Real-Time Clickstream Sharing

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Visualizing an Individual's Browsing Habits

Artificial intelligence, personalization, mobility, and the Semantic Web – these four aspects map out the next generation of the Internet, which some refer to as “Web 3.0”.[1] Whether or not we are currently using Web 3.0 is debatable, but one thing for certain is that the Semantic Web has started to shape our browsing experiences by creating the so-called Intelligent Web.

With clickstream analysis at the foundation of the Semantic Web, information regarding an individual’s browsing habits is obtained to create a personalized experience on the Internet. Leveraging today’s momentum of social media, multiple platforms have attempted to amalgamate the concept of clickstream analysis with social media to create a new web technology known as “real-time clickstream sharing”.

Contents

Background on the Semantic Web

Syntax and Semantics

Introduction to the Semantic Web

The Semantic Web is driven by semantics, the meaning behind words, rather than syntax, the structure of words. For example, the water is triangular has correct syntax but the semantics do not mean anything. The Internet currently functions by transmitting and receiving information written in a set of syntax rules known as HTML. The purpose of a web browser is to read HTML documents and compose them into web pages that users can interact with.[1] However, since computers can only understand syntax, the semantics behind each page is lost.

Organizations are currently modifying HTML with additional data so that computers can make sense of web pages more easily. The ability to understand both semantics and syntax in the Semantic Web will help shift the Internet from a passive role to an active one. The greatest benefit of the Semantic Web will be more accurate and tailored search results because computers will capture the semantics behind web pages to act as our own personal assistant when browsing the Internet.[2]

The Move Towards this Structure

Technology such as real-time clickstream sharing has the potential to take a prominent role in moving towards this new web structure and exploring the capabilities of the Semantic Web. The goal of real-time clickstream sharing is to create a more personalized browsing experience where content will be recommended by computers based on the unique interests of each user. This concept is highly correlated with what the Semantic Web will deliver but through a social media platform. In some ways, it is the starting point to how the Semantic Web will be prevalent in the near future.

Clickstream Analysis

The foundation of real-time clickstream sharing and the Semantic Web is based on clickstream analysis, the process of collecting, analyzing, and reporting aggregated clickstream data. Clickstreams are records of a user’s activity on the Internet, which includes every website and page visited by a user and the time spent on each one.[3] From a user perspective, clickstream analysis allows them to see where they have been so that they can return easily to previously viewed pages.

Clickstream Process

Every click a user performs on a web page is stored in multiple places. Website servers that host the website, web browsers used to navigate through web pages, the Internet Service Provider’s routers, and finally the servers of the advertisement networks that have their code embedded on sites. Essentially, every time a user clicks a link or visits a web page, clickstream data is created and stored to be analyzed.[4] Some of the information that clickstream data contains is the:

  • Number of pages accessed on the website
  • Items added or removed from the shopping cart
  • Amount of time spent on each page
  • Prior location before reaching the website[5]

However, the raw data that is collected is only useful if analyzed properly and transformed into information. The most prominent uses of clickstream analysis have come from performing general data mining, market research, and analyzing e-commerce and web traffic trends.

Data Mining

The terabytes of clickstream data that are collected on a daily basis have the potential for significant business value when analyzed effectively and correctly. Therefore, the biggest challenge that many businesses face is trying to transform the raw and complex data into more relevant information for decision-making.[6] Applying online analytical processing tools to the clickstream data has been the most useful since businesses can extract information and gain insights regarding market tends, product demand, and consumer behaviour.

Market Research

The ability to integrate clickstream data with other customer information, such as purchase history and demographic profiles, has allowed clickstream analysis to become a popular market research tool. A 360-degree view of a customer can be created based on the data collected, which allows marketers to identify customer preferences and patterns in purchasing behavior. This information can then be used to predict the likelihood of customer purchases from a specific site and gauge customer satisfaction with the website, both of which are essential to gaining a competitive advantage for e-commerce businesses. It will also allow online advertisements and promotions to be targeted specifically at market segments who are more likely to respond.[7]

Web Traffic and E-Commerce Analysis

Crazy Egg Heat Map

Web traffic analysis involves using the collection of clickstream data to examine how long a user remains on a web page, how long it takes the pages to load, and how much data is transmitted before a user moves on. Webmasters, researchers, and bloggers are able to analyze this data to gain insights on what users are doing on their website so that they can make improvements to increase traffic.[8] The most popular tools used for web traffic analysis are Crazy Egg and Google Analytics, both of which provide information on how visitors engage with a website through reports and visuals. One of the most popular features of Crazy Egg, as displayed on the right, is a heat map to visually show which areas of the page are clicked most often.[9]

