Clickstream

A click path or clickstream is the sequence of hyperlinks one or more website visitors follows on a given site, presented in the order viewed. A visitor's click path may start within the website or at a separate 3rd party website, often a search engine results page, and it continues as a sequence of successive webpages visited by the user. Click paths take call data and can match it to ad sources, keywords, and/or referring domains, in order to capture data. A click path or clickstream is the sequence of hyperlinks one or more website visitors follows on a given site, presented in the order viewed. A visitor's click path may start within the website or at a separate 3rd party website, often a search engine results page, and it continues as a sequence of successive webpages visited by the user. Click paths take call data and can match it to ad sources, keywords, and/or referring domains, in order to capture data. Clickstream analysis is useful for web activity analysis, software testing, market research, and for analyzing employee productivity. While navigating the World Wide Web, a 'user agent' (web browser) makes requests to another computer, known as a web server, every time the user selects a hyperlink. Most web servers store information about the sequence of links that a user 'clicks through' while visiting the websites that they host in log files for the site operator’s benefit. The information of interest can vary and may include: information downloaded, webpage visited previously, webpage visited afterwards, duration of time spent on page, etc. The information is most useful when the client/user is identified, which can be done through website registration or record matching through the client’s Internet service provider (ISP). Storage can also occur in a router, proxy server or ad server. Data mining, column-oriented DBMS, and integrated OLAP systems can be used in conjunction with clickstreams to better record and analyze this data. Use of clickstream data can raise privacy concerns, especially since some Internet service providers have resorted to selling users' clickstream data as a way to enhance revenue. There are 10-12 companies that purchase this data, typically for about $0.40/month per user. While this practice may not directly identify individual users, it is often possible to indirectly identify specific users, an example being the AOL search data scandal. Most consumers are unaware of this practice, and its potential for compromising their privacy. In addition, few ISPs publicly admit to this practice. As the world of online shopping grows, it is becoming easier for the privacy of individuals to become exploited. There have many cases of email addresses, phone numbers, and other personal information that have been stolen illegally from shoppers, clients, and many more to be used by third parties. These third parties can range from advertisers to hackers. There are consumers who actually benefit from this by gaining more targeted advertising and deals, but most are harmed by the lack of privacy. As the world of technology grows, consumers are more and more in risk of losing privacy. Clickstreams can be used to allow the user to see where they have been and allow them to easily return to a page they have already visited, a function that is already incorporated in most browsers. Clickstream can display the specific time and position that individuals browsed and closed the website, all the web pages they viewed, the duration they spent on each page and it can also show which pages are viewed most frequently. There is abundant information to be analyzed, individuals can check visitors clickstream in association with other statistical information, such as: visiting length, retrieval words, ISP, countries, explorers, etc. This process enables individuals to know their visitors deeply. Webmasters can gain insight into what visitors on their site are doing by using the clickstream. This data itself is 'neutral' in the sense that any dataset is neutral. The data can be used in various scenarios, one of which is marketing. Additionally, any webmaster, researcher, blogger or person with a website can learn about how to improve their site. The growing e-commerce industry has made it necessary to tailor to the needs and preferences of consumers. Click path data can be used to personalize product offerings. By using previous click path data, websites can predict what products the user is likely to purchase. Click path data can contain information about the user’s goals, interests, and knowledge and therefore can be used to predict their future actions and decisions. By using statistical models, websites can potentially increase their operating profits by streamlining results based on what the user is most likely to purchase.