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Explain Clickstream mining.
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• Click stream mining is a record of a user's activity on the internet, including every web site and every page of every web site that the users visits, how long the user was on a page or site, in what order the pages were visited, any newsgroups that the user participates in and even the email-addresses of mail that the users send and receive.

• Both ISPs and individual web sites are capable of tracking a user's clickstream. Clickstream data is becoming increasingly valuable to internet marketers and advertisers. Be aware of the big amount of data a clickstream generates.

• These 'footprints' visitors leave at a site grown wildly - large businesses may gather a terabyte of it every day. But the ability to analyses such data hasn't kept pace with the ability to capture it.

• The next frontier of web data analysis is better integration of clickstream data with other customer information such as purchase history and even demographic profiles, to form what's often called a "360-degree view" of a site visitor.

• Clickstream analysis can be seen as a four-stage process of collection, storage, analyis and reporting. The first two concentrate on gathering and formatting information, and the latter two on making sense of it.

• There are two levels of clickstream data analysis: Web traffic analysis, movement related, and commerce-based analysis, which looks at e-business-related activities.

 Web traffic analysis

o Web traffic analysis operates at the web server level and concentrate on how visitors navigate through the site.

o It measures the number of pages delivered to the customer as opposed to pages sent by the server. It determines how often visitors hit the browser stop button, how much of the page was delivered until they hit the button and how long they waited before they hit it.

o Performance parameters are also logged, such as length of time it took for loading a page ad determining how much data was transmitted.

o Commerce or e-business analysis can use higher level information out of clickstreams, such as tracking visitors' responses to pages and their content.

o One of the main reason for measuring clickstream data at this level is to analyze the effectiveness of the web as a channel to market.

o Measuring the success of commerce activities is much more difficult than evaluating web traffic, because it looks at why visitors behave in a particular way, not just where they went. So for high-level clickstream analysis it is possible even to see the reactions of the customers. What items do people buy and which they take out of their shopping basket.

o This provides business-level information about how visitors interact with the site which can be helpful to aid further site development.

o With clickstream data more values can be gained by combining them with information from other sources like direct marketing or sales.

o A direct mail campaign may be used to encourage customers to visit the web site. Now the effectiveness of the mail campaign can be measured by collecting clickstream data from users who have been sent mail shots and those who have not.

 E-business feedback

o The e-business analysis cycle is more sophisticated. This process combines web site activity with data from other sources, such as visitor profile information, sales databases and campaigns that include links to the web site.

o It provides higher-level information, more focused answers ad information that can be used to enhance e-commerce activities across the business as well as improving the web site.

o The e-business cycle is a continual process, involving the integration of web and other data with web-site activity data analysis, followed by improvements.

o The integration of e-business and enterprise data with web traffic and other type of data allows discoveries and insights that cannot be gained by observing web activity alone, and increases the potential for qualitative analysis.

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o Attempting clickstream analysis it is important to differ between the two techniques tools on the market which are used. Some analysis tools just report actions on web sites, while straightforward reporting tools will only log actions.

o A second consideration is whether the analysis tool supports real-time data feeds or uses a batch processing model. Batch processing can only ever analyses historical data, and this lengthens the time between customer actions and a firm's reaction.

o Take into this consideration that real-time data feeds are more in tune with the move towards dynamic web pages, customer profiling and the use of personalization engines.

o Real-time data feeds do not restrict the company generating weekly or monthly reports, but can support real-time reporting, which can speed up the decision making process when tuning the web site. However there are performance and bandwidth issues associated with real time reporting.

o Clickstream analysis automates much of the analysis process, but even with the best tools, some human intervention and analysis will be necessary, especially if the clickstream data is used in conjunction with other data sources.

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o For example, if site visits peak at a certain time on a particular day, the tool can readily recognize the spike but will not necessarily discern the reason, which may be that a special marketing campaign ran just beforehand.

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