E-commerce analysis uses clickstream data to quantify a user’s behaviour on a website when making potential purchases. Data related to which pages visitors often linger on, specific items they put in their shopping cart, and which items are frequently purchased is collected to gauge the overall response to the site content. Internet marketers and advertisers use this feedback to learn more about consumer behavior as well as which trends are gaining popularity.[10]

Privacy Issues

2006 AOL Search Data Scandal

The ease of collecting clickstream data has raised numerous concerns regarding privacy since there is potential for the sensitive data to be sold or released to the public. The AOL search data leak in 2006 is a prime example of how the misuse of clickstream data can lead to the violation of privacy for many individuals. As one of the largest search engines at the time, AOL released a detailed search log associated with over 650,000 users that was intended for research purposes.[11] However, personally identifiable information was present in the data as queries could be attributed to specific AOL user accounts if analyzed properly. This meant that an individual could be identified solely based on their search history.

Another issue of clickstream analysis is the unauthorized collection of clickstream data through spyware programs that can be installed on computers without user consent. This increases the risk of clickstreams containing user information being leaked to third parties that may use the information in harmful ways. This presents a threat if the clickstream data stored by websites and Internet service providers is stolen, thus compromising the privacy of numerous individuals.[12]

Real-Time Clickstream Sharing

Dscover.me, Voyurl, and Sitesimon are three social media platforms that currently allow users to take advantage of real-time clickstream sharing in different ways. Real-time clickstream sharing incorporates a social media aspect to clickstream analysis with the purpose of creating a richer browsing experience for users through the discovery of unique content.

Dscover.me is essentially a sharing application which provides no personal analytics, opting to simply collect links to share on the user's feed. Voyurl follows a heavily analytical approach by depicting user browsing habits in easy-to-understand ways while using the information to recommend additional content. Sitesimon sits between the two platforms by allowing content to be shared both passively and actively while providing recommended content to the user.

Dscover.me

Dscover.me

Launched in November 2010, Dscover.me transforms web browsing into a new way of socializing by introducing clickstream conversations. Users can instantly and effortlessly share articles, websites, videos, or products with their friends in real-time as they browse the Internet. Dscover.me aims to create a passive social media experience where a user’s browsing history is automatically publicized through a news feed.[13]

Dscover.me Home Screen

While actively browsing the Internet, Dscover.me works by sharing websites and links currently being viewed on to a feed called “My Discoveries”. Each link shared contains the website name, link, date and time of last visit, and the number of times visited, all of which is done passively with the installed browser plug-in. Users also have the ability to view the clickstreams of their friends in real-time to see what types of websites they are visiting. Finally, an “All Discoveries” feed consolidates shared content from all users on Dscover.me with the most viewed links at the top of the list.

The main differentiating feature of Dscover.me is the “Whitelist”, which initially works under the assumption that every website on the Internet cannot be shared. Therefore, a website must be checked off from the list before it is displayed on your feed. This helps mitigate privacy concerns regarding what information is shared since nothing is displayed without prior approval.[14] One of the major benefits of Dscover.me is it’s ease of use and the minimal amount of user engagement required since the main functions are viewing feeds, deleting shared content, and adjusting websites on the Whitelist.

Voyurl

Voyurl

As the newest of the three platforms which launched in February 2011, Voyurl focuses on the personal analytics side of real-time clickstream sharing by analyzing a user’s browsing behaviour in-depth. Personalized recommendations of web content are also provided in real-time and tailored to the user based on their unique browsing history. The differentiating feature of Voyurl is the ability for personal trends to be identified and portrayed in easy-to-understand information graphics.[15]

Voyurl Dashboard

Voyurl requires users to install a browser plug-in that monitors and tracks all web activity. The aim of Voyurl is to analyze the collected data and return it to users through a meaningful dashboard of information graphics depicting the analyzed browsing habits. Pie graphs show habits broken down by category, charts depict visits over a span of days or weeks, and tables and graphs indicate the number of pages viewed in a certain time frame. In addition, Voyurl boasts a content recommendation engine that continuously provides suggestions on new websites or information that might be of interest without requiring the user to actively share content.[16]

Voyurl addresses the prominent issue of privacy by introducing a comprehensive privacy policy, and an intriguing point to note is that Voyurl explicitly states that information may be sold or made public if necessary.[17] This transparency makes it clear that once people start using Voyurl, they have agreed to abide by any policies which have been set.

