a web analytics module to measure traffic referred to the client website by referring blog posts and to collect the traffic measurements of traffic referred to the client website by the referring blog posts, the referring blog posts including the crawled blog posts; and   an associator module to associate the traffic measurements with the extracted insight.   
     
     
         14 . The system of  claim 13 , wherein the associator module comprises:
 an aggregator module to aggregate the traffic measurements associated with the extracted insight across the crawled blog posts.   
     
     
         15 . The system of  claim 13 , wherein the aggregator module multiplies each of the traffic measurements by a weighting factor associated with respective referring blog posts to obtain a product, and then sums the products. 
     
     
         16 . The system of  claim 13 , further comprising:
 a presenter module to determine frequently reoccurring insights that reoccur frequently enough to be a driver for the traffic measurements; and to present a plurality of the frequently reoccurring insights and associated traffic measurement to the client.   
     
     
         17 . The system of  claim 13 , further comprising:
 an insights database that stores the extracted insights for each crawled blog.   
     
     
         18 . The system of  claim 17 , wherein the collector module includes:
 an insights dictionary that stores a list of predetermined insights terms for determining which insights to be extracted from each crawled blog post.   
     
     
         19 . The system of  claim 13 , further comprising:
 a referred traffic dynamics database that stores the traffic measurements associated with the extracted one or more insights.   
     
     
         20 . The system of  claim 16 , wherein the presenter module comprises:
 a graphic user interface module that presents the traffic measurements associated with the extracted one or more insights.   
     
     
         21 . The system of  claim 13 , wherein the collector module collects the traffic measurements referred from at least one additional blog post of the referring blog posts, the at least one additional blog post has not been crawled, and wherein the crawler module crawls the at least one additional blog post to extract the insight from the at least one additional blog post.