Switching from Webtrends to Google Analytics
We have been working with a client on a website (www.modernselling.com) for sales focused users for several years and have built a system to turn dynamically driven urls (such as news.apx?pageid=xx) into SEO friendly urls (such as news/sales-news-headlines/insider-trading-arrests.aspx).
The client has spent hundreds of hours (and therefore thousands of pounds) struggling with the behemoth otherwise known as Webtrends 8a in order to filter out the chaff traffic (robots and the like) from the valued traffic (actual users, referrals and actual advertising click rates). I won’t bore you with too much information but Webtrends is ultimately an enterprise piece of software and for smaller sites/start-ups and those with less time/budget (most of us) it’s analogous with using a sledge hammer to crack a nut! One example being that the installation documentation and support staff (US based) stress the application must run on its own server and has a recommended RAM size of 4GB. This might be OK for some large businesses but usually one dedicated server (hosting the website) is stretching the budget far enough for the aforementioned clientele without the associated costs of managing, maintaining and purchasing/renting a further server simple to do a bit of traffic analysis!*
So for the past 6 months we have been assessing and testing what the FREE Google Analytics (www.google.com/analytics/) has to offer. I have to say that I am impressed! Instead of tediously running pre-set up profiles and reports (hours of setting up and hours of laborious database churning) AKA the Webtrends Model we can report on everything we need by utilising the JavaScript functions available within the latest Google Analytics script (ga.js). By using pre-defined rules for advert impressions, advert click-throughs and editorial outbound links and applying them through pageTracker._trackPageview() we can record all the statistics we need.
The good news is that the client can now simply search for a string in Google Analytics (such as ‘advert-name-click’) and it will return all the statistics related to click-throughs for that advert. He can then calculate his conversion rates, see which section of his website is most effective for a particular advert and use the system to bill his clients who are all happy with the statistics and reports because they come through Google.
Remember if you are using pageTracker._trackPageview() multiple times on the same page that you must apply a filter to Google Analytics to ensure that your overall page impression statistics are not skewed – you must filter out anything other than the page impression.
More to follow on the detail…
*Note: in order for the client to return the required statistics though Webtrends we first had to write an asp.net desktop application to parse the raw log files to remove anything that looked like suspicious/robot traffic, he then set up some filters and rules in Webtrends (one for each advertising campaign) and ran the parsed logs through