Google has just added a function in Google Webmaster Tools that let’s you flag parameters you wish Google to ignore when crawling your site.

These can include things like session IDs, additional parameters and tracking ids. This is great way of handling the problem rather than forcing the webmaster to implement expensive work-around’s to be found in Google which has historically been the case.

Traditionally, sites that use session IDs as a way of tracking users or e-commerce, will have a disadvantage in search engine optimisation for a few reasons:

• Duplicate content
• Dispersion of page credit
• Potential for bot to get tied up on these additional pages and not crawl other important pages as often

On the tracking front, and speaking from personal experience, flagging removal of tracking IDs is a big boost to data integrity. A recent campaign I worked on saw several blog and news site pick up a unique tracking URL to refer back to the clients site, a tracking ID that was meant to be unique for an email campaign. Google then decided to pick this URL up as it crawled through the sites and it ranked it well in search. The result was most of the search visitors appeared to the analytics system that they came from the email campaign and the collected data were significantly impacted.

Great news and makes life a lot easier for web masters and marketers stuck with this problem.

http://googlewebmastercentral.blogspot.com/2009/10/new-parameter-handling-tool-helps-with.html

Every now and again you hear people talk about the inaccuracies of cookies, but most of the time level of extent of this inaccuracy is not really known.

Everything from campaign reach and frequency to monitoring a campaigns contribution to conversion rely on cookies to work their magic. Sometimes these don’t get taken with a grain of salt and can be misinterpreted - probably resulting in less credit to the channels that kick off the process and some good news, you're conversion rate of "real" user is higher than reported.

With users blocking cookies, clearing at end of session, deleting more regularly, using different browsers, using multiple computers, netbooks, mobiles, public pcs, and spending more time researching touching more online media points, little bits of attrition in the tracking integrity here and there add up.

We wanted to find out what the deal was, so hunting around for answers we found this great little exercise. Angie Brown from showmeanalytics.com explains how to estimate the impact of cookie deletion, and use it as a model that can be extended to some of the other problems that deleted cookies and lost identities have on data analysis. We did it with a site with less frequency than the example, and got 2.1 x inflated unique visitors than real users.

http://showmeanalytics.com/2009/04/calculating-the-effects-of-cookie-deletion/

An interesting point in Angie’s post is how different adoption rates of authentication can help rebuild a profile of an individual and tighten the accuracy of your data collection. When we think about authentication this doesn’t have to be a login. By encoding the users unique id on communications such as emails and MMS links, you will also help tie your customer intelligence back together.

I’d like to see analytics suites focus more on a view of the individual, rather than a view of the device. Does anyone know a service that can do this well?

Do you think analysts should adjust results to something more accurate to accommodate for its flaws?