There is a lot of data available in the web analytics platforms like Omniture, Webtrends etc. One of the key reports is the click-stream report. Having access to raw data can help understand the differences in the site browsing behavior in the first visit vs. the second vs. subsequent visits.
Analyzing the above mentioned data can help understand the patterns where in the process do the users' drop-off the website before converting. Also, how different is the behavior from first to the second to subsequent. This information can be used in multiple ways:
- Optimize the site content – make the content more easily accessible that the users are reading in the later visits
- Using cookie tracking – optimize how the site is presented to the users in the first visit vs. subsequent visits
These small changes can definitely lead to high conversions rates especially for e-commerce sites.
This technique can also be used in the way how ads are served to users who have dropped off the process before converting. Dynamic ad serving companies like Tumri and Teracent can be used to change the color, messaging to first visit vs. a user who has been to the web site.
2 comments:
Cookie tracking is great. But, what are the costs involved when serving a dynamic, database driving page per returning visitor? Speaking from the client site; how would I know if the return visit would convert given new content? Also, what metrics determine what should be changed in terms of content?
There are a lot of vendors who can serve dynamic content, may be offermatica - I have not done a pricing research.
This is a learning you will have to do based on user behaviour. So, for exmaple: if you notice that typically during the first visit, the users visit pages A and B. However, they don't convert. But you notice that in the subsequent visits, the users always visit page C before converting, then try to land the users who come back to the site to page C or a similar page. Thus, it should increase conversions.
Post a Comment