Sitesimon

Sitesimon

Launched in October 2010, Sitesimon focuses exclusively on content discovery and personalized recommendations based on user profiles. A “Recommended Content” list is compiled by analyzing clickstream data related to content that is actively shared in real-time on a user’s feed. This feature, along with a simple user interface, provides value through unique recommendations of personalized content tailored to individual interests. According to Sitesimon, it “analyzes your browsing habits and who you are connected with, learns what you love, and recommends the best, unique content for you.”[18]

Sitesimon Home Screen

Users can also share content with their friends by simply installing a browser plug-in and connecting their Facebook and/or Twitter accounts. Once connected, a list of friends will automatically be populated if there are other Sitesimon users on Facebook. Three different types of feeds can then be managed using a dashboard on the home page. The “Friends” feed shows all websites shared by friends, the “Public” feed displays content shared by all Sitesimon users, and the "Social" feed displays social media content from Facebook and Twitter to integrate the three platforms.

Sitesimon mitigates privacy issues by storing the data that is collected in a secure, anonymized database; thus if the information is ever sold to a third party, it would be aggregated so that nothing can be tied to an individual user.[19] This mitigates the situation that occurred during the 2006 AOL search data leak previously discussed. The policies are transparent and Sitesimon lets the user know which sites are being stored. For example, secure web pages containing “https”, e-mail clients, and sites prompting passwords are not recorded.[20]

Personal and Business Uses

Examples of Personal Analytics

Real-time clickstream sharing sites have the potential to become powerful replacements for things such as social bookmarking and information sharing. Voyurl users can see what their friends are looking at in real-time on the Internet, which allows users to discover content they would not have seen before. They also have the unique ability to compare browsing habits by analyzing and quantifying individual browsing behaviour. The current social media tools require actively posting links or waiting for links to be posted, but real-time clickstream sharing allows users to discover things that are current based on search volume, which in turn makes it easier for viral information to be spread faster to people with similar interests. One of the main benefits is that each of the available platforms are free and easy to use with the installation of a browser plug-in.

If these platforms become sustainable in the future, potential revenue models will provide business value to third party companies that may want to purchase the invaluable data collected in order to perform market research and data mining. These platforms may incorporate promoted products and links in the recommendation engine for companies willing to pay to promote their business. A better user profile can be formed as more data is collected by each platform, which ties in closely with behavioural targeted advertising that online businesses are aiming towards today.[21]

Privacy and Security Concerns

However, there are several factors that need to be considered before users choose to publicize their entire browsing history online. One of the most prominent issues would be the privacy and security factors that each platform attempts to address. Each platform require users to have their data tracked and analyzed for the benefits to be seen, but there is no way of knowing what is actually done with that data and how it is used behind the scenes. This will ultimately affect the rate of adoption since users are essentially providing open access to their personal data. With Dscover.me and Sitesimon, users will be revealing practically everything they view on the Internet in a manner that some refer to as "online exhibionism". Although this raises concerns regarding the consequences of the transparency of browsing habits, people who are worried about their privacy and having their online behaviour easily accessible have the ability to control the content that is shared and who it is shared with.[22]

Another concern is the fact that this concept of real-time clickstream sharing as a social media application is still new. Like any social media site, there is only value if there is enough critical mass, even more so if the entire purpose of the site is to share information. This means that there needs to be a way to entice users to start using these sites, or at least adopt it as another application to use alongside Twitter and Facebook.

Future Outlook

Rate of Adoption Curve

Numerous technology sites predicted that real-time clickstream sharing will take off as the next social media success for 2011, but it will be a while before these clients can achieve the critical mass necessary to become universally accepted like Facebook and Twitter. In fact, the personal use of real-time clickstream sharing sites will become obsolete due to the disadvantages discussed before and the high critical mass required. Although this happened in late November 2011, it was not surprising since the number of users on the site only amounted to a few hundred.[23] On the otherhand, Sitesimon and Voyurl are both still in beta testing with frequent downtimes for maintenance. Based on the rate of adoption S-curve to the right, only the 'innovators' have adopted this technology and each platform is experiencing difficulties attracting 'early adopters'.

