The world of Web Analytics

Marketing in any channel (traditional or web) is not completely effective unless analytics is in place. Whether businesses are using one or more channels, web analytics application packages can not only provide information on basic usage of data but also on how customers interact on the portal. Google Analytics is one of the free tools available that can help track web site usage and provide insights into ad campaign effectiveness. 

Previously, logs from web servers were used to parse information on web site traffic. With the arrival new web analytics 2.0 softwares such as Google Analytics, Omniture etc, it's becomes extremely easy to capture clickstream data and analyze in many useful number of ways. Simply place few lines of javascript code on every page you want to track and you're done! It's that easy. However, the real fun starts after placing the tags and start seeing reports.

While there are many metrics that can be used, each company has unique needs and business model, requiring to come up its own universal metric to measure effectiveness of the site. Here are few metrics that can help find better insights:

1. Visits - total number of requests (or sessions).
2. Unique visitors - number of unique individuals visiting.
3. Time on page and time of site
4. Bounce rate - percentage of sessions where time of site was less than five seconds
5. Exit rate - number of customers left the web site from a specific page.
6. Conversion Rate - percentage of uniques visitors submitted an order ( or completed one goal)
7. User engagement - overall engagement of user combined of other metrics such as unique visits, frequency of visits, recency of visit, depth of visit, time spent on site etc.

Analyzing above metrics should be the next important key to understanding how customers use web pages to get to where they want to and , more importantly, how customers buy, in case of an e-commerce site. For example, high bounce rate should be an alarming factor for any business that customers didn't even bother to click on any link. So, it further warrants one to find out what's wrong on the page and on the previous page in the path. Once the page is optimized, analytics reports will further show the result to prove or disprove the hypothesis.

This is just a start of the journey called data driven decision making!! So, let's begin.