What is Web Analytics ( Part – 2 Some terms and definitions)


While a shopkeeper that owned his business a hundred years ago may not have had the advantage of being able to sell a product instantaneously to a customer across the planet, he/she did have an advantage that is somewhat diminished by internet commerce – he had direct access to feedback from customers. He could tell who came to the shop, how long they stayed, if they purchased anything and ultimately know how his shop was doing. This is a less transparent process online. Web analytics is one way a website owner/ designer can offset this potential drawback. Using web analytics tools, he/she can get the same valuable information and gauge from that data how to improve the website, how to get a better ROI (Return on Investment) for their marketing, how to reach a particular demographic or even just to gauge how many people it has reached.


Web Analytics is a multipronged, ongoing process which requires a group of tools. Which tools ( for example free services like Google and Yahoo! That allow you to self monitor versus the services of a paid, professional company, such as Omniture or Sysomos) depends on the needs of the website owner.


The data generated by these Web Analytics tools falls into two categories:


Clickstream level data


This term refers to the data concerning all things clicked by your visitors. It is derived from “Visits, Visitors, Time on Site, Page Views, Bounce Rate[ i.e. “the percentage of sessions on your website with only one page view, or in other words, people who visited your site and then very quickly left.” ( J. Hodson)], Conversion Rate [i.e. “how many people are visiting your site, and then buying a product, or engaging in some other desired behavior “(J.Hodson)] and Sources (Kaushik, 2010).”


Multiple outcome Analysis data

This data is generated by setting goals and measuring progress towards those goals. Using both clickstream data and other tools such as Technorati or Klout, Enterprise Resource Planning (ERP) systems, and surveys ( paraphrasing of J.Hodson), multiple outcome analysis is concerned with increases in revenue, reduction in cost and improvements in customer satisfaction or loyalty.


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