Gosh!  Avinash Kaushik posted again and I’m so busy that I did not see it first - Andy Beal did see it and posted a link from his blog to Avainash’s post.

"We all agree that reporting is not analysis. We all agree that great analysts are hard to come by and few and far between (yet it is interesting that people disagree with the 10/90 rule and keep insisting on spending money on tools)."

 Is Avinash referring to me?   After using a variety of web metrics tools - I’m always ready to admit there are good tools at almost every price range but  a 10,000 tool is not going to be able to handle a really large site with many types of complex issues. (though it might handle everything up to a very large site with complex issues). 

# 9 You have not only heard of the Yahoo! Web Analytics group Yahoo! Web Analytics group but 20 mins of each day is spent reading all the posts.
Mr. Eric Peterson has had many great accomplishments but IMHO his best one is the Yahoo! Web Analytics Group. This is the most awesome collection of smart people in our industry who share their wisdom on every topic under the sun that touches our world. I personally read all the posts every day and I learn about challenges others are facing, innovative ways to solve those challenges, general trends in the industry, pointers to the latest and coolest happenings that impact us and on and on. There are repeat questions, the interesting thing is that even those get different answers all the time. 

Avinash has a point - I don’t read enough of this Webmetrics stuff (I’m too busy writing about it and doing it) but I just subscribed to the Yahoo! Web Analytics Group as I have to learn more - and maybe comment on the what others are writing about …. after all, this is a Web Metrics blog).

# 6 You understand the technical differences between page tagging, log files, packet sniffing & beacons.
This is specific to Web Analysts. How data is captured is perhaps the most critical part your ability to “process” the data and find insights. Each data capture methodology comes has its benefits and dangerous negatives. You understand hard core the technical differences between each data capture methodology and then appropriately adjust the kind of analysis you do and the value you extract from whatever your company uses.

On a technical level I probably don’t know as much about the differences in these methods as I should.   I know certain types of information are easier to retrieve from a log based web analytics solutions (ie: Podcasts and RSS Feeds) and I’ve had to do that.   The technical issues behind why one uses one type of solution over another I probably could broaden my knowledge on.

# 1 You play “Offence” and not just “Defence.”
Most of us in this field play “Defence”: we supply data or we provide reports or we at times provide dashboards. Mostly we react. But we don’t play “Offence”:  we don’t get in front of the business and say this is what you should measure, we don’t reply to the question “show me what the tool provides” with “tell me your strategic objectives and I’ll tell you what insights I can provide with the data I have”.

This sounds great - and I’ve tried to do it with some of my clients (and former clients) when they are willing to listen - but when it comes down to it - many businesses don’t really want you to be too much in their face with information that may conflict with their own business objectives.  

"A key skill of being a great analyst is the ability to have patience, survive and stay motivated in a world where people might ask for sub optimal things. Of course you know better but transforming perceptions is a very hard job and take a long time. But you are a survivor, except the part about a million dollars in the end! ; )

And I might add, have sub optimal tools to pull the data.    I think what helps me is having several clients where I can express my ideas and explore findings - I get a good mix of large corporate types of things but also work with much smaller sites on my own - where I can see cause and effect more clearly.

For example: search traffic goes up for part of a large corporation in Japan - how easy would it be to know why it went up?   A large corporation has so many promotions going on from so many different business groups - it is very hard to know why traffic jumps up - esp at the log data for a country whose language you don’t speak.   I’ve tried to solve problems, like that, and I know how difficult it can be to take web data and make intelligence out of it.