Archive

Posts Tagged ‘web analytics’

Observation on Exit rate and bounce rate

Bounce Rate:

(Landing page = Exit page) =>Bounce rate

Exit Rate:

Any landing page ->Traverse -> exit on X page 
=> Exit Rate = Page views of ‘X’ page / No. of exits from ‘X’ page (including bounces)

The exit rate says that for all cases where someone visited that page (including the bounces); it was the last page that much % of time. Bounce and exit rate both calculated based on page views and not based on unique pages views. Exit rate include bounces.

Consider one example,

My website is having one page named Product1.html, having 35% exit rate and 28% bounce rate. As I mentioned, bounce rate is a part of exit rate; we can take difference of these two to get interesting information. Exit Rate (35%) – Bounce Rate (28%) = 7% visited other pages on my site then came back to the main product1.html page and exited from that page. This observation has an exception, like what if Bounce rate is greater than exit rate!

Logically, greater bounce rate than exit rate is bit misleading in understanding the behavior of users. Means, when people landing on a particular page and exiting from there only, what’s the reason behind people exit less when they’re landing on some other page, traverse certain number of pages and coming on that page. If a page is not really happening in engaging its visitors then exit rate and bounce rate should be almost equal.

Website Visitor Segmentation – Web Analytics

Website visitor segmentation is one of the most important steps in understanding the behavioral aspect of people visiting our website. Following visitor segmentation has been made based on what exactly happen technically when someone attempts to open the website. The segmentation gives an idea on how to put a visitor into certain relevant segment based on their arrival pattern and the response recorded by the analytics system.

Here’s the explaination on how a request for specific web page is treated at technical level: 

Visitors

    • New Visitor
      • Anonymous
        • Exit before tracking
        • Cookie deletion & Cookie detection problem
        • Private / Safe browsing
        • Proxy
      • Observed
        • Robots / Crawlers
        • Showing hits as ‘not identified’
        • Soft 404
      • Identified
        • Tracking of successful visit
        • Event firing in response to action
        • Form fill-up (Not submitted)
      • Verified
        • Verified by email address
        • Form fill-up and submitted
        • Transaction completion
    • Returning Visitor
      • Identified as new visit
        • Deletion of cookie
        • Forget password & unable to retrieve, attempting new login
      • Verified returning visitor
        • Tracking cookie successfully
        • Visitor already having Login credential for website

It becomes very crucial to consider certain assumption on number of Anonymous visitors while considering the overall visitors to a website. This assumption helps us in identifying issues with website loading, tracking and other GUI related problems. Also, by carefully assuming Anonymous visitor figure we can achieve a precise statistics of conversion rate and bounce rate.

As we can see, only identified and verified visitors matter to us while judging the conversion rate. But on the other hand we can’t ignore Anonymous and Observed visitors to our website as they might be the prospects to our website, and we might have lost them.