Why Personalised Web Analytics Make Sense

Google analytics has pretty much wrapped up the market with easy to use web analytics for your website. But these web analytics miss a trick - they miss being able to tell you exactly who the person was that visited this or that page, and in so doing, you miss a great piece of the puzzle in terms of trying to work out what motivated the page visit.

It is a marketeer's dream to be able to understand what motivates people to visit pages or make transaction on the web, because, armed with this knowledge, the organization can really put out offerings which are both hugely attractive and lead to transactional conversions. The answer to taking web analytics to the next level lies in identifying the page visits of each web visitor and comparing them to the profile you have of this user in your CRM database (the repository of all customer knowledge). This sort of comparison allows one to access a huge array of information that you just cannot get from Google. For instance, imagine being able to see how many junior members were hitting the page about upgrading their membership, or how many members that had been sent a mailing had actually gone on and registered for a particular session at an event. Not only could you cross-reference web behavior with transactional behavior in the CRM (conversions), but you can also look at how different demographic segments in your database behave differently on the web - and then put out personalized pages for each of these demographics according to what motivates them!  The question is - how can we actually do this?

The Zengagers team have pondered long and hard on this and come up with WebSenz - a tool that is able to analyze the web logs of any RiSE website and turn reams of text into meaningful data related to each contact in iMIS. So, as soon as someone has identified themselves in RiSe (by logging in), each and every page hit is registered against their profile in data tables. Not only that, WebSenz also analyzes their IP address, web browser and device, plus where they came from. Amazing information, but the important thing is that you can aggregate all this data up using IQA queries and dashboards to make sense of the total amount of data and cross-reference with other data tables in iMIS.

Sound fantastical? Its not - we have clients who are already using this functionality to put their organizations ahead of the competition by ensuring they know exactly what their members or donors are doing on the web. You can find more information about the product here