The Semantic Web Revisted

While real-time clickstream sharing social media sites will see little success, the characteristics of these platforms are similar in some ways to what the Semantic Web is expected to deliver in the near future. With users passively browsing the Internet and clickstream data being collected in the background, these platforms can learn what each user is interested in to tailor specific content that would interest them. The abundance of data available to be analyzed indicates that computers will soon be able to understand the semantics behind the information in order to help users more effectively by going beyond just providing recommended content to view on the web. Real-time clickstream sharing is allowing computers to take a more active role in creating a richer browsing experience, but with the Semantic Web, the computer will be able to understand individual browsing behaviour and interests. This will then allow them to provide more personalized search results, articles, and ultimately become intelligent enough to perform various tasks and simplify the amount of work users will have to do.

Future Trends for Social Media

The Semantic Web

It is unlikely that real-time clickstream sharing will make its mark on the social media world as a standalone application such as Facebook and Twitter, but it may still play a part in changing the face of social media. Real-time clickstream sharing will serve as the foundation for the Semantic Web, which is one step closer to converging towards Web 3.0. The concept of having a computer knowing personal interests and browsing behaviour has its roots in the analytical aspect of real-time clickstream sharing and clickstream analysis.

Although social media is already heavily ingrained in our daily lives, the introduction of the Semantic Web will transform the concept into a practically ubiquitous presence. Search engines will provide more meaningful results and have the ability to recognize relationships between search terms and standalone phrases. For example, tourists searching for “sushi” will be introduced to pages which advertise “the best California rolls”, a connection the current Web would not be able to make. In essence, the roles of the user and the web will change as the Internet will literally become an extension of the brain in the virtual world and reduce the need for users to take a proactive role on the Internet.

Evolution of Real-Time Clickstream Sharing

The Semantic Web is something that will grow as the user does, since its heart is in the data being collected and analyzed. Better predictive models will be generated as more users engage in platforms similar to real-time clickstream sharing. However, it is important to recognize that the original intent of the Web was to expose users to the vast amount of information available, rather than isolate the users with only content that the computer thinks will interest them. Thus the challenge then is to create algorithms which will emulate not only the behavior and interests of the individual user, but their curiosity as well. As seen in the past, clickstream analysis has slowly evolved into more meaningful business applications with the most recent evolution into a social media aspect. Now with real-time clickstream sharing available to users of the Internet, this new technology has the potential to propel us into the Semantic Web and ultimately, Web 3.0.

References

  1. http://en.wikipedia.org/wiki/HTML
  2. http://himmele.blogspot.com/2011/11/apples-siri-and-semantic-web.html
  3. http://www.slideshare.net/intuitiv/clickstream-analysis
  4. http://ecommerce.about.com/od/eCommerce-Marketing-Strategies/a/Clickstream.htm
  5. http://ecommerce.about.com/od/eCommerce-Marketing-Strategies/a/Clickstream.htm
  6. http://www.zdnet.com/news/battling-business-data-overload/124020
  7. http://www.slideshare.net/intuitiv/clickstream-analysis
  8. http://searchcrm.techtarget.com/definition/clickstream-analysis
  9. http://www.crazyegg.com/home3
  10. http://searchcrm.techtarget.com/definition/clickstream-analysis
  11. http://en.wikipedia.org/wiki/AOL_search_data_leak
  12. http://en.wikipedia.org/wiki/Clickstream
  13. http://abcnews.go.com/Technology/clickstream-sharing-sites-reveal-step-online/story?id=13263067#.TuKvBWPTr1R
  14. http://techcrunch.com/2010/11/17/dscover/
  15. http://www.fastcodesign.com/1664577/voyurl-turns-your-browsing-activity-into-personal-infographics
  16. http://www.fastcodesign.com/1664577/voyurl-turns-your-browsing-activity-into-personal-infographics
  17. http://www.voyurl.com/about/privacy
  18. http://sitesimon.com/aboutus
  19. http://sitesimon.com/privacy
  20. http://www.sitesimon.com/
  21. http://en.wikipedia.org/wiki/Behavioral_targeting
  22. http://abcnews.go.com/Technology/clickstream-sharing-sites-reveal-step-online/story?id=13263067
  23. http://www.dscover.me
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